From ed362008f0a317729f8404e86e57d8a6ceb60f21 Mon Sep 17 00:00:00 2001 From: Davies Liu Date: Tue, 16 Dec 2014 11:19:36 -0800 Subject: [PATCH 001/320] [SPARK-4437] update doc for WholeCombineFileRecordReader update doc for WholeCombineFileRecordReader Author: Davies Liu Author: Josh Rosen Closes #3301 from davies/fix_doc and squashes the following commits: 1d7422f [Davies Liu] Merge pull request #2 from JoshRosen/whole-text-file-cleanup dc3d21a [Josh Rosen] More genericization in ConfigurableCombineFileRecordReader. 95d13eb [Davies Liu] address comment bf800b9 [Davies Liu] update doc for WholeCombineFileRecordReader --- .../input/WholeTextFileInputFormat.scala | 12 ++---- .../input/WholeTextFileRecordReader.scala | 43 ++++++++++--------- 2 files changed, 25 insertions(+), 30 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/input/WholeTextFileInputFormat.scala b/core/src/main/scala/org/apache/spark/input/WholeTextFileInputFormat.scala index d3601cca832b2..aaef7c74eea33 100644 --- a/core/src/main/scala/org/apache/spark/input/WholeTextFileInputFormat.scala +++ b/core/src/main/scala/org/apache/spark/input/WholeTextFileInputFormat.scala @@ -19,7 +19,6 @@ package org.apache.spark.input import scala.collection.JavaConversions._ -import org.apache.hadoop.conf.{Configuration, Configurable} import org.apache.hadoop.fs.Path import org.apache.hadoop.mapreduce.InputSplit import org.apache.hadoop.mapreduce.JobContext @@ -38,18 +37,13 @@ private[spark] class WholeTextFileInputFormat override protected def isSplitable(context: JobContext, file: Path): Boolean = false - private var conf: Configuration = _ - def setConf(c: Configuration) { - conf = c - } - def getConf: Configuration = conf - override def createRecordReader( split: InputSplit, context: TaskAttemptContext): RecordReader[String, String] = { - val reader = new WholeCombineFileRecordReader(split, context) - reader.setConf(conf) + val reader = + new ConfigurableCombineFileRecordReader(split, context, classOf[WholeTextFileRecordReader]) + reader.setConf(getConf) reader } diff --git a/core/src/main/scala/org/apache/spark/input/WholeTextFileRecordReader.scala b/core/src/main/scala/org/apache/spark/input/WholeTextFileRecordReader.scala index 6d59b24eb0596..1b1131b9b8831 100644 --- a/core/src/main/scala/org/apache/spark/input/WholeTextFileRecordReader.scala +++ b/core/src/main/scala/org/apache/spark/input/WholeTextFileRecordReader.scala @@ -17,7 +17,7 @@ package org.apache.spark.input -import org.apache.hadoop.conf.{Configuration, Configurable} +import org.apache.hadoop.conf.{Configuration, Configurable => HConfigurable} import com.google.common.io.{ByteStreams, Closeables} import org.apache.hadoop.io.Text @@ -27,6 +27,18 @@ import org.apache.hadoop.mapreduce.lib.input.{CombineFileSplit, CombineFileRecor import org.apache.hadoop.mapreduce.RecordReader import org.apache.hadoop.mapreduce.TaskAttemptContext + +/** + * A trait to implement [[org.apache.hadoop.conf.Configurable Configurable]] interface. + */ +private[spark] trait Configurable extends HConfigurable { + private var conf: Configuration = _ + def setConf(c: Configuration) { + conf = c + } + def getConf: Configuration = conf +} + /** * A [[org.apache.hadoop.mapreduce.RecordReader RecordReader]] for reading a single whole text file * out in a key-value pair, where the key is the file path and the value is the entire content of @@ -38,12 +50,6 @@ private[spark] class WholeTextFileRecordReader( index: Integer) extends RecordReader[String, String] with Configurable { - private var conf: Configuration = _ - def setConf(c: Configuration) { - conf = c - } - def getConf: Configuration = conf - private[this] val path = split.getPath(index) private[this] val fs = path.getFileSystem(context.getConfiguration) @@ -87,29 +93,24 @@ private[spark] class WholeTextFileRecordReader( /** - * A [[org.apache.hadoop.mapreduce.RecordReader RecordReader]] for reading a single whole text file - * out in a key-value pair, where the key is the file path and the value is the entire content of - * the file. + * A [[org.apache.hadoop.mapreduce.lib.input.CombineFileRecordReader CombineFileRecordReader]] + * that can pass Hadoop Configuration to [[org.apache.hadoop.conf.Configurable Configurable]] + * RecordReaders. */ -private[spark] class WholeCombineFileRecordReader( +private[spark] class ConfigurableCombineFileRecordReader[K, V]( split: InputSplit, - context: TaskAttemptContext) - extends CombineFileRecordReader[String, String]( + context: TaskAttemptContext, + recordReaderClass: Class[_ <: RecordReader[K, V] with HConfigurable]) + extends CombineFileRecordReader[K, V]( split.asInstanceOf[CombineFileSplit], context, - classOf[WholeTextFileRecordReader] + recordReaderClass ) with Configurable { - private var conf: Configuration = _ - def setConf(c: Configuration) { - conf = c - } - def getConf: Configuration = conf - override def initNextRecordReader(): Boolean = { val r = super.initNextRecordReader() if (r) { - this.curReader.asInstanceOf[WholeTextFileRecordReader].setConf(conf) + this.curReader.asInstanceOf[HConfigurable].setConf(getConf) } r } From cb484474934d664000df3d63a326bcd6b12f2f09 Mon Sep 17 00:00:00 2001 From: jbencook Date: Tue, 16 Dec 2014 11:37:23 -0800 Subject: [PATCH 002/320] [SPARK-4855][mllib] testing the Chi-squared hypothesis test This PR tests the pyspark Chi-squared hypothesis test from this commit: c8abddc5164d8cf11cdede6ab3d5d1ea08028708 and moves some of the error messaging in to python. It is a port of the Scala tests here: [HypothesisTestSuite.scala](https://github.com/apache/spark/blob/master/mllib/src/test/scala/org/apache/spark/mllib/stat/HypothesisTestSuite.scala) Hopefully, SPARK-2980 can be closed. Author: jbencook Closes #3679 from jbencook/master and squashes the following commits: 44078e0 [jbencook] checking that bad input throws the correct exceptions f12ee10 [jbencook] removing checks for ValueError since input tests are on the Scala side 7536cf1 [jbencook] removing python checks for invalid input a17ee84 [jbencook] [SPARK-2980][mllib] adding unit tests for the pyspark chi-squared test 3aeb0d9 [jbencook] [SPARK-2980][mllib] bringing Chi-squared error messages to the python side --- python/pyspark/mllib/tests.py | 100 +++++++++++++++++++++++++++++++++- 1 file changed, 99 insertions(+), 1 deletion(-) diff --git a/python/pyspark/mllib/tests.py b/python/pyspark/mllib/tests.py index 8332f8e061f48..5034f229e824a 100644 --- a/python/pyspark/mllib/tests.py +++ b/python/pyspark/mllib/tests.py @@ -23,6 +23,7 @@ import array as pyarray from numpy import array, array_equal +from py4j.protocol import Py4JJavaError if sys.version_info[:2] <= (2, 6): try: @@ -34,7 +35,7 @@ import unittest from pyspark.mllib.linalg import Vector, SparseVector, DenseVector, VectorUDT, _convert_to_vector,\ - DenseMatrix + DenseMatrix, Vectors, Matrices from pyspark.mllib.regression import LabeledPoint from pyspark.mllib.random import RandomRDDs from pyspark.mllib.stat import Statistics @@ -400,6 +401,103 @@ def test_regression(self): self.assertTrue(dt_model.predict(features[3]) > 0) +class ChiSqTestTests(PySparkTestCase): + def test_goodness_of_fit(self): + from numpy import inf + + observed = Vectors.dense([4, 6, 5]) + pearson = Statistics.chiSqTest(observed) + + # Validated against the R command `chisq.test(c(4, 6, 5), p=c(1/3, 1/3, 1/3))` + self.assertEqual(pearson.statistic, 0.4) + self.assertEqual(pearson.degreesOfFreedom, 2) + self.assertAlmostEqual(pearson.pValue, 0.8187, 4) + + # Different expected and observed sum + observed1 = Vectors.dense([21, 38, 43, 80]) + expected1 = Vectors.dense([3, 5, 7, 20]) + pearson1 = Statistics.chiSqTest(observed1, expected1) + + # Results validated against the R command + # `chisq.test(c(21, 38, 43, 80), p=c(3/35, 1/7, 1/5, 4/7))` + self.assertAlmostEqual(pearson1.statistic, 14.1429, 4) + self.assertEqual(pearson1.degreesOfFreedom, 3) + self.assertAlmostEqual(pearson1.pValue, 0.002717, 4) + + # Vectors with different sizes + observed3 = Vectors.dense([1.0, 2.0, 3.0]) + expected3 = Vectors.dense([1.0, 2.0, 3.0, 4.0]) + self.assertRaises(ValueError, Statistics.chiSqTest, observed3, expected3) + + # Negative counts in observed + neg_obs = Vectors.dense([1.0, 2.0, 3.0, -4.0]) + self.assertRaises(Py4JJavaError, Statistics.chiSqTest, neg_obs, expected1) + + # Count = 0.0 in expected but not observed + zero_expected = Vectors.dense([1.0, 0.0, 3.0]) + pearson_inf = Statistics.chiSqTest(observed, zero_expected) + self.assertEqual(pearson_inf.statistic, inf) + self.assertEqual(pearson_inf.degreesOfFreedom, 2) + self.assertEqual(pearson_inf.pValue, 0.0) + + # 0.0 in expected and observed simultaneously + zero_observed = Vectors.dense([2.0, 0.0, 1.0]) + self.assertRaises(Py4JJavaError, Statistics.chiSqTest, zero_observed, zero_expected) + + def test_matrix_independence(self): + data = [40.0, 24.0, 29.0, 56.0, 32.0, 42.0, 31.0, 10.0, 0.0, 30.0, 15.0, 12.0] + chi = Statistics.chiSqTest(Matrices.dense(3, 4, data)) + + # Results validated against R command + # `chisq.test(rbind(c(40, 56, 31, 30),c(24, 32, 10, 15), c(29, 42, 0, 12)))` + self.assertAlmostEqual(chi.statistic, 21.9958, 4) + self.assertEqual(chi.degreesOfFreedom, 6) + self.assertAlmostEqual(chi.pValue, 0.001213, 4) + + # Negative counts + neg_counts = Matrices.dense(2, 2, [4.0, 5.0, 3.0, -3.0]) + self.assertRaises(Py4JJavaError, Statistics.chiSqTest, neg_counts) + + # Row sum = 0.0 + row_zero = Matrices.dense(2, 2, [0.0, 1.0, 0.0, 2.0]) + self.assertRaises(Py4JJavaError, Statistics.chiSqTest, row_zero) + + # Column sum = 0.0 + col_zero = Matrices.dense(2, 2, [0.0, 0.0, 2.0, 2.0]) + self.assertRaises(Py4JJavaError, Statistics.chiSqTest, col_zero) + + def test_chi_sq_pearson(self): + data = [ + LabeledPoint(0.0, Vectors.dense([0.5, 10.0])), + LabeledPoint(0.0, Vectors.dense([1.5, 20.0])), + LabeledPoint(1.0, Vectors.dense([1.5, 30.0])), + LabeledPoint(0.0, Vectors.dense([3.5, 30.0])), + LabeledPoint(0.0, Vectors.dense([3.5, 40.0])), + LabeledPoint(1.0, Vectors.dense([3.5, 40.0])) + ] + + for numParts in [2, 4, 6, 8]: + chi = Statistics.chiSqTest(self.sc.parallelize(data, numParts)) + feature1 = chi[0] + self.assertEqual(feature1.statistic, 0.75) + self.assertEqual(feature1.degreesOfFreedom, 2) + self.assertAlmostEqual(feature1.pValue, 0.6873, 4) + + feature2 = chi[1] + self.assertEqual(feature2.statistic, 1.5) + self.assertEqual(feature2.degreesOfFreedom, 3) + self.assertAlmostEqual(feature2.pValue, 0.6823, 4) + + def test_right_number_of_results(self): + num_cols = 1001 + sparse_data = [ + LabeledPoint(0.0, Vectors.sparse(num_cols, [(100, 2.0)])), + LabeledPoint(0.1, Vectors.sparse(num_cols, [(200, 1.0)])) + ] + chi = Statistics.chiSqTest(self.sc.parallelize(sparse_data)) + self.assertEqual(len(chi), num_cols) + self.assertIsNotNone(chi[1000]) + if __name__ == "__main__": if not _have_scipy: print "NOTE: Skipping SciPy tests as it does not seem to be installed" From d12c0711faa3d4333513fcbbbee4868bcb784a26 Mon Sep 17 00:00:00 2001 From: Mike Jennings Date: Tue, 16 Dec 2014 12:13:21 -0800 Subject: [PATCH 003/320] [SPARK-3405] add subnet-id and vpc-id options to spark_ec2.py Based on this gist: https://gist.github.com/amar-analytx/0b62543621e1f246c0a2 We use security group ids instead of security group to get around this issue: https://github.com/boto/boto/issues/350 Author: Mike Jennings Author: Mike Jennings Closes #2872 from mvj101/SPARK-3405 and squashes the following commits: be9cb43 [Mike Jennings] `pep8 spark_ec2.py` runs cleanly. 4dc6756 [Mike Jennings] Remove duplicate comment 731d94c [Mike Jennings] Update for code review. ad90a36 [Mike Jennings] Merge branch 'master' of https://github.com/apache/spark into SPARK-3405 1ebffa1 [Mike Jennings] Merge branch 'master' into SPARK-3405 52aaeec [Mike Jennings] [SPARK-3405] add subnet-id and vpc-id options to spark_ec2.py --- docs/ec2-scripts.md | 19 +++++++++++++ ec2/spark_ec2.py | 66 ++++++++++++++++++++++++++++++++++----------- 2 files changed, 70 insertions(+), 15 deletions(-) diff --git a/docs/ec2-scripts.md b/docs/ec2-scripts.md index ed51d0abb3a45..d50f445d7ecc7 100644 --- a/docs/ec2-scripts.md +++ b/docs/ec2-scripts.md @@ -94,6 +94,25 @@ another. permissions on your private key file, you can run `launch` with the `--resume` option to restart the setup process on an existing cluster. +# Launching a Cluster in a VPC + +- Run + `./spark-ec2 -k -i -s --vpc-id= --subnet-id= launch `, + where `` is the name of your EC2 key pair (that you gave it + when you created it), `` is the private key file for your + key pair, `` is the number of slave nodes to launch (try + 1 at first), `` is the name of your VPC, `` is the + name of your subnet, and `` is the name to give to your + cluster. + + For example: + + ```bash + export AWS_SECRET_ACCESS_KEY=AaBbCcDdEeFGgHhIiJjKkLlMmNnOoPpQqRrSsTtU +export AWS_ACCESS_KEY_ID=ABCDEFG1234567890123 +./spark-ec2 --key-pair=awskey --identity-file=awskey.pem --region=us-west-1 --zone=us-west-1a --vpc-id=vpc-a28d24c7 --subnet-id=subnet-4eb27b39 --spark-version=1.1.0 launch my-spark-cluster + ``` + # Running Applications - Go into the `ec2` directory in the release of Spark you downloaded. diff --git a/ec2/spark_ec2.py b/ec2/spark_ec2.py index 5f9e484212635..92adfd2d07b5b 100755 --- a/ec2/spark_ec2.py +++ b/ec2/spark_ec2.py @@ -162,6 +162,10 @@ def parse_args(): parser.add_option( "--copy-aws-credentials", action="store_true", default=False, help="Add AWS credentials to hadoop configuration to allow Spark to access S3") + parser.add_option( + "--subnet-id", default=None, help="VPC subnet to launch instances in") + parser.add_option( + "--vpc-id", default=None, help="VPC to launch instances in") (opts, args) = parser.parse_args() if len(args) != 2: @@ -186,14 +190,14 @@ def parse_args(): # Get the EC2 security group of the given name, creating it if it doesn't exist -def get_or_make_group(conn, name): +def get_or_make_group(conn, name, vpc_id): groups = conn.get_all_security_groups() group = [g for g in groups if g.name == name] if len(group) > 0: return group[0] else: print "Creating security group " + name - return conn.create_security_group(name, "Spark EC2 group") + return conn.create_security_group(name, "Spark EC2 group", vpc_id) # Check whether a given EC2 instance object is in a state we consider active, @@ -303,12 +307,26 @@ def launch_cluster(conn, opts, cluster_name): user_data_content = user_data_file.read() print "Setting up security groups..." - master_group = get_or_make_group(conn, cluster_name + "-master") - slave_group = get_or_make_group(conn, cluster_name + "-slaves") + master_group = get_or_make_group(conn, cluster_name + "-master", opts.vpc_id) + slave_group = get_or_make_group(conn, cluster_name + "-slaves", opts.vpc_id) authorized_address = opts.authorized_address if master_group.rules == []: # Group was just now created - master_group.authorize(src_group=master_group) - master_group.authorize(src_group=slave_group) + if opts.vpc_id is None: + master_group.authorize(src_group=master_group) + master_group.authorize(src_group=slave_group) + else: + master_group.authorize(ip_protocol='icmp', from_port=-1, to_port=-1, + src_group=master_group) + master_group.authorize(ip_protocol='tcp', from_port=0, to_port=65535, + src_group=master_group) + master_group.authorize(ip_protocol='udp', from_port=0, to_port=65535, + src_group=master_group) + master_group.authorize(ip_protocol='icmp', from_port=-1, to_port=-1, + src_group=slave_group) + master_group.authorize(ip_protocol='tcp', from_port=0, to_port=65535, + src_group=slave_group) + master_group.authorize(ip_protocol='udp', from_port=0, to_port=65535, + src_group=slave_group) master_group.authorize('tcp', 22, 22, authorized_address) master_group.authorize('tcp', 8080, 8081, authorized_address) master_group.authorize('tcp', 18080, 18080, authorized_address) @@ -320,8 +338,22 @@ def launch_cluster(conn, opts, cluster_name): if opts.ganglia: master_group.authorize('tcp', 5080, 5080, authorized_address) if slave_group.rules == []: # Group was just now created - slave_group.authorize(src_group=master_group) - slave_group.authorize(src_group=slave_group) + if opts.vpc_id is None: + slave_group.authorize(src_group=master_group) + slave_group.authorize(src_group=slave_group) + else: + slave_group.authorize(ip_protocol='icmp', from_port=-1, to_port=-1, + src_group=master_group) + slave_group.authorize(ip_protocol='tcp', from_port=0, to_port=65535, + src_group=master_group) + slave_group.authorize(ip_protocol='udp', from_port=0, to_port=65535, + src_group=master_group) + slave_group.authorize(ip_protocol='icmp', from_port=-1, to_port=-1, + src_group=slave_group) + slave_group.authorize(ip_protocol='tcp', from_port=0, to_port=65535, + src_group=slave_group) + slave_group.authorize(ip_protocol='udp', from_port=0, to_port=65535, + src_group=slave_group) slave_group.authorize('tcp', 22, 22, authorized_address) slave_group.authorize('tcp', 8080, 8081, authorized_address) slave_group.authorize('tcp', 50060, 50060, authorized_address) @@ -341,11 +373,12 @@ def launch_cluster(conn, opts, cluster_name): if opts.ami is None: opts.ami = get_spark_ami(opts) - additional_groups = [] + # we use group ids to work around https://github.com/boto/boto/issues/350 + additional_group_ids = [] if opts.additional_security_group: - additional_groups = [sg - for sg in conn.get_all_security_groups() - if opts.additional_security_group in (sg.name, sg.id)] + additional_group_ids = [sg.id + for sg in conn.get_all_security_groups() + if opts.additional_security_group in (sg.name, sg.id)] print "Launching instances..." try: @@ -392,9 +425,10 @@ def launch_cluster(conn, opts, cluster_name): placement=zone, count=num_slaves_this_zone, key_name=opts.key_pair, - security_groups=[slave_group] + additional_groups, + security_group_ids=[slave_group.id] + additional_group_ids, instance_type=opts.instance_type, block_device_map=block_map, + subnet_id=opts.subnet_id, user_data=user_data_content) my_req_ids += [req.id for req in slave_reqs] i += 1 @@ -441,12 +475,13 @@ def launch_cluster(conn, opts, cluster_name): num_slaves_this_zone = get_partition(opts.slaves, num_zones, i) if num_slaves_this_zone > 0: slave_res = image.run(key_name=opts.key_pair, - security_groups=[slave_group] + additional_groups, + security_group_ids=[slave_group.id] + additional_group_ids, instance_type=opts.instance_type, placement=zone, min_count=num_slaves_this_zone, max_count=num_slaves_this_zone, block_device_map=block_map, + subnet_id=opts.subnet_id, user_data=user_data_content) slave_nodes += slave_res.instances print "Launched %d slaves in %s, regid = %s" % (num_slaves_this_zone, @@ -467,12 +502,13 @@ def launch_cluster(conn, opts, cluster_name): if opts.zone == 'all': opts.zone = random.choice(conn.get_all_zones()).name master_res = image.run(key_name=opts.key_pair, - security_groups=[master_group] + additional_groups, + security_group_ids=[master_group.id] + additional_group_ids, instance_type=master_type, placement=opts.zone, min_count=1, max_count=1, block_device_map=block_map, + subnet_id=opts.subnet_id, user_data=user_data_content) master_nodes = master_res.instances print "Launched master in %s, regid = %s" % (zone, master_res.id) From 17688d14299f18a93591818ae5fef69e9dc20eb5 Mon Sep 17 00:00:00 2001 From: Judy Nash Date: Tue, 16 Dec 2014 12:37:26 -0800 Subject: [PATCH 004/320] [SQL] SPARK-4700: Add HTTP protocol spark thrift server Add HTTP protocol support and test cases to spark thrift server, so users can deploy thrift server in both TCP and http mode. Author: Judy Nash Author: judynash Closes #3672 from judynash/master and squashes the following commits: 526315d [Judy Nash] correct spacing on startThriftServer method 31a6520 [Judy Nash] fix code style issues and update sql programming guide format issue 47bf87e [Judy Nash] modify withJdbcStatement method definition to meet less than 100 line length 2e9c11c [Judy Nash] add thrift server in http mode documentation on sql programming guide 1cbd305 [Judy Nash] Merge remote-tracking branch 'upstream/master' 2b1d312 [Judy Nash] updated http thrift server support based on feedback 377532c [judynash] add HTTP protocol spark thrift server --- docs/sql-programming-guide.md | 12 +++ .../hive/thriftserver/HiveThriftServer2.scala | 21 ++++- .../thriftserver/HiveThriftServer2Suite.scala | 77 +++++++++++++++---- 3 files changed, 93 insertions(+), 17 deletions(-) diff --git a/docs/sql-programming-guide.md b/docs/sql-programming-guide.md index be284fbe217a5..ad51b9cf416ed 100644 --- a/docs/sql-programming-guide.md +++ b/docs/sql-programming-guide.md @@ -938,6 +938,18 @@ Configuration of Hive is done by placing your `hive-site.xml` file in `conf/`. You may also use the beeline script that comes with Hive. +Thrift JDBC server also supports sending thrift RPC messages over HTTP transport. +Use the following setting to enable HTTP mode as system property or in `hive-site.xml` file in `conf/`: + + hive.server2.transport.mode - Set this to value: http + hive.server2.thrift.http.port - HTTP port number fo listen on; default is 10001 + hive.server2.http.endpoint - HTTP endpoint; default is cliservice + +To test, use beeline to connect to the JDBC/ODBC server in http mode with: + + beeline> !connect jdbc:hive2://:/?hive.server2.transport.mode=http;hive.server2.thrift.http.path= + + ## Running the Spark SQL CLI The Spark SQL CLI is a convenient tool to run the Hive metastore service in local mode and execute diff --git a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala index bd4e99492b395..c5b73234fa1de 100644 --- a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala +++ b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala @@ -19,7 +19,8 @@ package org.apache.spark.sql.hive.thriftserver import org.apache.commons.logging.LogFactory import org.apache.hadoop.hive.conf.HiveConf -import org.apache.hive.service.cli.thrift.ThriftBinaryCLIService +import org.apache.hadoop.hive.conf.HiveConf.ConfVars +import org.apache.hive.service.cli.thrift.{ThriftBinaryCLIService, ThriftHttpCLIService} import org.apache.hive.service.server.{HiveServer2, ServerOptionsProcessor} import org.apache.spark.Logging @@ -85,10 +86,22 @@ private[hive] class HiveThriftServer2(hiveContext: HiveContext) setSuperField(this, "cliService", sparkSqlCliService) addService(sparkSqlCliService) - val thriftCliService = new ThriftBinaryCLIService(sparkSqlCliService) - setSuperField(this, "thriftCLIService", thriftCliService) - addService(thriftCliService) + if (isHTTPTransportMode(hiveConf)) { + val thriftCliService = new ThriftHttpCLIService(sparkSqlCliService) + setSuperField(this, "thriftCLIService", thriftCliService) + addService(thriftCliService) + } else { + val thriftCliService = new ThriftBinaryCLIService(sparkSqlCliService) + setSuperField(this, "thriftCLIService", thriftCliService) + addService(thriftCliService) + } initCompositeService(hiveConf) } + + private def isHTTPTransportMode(hiveConf: HiveConf): Boolean = { + val transportMode: String = hiveConf.getVar(ConfVars.HIVE_SERVER2_TRANSPORT_MODE) + transportMode.equalsIgnoreCase("http") + } + } diff --git a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suite.scala b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suite.scala index 23d12cbff3495..94d5ed4f1d15e 100644 --- a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suite.scala +++ b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suite.scala @@ -70,11 +70,20 @@ class HiveThriftServer2Suite extends FunSuite with Logging { port } - def withJdbcStatement(serverStartTimeout: FiniteDuration = 1.minute)(f: Statement => Unit) { + def withJdbcStatement( + serverStartTimeout: FiniteDuration = 1.minute, + httpMode: Boolean = false)( + f: Statement => Unit) { val port = randomListeningPort - startThriftServer(port, serverStartTimeout) { - val jdbcUri = s"jdbc:hive2://${"localhost"}:$port/" + startThriftServer(port, serverStartTimeout, httpMode) { + val jdbcUri = if (httpMode) { + s"jdbc:hive2://${"localhost"}:$port/" + + "default?hive.server2.transport.mode=http;hive.server2.thrift.http.path=cliservice" + } else { + s"jdbc:hive2://${"localhost"}:$port/" + } + val user = System.getProperty("user.name") val connection = DriverManager.getConnection(jdbcUri, user, "") val statement = connection.createStatement() @@ -113,7 +122,8 @@ class HiveThriftServer2Suite extends FunSuite with Logging { def startThriftServer( port: Int, - serverStartTimeout: FiniteDuration = 1.minute)( + serverStartTimeout: FiniteDuration = 1.minute, + httpMode: Boolean = false)( f: => Unit) { val startScript = "../../sbin/start-thriftserver.sh".split("/").mkString(File.separator) val stopScript = "../../sbin/stop-thriftserver.sh".split("/").mkString(File.separator) @@ -121,15 +131,28 @@ class HiveThriftServer2Suite extends FunSuite with Logging { val warehousePath = getTempFilePath("warehouse") val metastorePath = getTempFilePath("metastore") val metastoreJdbcUri = s"jdbc:derby:;databaseName=$metastorePath;create=true" + val command = - s"""$startScript - | --master local - | --hiveconf hive.root.logger=INFO,console - | --hiveconf ${ConfVars.METASTORECONNECTURLKEY}=$metastoreJdbcUri - | --hiveconf ${ConfVars.METASTOREWAREHOUSE}=$warehousePath - | --hiveconf ${ConfVars.HIVE_SERVER2_THRIFT_BIND_HOST}=${"localhost"} - | --hiveconf ${ConfVars.HIVE_SERVER2_THRIFT_PORT}=$port - """.stripMargin.split("\\s+").toSeq + if (httpMode) { + s"""$startScript + | --master local + | --hiveconf hive.root.logger=INFO,console + | --hiveconf ${ConfVars.METASTORECONNECTURLKEY}=$metastoreJdbcUri + | --hiveconf ${ConfVars.METASTOREWAREHOUSE}=$warehousePath + | --hiveconf ${ConfVars.HIVE_SERVER2_THRIFT_BIND_HOST}=localhost + | --hiveconf ${ConfVars.HIVE_SERVER2_TRANSPORT_MODE}=http + | --hiveconf ${ConfVars.HIVE_SERVER2_THRIFT_HTTP_PORT}=$port + """.stripMargin.split("\\s+").toSeq + } else { + s"""$startScript + | --master local + | --hiveconf hive.root.logger=INFO,console + | --hiveconf ${ConfVars.METASTORECONNECTURLKEY}=$metastoreJdbcUri + | --hiveconf ${ConfVars.METASTOREWAREHOUSE}=$warehousePath + | --hiveconf ${ConfVars.HIVE_SERVER2_THRIFT_BIND_HOST}=localhost + | --hiveconf ${ConfVars.HIVE_SERVER2_THRIFT_PORT}=$port + """.stripMargin.split("\\s+").toSeq + } val serverRunning = Promise[Unit]() val buffer = new ArrayBuffer[String]() @@ -140,7 +163,8 @@ class HiveThriftServer2Suite extends FunSuite with Logging { def captureLogOutput(line: String): Unit = { buffer += line - if (line.contains("ThriftBinaryCLIService listening on")) { + if (line.contains("ThriftBinaryCLIService listening on") || + line.contains("Started ThriftHttpCLIService in http")) { serverRunning.success(()) } } @@ -217,6 +241,25 @@ class HiveThriftServer2Suite extends FunSuite with Logging { } } + test("Test JDBC query execution in Http Mode") { + withJdbcStatement(httpMode = true) { statement => + val queries = Seq( + "SET spark.sql.shuffle.partitions=3", + "DROP TABLE IF EXISTS test", + "CREATE TABLE test(key INT, val STRING)", + s"LOAD DATA LOCAL INPATH '${TestData.smallKv}' OVERWRITE INTO TABLE test", + "CACHE TABLE test") + + queries.foreach(statement.execute) + + assertResult(5, "Row count mismatch") { + val resultSet = statement.executeQuery("SELECT COUNT(*) FROM test") + resultSet.next() + resultSet.getInt(1) + } + } + } + test("SPARK-3004 regression: result set containing NULL") { withJdbcStatement() { statement => val queries = Seq( @@ -267,6 +310,14 @@ class HiveThriftServer2Suite extends FunSuite with Logging { } } + test("Checks Hive version in Http Mode") { + withJdbcStatement(httpMode = true) { statement => + val resultSet = statement.executeQuery("SET spark.sql.hive.version") + resultSet.next() + assert(resultSet.getString(1) === s"spark.sql.hive.version=${HiveShim.version}") + } + } + test("SPARK-4292 regression: result set iterator issue") { withJdbcStatement() { statement => val queries = Seq( From 1a9e35e57ab80984b81802ffc461d19cc9239edd Mon Sep 17 00:00:00 2001 From: Peter Vandenabeele Date: Tue, 16 Dec 2014 13:57:55 -0800 Subject: [PATCH 005/320] [DOCS][SQL] Add a Note on jsonFile having separate JSON objects per line * This commit hopes to avoid the confusion I faced when trying to submit a regular, valid multi-line JSON file, also see http://apache-spark-user-list.1001560.n3.nabble.com/Loading-JSON-Dataset-fails-with-com-fasterxml-jackson-databind-JsonMappingException-td20041.html Author: Peter Vandenabeele Closes #3517 from petervandenabeele/pv-docs-note-on-jsonFile-format/01 and squashes the following commits: 1f98e52 [Peter Vandenabeele] Revert to people.json and simple Note text 6b6e062 [Peter Vandenabeele] Change the "JSON" connotation to "txt" fca7dfb [Peter Vandenabeele] Add a Note on jsonFile having separate JSON objects per line --- docs/sql-programming-guide.md | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/docs/sql-programming-guide.md b/docs/sql-programming-guide.md index ad51b9cf416ed..2aea8a8aedafc 100644 --- a/docs/sql-programming-guide.md +++ b/docs/sql-programming-guide.md @@ -625,6 +625,10 @@ This conversion can be done using one of two methods in a SQLContext: * `jsonFile` - loads data from a directory of JSON files where each line of the files is a JSON object. * `jsonRDD` - loads data from an existing RDD where each element of the RDD is a string containing a JSON object. +Note that the file that is offered as _jsonFile_ is not a typical JSON file. Each +line must contain a separate, self-contained valid JSON object. As a consequence, +a regular multi-line JSON file will most often fail. + {% highlight scala %} // sc is an existing SparkContext. val sqlContext = new org.apache.spark.sql.SQLContext(sc) @@ -663,6 +667,10 @@ This conversion can be done using one of two methods in a JavaSQLContext : * `jsonFile` - loads data from a directory of JSON files where each line of the files is a JSON object. * `jsonRDD` - loads data from an existing RDD where each element of the RDD is a string containing a JSON object. +Note that the file that is offered as _jsonFile_ is not a typical JSON file. Each +line must contain a separate, self-contained valid JSON object. As a consequence, +a regular multi-line JSON file will most often fail. + {% highlight java %} // sc is an existing JavaSparkContext. JavaSQLContext sqlContext = new org.apache.spark.sql.api.java.JavaSQLContext(sc); @@ -701,6 +709,10 @@ This conversion can be done using one of two methods in a SQLContext: * `jsonFile` - loads data from a directory of JSON files where each line of the files is a JSON object. * `jsonRDD` - loads data from an existing RDD where each element of the RDD is a string containing a JSON object. +Note that the file that is offered as _jsonFile_ is not a typical JSON file. Each +line must contain a separate, self-contained valid JSON object. As a consequence, +a regular multi-line JSON file will most often fail. + {% highlight python %} # sc is an existing SparkContext. from pyspark.sql import SQLContext From dc8280dcca7b54793a3db644f74fd33460960d4a Mon Sep 17 00:00:00 2001 From: jerryshao Date: Tue, 16 Dec 2014 14:08:28 -0800 Subject: [PATCH 006/320] [SPARK-4847][SQL]Fix "extraStrategies cannot take effect in SQLContext" issue Author: jerryshao Closes #3698 from jerryshao/SPARK-4847 and squashes the following commits: 4741130 [jerryshao] Make later added extraStrategies effect when calling strategies --- sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala | 2 +- .../src/main/scala/org/apache/spark/sql/hive/HiveContext.scala | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala index 31cc4170aa867..ebd4cc920b1ad 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala @@ -327,7 +327,7 @@ class SQLContext(@transient val sparkContext: SparkContext) def numPartitions = self.numShufflePartitions - val strategies: Seq[Strategy] = + def strategies: Seq[Strategy] = extraStrategies ++ ( CommandStrategy(self) :: DataSourceStrategy :: diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala index 6008e46fefa86..7de440773023f 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala @@ -338,7 +338,7 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { val hivePlanner = new SparkPlanner with HiveStrategies { val hiveContext = self - override val strategies: Seq[Strategy] = extraStrategies ++ Seq( + override def strategies: Seq[Strategy] = extraStrategies ++ Seq( DataSourceStrategy, CommandStrategy(self), HiveCommandStrategy(self), From 6530243a52b05007e566d458cd8f075e851e91f1 Mon Sep 17 00:00:00 2001 From: zsxwing Date: Tue, 16 Dec 2014 14:13:40 -0800 Subject: [PATCH 007/320] [SPARK-4812][SQL] Fix the initialization issue of 'codegenEnabled' The problem is `codegenEnabled` is `val`, but it uses a `val` `sqlContext`, which can be override by subclasses. Here is a simple example to show this issue. ```Scala scala> :paste // Entering paste mode (ctrl-D to finish) abstract class Foo { protected val sqlContext = "Foo" val codegenEnabled: Boolean = { println(sqlContext) // it will call subclass's `sqlContext` which has not yet been initialized. if (sqlContext != null) { true } else { false } } } class Bar extends Foo { override val sqlContext = "Bar" } println(new Bar().codegenEnabled) // Exiting paste mode, now interpreting. null false defined class Foo defined class Bar ``` We should make `sqlContext` `final` to prevent subclasses from overriding it incorrectly. Author: zsxwing Closes #3660 from zsxwing/SPARK-4812 and squashes the following commits: 1cbb623 [zsxwing] Make `sqlContext` final to prevent subclasses from overriding it incorrectly --- .../apache/spark/sql/columnar/InMemoryColumnarTableScan.scala | 2 -- .../main/scala/org/apache/spark/sql/execution/SparkPlan.scala | 2 +- 2 files changed, 1 insertion(+), 3 deletions(-) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala index 0cebe823b2707..1e432485c4c29 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala @@ -175,8 +175,6 @@ private[sql] case class InMemoryColumnarTableScan( relation: InMemoryRelation) extends LeafNode { - @transient override val sqlContext = relation.child.sqlContext - override def output: Seq[Attribute] = attributes private def statsFor(a: Attribute) = relation.partitionStatistics.forAttribute(a) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala index 4cd8e7d657250..017c78d2c66d4 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala @@ -44,7 +44,7 @@ abstract class SparkPlan extends QueryPlan[SparkPlan] with Logging with Serializ * populated by the query planning infrastructure. */ @transient - protected[spark] val sqlContext = SparkPlan.currentContext.get() + protected[spark] final val sqlContext = SparkPlan.currentContext.get() protected def sparkContext = sqlContext.sparkContext From b0dfdbdd181d1eea83d70dd0959297903952dd74 Mon Sep 17 00:00:00 2001 From: Holden Karau Date: Tue, 16 Dec 2014 14:37:04 -0800 Subject: [PATCH 008/320] SPARK-4767: Add support for launching in a specified placement group to spark_ec2 Placement groups are cool and all the cool kids are using them. Lets add support for them to spark_ec2.py because I'm lazy Author: Holden Karau Closes #3623 from holdenk/SPARK-4767-add-support-for-launching-in-a-specified-placement-group-to-spark-ec2-scripts and squashes the following commits: 111a5fd [Holden Karau] merge in master 70ace25 [Holden Karau] Placement groups are cool and all the cool kids are using them. Lets add support for them to spark_ec2.py because I'm lazy --- ec2/spark_ec2.py | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/ec2/spark_ec2.py b/ec2/spark_ec2.py index 92adfd2d07b5b..4e8f5c1f44041 100755 --- a/ec2/spark_ec2.py +++ b/ec2/spark_ec2.py @@ -120,6 +120,10 @@ def parse_args(): "Only possible on EBS-backed AMIs. " + "EBS volumes are only attached if --ebs-vol-size > 0." + "Only support up to 8 EBS volumes.") + parser.add_option("--placement-group", type="string", default=None, + help="Which placement group to try and launch " + + "instances into. Assumes placement group is already " + + "created.") parser.add_option( "--swap", metavar="SWAP", type="int", default=1024, help="Swap space to set up per node, in MB (default: %default)") @@ -429,6 +433,7 @@ def launch_cluster(conn, opts, cluster_name): instance_type=opts.instance_type, block_device_map=block_map, subnet_id=opts.subnet_id, + placement_group=opts.placement_group, user_data=user_data_content) my_req_ids += [req.id for req in slave_reqs] i += 1 @@ -482,6 +487,7 @@ def launch_cluster(conn, opts, cluster_name): max_count=num_slaves_this_zone, block_device_map=block_map, subnet_id=opts.subnet_id, + placement_group=opts.placement_group, user_data=user_data_content) slave_nodes += slave_res.instances print "Launched %d slaves in %s, regid = %s" % (num_slaves_this_zone, @@ -509,7 +515,9 @@ def launch_cluster(conn, opts, cluster_name): max_count=1, block_device_map=block_map, subnet_id=opts.subnet_id, + placement_group=opts.placement_group, user_data=user_data_content) + master_nodes = master_res.instances print "Launched master in %s, regid = %s" % (zone, master_res.id) From ea1315e3e26507c8e1cab877cec5fe69c2899ae8 Mon Sep 17 00:00:00 2001 From: wangxiaojing Date: Tue, 16 Dec 2014 14:45:56 -0800 Subject: [PATCH 009/320] [SPARK-4527][SQl]Add BroadcastNestedLoopJoin operator selection testsuite In `JoinSuite` add BroadcastNestedLoopJoin operator selection testsuite Author: wangxiaojing Closes #3395 from wangxiaojing/SPARK-4527 and squashes the following commits: ea0e495 [wangxiaojing] change style 53c3952 [wangxiaojing] Add BroadcastNestedLoopJoin operator selection testsuite --- .../src/test/scala/org/apache/spark/sql/JoinSuite.scala | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala index 8b4cf5bac0187..0378fd7e367f0 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala @@ -80,8 +80,13 @@ class JoinSuite extends QueryTest with BeforeAndAfterEach { classOf[HashOuterJoin]), ("SELECT * FROM testData right join testData2 ON key = a and key = 2", classOf[HashOuterJoin]), - ("SELECT * FROM testData full outer join testData2 ON key = a", classOf[HashOuterJoin]) - // TODO add BroadcastNestedLoopJoin + ("SELECT * FROM testData full outer join testData2 ON key = a", classOf[HashOuterJoin]), + ("SELECT * FROM testData left JOIN testData2 ON (key * a != key + a)", + classOf[BroadcastNestedLoopJoin]), + ("SELECT * FROM testData right JOIN testData2 ON (key * a != key + a)", + classOf[BroadcastNestedLoopJoin]), + ("SELECT * FROM testData full JOIN testData2 ON (key * a != key + a)", + classOf[BroadcastNestedLoopJoin]) ).foreach { case (query, joinClass) => assertJoin(query, joinClass) } } From 30f6b85c816d1ef611a7be071af0053d64b6fe9e Mon Sep 17 00:00:00 2001 From: tianyi Date: Tue, 16 Dec 2014 15:22:29 -0800 Subject: [PATCH 010/320] [SPARK-4483][SQL]Optimization about reduce memory costs during the HashOuterJoin MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit In `HashOuterJoin.scala`, spark read data from both side of join operation before zip them together. It is a waste for memory. We are trying to read data from only one side, put them into a hashmap, and then generate the `JoinedRow` with data from other side one by one. Currently, we could only do this optimization for `left outer join` and `right outer join`. For `full outer join`, we will do something in another issue. for table test_csv contains 1 million records table dim_csv contains 10 thousand records SQL: `select * from test_csv a left outer join dim_csv b on a.key = b.key` the result is: master: ``` CSV: 12671 ms CSV: 9021 ms CSV: 9200 ms Current Mem Usage:787788984 ``` after patch： ``` CSV: 10382 ms CSV: 7543 ms CSV: 7469 ms Current Mem Usage:208145728 ``` Author: tianyi Author: tianyi Closes #3375 from tianyi/SPARK-4483 and squashes the following commits: 72a8aec [tianyi] avoid having mutable state stored inside of the task 99c5c97 [tianyi] performance optimization d2f94d7 [tianyi] fix bug: missing output when the join-key is null. 2be45d1 [tianyi] fix spell bug 1f2c6f1 [tianyi] remove commented codes a676de6 [tianyi] optimize some codes 9e7d5b5 [tianyi] remove commented old codes 838707d [tianyi] Optimization about reduce memory costs during the HashOuterJoin --- .../sql/execution/joins/HashOuterJoin.scala | 128 +++++++++--------- 1 file changed, 64 insertions(+), 64 deletions(-) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashOuterJoin.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashOuterJoin.scala index b73041d306b36..59ef904272545 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashOuterJoin.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashOuterJoin.scala @@ -68,66 +68,56 @@ case class HashOuterJoin( @transient private[this] lazy val DUMMY_LIST = Seq[Row](null) @transient private[this] lazy val EMPTY_LIST = Seq.empty[Row] + @transient private[this] lazy val leftNullRow = new GenericRow(left.output.length) + @transient private[this] lazy val rightNullRow = new GenericRow(right.output.length) + @transient private[this] lazy val boundCondition = + condition.map(newPredicate(_, left.output ++ right.output)).getOrElse((row: Row) => true) + // TODO we need to rewrite all of the iterators with our own implementation instead of the Scala // iterator for performance purpose. private[this] def leftOuterIterator( - key: Row, leftIter: Iterable[Row], rightIter: Iterable[Row]): Iterator[Row] = { - val joinedRow = new JoinedRow() - val rightNullRow = new GenericRow(right.output.length) - val boundCondition = - condition.map(newPredicate(_, left.output ++ right.output)).getOrElse((row: Row) => true) - - leftIter.iterator.flatMap { l => - joinedRow.withLeft(l) - var matched = false - (if (!key.anyNull) rightIter.collect { case r if (boundCondition(joinedRow.withRight(r))) => - matched = true - joinedRow.copy + key: Row, joinedRow: JoinedRow, rightIter: Iterable[Row]): Iterator[Row] = { + val ret: Iterable[Row] = ( + if (!key.anyNull) { + val temp = rightIter.collect { + case r if (boundCondition(joinedRow.withRight(r))) => joinedRow.copy + } + if (temp.size == 0) { + joinedRow.withRight(rightNullRow).copy :: Nil + } else { + temp + } } else { - Nil - }) ++ DUMMY_LIST.filter(_ => !matched).map( _ => { - // DUMMY_LIST.filter(_ => !matched) is a tricky way to add additional row, - // as we don't know whether we need to append it until finish iterating all of the - // records in right side. - // If we didn't get any proper row, then append a single row with empty right - joinedRow.withRight(rightNullRow).copy - }) - } + joinedRow.withRight(rightNullRow).copy :: Nil + } + ) + ret.iterator } private[this] def rightOuterIterator( - key: Row, leftIter: Iterable[Row], rightIter: Iterable[Row]): Iterator[Row] = { - val joinedRow = new JoinedRow() - val leftNullRow = new GenericRow(left.output.length) - val boundCondition = - condition.map(newPredicate(_, left.output ++ right.output)).getOrElse((row: Row) => true) - - rightIter.iterator.flatMap { r => - joinedRow.withRight(r) - var matched = false - (if (!key.anyNull) leftIter.collect { case l if (boundCondition(joinedRow.withLeft(l))) => - matched = true - joinedRow.copy + key: Row, leftIter: Iterable[Row], joinedRow: JoinedRow): Iterator[Row] = { + + val ret: Iterable[Row] = ( + if (!key.anyNull) { + val temp = leftIter.collect { + case l if (boundCondition(joinedRow.withLeft(l))) => joinedRow.copy + } + if (temp.size == 0) { + joinedRow.withLeft(leftNullRow).copy :: Nil + } else { + temp + } } else { - Nil - }) ++ DUMMY_LIST.filter(_ => !matched).map( _ => { - // DUMMY_LIST.filter(_ => !matched) is a tricky way to add additional row, - // as we don't know whether we need to append it until finish iterating all of the - // records in left side. - // If we didn't get any proper row, then append a single row with empty left. - joinedRow.withLeft(leftNullRow).copy - }) - } + joinedRow.withLeft(leftNullRow).copy :: Nil + } + ) + ret.iterator } private[this] def fullOuterIterator( - key: Row, leftIter: Iterable[Row], rightIter: Iterable[Row]): Iterator[Row] = { - val joinedRow = new JoinedRow() - val leftNullRow = new GenericRow(left.output.length) - val rightNullRow = new GenericRow(right.output.length) - val boundCondition = - condition.map(newPredicate(_, left.output ++ right.output)).getOrElse((row: Row) => true) + key: Row, leftIter: Iterable[Row], rightIter: Iterable[Row], + joinedRow: JoinedRow): Iterator[Row] = { if (!key.anyNull) { // Store the positions of records in right, if one of its associated row satisfy @@ -193,27 +183,37 @@ case class HashOuterJoin( } override def execute() = { + val joinedRow = new JoinedRow() left.execute().zipPartitions(right.execute()) { (leftIter, rightIter) => // TODO this probably can be replaced by external sort (sort merged join?) - // Build HashMap for current partition in left relation - val leftHashTable = buildHashTable(leftIter, newProjection(leftKeys, left.output)) - // Build HashMap for current partition in right relation - val rightHashTable = buildHashTable(rightIter, newProjection(rightKeys, right.output)) - val boundCondition = - condition.map(newPredicate(_, left.output ++ right.output)).getOrElse((row: Row) => true) + joinType match { - case LeftOuter => leftHashTable.keysIterator.flatMap { key => - leftOuterIterator(key, leftHashTable.getOrElse(key, EMPTY_LIST), - rightHashTable.getOrElse(key, EMPTY_LIST)) + case LeftOuter => { + val rightHashTable = buildHashTable(rightIter, newProjection(rightKeys, right.output)) + val keyGenerator = newProjection(leftKeys, left.output) + leftIter.flatMap( currentRow => { + val rowKey = keyGenerator(currentRow) + joinedRow.withLeft(currentRow) + leftOuterIterator(rowKey, joinedRow, rightHashTable.getOrElse(rowKey, EMPTY_LIST)) + }) } - case RightOuter => rightHashTable.keysIterator.flatMap { key => - rightOuterIterator(key, leftHashTable.getOrElse(key, EMPTY_LIST), - rightHashTable.getOrElse(key, EMPTY_LIST)) + case RightOuter => { + val leftHashTable = buildHashTable(leftIter, newProjection(leftKeys, left.output)) + val keyGenerator = newProjection(rightKeys, right.output) + rightIter.flatMap ( currentRow => { + val rowKey = keyGenerator(currentRow) + joinedRow.withRight(currentRow) + rightOuterIterator(rowKey, leftHashTable.getOrElse(rowKey, EMPTY_LIST), joinedRow) + }) } - case FullOuter => (leftHashTable.keySet ++ rightHashTable.keySet).iterator.flatMap { key => - fullOuterIterator(key, - leftHashTable.getOrElse(key, EMPTY_LIST), - rightHashTable.getOrElse(key, EMPTY_LIST)) + case FullOuter => { + val leftHashTable = buildHashTable(leftIter, newProjection(leftKeys, left.output)) + val rightHashTable = buildHashTable(rightIter, newProjection(rightKeys, right.output)) + (leftHashTable.keySet ++ rightHashTable.keySet).iterator.flatMap { key => + fullOuterIterator(key, + leftHashTable.getOrElse(key, EMPTY_LIST), + rightHashTable.getOrElse(key, EMPTY_LIST), joinedRow) + } } case x => throw new Exception(s"HashOuterJoin should not take $x as the JoinType") } From a66c23e134a0b1ad9540626fb7436d70d577d929 Mon Sep 17 00:00:00 2001 From: Michael Armbrust Date: Tue, 16 Dec 2014 15:31:19 -0800 Subject: [PATCH 011/320] [SPARK-4827][SQL] Fix resolution of deeply nested Project(attr, Project(Star,...)). Since `AttributeReference` resolution and `*` expansion are currently in separate rules, each pair requires a full iteration instead of being able to resolve in a single pass. Since its pretty easy to construct queries that have many of these in a row, I combine them into a single rule in this PR. Author: Michael Armbrust Closes #3674 from marmbrus/projectStars and squashes the following commits: d83d6a1 [Michael Armbrust] Fix resolution of deeply nested Project(attr, Project(Star,...)). --- .../sql/catalyst/analysis/Analyzer.scala | 75 +++++++++---------- .../sql/catalyst/analysis/AnalysisSuite.scala | 12 ++- 2 files changed, 45 insertions(+), 42 deletions(-) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala index 04639219a3650..ea9bb3978691a 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala @@ -58,7 +58,6 @@ class Analyzer(catalog: Catalog, ResolveSortReferences :: NewRelationInstances :: ImplicitGenerate :: - StarExpansion :: ResolveFunctions :: GlobalAggregates :: UnresolvedHavingClauseAttributes :: @@ -153,7 +152,34 @@ class Analyzer(catalog: Catalog, */ object ResolveReferences extends Rule[LogicalPlan] { def apply(plan: LogicalPlan): LogicalPlan = plan transformUp { - case q: LogicalPlan if q.childrenResolved => + case p: LogicalPlan if !p.childrenResolved => p + + // If the projection list contains Stars, expand it. + case p@Project(projectList, child) if containsStar(projectList) => + Project( + projectList.flatMap { + case s: Star => s.expand(child.output, resolver) + case o => o :: Nil + }, + child) + case t: ScriptTransformation if containsStar(t.input) => + t.copy( + input = t.input.flatMap { + case s: Star => s.expand(t.child.output, resolver) + case o => o :: Nil + } + ) + + // If the aggregate function argument contains Stars, expand it. + case a: Aggregate if containsStar(a.aggregateExpressions) => + a.copy( + aggregateExpressions = a.aggregateExpressions.flatMap { + case s: Star => s.expand(a.child.output, resolver) + case o => o :: Nil + } + ) + + case q: LogicalPlan => logTrace(s"Attempting to resolve ${q.simpleString}") q transformExpressions { case u @ UnresolvedAttribute(name) => @@ -163,6 +189,12 @@ class Analyzer(catalog: Catalog, result } } + + /** + * Returns true if `exprs` contains a [[Star]]. + */ + protected def containsStar(exprs: Seq[Expression]): Boolean = + exprs.collect { case _: Star => true}.nonEmpty } /** @@ -277,45 +309,6 @@ class Analyzer(catalog: Catalog, Generate(g, join = false, outer = false, None, child) } } - - /** - * Expands any references to [[Star]] (*) in project operators. - */ - object StarExpansion extends Rule[LogicalPlan] { - def apply(plan: LogicalPlan): LogicalPlan = plan transform { - // Wait until children are resolved - case p: LogicalPlan if !p.childrenResolved => p - // If the projection list contains Stars, expand it. - case p @ Project(projectList, child) if containsStar(projectList) => - Project( - projectList.flatMap { - case s: Star => s.expand(child.output, resolver) - case o => o :: Nil - }, - child) - case t: ScriptTransformation if containsStar(t.input) => - t.copy( - input = t.input.flatMap { - case s: Star => s.expand(t.child.output, resolver) - case o => o :: Nil - } - ) - // If the aggregate function argument contains Stars, expand it. - case a: Aggregate if containsStar(a.aggregateExpressions) => - a.copy( - aggregateExpressions = a.aggregateExpressions.flatMap { - case s: Star => s.expand(a.child.output, resolver) - case o => o :: Nil - } - ) - } - - /** - * Returns true if `exprs` contains a [[Star]]. - */ - protected def containsStar(exprs: Seq[Expression]): Boolean = - exprs.collect { case _: Star => true }.nonEmpty - } } /** diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala index 33a3cba3d4c0e..82f2101d8ce17 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala @@ -19,12 +19,14 @@ package org.apache.spark.sql.catalyst.analysis import org.scalatest.{BeforeAndAfter, FunSuite} -import org.apache.spark.sql.catalyst.dsl.expressions._ import org.apache.spark.sql.catalyst.expressions.{Alias, AttributeReference} import org.apache.spark.sql.catalyst.errors.TreeNodeException import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.catalyst.dsl.expressions._ +import org.apache.spark.sql.catalyst.dsl.plans._ + class AnalysisSuite extends FunSuite with BeforeAndAfter { val caseSensitiveCatalog = new SimpleCatalog(true) val caseInsensitiveCatalog = new SimpleCatalog(false) @@ -46,6 +48,14 @@ class AnalysisSuite extends FunSuite with BeforeAndAfter { caseInsensitiveCatalog.registerTable(None, "TaBlE", testRelation) } + test("union project *") { + val plan = (1 to 100) + .map(_ => testRelation) + .fold[LogicalPlan](testRelation)((a,b) => a.select(Star(None)).select('a).unionAll(b.select(Star(None)))) + + assert(caseInsensitiveAnalyze(plan).resolved) + } + test("analyze project") { assert( caseSensitiveAnalyze(Project(Seq(UnresolvedAttribute("a")), testRelation)) === From fa66ef6c97e87c9255b67b03836a4ba50598ebae Mon Sep 17 00:00:00 2001 From: Jacky Li Date: Tue, 16 Dec 2014 15:34:59 -0800 Subject: [PATCH 012/320] [SPARK-4269][SQL] make wait time configurable in BroadcastHashJoin In BroadcastHashJoin, currently it is using a hard coded value (5 minutes) to wait for the execution and broadcast of the small table. In my opinion, it should be a configurable value since broadcast may exceed 5 minutes in some case, like in a busy/congested network environment. Author: Jacky Li Closes #3133 from jackylk/timeout-config and squashes the following commits: 733ac08 [Jacky Li] add spark.sql.broadcastTimeout in SQLConf.scala 557acd4 [Jacky Li] switch to sqlContext.getConf 81a5e20 [Jacky Li] make wait time configurable in BroadcastHashJoin --- .../src/main/scala/org/apache/spark/sql/SQLConf.scala | 7 +++++++ .../spark/sql/execution/joins/BroadcastHashJoin.scala | 11 ++++++++++- 2 files changed, 17 insertions(+), 1 deletion(-) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala index 9697beb132fbb..f5abf71d6c7b9 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala @@ -38,6 +38,7 @@ private[spark] object SQLConf { val PARQUET_FILTER_PUSHDOWN_ENABLED = "spark.sql.parquet.filterPushdown" val COLUMN_NAME_OF_CORRUPT_RECORD = "spark.sql.columnNameOfCorruptRecord" + val BROADCAST_TIMEOUT = "spark.sql.broadcastTimeout" // Options that control which operators can be chosen by the query planner. These should be // considered hints and may be ignored by future versions of Spark SQL. @@ -148,6 +149,12 @@ private[sql] trait SQLConf { private[spark] def columnNameOfCorruptRecord: String = getConf(COLUMN_NAME_OF_CORRUPT_RECORD, "_corrupt_record") + /** + * Timeout in seconds for the broadcast wait time in hash join + */ + private[spark] def broadcastTimeout: Int = + getConf(BROADCAST_TIMEOUT, (5 * 60).toString).toInt + /** ********************** SQLConf functionality methods ************ */ /** Set Spark SQL configuration properties. */ diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastHashJoin.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastHashJoin.scala index 5cf2a785adc7d..fbe1d06ed2e82 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastHashJoin.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastHashJoin.scala @@ -42,6 +42,15 @@ case class BroadcastHashJoin( right: SparkPlan) extends BinaryNode with HashJoin { + val timeout = { + val timeoutValue = sqlContext.broadcastTimeout + if (timeoutValue < 0) { + Duration.Inf + } else { + timeoutValue.seconds + } + } + override def outputPartitioning: Partitioning = streamedPlan.outputPartitioning override def requiredChildDistribution = @@ -56,7 +65,7 @@ case class BroadcastHashJoin( } override def execute() = { - val broadcastRelation = Await.result(broadcastFuture, 5.minute) + val broadcastRelation = Await.result(broadcastFuture, timeout) streamedPlan.execute().mapPartitions { streamedIter => hashJoin(streamedIter, broadcastRelation.value) From 6f80b749e0f23f2f5c83993b87f73c8943b99db8 Mon Sep 17 00:00:00 2001 From: Andrew Or Date: Tue, 16 Dec 2014 17:55:27 -0800 Subject: [PATCH 013/320] [Release] Major improvements to generate contributors script This commit introduces several major improvements to the script that generates the contributors list for release notes, notably: (1) Use release tags instead of a range of commits. Across branches, commits are not actually strictly two-dimensional, and so it is not sufficient to specify a start hash and an end hash. Otherwise, we end up counting commits that were already merged in an older branch. (2) Match PR numbers in addition to commit hashes. This is related to the first point in that if a PR is already merged in an older minor release tag, it should be filtered out here. This requires us to do some intelligent regex parsing on the commit description in addition to just relying on the GitHub API. (3) Relax author validity check. The old code fails on a name that has many middle names, for instance. The test was just too strict. (4) Use GitHub authentication. This allows us to make far more requests through the GitHub API than before (5000 as opposed to 60 per hour). (5) Translate from Github username, not commit author name. This is important because the commit author name is not always configured correctly by the user. For instance, the username "falaki" used to resolve to just "Hossein", which was treated as a github username and translated to something else that is completely arbitrary. (6) Add an option to use the untranslated name. If there is not a satisfactory candidate to replace the untranslated name with, at least allow the user to not translate it. --- dev/create-release/generate-contributors.py | 156 +++++++++++-------- dev/create-release/releaseutils.py | 94 +++++++++-- dev/create-release/translate-contributors.py | 45 ++++-- 3 files changed, 206 insertions(+), 89 deletions(-) diff --git a/dev/create-release/generate-contributors.py b/dev/create-release/generate-contributors.py index a3b78a3eac6d0..e8f81ccbce740 100755 --- a/dev/create-release/generate-contributors.py +++ b/dev/create-release/generate-contributors.py @@ -26,75 +26,103 @@ # You must set the following before use! JIRA_API_BASE = os.environ.get("JIRA_API_BASE", "https://issues.apache.org/jira") -START_COMMIT = os.environ.get("START_COMMIT", "37b100") -END_COMMIT = os.environ.get("END_COMMIT", "3693ae") - -# If commit range is not specified, prompt the user to provide it -if not START_COMMIT or not END_COMMIT: - print "A commit range is required to proceed." - if not START_COMMIT: - START_COMMIT = raw_input("Please specify starting commit hash (inclusive): ") - if not END_COMMIT: - END_COMMIT = raw_input("Please specify ending commit hash (non-inclusive): ") - -# Verify provided arguments -start_commit_line = get_one_line(START_COMMIT) -end_commit_line = get_one_line(END_COMMIT) -num_commits = num_commits_in_range(START_COMMIT, END_COMMIT) -if not start_commit_line: sys.exit("Start commit %s not found!" % START_COMMIT) -if not end_commit_line: sys.exit("End commit %s not found!" % END_COMMIT) -if num_commits == 0: - sys.exit("There are no commits in the provided range [%s, %s)" % (START_COMMIT, END_COMMIT)) +RELEASE_TAG = os.environ.get("START_COMMIT", "v1.2.0-rc2") +PREVIOUS_RELEASE_TAG = os.environ.get("END_COMMIT", "v1.1.0") + +# If the release tags are not provided, prompt the user to provide them +while not tag_exists(RELEASE_TAG): + RELEASE_TAG = raw_input("Please provide a valid release tag: ") +while not tag_exists(PREVIOUS_RELEASE_TAG): + print "Please specify the previous release tag." + PREVIOUS_RELEASE_TAG = raw_input(\ + "For instance, if you are releasing v1.2.0, you should specify v1.1.0: ") + +# Gather commits found in the new tag but not in the old tag. +# This filters commits based on both the git hash and the PR number. +# If either is present in the old tag, then we ignore the commit. +print "Gathering new commits between tags %s and %s" % (PREVIOUS_RELEASE_TAG, RELEASE_TAG) +release_commits = get_commits(RELEASE_TAG) +previous_release_commits = get_commits(PREVIOUS_RELEASE_TAG) +previous_release_hashes = set() +previous_release_prs = set() +for old_commit in previous_release_commits: + previous_release_hashes.add(old_commit.get_hash()) + if old_commit.get_pr_number(): + previous_release_prs.add(old_commit.get_pr_number()) +new_commits = [] +for this_commit in release_commits: + this_hash = this_commit.get_hash() + this_pr_number = this_commit.get_pr_number() + if this_hash in previous_release_hashes: + continue + if this_pr_number and this_pr_number in previous_release_prs: + continue + new_commits.append(this_commit) +if not new_commits: + sys.exit("There are no new commits between %s and %s!" % (PREVIOUS_RELEASE_TAG, RELEASE_TAG)) + +# Prompt the user for confirmation that the commit range is correct print "\n==================================================================================" print "JIRA server: %s" % JIRA_API_BASE -print "Start commit (inclusive): %s" % start_commit_line -print "End commit (non-inclusive): %s" % end_commit_line -print "Number of commits in this range: %s" % num_commits +print "Release tag: %s" % RELEASE_TAG +print "Previous release tag: %s" % PREVIOUS_RELEASE_TAG +print "Number of commits in this range: %s" % len(new_commits) print -response = raw_input("Is this correct? [Y/n] ") -if response.lower() != "y" and response: - sys.exit("Ok, exiting") +def print_indented(_list): + for x in _list: print " %s" % x +if yesOrNoPrompt("Show all commits?"): + print_indented(new_commits) print "==================================================================================\n" - -# Find all commits within this range -print "Gathering commits within range [%s..%s)" % (START_COMMIT, END_COMMIT) -commits = get_one_line_commits(START_COMMIT, END_COMMIT) -if not commits: sys.exit("Error: No commits found within this range!") -commits = commits.split("\n") +if not yesOrNoPrompt("Does this look correct?"): + sys.exit("Ok, exiting") # Filter out special commits releases = [] +maintenance = [] reverts = [] nojiras = [] filtered_commits = [] -def is_release(commit): - return re.findall("\[release\]", commit.lower()) or\ - "maven-release-plugin" in commit or "CHANGES.txt" in commit -def has_no_jira(commit): - return not re.findall("SPARK-[0-9]+", commit.upper()) -def is_revert(commit): - return "revert" in commit.lower() -def is_docs(commit): - return re.findall("docs*", commit.lower()) or "programming guide" in commit.lower() -for c in commits: - if not c: continue - elif is_release(c): releases.append(c) - elif is_revert(c): reverts.append(c) - elif is_docs(c): filtered_commits.append(c) # docs may not have JIRA numbers - elif has_no_jira(c): nojiras.append(c) +def is_release(commit_title): + return re.findall("\[release\]", commit_title.lower()) or\ + "preparing spark release" in commit_title.lower() or\ + "preparing development version" in commit_title.lower() or\ + "CHANGES.txt" in commit_title +def is_maintenance(commit_title): + return "maintenance" in commit_title.lower() or\ + "manually close" in commit_title.lower() +def has_no_jira(commit_title): + return not re.findall("SPARK-[0-9]+", commit_title.upper()) +def is_revert(commit_title): + return "revert" in commit_title.lower() +def is_docs(commit_title): + return re.findall("docs*", commit_title.lower()) or\ + "programming guide" in commit_title.lower() +for c in new_commits: + t = c.get_title() + if not t: continue + elif is_release(t): releases.append(c) + elif is_maintenance(t): maintenance.append(c) + elif is_revert(t): reverts.append(c) + elif is_docs(t): filtered_commits.append(c) # docs may not have JIRA numbers + elif has_no_jira(t): nojiras.append(c) else: filtered_commits.append(c) # Warn against ignored commits -def print_indented(_list): - for x in _list: print " %s" % x -if releases or reverts or nojiras: +if releases or maintenance or reverts or nojiras: print "\n==================================================================================" - if releases: print "Releases (%d)" % len(releases); print_indented(releases) - if reverts: print "Reverts (%d)" % len(reverts); print_indented(reverts) - if nojiras: print "No JIRA (%d)" % len(nojiras); print_indented(nojiras) + if releases: print "Found %d release commits" % len(releases) + if maintenance: print "Found %d maintenance commits" % len(maintenance) + if reverts: print "Found %d revert commits" % len(reverts) + if nojiras: print "Found %d commits with no JIRA" % len(nojiras) + print "* Warning: these commits will be ignored.\n" + if yesOrNoPrompt("Show ignored commits?"): + if releases: print "Release (%d)" % len(releases); print_indented(releases) + if maintenance: print "Maintenance (%d)" % len(maintenance); print_indented(maintenance) + if reverts: print "Revert (%d)" % len(reverts); print_indented(reverts) + if nojiras: print "No JIRA (%d)" % len(nojiras); print_indented(nojiras) print "==================== Warning: the above commits will be ignored ==================\n" -response = raw_input("%d commits left to process. Ok to proceed? [Y/n] " % len(filtered_commits)) -if response.lower() != "y" and response: +prompt_msg = "%d commits left to process after filtering. Ok to proceed?" % len(filtered_commits) +if not yesOrNoPrompt(prompt_msg): sys.exit("Ok, exiting.") # Keep track of warnings to tell the user at the end @@ -123,10 +151,11 @@ def print_indented(_list): jira_client = JIRA(options = jira_options) print "\n=========================== Compiling contributor list ===========================" for commit in filtered_commits: - commit_hash = re.findall("^[a-z0-9]+", commit)[0] - issues = re.findall("SPARK-[0-9]+", commit.upper()) - author = get_author(commit_hash) - author = unidecode.unidecode(unicode(author, "UTF-8")).strip() # guard against special characters + _hash = commit.get_hash() + title = commit.get_title() + issues = re.findall("SPARK-[0-9]+", title.upper()) + author = commit.get_author() + date = get_date(_hash) # If the author name is invalid, keep track of it along # with all associated issues so we can translate it later if is_valid_author(author): @@ -136,9 +165,8 @@ def print_indented(_list): invalid_authors[author] = set() for issue in issues: invalid_authors[author].add(issue) - date = get_date(commit_hash) - # Parse components from the commit message, if any - commit_components = find_components(commit, commit_hash) + # Parse components from the commit title, if any + commit_components = find_components(title, _hash) # Populate or merge an issue into author_info[author] def populate(issue_type, components): components = components or [CORE_COMPONENT] # assume core if no components provided @@ -153,14 +181,14 @@ def populate(issue_type, components): jira_issue = jira_client.issue(issue) jira_type = jira_issue.fields.issuetype.name jira_type = translate_issue_type(jira_type, issue, warnings) - jira_components = [translate_component(c.name, commit_hash, warnings)\ + jira_components = [translate_component(c.name, _hash, warnings)\ for c in jira_issue.fields.components] all_components = set(jira_components + commit_components) populate(jira_type, all_components) # For docs without an associated JIRA, manually add it ourselves - if is_docs(commit) and not issues: + if is_docs(title) and not issues: populate("documentation", commit_components) - print " Processed commit %s authored by %s on %s" % (commit_hash, author, date) + print " Processed commit %s authored by %s on %s" % (_hash, author, date) print "==================================================================================\n" # Write to contributors file ordered by author names diff --git a/dev/create-release/releaseutils.py b/dev/create-release/releaseutils.py index 76a10c32886d4..18e16bcb90514 100755 --- a/dev/create-release/releaseutils.py +++ b/dev/create-release/releaseutils.py @@ -19,6 +19,7 @@ # This file contains helper methods used in creating a release. import re +import sys from subprocess import Popen, PIPE try: @@ -47,20 +48,85 @@ # Contributors list file name contributors_file_name = "contributors.txt" +# Prompt the user to answer yes or no until they do so +def yesOrNoPrompt(msg): + response = raw_input("%s [y/n]: " % msg) + while response != "y" and response != "n": + return yesOrNoPrompt(msg) + return response == "y" + # Utility functions run git commands (written with Git 1.8.5) def run_cmd(cmd): return Popen(cmd, stdout=PIPE).communicate()[0] -def get_author(commit_hash): - return run_cmd(["git", "show", "--quiet", "--pretty=format:%an", commit_hash]) +def run_cmd_error(cmd): return Popen(cmd, stderr=PIPE).communicate()[1] def get_date(commit_hash): return run_cmd(["git", "show", "--quiet", "--pretty=format:%cd", commit_hash]) -def get_one_line(commit_hash): - return run_cmd(["git", "show", "--quiet", "--pretty=format:\"%h %cd %s\"", commit_hash]) -def get_one_line_commits(start_hash, end_hash): - return run_cmd(["git", "log", "--oneline", "%s..%s" % (start_hash, end_hash)]) -def num_commits_in_range(start_hash, end_hash): - output = run_cmd(["git", "log", "--oneline", "%s..%s" % (start_hash, end_hash)]) - lines = [line for line in output.split("\n") if line] # filter out empty lines - return len(lines) +def tag_exists(tag): + stderr = run_cmd_error(["git", "checkout", tag]) + return "error" not in stderr + +# A type-safe representation of a commit +class Commit: + def __init__(self, _hash, author, title, pr_number = None): + self._hash = _hash + self.author = author + self.title = title + self.pr_number = pr_number + def get_hash(self): return self._hash + def get_author(self): return self.author + def get_title(self): return self.title + def get_pr_number(self): return self.pr_number + def __str__(self): + closes_pr = "(Closes #%s)" % self.pr_number if self.pr_number else "" + return "%s %s %s %s" % (self._hash, self.author, self.title, closes_pr) + +# Return all commits that belong to the specified tag. +# +# Under the hood, this runs a `git log` on that tag and parses the fields +# from the command output to construct a list of Commit objects. Note that +# because certain fields reside in the commit description and cannot be parsed +# through the Github API itself, we need to do some intelligent regex parsing +# to extract those fields. +# +# This is written using Git 1.8.5. +def get_commits(tag): + commit_start_marker = "|=== COMMIT START MARKER ===|" + commit_end_marker = "|=== COMMIT END MARKER ===|" + field_end_marker = "|=== COMMIT FIELD END MARKER ===|" + log_format =\ + commit_start_marker + "%h" +\ + field_end_marker + "%an" +\ + field_end_marker + "%s" +\ + commit_end_marker + "%b" + output = run_cmd(["git", "log", "--quiet", "--pretty=format:" + log_format, tag]) + commits = [] + raw_commits = [c for c in output.split(commit_start_marker) if c] + for commit in raw_commits: + if commit.count(commit_end_marker) != 1: + print "Commit end marker not found in commit: " + for line in commit.split("\n"): print line + sys.exit(1) + # Separate commit digest from the body + # From the digest we extract the hash, author and the title + # From the body, we extract the PR number and the github username + [commit_digest, commit_body] = commit.split(commit_end_marker) + if commit_digest.count(field_end_marker) != 2: + sys.exit("Unexpected format in commit: %s" % commit_digest) + [_hash, author, title] = commit_digest.split(field_end_marker) + # The PR number and github username is in the commit message + # itself and cannot be accessed through any Github API + pr_number = None + match = re.search("Closes #([0-9]+) from ([^/\\s]+)/", commit_body) + if match: + [pr_number, github_username] = match.groups() + # If the author name is not valid, use the github + # username so we can translate it properly later + if not is_valid_author(author): + author = github_username + # Guard against special characters + author = unidecode.unidecode(unicode(author, "UTF-8")).strip() + commit = Commit(_hash, author, title, pr_number) + commits.append(commit) + return commits # Maintain a mapping for translating issue types to contributions in the release notes # This serves an additional function of warning the user against unknown issue types @@ -70,10 +136,13 @@ def num_commits_in_range(start_hash, end_hash): known_issue_types = { "bug": "bug fixes", "build": "build fixes", + "dependency upgrade": "build fixes", "improvement": "improvements", "new feature": "new features", "documentation": "documentation", - "test": "test" + "test": "test", + "task": "improvement", + "sub-task": "improvement" } # Maintain a mapping for translating component names when creating the release notes @@ -176,8 +245,7 @@ def get_jira_name(author, jira_client): # Return whether the given name is in the form def is_valid_author(author): if not author: return False - author_words = len(author.split(" ")) - return author_words == 2 or author_words == 3 + return " " in author and not re.findall("[0-9]", author) # Capitalize the first letter of each word in the given author name def capitalize_author(author): diff --git a/dev/create-release/translate-contributors.py b/dev/create-release/translate-contributors.py index ef4625b003cb6..462c21142f75f 100755 --- a/dev/create-release/translate-contributors.py +++ b/dev/create-release/translate-contributors.py @@ -37,8 +37,11 @@ JIRA_API_BASE = os.environ.get("JIRA_API_BASE", "https://issues.apache.org/jira") JIRA_USERNAME = os.environ.get("JIRA_USERNAME", None) JIRA_PASSWORD = os.environ.get("JIRA_PASSWORD", None) +GITHUB_API_TOKEN = os.environ.get("GITHUB_API_TOKEN", None) if not JIRA_USERNAME or not JIRA_PASSWORD: sys.exit("Both JIRA_USERNAME and JIRA_PASSWORD must be set") +if not GITHUB_API_TOKEN: + sys.exit("GITHUB_API_TOKEN must be set") # Write new contributors list to .new if not os.path.isfile(contributors_file_name): @@ -62,7 +65,7 @@ # Setup Github and JIRA clients jira_options = { "server": JIRA_API_BASE } jira_client = JIRA(options = jira_options, basic_auth = (JIRA_USERNAME, JIRA_PASSWORD)) -github_client = Github() +github_client = Github(GITHUB_API_TOKEN) # Generate candidates for the given author. This should only be called if the given author # name does not represent a full name as this operation is somewhat expensive. Under the @@ -94,7 +97,14 @@ def generate_candidates(author, issues): # Then do the same for the assignee of each of the associated JIRAs # Note that a given issue may not have an assignee, or the assignee may not have a full name for issue in issues: - jira_issue = jira_client.issue(issue) + try: + jira_issue = jira_client.issue(issue) + except JIRAError as e: + # Do not exit just because an issue is not found! + if e.status_code == 404: + warnings.append("Issue %s not found!" % issue) + continue + raise e jira_assignee = jira_issue.fields.assignee if jira_assignee: user_name = jira_assignee.name @@ -123,9 +133,10 @@ def generate_candidates(author, issues): # In non-interactive mode, this script picks the first valid author name from the candidates # If no such name exists, the original name is used (without the JIRA numbers). print "\n========================== Translating contributor list ==========================" -for line in contributors_file: +lines = contributors_file.readlines() +for i, line in enumerate(lines): author = line.split(" - ")[0] - print "Processing author %s" % author + print "Processing author %s (%d/%d)" % (author, i + 1, len(lines)) if not author: print " ERROR: Expected the following format - " print " ERROR: Actual = %s" % line @@ -135,30 +146,39 @@ def generate_candidates(author, issues): candidates = generate_candidates(new_author, issues) # Print out potential replacement candidates along with the sources, e.g. # [X] No full name found for Github user andrewor14 + # [X] No assignee found for SPARK-1763 # [0] Andrew Or - Full name of JIRA user andrewor14 # [1] Andrew Orso - Full name of SPARK-1444 assignee andrewor14 # [2] Andrew Ordall - Full name of SPARK-1663 assignee andrewor14 - # [X] No assignee found for SPARK-1763 - # [3] Custom + # [3] andrewor14 - Raw Github username + # [4] Custom candidate_names = [] + bad_prompts = [] # Prompts that can't actually be selected; print these first. + good_prompts = [] # Prompts that contain valid choices for candidate, source in candidates: if candidate == NOT_FOUND: - print " [X] %s" % source + bad_prompts.append(" [X] %s" % source) else: index = len(candidate_names) candidate_names.append(candidate) - print " [%d] %s - %s" % (index, candidate, source) - custom_index = len(candidate_names) + good_prompts.append(" [%d] %s - %s" % (index, candidate, source)) + raw_index = len(candidate_names) + custom_index = len(candidate_names) + 1 + for p in bad_prompts: print p + if bad_prompts: print " ---" + for p in good_prompts: print p # In interactive mode, additionally provide "custom" option and await user response if INTERACTIVE_MODE: + print " [%d] %s - Raw Github username" % (raw_index, new_author) print " [%d] Custom" % custom_index response = raw_input(" Your choice: ") - while not response.isdigit() or int(response) > custom_index: - response = raw_input(" Please enter an integer between 0 and %d: " % custom_index) + last_index = custom_index + while not response.isdigit() or int(response) > last_index: + response = raw_input(" Please enter an integer between 0 and %d: " % last_index) response = int(response) if response == custom_index: new_author = raw_input(" Please type a custom name for this author: ") - else: + elif response != raw_index: new_author = candidate_names[response] # In non-interactive mode, just pick the first candidate else: @@ -175,6 +195,7 @@ def generate_candidates(author, issues): print " * Replacing %s with %s" % (author, new_author) line = line.replace(author, new_author) new_contributors_file.write(line) + new_contributors_file.flush() print "==================================================================================\n" contributors_file.close() new_contributors_file.close() From b85044ecfa825ff68c8e57eeffa4d9f214335e66 Mon Sep 17 00:00:00 2001 From: Andrew Or Date: Tue, 16 Dec 2014 19:28:43 -0800 Subject: [PATCH 014/320] [Release] Cache known author translations locally This bypasses unnecessary calls to the Github and JIRA API. Additionally, having a local cache allows us to remember names that we had to manually discover ourselves. --- dev/create-release/generate-contributors.py | 18 +++--- dev/create-release/known_translations | 59 ++++++++++++++++++ dev/create-release/releaseutils.py | 4 +- dev/create-release/translate-contributors.py | 64 ++++++++++++++------ 4 files changed, 116 insertions(+), 29 deletions(-) create mode 100644 dev/create-release/known_translations diff --git a/dev/create-release/generate-contributors.py b/dev/create-release/generate-contributors.py index e8f81ccbce740..e65c5d8233098 100755 --- a/dev/create-release/generate-contributors.py +++ b/dev/create-release/generate-contributors.py @@ -26,8 +26,8 @@ # You must set the following before use! JIRA_API_BASE = os.environ.get("JIRA_API_BASE", "https://issues.apache.org/jira") -RELEASE_TAG = os.environ.get("START_COMMIT", "v1.2.0-rc2") -PREVIOUS_RELEASE_TAG = os.environ.get("END_COMMIT", "v1.1.0") +RELEASE_TAG = os.environ.get("RELEASE_TAG", "v1.2.0-rc2") +PREVIOUS_RELEASE_TAG = os.environ.get("PREVIOUS_RELEASE_TAG", "v1.1.0") # If the release tags are not provided, prompt the user to provide them while not tag_exists(RELEASE_TAG): @@ -35,7 +35,7 @@ while not tag_exists(PREVIOUS_RELEASE_TAG): print "Please specify the previous release tag." PREVIOUS_RELEASE_TAG = raw_input(\ - "For instance, if you are releasing v1.2.0, you should specify v1.1.0: ") + "For instance, if you are releasing v1.2.0, you should specify v1.1.0: ") # Gather commits found in the new tag but not in the old tag. # This filters commits based on both the git hash and the PR number. @@ -84,9 +84,9 @@ def print_indented(_list): filtered_commits = [] def is_release(commit_title): return re.findall("\[release\]", commit_title.lower()) or\ - "preparing spark release" in commit_title.lower() or\ - "preparing development version" in commit_title.lower() or\ - "CHANGES.txt" in commit_title + "preparing spark release" in commit_title.lower() or\ + "preparing development version" in commit_title.lower() or\ + "CHANGES.txt" in commit_title def is_maintenance(commit_title): return "maintenance" in commit_title.lower() or\ "manually close" in commit_title.lower() @@ -96,7 +96,7 @@ def is_revert(commit_title): return "revert" in commit_title.lower() def is_docs(commit_title): return re.findall("docs*", commit_title.lower()) or\ - "programming guide" in commit_title.lower() + "programming guide" in commit_title.lower() for c in new_commits: t = c.get_title() if not t: continue @@ -182,7 +182,7 @@ def populate(issue_type, components): jira_type = jira_issue.fields.issuetype.name jira_type = translate_issue_type(jira_type, issue, warnings) jira_components = [translate_component(c.name, _hash, warnings)\ - for c in jira_issue.fields.components] + for c in jira_issue.fields.components] all_components = set(jira_components + commit_components) populate(jira_type, all_components) # For docs without an associated JIRA, manually add it ourselves @@ -213,7 +213,7 @@ def populate(issue_type, components): # e.g. Bug fixes in MLlib, Core, and Streaming; documentation in YARN else: contributions = ["%s in %s" % (issue_type, nice_join(comps)) \ - for issue_type, comps in author_info[author].items()] + for issue_type, comps in author_info[author].items()] contribution = "; ".join(contributions) # Do not use python's capitalize() on the whole string to preserve case assert contribution diff --git a/dev/create-release/known_translations b/dev/create-release/known_translations new file mode 100644 index 0000000000000..b74e4ee8a330b --- /dev/null +++ b/dev/create-release/known_translations @@ -0,0 +1,59 @@ +# This is a mapping of names to be translated through translate-contributors.py +# The format expected on each line should be: - +CodingCat - Nan Zhu +CrazyJvm - Chao Chen +EugenCepoi - Eugen Cepoi +GraceH - Jie Huang +JerryLead - Lijie Xu +Leolh - Liu Hao +Lewuathe - Kai Sasaki +RongGu - Rong Gu +Shiti - Shiti Saxena +Victsm - Min Shen +WangTaoTheTonic - Wang Tao +XuTingjun - Tingjun Xu +YanTangZhai - Yantang Zhai +alexdebrie - Alex DeBrie +alokito - Alok Saldanha +anantasty - Anant Asthana +andrewor14 - Andrew Or +aniketbhatnagar - Aniket Bhatnagar +arahuja - Arun Ahuja +brkyvz - Burak Yavuz +chesterxgchen - Chester Chen +chiragaggarwal - Chirag Aggarwal +chouqin - Qiping Li +cocoatomo - Tomohiko K. +coderfi - Fairiz Azizi +coderxiang - Shuo Xiang +davies - Davies Liu +epahomov - Egor Pahomov +falaki - Hossein Falaki +freeman-lab - Jeremy Freeman +industrial-sloth - Jascha Swisher +jackylk - Jacky Li +jayunit100 - Jay Vyas +jerryshao - Saisai Shao +jkbradley - Joseph Bradley +lianhuiwang - Lianhui Wang +lirui-intel - Rui Li +luluorta - Lu Lu +luogankun - Gankun Luo +maji2014 - Derek Ma +mccheah - Matthew Cheah +mengxr - Xiangrui Meng +nartz - Nathan Artz +odedz - Oded Zimerman +ravipesala - Ravindra Pesala +roxchkplusony - Victor Tso +scwf - Wang Fei +shimingfei - Shiming Fei +surq - Surong Quan +suyanNone - Su Yan +tedyu - Ted Yu +tigerquoll - Dale Richardson +wangxiaojing - Xiaojing Wang +watermen - Yadong Qi +witgo - Guoqiang Li +xinyunh - Xinyun Huang +zsxwing - Shixiong Zhu diff --git a/dev/create-release/releaseutils.py b/dev/create-release/releaseutils.py index 18e16bcb90514..26221b270394e 100755 --- a/dev/create-release/releaseutils.py +++ b/dev/create-release/releaseutils.py @@ -57,11 +57,11 @@ def yesOrNoPrompt(msg): # Utility functions run git commands (written with Git 1.8.5) def run_cmd(cmd): return Popen(cmd, stdout=PIPE).communicate()[0] -def run_cmd_error(cmd): return Popen(cmd, stderr=PIPE).communicate()[1] +def run_cmd_error(cmd): return Popen(cmd, stdout=PIPE, stderr=PIPE).communicate()[1] def get_date(commit_hash): return run_cmd(["git", "show", "--quiet", "--pretty=format:%cd", commit_hash]) def tag_exists(tag): - stderr = run_cmd_error(["git", "checkout", tag]) + stderr = run_cmd_error(["git", "show", tag]) return "error" not in stderr # A type-safe representation of a commit diff --git a/dev/create-release/translate-contributors.py b/dev/create-release/translate-contributors.py index 462c21142f75f..f3b1efdd42785 100755 --- a/dev/create-release/translate-contributors.py +++ b/dev/create-release/translate-contributors.py @@ -67,6 +67,19 @@ jira_client = JIRA(options = jira_options, basic_auth = (JIRA_USERNAME, JIRA_PASSWORD)) github_client = Github(GITHUB_API_TOKEN) +# Load known author translations that are cached locally +known_translations = {} +known_translations_file_name = "known_translations" +known_translations_file = open(known_translations_file_name, "r") +for line in known_translations_file: + if line.startswith("#"): continue + [old_name, new_name] = line.split(" - ") + known_translations[old_name] = new_name +known_translations_file.close() + +# Open again in case the user adds new mappings +known_translations_file = open(known_translations_file_name, "a") + # Generate candidates for the given author. This should only be called if the given author # name does not represent a full name as this operation is somewhat expensive. Under the # hood, it makes several calls to the Github and JIRA API servers to find the candidates. @@ -83,17 +96,17 @@ def generate_candidates(author, issues): candidates = [] # First check for full name of Github user - github_name = get_github_name(new_author, github_client) + github_name = get_github_name(author, github_client) if github_name: - candidates.append((github_name, "Full name of Github user %s" % new_author)) + candidates.append((github_name, "Full name of Github user %s" % author)) else: - candidates.append((NOT_FOUND, "No full name found for Github user %s" % new_author)) + candidates.append((NOT_FOUND, "No full name found for Github user %s" % author)) # Then do the same for JIRA user - jira_name = get_jira_name(new_author, jira_client) + jira_name = get_jira_name(author, jira_client) if jira_name: - candidates.append((jira_name, "Full name of JIRA user %s" % new_author)) + candidates.append((jira_name, "Full name of JIRA user %s" % author)) else: - candidates.append((NOT_FOUND, "No full name found for JIRA user %s" % new_author)) + candidates.append((NOT_FOUND, "No full name found for JIRA user %s" % author)) # Then do the same for the assignee of each of the associated JIRAs # Note that a given issue may not have an assignee, or the assignee may not have a full name for issue in issues: @@ -135,15 +148,24 @@ def generate_candidates(author, issues): print "\n========================== Translating contributor list ==========================" lines = contributors_file.readlines() for i, line in enumerate(lines): - author = line.split(" - ")[0] - print "Processing author %s (%d/%d)" % (author, i + 1, len(lines)) - if not author: - print " ERROR: Expected the following format - " - print " ERROR: Actual = %s" % line - if not is_valid_author(author): - new_author = author.split("/")[0] - issues = author.split("/")[1:] - candidates = generate_candidates(new_author, issues) + temp_author = line.split(" - ")[0] + print "Processing author %s (%d/%d)" % (temp_author, i + 1, len(lines)) + if not temp_author: + error_msg = " ERROR: Expected the following format - \n" + error_msg += " ERROR: Actual = %s" % line + print error_msg + warnings.append(error_msg) + new_contributors_file.write(line) + new_contributors_file.flush() + continue + author = temp_author.split("/")[0] + # Use the local copy of known translations where possible + if author in known_translations: + line = line.replace(temp_author, known_translations[author]) + elif not is_valid_author(author): + new_author = author + issues = temp_author.split("/")[1:] + candidates = generate_candidates(author, issues) # Print out potential replacement candidates along with the sources, e.g. # [X] No full name found for Github user andrewor14 # [X] No assignee found for SPARK-1763 @@ -169,7 +191,7 @@ def generate_candidates(author, issues): for p in good_prompts: print p # In interactive mode, additionally provide "custom" option and await user response if INTERACTIVE_MODE: - print " [%d] %s - Raw Github username" % (raw_index, new_author) + print " [%d] %s - Raw Github username" % (raw_index, author) print " [%d] Custom" % custom_index response = raw_input(" Your choice: ") last_index = custom_index @@ -191,9 +213,15 @@ def generate_candidates(author, issues): if is_valid_author(new_author): new_author = capitalize_author(new_author) else: - warnings.append("Unable to find a valid name %s for author %s" % (new_author, author)) + warnings.append("Unable to find a valid name %s for author %s" % (author, temp_author)) print " * Replacing %s with %s" % (author, new_author) - line = line.replace(author, new_author) + # If we are in interactive mode, prompt the user whether we want to remember this new mapping + if INTERACTIVE_MODE and\ + author not in known_translations and\ + yesOrNoPrompt(" Add mapping %s -> %s to known translations file?" % (author, new_author)): + known_translations_file.write("%s - %s\n" % (author, new_author)) + known_translations_file.flush() + line = line.replace(temp_author, author) new_contributors_file.write(line) new_contributors_file.flush() print "==================================================================================\n" From 3b395e10510782474789c9098084503f98ca4830 Mon Sep 17 00:00:00 2001 From: Cheng Lian Date: Tue, 16 Dec 2014 21:16:03 -0800 Subject: [PATCH 015/320] [SPARK-4798][SQL] A new set of Parquet testing API and test suites This PR provides a set Parquet testing API (see trait `ParquetTest`) that enables developers to write more concise test cases. A new set of Parquet test suites built upon this API are added and aim to replace the old `ParquetQuerySuite`. To avoid potential merge conflicts, old testing code are not removed yet. The following classes can be safely removed after most Parquet related PRs are handled: - `ParquetQuerySuite` - `ParquetTestData` [Review on Reviewable](https://reviewable.io/reviews/apache/spark/3644) Author: Cheng Lian Closes #3644 from liancheng/parquet-tests and squashes the following commits: 800e745 [Cheng Lian] Enforces ordering of test output 3bb8731 [Cheng Lian] Refactors HiveParquetSuite aa2cb2e [Cheng Lian] Decouples ParquetTest and TestSQLContext 7b43a68 [Cheng Lian] Updates ParquetTest Scaladoc 7f07af0 [Cheng Lian] Adds a new set of Parquet test suites --- .../scala/org/apache/spark/sql/SQLConf.scala | 4 + .../spark/sql/parquet/ParquetTest.scala | 127 ++++++++ .../sql/parquet/ParquetFilterSuite.scala | 253 +++++++++++++++ .../spark/sql/parquet/ParquetIOSuite.scala | 287 ++++++++++++++++++ .../sql/parquet/ParquetQuerySuite2.scala | 110 +++++++ .../sql/parquet/ParquetSchemaSuite.scala | 164 ++++++++++ .../spark/sql/parquet/HiveParquetSuite.scala | 119 +++----- .../spark/sql/parquet/parquetSuites.scala | 6 +- 8 files changed, 989 insertions(+), 81 deletions(-) create mode 100644 sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTest.scala create mode 100644 sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala create mode 100644 sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala create mode 100644 sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite2.scala create mode 100644 sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetSchemaSuite.scala diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala index f5abf71d6c7b9..f5bf935522dad 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala @@ -188,6 +188,10 @@ private[sql] trait SQLConf { */ def getAllConfs: immutable.Map[String, String] = settings.synchronized { settings.toMap } + private[spark] def unsetConf(key: String) { + settings -= key + } + private[spark] def clear() { settings.clear() } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTest.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTest.scala new file mode 100644 index 0000000000000..b4d48902fd2c6 --- /dev/null +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTest.scala @@ -0,0 +1,127 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.parquet + +import java.io.File + +import scala.reflect.ClassTag +import scala.reflect.runtime.universe.TypeTag +import scala.util.Try + +import org.apache.spark.sql.{SQLContext, SchemaRDD} +import org.apache.spark.sql.catalyst.util +import org.apache.spark.util.Utils + +/** + * A helper trait that provides convenient facilities for Parquet testing. + * + * NOTE: Considering classes `Tuple1` ... `Tuple22` all extend `Product`, it would be more + * convenient to use tuples rather than special case classes when writing test cases/suites. + * Especially, `Tuple1.apply` can be used to easily wrap a single type/value. + */ +trait ParquetTest { + val sqlContext: SQLContext + + import sqlContext._ + + protected def configuration = sparkContext.hadoopConfiguration + + /** + * Sets all SQL configurations specified in `pairs`, calls `f`, and then restore all SQL + * configurations. + * + * @todo Probably this method should be moved to a more general place + */ + protected def withSQLConf(pairs: (String, String)*)(f: => Unit): Unit = { + val (keys, values) = pairs.unzip + val currentValues = keys.map(key => Try(getConf(key)).toOption) + (keys, values).zipped.foreach(setConf) + try f finally { + keys.zip(currentValues).foreach { + case (key, Some(value)) => setConf(key, value) + case (key, None) => unsetConf(key) + } + } + } + + /** + * Generates a temporary path without creating the actual file/directory, then pass it to `f`. If + * a file/directory is created there by `f`, it will be delete after `f` returns. + * + * @todo Probably this method should be moved to a more general place + */ + protected def withTempPath(f: File => Unit): Unit = { + val file = util.getTempFilePath("parquetTest").getCanonicalFile + try f(file) finally if (file.exists()) Utils.deleteRecursively(file) + } + + /** + * Creates a temporary directory, which is then passed to `f` and will be deleted after `f` + * returns. + * + * @todo Probably this method should be moved to a more general place + */ + protected def withTempDir(f: File => Unit): Unit = { + val dir = Utils.createTempDir().getCanonicalFile + try f(dir) finally Utils.deleteRecursively(dir) + } + + /** + * Writes `data` to a Parquet file, which is then passed to `f` and will be deleted after `f` + * returns. + */ + protected def withParquetFile[T <: Product: ClassTag: TypeTag] + (data: Seq[T]) + (f: String => Unit): Unit = { + withTempPath { file => + sparkContext.parallelize(data).saveAsParquetFile(file.getCanonicalPath) + f(file.getCanonicalPath) + } + } + + /** + * Writes `data` to a Parquet file and reads it back as a SchemaRDD, which is then passed to `f`. + * The Parquet file will be deleted after `f` returns. + */ + protected def withParquetRDD[T <: Product: ClassTag: TypeTag] + (data: Seq[T]) + (f: SchemaRDD => Unit): Unit = { + withParquetFile(data)(path => f(parquetFile(path))) + } + + /** + * Drops temporary table `tableName` after calling `f`. + */ + protected def withTempTable(tableName: String)(f: => Unit): Unit = { + try f finally dropTempTable(tableName) + } + + /** + * Writes `data` to a Parquet file, reads it back as a SchemaRDD and registers it as a temporary + * table named `tableName`, then call `f`. The temporary table together with the Parquet file will + * be dropped/deleted after `f` returns. + */ + protected def withParquetTable[T <: Product: ClassTag: TypeTag] + (data: Seq[T], tableName: String) + (f: => Unit): Unit = { + withParquetRDD(data) { rdd => + rdd.registerTempTable(tableName) + withTempTable(tableName)(f) + } + } +} diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala new file mode 100644 index 0000000000000..111a459e6d27d --- /dev/null +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala @@ -0,0 +1,253 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.parquet + +import parquet.filter2.predicate.Operators._ +import parquet.filter2.predicate.{FilterPredicate, Operators} + +import org.apache.spark.sql.catalyst.dsl.expressions._ +import org.apache.spark.sql.catalyst.expressions.{Literal, Predicate, Row} +import org.apache.spark.sql.test.TestSQLContext +import org.apache.spark.sql.{QueryTest, SQLConf, SchemaRDD} + +/** + * A test suite that tests Parquet filter2 API based filter pushdown optimization. + * + * Notice that `!(a cmp b)` are always transformed to its negated form `a cmp' b` by the + * `BooleanSimplification` optimization rule whenever possible. As a result, predicate `!(a < 1)` + * results a `GtEq` filter predicate rather than a `Not`. + * + * @todo Add test cases for `IsNull` and `IsNotNull` after merging PR #3367 + */ +class ParquetFilterSuite extends QueryTest with ParquetTest { + val sqlContext = TestSQLContext + + private def checkFilterPushdown( + rdd: SchemaRDD, + output: Seq[Symbol], + predicate: Predicate, + filterClass: Class[_ <: FilterPredicate], + checker: (SchemaRDD, Any) => Unit, + expectedResult: => Any): Unit = { + withSQLConf(SQLConf.PARQUET_FILTER_PUSHDOWN_ENABLED -> "true") { + val query = rdd.select(output.map(_.attr): _*).where(predicate) + + val maybeAnalyzedPredicate = query.queryExecution.executedPlan.collect { + case plan: ParquetTableScan => plan.columnPruningPred + }.flatten.reduceOption(_ && _) + + assert(maybeAnalyzedPredicate.isDefined) + maybeAnalyzedPredicate.foreach { pred => + val maybeFilter = ParquetFilters.createFilter(pred) + assert(maybeFilter.isDefined, s"Couldn't generate filter predicate for $pred") + maybeFilter.foreach(f => assert(f.getClass === filterClass)) + } + + checker(query, expectedResult) + } + } + + private def checkFilterPushdown + (rdd: SchemaRDD, output: Symbol*) + (predicate: Predicate, filterClass: Class[_ <: FilterPredicate]) + (expectedResult: => Any): Unit = { + checkFilterPushdown(rdd, output, predicate, filterClass, checkAnswer _, expectedResult) + } + + def checkBinaryFilterPushdown + (rdd: SchemaRDD, output: Symbol*) + (predicate: Predicate, filterClass: Class[_ <: FilterPredicate]) + (expectedResult: => Any): Unit = { + def checkBinaryAnswer(rdd: SchemaRDD, result: Any): Unit = { + val actual = rdd.map(_.getAs[Array[Byte]](0).mkString(",")).collect().toSeq + val expected = result match { + case s: Seq[_] => s.map(_.asInstanceOf[Row].getAs[Array[Byte]](0).mkString(",")) + case s => Seq(s.asInstanceOf[Array[Byte]].mkString(",")) + } + assert(actual.sorted === expected.sorted) + } + checkFilterPushdown(rdd, output, predicate, filterClass, checkBinaryAnswer _, expectedResult) + } + + test("filter pushdown - boolean") { + withParquetRDD((true :: false :: Nil).map(Tuple1.apply)) { rdd => + checkFilterPushdown(rdd, '_1)('_1 === true, classOf[Eq[java.lang.Boolean]])(true) + checkFilterPushdown(rdd, '_1)('_1 !== true, classOf[Operators.Not])(false) + } + } + + test("filter pushdown - integer") { + withParquetRDD((1 to 4).map(Tuple1.apply)) { rdd => + checkFilterPushdown(rdd, '_1)('_1 === 1, classOf[Eq[Integer]])(1) + checkFilterPushdown(rdd, '_1)('_1 !== 1, classOf[Operators.Not]) { + (2 to 4).map(Row.apply(_)) + } + + checkFilterPushdown(rdd, '_1)('_1 < 2, classOf[Lt [Integer]])(1) + checkFilterPushdown(rdd, '_1)('_1 > 3, classOf[Gt [Integer]])(4) + checkFilterPushdown(rdd, '_1)('_1 <= 1, classOf[LtEq[Integer]])(1) + checkFilterPushdown(rdd, '_1)('_1 >= 4, classOf[GtEq[Integer]])(4) + + checkFilterPushdown(rdd, '_1)(Literal(1) === '_1, classOf[Eq [Integer]])(1) + checkFilterPushdown(rdd, '_1)(Literal(2) > '_1, classOf[Lt [Integer]])(1) + checkFilterPushdown(rdd, '_1)(Literal(3) < '_1, classOf[Gt [Integer]])(4) + checkFilterPushdown(rdd, '_1)(Literal(1) >= '_1, classOf[LtEq[Integer]])(1) + checkFilterPushdown(rdd, '_1)(Literal(4) <= '_1, classOf[GtEq[Integer]])(4) + + checkFilterPushdown(rdd, '_1)(!('_1 < 4), classOf[Operators.GtEq[Integer]])(4) + checkFilterPushdown(rdd, '_1)('_1 > 2 && '_1 < 4, classOf[Operators.And])(3) + checkFilterPushdown(rdd, '_1)('_1 < 2 || '_1 > 3, classOf[Operators.Or]) { + Seq(Row(1), Row(4)) + } + } + } + + test("filter pushdown - long") { + withParquetRDD((1 to 4).map(i => Tuple1.apply(i.toLong))) { rdd => + checkFilterPushdown(rdd, '_1)('_1 === 1, classOf[Eq[java.lang.Long]])(1) + checkFilterPushdown(rdd, '_1)('_1 !== 1, classOf[Operators.Not]) { + (2 to 4).map(Row.apply(_)) + } + + checkFilterPushdown(rdd, '_1)('_1 < 2, classOf[Lt [java.lang.Long]])(1) + checkFilterPushdown(rdd, '_1)('_1 > 3, classOf[Gt [java.lang.Long]])(4) + checkFilterPushdown(rdd, '_1)('_1 <= 1, classOf[LtEq[java.lang.Long]])(1) + checkFilterPushdown(rdd, '_1)('_1 >= 4, classOf[GtEq[java.lang.Long]])(4) + + checkFilterPushdown(rdd, '_1)(Literal(1) === '_1, classOf[Eq [Integer]])(1) + checkFilterPushdown(rdd, '_1)(Literal(2) > '_1, classOf[Lt [java.lang.Long]])(1) + checkFilterPushdown(rdd, '_1)(Literal(3) < '_1, classOf[Gt [java.lang.Long]])(4) + checkFilterPushdown(rdd, '_1)(Literal(1) >= '_1, classOf[LtEq[java.lang.Long]])(1) + checkFilterPushdown(rdd, '_1)(Literal(4) <= '_1, classOf[GtEq[java.lang.Long]])(4) + + checkFilterPushdown(rdd, '_1)(!('_1 < 4), classOf[Operators.GtEq[java.lang.Long]])(4) + checkFilterPushdown(rdd, '_1)('_1 > 2 && '_1 < 4, classOf[Operators.And])(3) + checkFilterPushdown(rdd, '_1)('_1 < 2 || '_1 > 3, classOf[Operators.Or]) { + Seq(Row(1), Row(4)) + } + } + } + + test("filter pushdown - float") { + withParquetRDD((1 to 4).map(i => Tuple1.apply(i.toFloat))) { rdd => + checkFilterPushdown(rdd, '_1)('_1 === 1, classOf[Eq[java.lang.Float]])(1) + checkFilterPushdown(rdd, '_1)('_1 !== 1, classOf[Operators.Not]) { + (2 to 4).map(Row.apply(_)) + } + + checkFilterPushdown(rdd, '_1)('_1 < 2, classOf[Lt [java.lang.Float]])(1) + checkFilterPushdown(rdd, '_1)('_1 > 3, classOf[Gt [java.lang.Float]])(4) + checkFilterPushdown(rdd, '_1)('_1 <= 1, classOf[LtEq[java.lang.Float]])(1) + checkFilterPushdown(rdd, '_1)('_1 >= 4, classOf[GtEq[java.lang.Float]])(4) + + checkFilterPushdown(rdd, '_1)(Literal(1) === '_1, classOf[Eq [Integer]])(1) + checkFilterPushdown(rdd, '_1)(Literal(2) > '_1, classOf[Lt [java.lang.Float]])(1) + checkFilterPushdown(rdd, '_1)(Literal(3) < '_1, classOf[Gt [java.lang.Float]])(4) + checkFilterPushdown(rdd, '_1)(Literal(1) >= '_1, classOf[LtEq[java.lang.Float]])(1) + checkFilterPushdown(rdd, '_1)(Literal(4) <= '_1, classOf[GtEq[java.lang.Float]])(4) + + checkFilterPushdown(rdd, '_1)(!('_1 < 4), classOf[Operators.GtEq[java.lang.Float]])(4) + checkFilterPushdown(rdd, '_1)('_1 > 2 && '_1 < 4, classOf[Operators.And])(3) + checkFilterPushdown(rdd, '_1)('_1 < 2 || '_1 > 3, classOf[Operators.Or]) { + Seq(Row(1), Row(4)) + } + } + } + + test("filter pushdown - double") { + withParquetRDD((1 to 4).map(i => Tuple1.apply(i.toDouble))) { rdd => + checkFilterPushdown(rdd, '_1)('_1 === 1, classOf[Eq[java.lang.Double]])(1) + checkFilterPushdown(rdd, '_1)('_1 !== 1, classOf[Operators.Not]) { + (2 to 4).map(Row.apply(_)) + } + + checkFilterPushdown(rdd, '_1)('_1 < 2, classOf[Lt [java.lang.Double]])(1) + checkFilterPushdown(rdd, '_1)('_1 > 3, classOf[Gt [java.lang.Double]])(4) + checkFilterPushdown(rdd, '_1)('_1 <= 1, classOf[LtEq[java.lang.Double]])(1) + checkFilterPushdown(rdd, '_1)('_1 >= 4, classOf[GtEq[java.lang.Double]])(4) + + checkFilterPushdown(rdd, '_1)(Literal(1) === '_1, classOf[Eq[Integer]])(1) + checkFilterPushdown(rdd, '_1)(Literal(2) > '_1, classOf[Lt [java.lang.Double]])(1) + checkFilterPushdown(rdd, '_1)(Literal(3) < '_1, classOf[Gt [java.lang.Double]])(4) + checkFilterPushdown(rdd, '_1)(Literal(1) >= '_1, classOf[LtEq[java.lang.Double]])(1) + checkFilterPushdown(rdd, '_1)(Literal(4) <= '_1, classOf[GtEq[java.lang.Double]])(4) + + checkFilterPushdown(rdd, '_1)(!('_1 < 4), classOf[Operators.GtEq[java.lang.Double]])(4) + checkFilterPushdown(rdd, '_1)('_1 > 2 && '_1 < 4, classOf[Operators.And])(3) + checkFilterPushdown(rdd, '_1)('_1 < 2 || '_1 > 3, classOf[Operators.Or]) { + Seq(Row(1), Row(4)) + } + } + } + + test("filter pushdown - string") { + withParquetRDD((1 to 4).map(i => Tuple1.apply(i.toString))) { rdd => + checkFilterPushdown(rdd, '_1)('_1 === "1", classOf[Eq[String]])("1") + checkFilterPushdown(rdd, '_1)('_1 !== "1", classOf[Operators.Not]) { + (2 to 4).map(i => Row.apply(i.toString)) + } + + checkFilterPushdown(rdd, '_1)('_1 < "2", classOf[Lt [java.lang.String]])("1") + checkFilterPushdown(rdd, '_1)('_1 > "3", classOf[Gt [java.lang.String]])("4") + checkFilterPushdown(rdd, '_1)('_1 <= "1", classOf[LtEq[java.lang.String]])("1") + checkFilterPushdown(rdd, '_1)('_1 >= "4", classOf[GtEq[java.lang.String]])("4") + + checkFilterPushdown(rdd, '_1)(Literal("1") === '_1, classOf[Eq [java.lang.String]])("1") + checkFilterPushdown(rdd, '_1)(Literal("2") > '_1, classOf[Lt [java.lang.String]])("1") + checkFilterPushdown(rdd, '_1)(Literal("3") < '_1, classOf[Gt [java.lang.String]])("4") + checkFilterPushdown(rdd, '_1)(Literal("1") >= '_1, classOf[LtEq[java.lang.String]])("1") + checkFilterPushdown(rdd, '_1)(Literal("4") <= '_1, classOf[GtEq[java.lang.String]])("4") + + checkFilterPushdown(rdd, '_1)(!('_1 < "4"), classOf[Operators.GtEq[java.lang.String]])("4") + checkFilterPushdown(rdd, '_1)('_1 > "2" && '_1 < "4", classOf[Operators.And])("3") + checkFilterPushdown(rdd, '_1)('_1 < "2" || '_1 > "3", classOf[Operators.Or]) { + Seq(Row("1"), Row("4")) + } + } + } + + test("filter pushdown - binary") { + implicit class IntToBinary(int: Int) { + def b: Array[Byte] = int.toString.getBytes("UTF-8") + } + + withParquetRDD((1 to 4).map(i => Tuple1.apply(i.b))) { rdd => + checkBinaryFilterPushdown(rdd, '_1)('_1 === 1.b, classOf[Eq[Array[Byte]]])(1.b) + checkBinaryFilterPushdown(rdd, '_1)('_1 !== 1.b, classOf[Operators.Not]) { + (2 to 4).map(i => Row.apply(i.b)).toSeq + } + + checkBinaryFilterPushdown(rdd, '_1)('_1 < 2.b, classOf[Lt [Array[Byte]]])(1.b) + checkBinaryFilterPushdown(rdd, '_1)('_1 > 3.b, classOf[Gt [Array[Byte]]])(4.b) + checkBinaryFilterPushdown(rdd, '_1)('_1 <= 1.b, classOf[LtEq[Array[Byte]]])(1.b) + checkBinaryFilterPushdown(rdd, '_1)('_1 >= 4.b, classOf[GtEq[Array[Byte]]])(4.b) + + checkBinaryFilterPushdown(rdd, '_1)(Literal(1.b) === '_1, classOf[Eq [Array[Byte]]])(1.b) + checkBinaryFilterPushdown(rdd, '_1)(Literal(2.b) > '_1, classOf[Lt [Array[Byte]]])(1.b) + checkBinaryFilterPushdown(rdd, '_1)(Literal(3.b) < '_1, classOf[Gt [Array[Byte]]])(4.b) + checkBinaryFilterPushdown(rdd, '_1)(Literal(1.b) >= '_1, classOf[LtEq[Array[Byte]]])(1.b) + checkBinaryFilterPushdown(rdd, '_1)(Literal(4.b) <= '_1, classOf[GtEq[Array[Byte]]])(4.b) + + checkBinaryFilterPushdown(rdd, '_1)(!('_1 < 4.b), classOf[Operators.GtEq[Array[Byte]]])(4.b) + checkBinaryFilterPushdown(rdd, '_1)('_1 > 2.b && '_1 < 4.b, classOf[Operators.And])(3.b) + checkBinaryFilterPushdown(rdd, '_1)('_1 < 2.b || '_1 > 3.b, classOf[Operators.Or]) { + Seq(Row(1.b), Row(4.b)) + } + } + } +} diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala new file mode 100644 index 0000000000000..10a01474e95be --- /dev/null +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala @@ -0,0 +1,287 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.parquet + +import scala.collection.JavaConversions._ +import scala.reflect.ClassTag +import scala.reflect.runtime.universe.TypeTag + +import org.apache.hadoop.conf.Configuration +import org.apache.hadoop.fs.{FileSystem, Path} +import parquet.example.data.simple.SimpleGroup +import parquet.example.data.{Group, GroupWriter} +import parquet.hadoop.api.WriteSupport +import parquet.hadoop.api.WriteSupport.WriteContext +import parquet.hadoop.metadata.CompressionCodecName +import parquet.hadoop.{ParquetFileWriter, ParquetWriter} +import parquet.io.api.RecordConsumer +import parquet.schema.{MessageType, MessageTypeParser} + +import org.apache.spark.sql.catalyst.ScalaReflection +import org.apache.spark.sql.catalyst.expressions.Row +import org.apache.spark.sql.catalyst.types.DecimalType +import org.apache.spark.sql.test.TestSQLContext +import org.apache.spark.sql.test.TestSQLContext._ +import org.apache.spark.sql.{QueryTest, SQLConf, SchemaRDD} + +// Write support class for nested groups: ParquetWriter initializes GroupWriteSupport +// with an empty configuration (it is after all not intended to be used in this way?) +// and members are private so we need to make our own in order to pass the schema +// to the writer. +private[parquet] class TestGroupWriteSupport(schema: MessageType) extends WriteSupport[Group] { + var groupWriter: GroupWriter = null + + override def prepareForWrite(recordConsumer: RecordConsumer): Unit = { + groupWriter = new GroupWriter(recordConsumer, schema) + } + + override def init(configuration: Configuration): WriteContext = { + new WriteContext(schema, new java.util.HashMap[String, String]()) + } + + override def write(record: Group) { + groupWriter.write(record) + } +} + +/** + * A test suite that tests basic Parquet I/O. + */ +class ParquetIOSuite extends QueryTest with ParquetTest { + val sqlContext = TestSQLContext + + /** + * Writes `data` to a Parquet file, reads it back and check file contents. + */ + protected def checkParquetFile[T <: Product: ClassTag: TypeTag](data: Seq[T]): Unit = { + withParquetRDD(data)(checkAnswer(_, data)) + } + + test("basic data types (without binary)") { + val data = (1 to 4).map { i => + (i % 2 == 0, i, i.toLong, i.toFloat, i.toDouble) + } + checkParquetFile(data) + } + + test("raw binary") { + val data = (1 to 4).map(i => Tuple1(Array.fill(3)(i.toByte))) + withParquetRDD(data) { rdd => + assertResult(data.map(_._1.mkString(",")).sorted) { + rdd.collect().map(_.getAs[Array[Byte]](0).mkString(",")).sorted + } + } + } + + test("string") { + val data = (1 to 4).map(i => Tuple1(i.toString)) + // Property spark.sql.parquet.binaryAsString shouldn't affect Parquet files written by Spark SQL + // as we store Spark SQL schema in the extra metadata. + withSQLConf(SQLConf.PARQUET_BINARY_AS_STRING -> "false")(checkParquetFile(data)) + withSQLConf(SQLConf.PARQUET_BINARY_AS_STRING -> "true")(checkParquetFile(data)) + } + + test("fixed-length decimals") { + def makeDecimalRDD(decimal: DecimalType): SchemaRDD = + sparkContext + .parallelize(0 to 1000) + .map(i => Tuple1(i / 100.0)) + .select('_1 cast decimal) + + for ((precision, scale) <- Seq((5, 2), (1, 0), (1, 1), (18, 10), (18, 17))) { + withTempPath { dir => + val data = makeDecimalRDD(DecimalType(precision, scale)) + data.saveAsParquetFile(dir.getCanonicalPath) + checkAnswer(parquetFile(dir.getCanonicalPath), data.collect().toSeq) + } + } + + // Decimals with precision above 18 are not yet supported + intercept[RuntimeException] { + withTempPath { dir => + makeDecimalRDD(DecimalType(19, 10)).saveAsParquetFile(dir.getCanonicalPath) + parquetFile(dir.getCanonicalPath).collect() + } + } + + // Unlimited-length decimals are not yet supported + intercept[RuntimeException] { + withTempPath { dir => + makeDecimalRDD(DecimalType.Unlimited).saveAsParquetFile(dir.getCanonicalPath) + parquetFile(dir.getCanonicalPath).collect() + } + } + } + + test("map") { + val data = (1 to 4).map(i => Tuple1(Map(i -> s"val_$i"))) + checkParquetFile(data) + } + + test("array") { + val data = (1 to 4).map(i => Tuple1(Seq(i, i + 1))) + checkParquetFile(data) + } + + test("struct") { + val data = (1 to 4).map(i => Tuple1((i, s"val_$i"))) + withParquetRDD(data) { rdd => + // Structs are converted to `Row`s + checkAnswer(rdd, data.map { case Tuple1(struct) => + Tuple1(Row(struct.productIterator.toSeq: _*)) + }) + } + } + + test("nested struct with array of array as field") { + val data = (1 to 4).map(i => Tuple1((i, Seq(Seq(s"val_$i"))))) + withParquetRDD(data) { rdd => + // Structs are converted to `Row`s + checkAnswer(rdd, data.map { case Tuple1(struct) => + Tuple1(Row(struct.productIterator.toSeq: _*)) + }) + } + } + + test("nested map with struct as value type") { + val data = (1 to 4).map(i => Tuple1(Map(i -> (i, s"val_$i")))) + withParquetRDD(data) { rdd => + checkAnswer(rdd, data.map { case Tuple1(m) => + Tuple1(m.mapValues(struct => Row(struct.productIterator.toSeq: _*))) + }) + } + } + + test("nulls") { + val allNulls = ( + null.asInstanceOf[java.lang.Boolean], + null.asInstanceOf[Integer], + null.asInstanceOf[java.lang.Long], + null.asInstanceOf[java.lang.Float], + null.asInstanceOf[java.lang.Double]) + + withParquetRDD(allNulls :: Nil) { rdd => + val rows = rdd.collect() + assert(rows.size === 1) + assert(rows.head === Row(Seq.fill(5)(null): _*)) + } + } + + test("nones") { + val allNones = ( + None.asInstanceOf[Option[Int]], + None.asInstanceOf[Option[Long]], + None.asInstanceOf[Option[String]]) + + withParquetRDD(allNones :: Nil) { rdd => + val rows = rdd.collect() + assert(rows.size === 1) + assert(rows.head === Row(Seq.fill(3)(null): _*)) + } + } + + test("compression codec") { + def compressionCodecFor(path: String) = { + val codecs = ParquetTypesConverter + .readMetaData(new Path(path), Some(configuration)) + .getBlocks + .flatMap(_.getColumns) + .map(_.getCodec.name()) + .distinct + + assert(codecs.size === 1) + codecs.head + } + + val data = (0 until 10).map(i => (i, i.toString)) + + def checkCompressionCodec(codec: CompressionCodecName): Unit = { + withSQLConf(SQLConf.PARQUET_COMPRESSION -> codec.name()) { + withParquetFile(data) { path => + assertResult(parquetCompressionCodec.toUpperCase) { + compressionCodecFor(path) + } + } + } + } + + // Checks default compression codec + checkCompressionCodec(CompressionCodecName.fromConf(parquetCompressionCodec)) + + checkCompressionCodec(CompressionCodecName.UNCOMPRESSED) + checkCompressionCodec(CompressionCodecName.GZIP) + checkCompressionCodec(CompressionCodecName.SNAPPY) + } + + test("read raw Parquet file") { + def makeRawParquetFile(path: Path): Unit = { + val schema = MessageTypeParser.parseMessageType( + """ + |message root { + | required boolean _1; + | required int32 _2; + | required int64 _3; + | required float _4; + | required double _5; + |} + """.stripMargin) + + val writeSupport = new TestGroupWriteSupport(schema) + val writer = new ParquetWriter[Group](path, writeSupport) + + (0 until 10).foreach { i => + val record = new SimpleGroup(schema) + record.add(0, i % 2 == 0) + record.add(1, i) + record.add(2, i.toLong) + record.add(3, i.toFloat) + record.add(4, i.toDouble) + writer.write(record) + } + + writer.close() + } + + withTempDir { dir => + val path = new Path(dir.toURI.toString, "part-r-0.parquet") + makeRawParquetFile(path) + checkAnswer(parquetFile(path.toString), (0 until 10).map { i => + (i % 2 == 0, i, i.toLong, i.toFloat, i.toDouble) + }) + } + } + + test("write metadata") { + withTempPath { file => + val path = new Path(file.toURI.toString) + val fs = FileSystem.getLocal(configuration) + val attributes = ScalaReflection.attributesFor[(Int, String)] + ParquetTypesConverter.writeMetaData(attributes, path, configuration) + + assert(fs.exists(new Path(path, ParquetFileWriter.PARQUET_COMMON_METADATA_FILE))) + assert(fs.exists(new Path(path, ParquetFileWriter.PARQUET_METADATA_FILE))) + + val metaData = ParquetTypesConverter.readMetaData(path, Some(configuration)) + val actualSchema = metaData.getFileMetaData.getSchema + val expectedSchema = ParquetTypesConverter.convertFromAttributes(attributes) + + actualSchema.checkContains(expectedSchema) + expectedSchema.checkContains(actualSchema) + } + } +} diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite2.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite2.scala new file mode 100644 index 0000000000000..daa7ca65cd993 --- /dev/null +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite2.scala @@ -0,0 +1,110 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.parquet + +import org.apache.spark.sql.QueryTest +import org.apache.spark.sql.catalyst.expressions.Row +import org.apache.spark.sql.test.TestSQLContext +import org.apache.spark.sql.test.TestSQLContext._ + +/** + * A test suite that tests various Parquet queries. + */ +class ParquetQuerySuite2 extends QueryTest with ParquetTest { + val sqlContext = TestSQLContext + + test("simple projection") { + withParquetTable((0 until 10).map(i => (i, i.toString)), "t") { + checkAnswer(sql("SELECT _1 FROM t"), (0 until 10).map(Row.apply(_))) + } + } + + test("insertion") { + withTempDir { dir => + val data = (0 until 10).map(i => (i, i.toString)) + withParquetTable(data, "t") { + createParquetFile[(Int, String)](dir.toString).registerTempTable("dest") + withTempTable("dest") { + sql("INSERT OVERWRITE INTO dest SELECT * FROM t") + checkAnswer(table("dest"), data) + } + } + } + } + + test("appending") { + val data = (0 until 10).map(i => (i, i.toString)) + withParquetTable(data, "t") { + sql("INSERT INTO t SELECT * FROM t") + checkAnswer(table("t"), data ++ data) + } + } + + test("self-join") { + // 4 rows, cells of column 1 of row 2 and row 4 are null + val data = (1 to 4).map { i => + val maybeInt = if (i % 2 == 0) None else Some(i) + (maybeInt, i.toString) + } + + withParquetTable(data, "t") { + val selfJoin = sql("SELECT * FROM t x JOIN t y WHERE x._1 = y._1") + val queryOutput = selfJoin.queryExecution.analyzed.output + + assertResult(4, s"Field count mismatches")(queryOutput.size) + assertResult(2, s"Duplicated expression ID in query plan:\n $selfJoin") { + queryOutput.filter(_.name == "_1").map(_.exprId).size + } + + checkAnswer(selfJoin, List(Row(1, "1", 1, "1"), Row(3, "3", 3, "3"))) + } + } + + test("nested data - struct with array field") { + val data = (1 to 10).map(i => Tuple1((i, Seq(s"val_$i")))) + withParquetTable(data, "t") { + checkAnswer(sql("SELECT _1._2[0] FROM t"), data.map { + case Tuple1((_, Seq(string))) => Row(string) + }) + } + } + + test("nested data - array of struct") { + val data = (1 to 10).map(i => Tuple1(Seq(i -> s"val_$i"))) + withParquetTable(data, "t") { + checkAnswer(sql("SELECT _1[0]._2 FROM t"), data.map { + case Tuple1(Seq((_, string))) => Row(string) + }) + } + } + + test("SPARK-1913 regression: columns only referenced by pushed down filters should remain") { + withParquetTable((1 to 10).map(Tuple1.apply), "t") { + checkAnswer(sql(s"SELECT _1 FROM t WHERE _1 < 10"), (1 to 9).map(Row.apply(_))) + } + } + + test("SPARK-3536 regression: query empty Parquet file shouldn't throw") { + withTempDir { dir => + createParquetFile[(Int, String)](dir.toString).registerTempTable("t") + withTempTable("t") { + checkAnswer(sql("SELECT * FROM t"), Seq.empty[Row]) + } + } + } +} diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetSchemaSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetSchemaSuite.scala new file mode 100644 index 0000000000000..34d61bf908483 --- /dev/null +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetSchemaSuite.scala @@ -0,0 +1,164 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.parquet + +import scala.reflect.ClassTag +import scala.reflect.runtime.universe.TypeTag + +import org.scalatest.FunSuite +import parquet.schema.MessageTypeParser + +import org.apache.spark.sql.catalyst.ScalaReflection +import org.apache.spark.sql.catalyst.types.{BinaryType, IntegerType, StructField, StructType} +import org.apache.spark.sql.test.TestSQLContext + +class ParquetSchemaSuite extends FunSuite with ParquetTest { + val sqlContext = TestSQLContext + + /** + * Checks whether the reflected Parquet message type for product type `T` conforms `messageType`. + */ + private def testSchema[T <: Product: ClassTag: TypeTag]( + testName: String, messageType: String): Unit = { + test(testName) { + val actual = ParquetTypesConverter.convertFromAttributes(ScalaReflection.attributesFor[T]) + val expected = MessageTypeParser.parseMessageType(messageType) + actual.checkContains(expected) + expected.checkContains(actual) + } + } + + testSchema[(Boolean, Int, Long, Float, Double, Array[Byte])]( + "basic types", + """ + |message root { + | required boolean _1; + | required int32 _2; + | required int64 _3; + | required float _4; + | required double _5; + | optional binary _6; + |} + """.stripMargin) + + testSchema[(Byte, Short, Int, Long)]( + "logical integral types", + """ + |message root { + | required int32 _1 (INT_8); + | required int32 _2 (INT_16); + | required int32 _3 (INT_32); + | required int64 _4 (INT_64); + |} + """.stripMargin) + + // Currently String is the only supported logical binary type. + testSchema[Tuple1[String]]( + "binary logical types", + """ + |message root { + | optional binary _1 (UTF8); + |} + """.stripMargin) + + testSchema[Tuple1[Seq[Int]]]( + "array", + """ + |message root { + | optional group _1 (LIST) { + | repeated int32 array; + | } + |} + """.stripMargin) + + testSchema[Tuple1[Map[Int, String]]]( + "map", + """ + |message root { + | optional group _1 (MAP) { + | repeated group map (MAP_KEY_VALUE) { + | required int32 key; + | optional binary value (UTF8); + | } + | } + |} + """.stripMargin) + + testSchema[Tuple1[Pair[Int, String]]]( + "struct", + """ + |message root { + | optional group _1 { + | required int32 _1; + | optional binary _2 (UTF8); + | } + |} + """.stripMargin) + + testSchema[Tuple1[Map[Int, (String, Seq[(Int, Double)])]]]( + "deeply nested type", + """ + |message root { + | optional group _1 (MAP) { + | repeated group map (MAP_KEY_VALUE) { + | required int32 key; + | optional group value { + | optional binary _1 (UTF8); + | optional group _2 (LIST) { + | repeated group bag { + | optional group array { + | required int32 _1; + | required double _2; + | } + | } + | } + | } + | } + | } + |} + """.stripMargin) + + testSchema[(Option[Int], Map[Int, Option[Double]])]( + "optional types", + """ + |message root { + | optional int32 _1; + | optional group _2 (MAP) { + | repeated group map (MAP_KEY_VALUE) { + | required int32 key; + | optional double value; + | } + | } + |} + """.stripMargin) + + test("DataType string parser compatibility") { + val schema = StructType(List( + StructField("c1", IntegerType, false), + StructField("c2", BinaryType, true))) + + val fromCaseClassString = ParquetTypesConverter.convertFromString(schema.toString) + val fromJson = ParquetTypesConverter.convertFromString(schema.json) + + (fromCaseClassString, fromJson).zipped.foreach { (a, b) => + assert(a.name == b.name) + assert(a.dataType === b.dataType) + assert(a.nullable === b.nullable) + } + } +} diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/parquet/HiveParquetSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/parquet/HiveParquetSuite.scala index 6f57fe8958387..4bc14bad0ad5f 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/parquet/HiveParquetSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/parquet/HiveParquetSuite.scala @@ -17,103 +17,66 @@ package org.apache.spark.sql.parquet -import java.io.File - -import org.scalatest.{BeforeAndAfterAll, BeforeAndAfterEach, FunSuite} - -import org.apache.spark.sql.catalyst.expressions.{AttributeReference, Row} -import org.apache.spark.sql.catalyst.types.{DataType, StringType, IntegerType} -import org.apache.spark.sql.{parquet, SchemaRDD} -import org.apache.spark.util.Utils - -// Implicits -import org.apache.spark.sql.hive.test.TestHive._ +import org.apache.spark.sql.QueryTest +import org.apache.spark.sql.catalyst.expressions.Row +import org.apache.spark.sql.hive.test.TestHive case class Cases(lower: String, UPPER: String) -class HiveParquetSuite extends FunSuite with BeforeAndAfterAll with BeforeAndAfterEach { - - val dirname = Utils.createTempDir() - - var testRDD: SchemaRDD = null - - override def beforeAll() { - // write test data - ParquetTestData.writeFile() - testRDD = parquetFile(ParquetTestData.testDir.toString) - testRDD.registerTempTable("testsource") - } - - override def afterAll() { - Utils.deleteRecursively(ParquetTestData.testDir) - Utils.deleteRecursively(dirname) - reset() // drop all tables that were registered as part of the tests - } - - // in case tests are failing we delete before and after each test - override def beforeEach() { - Utils.deleteRecursively(dirname) - } +class HiveParquetSuite extends QueryTest with ParquetTest { + val sqlContext = TestHive - override def afterEach() { - Utils.deleteRecursively(dirname) - } + import sqlContext._ test("Case insensitive attribute names") { - val tempFile = File.createTempFile("parquet", "") - tempFile.delete() - sparkContext.parallelize(1 to 10) - .map(_.toString) - .map(i => Cases(i, i)) - .saveAsParquetFile(tempFile.getCanonicalPath) - - parquetFile(tempFile.getCanonicalPath).registerTempTable("cases") - sql("SELECT upper FROM cases").collect().map(_.getString(0)) === (1 to 10).map(_.toString) - sql("SELECT LOWER FROM cases").collect().map(_.getString(0)) === (1 to 10).map(_.toString) + withParquetTable((1 to 4).map(i => Cases(i.toString, i.toString)), "cases") { + val expected = (1 to 4).map(i => Row(i.toString)) + checkAnswer(sql("SELECT upper FROM cases"), expected) + checkAnswer(sql("SELECT LOWER FROM cases"), expected) + } } test("SELECT on Parquet table") { - val rdd = sql("SELECT * FROM testsource").collect() - assert(rdd != null) - assert(rdd.forall(_.size == 6)) + val data = (1 to 4).map(i => (i, s"val_$i")) + withParquetTable(data, "t") { + checkAnswer(sql("SELECT * FROM t"), data) + } } test("Simple column projection + filter on Parquet table") { - val rdd = sql("SELECT myboolean, mylong FROM testsource WHERE myboolean=true").collect() - assert(rdd.size === 5, "Filter returned incorrect number of rows") - assert(rdd.forall(_.getBoolean(0)), "Filter returned incorrect Boolean field value") + withParquetTable((1 to 4).map(i => (i % 2 == 0, i, s"val_$i")), "t") { + checkAnswer( + sql("SELECT `_1`, `_3` FROM t WHERE `_1` = true"), + Seq(Row(true, "val_2"), Row(true, "val_4"))) + } } test("Converting Hive to Parquet Table via saveAsParquetFile") { - sql("SELECT * FROM src").saveAsParquetFile(dirname.getAbsolutePath) - parquetFile(dirname.getAbsolutePath).registerTempTable("ptable") - val rddOne = sql("SELECT * FROM src").collect().sortBy(_.getInt(0)) - val rddTwo = sql("SELECT * from ptable").collect().sortBy(_.getInt(0)) - - compareRDDs(rddOne, rddTwo, "src (Hive)", Seq("key:Int", "value:String")) + withTempPath { dir => + sql("SELECT * FROM src").saveAsParquetFile(dir.getCanonicalPath) + parquetFile(dir.getCanonicalPath).registerTempTable("p") + withTempTable("p") { + checkAnswer( + sql("SELECT * FROM src ORDER BY key"), + sql("SELECT * from p ORDER BY key").collect().toSeq) + } + } } - test("INSERT OVERWRITE TABLE Parquet table") { - sql("SELECT * FROM testsource").saveAsParquetFile(dirname.getAbsolutePath) - parquetFile(dirname.getAbsolutePath).registerTempTable("ptable") - // let's do three overwrites for good measure - sql("INSERT OVERWRITE TABLE ptable SELECT * FROM testsource").collect() - sql("INSERT OVERWRITE TABLE ptable SELECT * FROM testsource").collect() - sql("INSERT OVERWRITE TABLE ptable SELECT * FROM testsource").collect() - val rddCopy = sql("SELECT * FROM ptable").collect() - val rddOrig = sql("SELECT * FROM testsource").collect() - assert(rddCopy.size === rddOrig.size, "INSERT OVERWRITE changed size of table??") - compareRDDs(rddOrig, rddCopy, "testsource", ParquetTestData.testSchemaFieldNames) - } - private def compareRDDs(rddOne: Array[Row], rddTwo: Array[Row], tableName: String, fieldNames: Seq[String]) { - var counter = 0 - (rddOne, rddTwo).zipped.foreach { - (a,b) => (a,b).zipped.toArray.zipWithIndex.foreach { - case ((value_1, value_2), index) => - assert(value_1 === value_2, s"table $tableName row $counter field ${fieldNames(index)} don't match") + test("INSERT OVERWRITE TABLE Parquet table") { + withParquetTable((1 to 4).map(i => (i, s"val_$i")), "t") { + withTempPath { file => + sql("SELECT * FROM t LIMIT 1").saveAsParquetFile(file.getCanonicalPath) + parquetFile(file.getCanonicalPath).registerTempTable("p") + withTempTable("p") { + // let's do three overwrites for good measure + sql("INSERT OVERWRITE TABLE p SELECT * FROM t") + sql("INSERT OVERWRITE TABLE p SELECT * FROM t") + sql("INSERT OVERWRITE TABLE p SELECT * FROM t") + checkAnswer(sql("SELECT * FROM p"), sql("SELECT * FROM t").collect().toSeq) + } } - counter = counter + 1 } } } diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/parquet/parquetSuites.scala b/sql/hive/src/test/scala/org/apache/spark/sql/parquet/parquetSuites.scala index 488ebba043794..fc0e42c201d56 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/parquet/parquetSuites.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/parquet/parquetSuites.scala @@ -37,7 +37,7 @@ case class ParquetDataWithKey(p: Int, intField: Int, stringField: String) * A suite to test the automatic conversion of metastore tables with parquet data to use the * built in parquet support. */ -class ParquetMetastoreSuite extends ParquetTest { +class ParquetMetastoreSuite extends ParquetPartitioningTest { override def beforeAll(): Unit = { super.beforeAll() @@ -112,7 +112,7 @@ class ParquetMetastoreSuite extends ParquetTest { /** * A suite of tests for the Parquet support through the data sources API. */ -class ParquetSourceSuite extends ParquetTest { +class ParquetSourceSuite extends ParquetPartitioningTest { override def beforeAll(): Unit = { super.beforeAll() @@ -145,7 +145,7 @@ class ParquetSourceSuite extends ParquetTest { /** * A collection of tests for parquet data with various forms of partitioning. */ -abstract class ParquetTest extends QueryTest with BeforeAndAfterAll { +abstract class ParquetPartitioningTest extends QueryTest with BeforeAndAfterAll { var partitionedTableDir: File = null var partitionedTableDirWithKey: File = null From 0aa834adeaf4e31d63198e4197dc592790d3d0cc Mon Sep 17 00:00:00 2001 From: Cheng Hao Date: Tue, 16 Dec 2014 21:18:39 -0800 Subject: [PATCH 016/320] [SPARK-4744] [SQL] Short circuit evaluation for AND & OR in CodeGen Author: Cheng Hao Closes #3606 from chenghao-intel/codegen_short_circuit and squashes the following commits: f466303 [Cheng Hao] short circuit for AND & OR --- .../expressions/codegen/CodeGenerator.scala | 38 +++++++++---------- 1 file changed, 19 insertions(+), 19 deletions(-) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala index ab71e15e1f573..48727d5e90140 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala @@ -314,20 +314,20 @@ abstract class CodeGenerator[InType <: AnyRef, OutType <: AnyRef] extends Loggin val eval1 = expressionEvaluator(e1) val eval2 = expressionEvaluator(e2) - eval1.code ++ eval2.code ++ q""" + ..${eval1.code} var $nullTerm = false var $primitiveTerm: ${termForType(BooleanType)} = false - if ((!${eval1.nullTerm} && !${eval1.primitiveTerm}) || - (!${eval2.nullTerm} && !${eval2.primitiveTerm})) { - $nullTerm = false - $primitiveTerm = false - } else if (${eval1.nullTerm} || ${eval2.nullTerm} ) { - $nullTerm = true + if (!${eval1.nullTerm} && ${eval1.primitiveTerm} == false) { } else { - $nullTerm = false - $primitiveTerm = true + ..${eval2.code} + if (!${eval2.nullTerm} && ${eval2.primitiveTerm} == false) { + } else if (!${eval1.nullTerm} && !${eval2.nullTerm}) { + $primitiveTerm = true + } else { + $nullTerm = true + } } """.children @@ -335,20 +335,22 @@ abstract class CodeGenerator[InType <: AnyRef, OutType <: AnyRef] extends Loggin val eval1 = expressionEvaluator(e1) val eval2 = expressionEvaluator(e2) - eval1.code ++ eval2.code ++ q""" + ..${eval1.code} var $nullTerm = false var $primitiveTerm: ${termForType(BooleanType)} = false - if ((!${eval1.nullTerm} && ${eval1.primitiveTerm}) || - (!${eval2.nullTerm} && ${eval2.primitiveTerm})) { - $nullTerm = false + if (!${eval1.nullTerm} && ${eval1.primitiveTerm}) { $primitiveTerm = true - } else if (${eval1.nullTerm} || ${eval2.nullTerm} ) { - $nullTerm = true } else { - $nullTerm = false - $primitiveTerm = false + ..${eval2.code} + if (!${eval2.nullTerm} && ${eval2.primitiveTerm}) { + $primitiveTerm = true + } else if (!${eval1.nullTerm} && !${eval2.nullTerm}) { + $primitiveTerm = false + } else { + $nullTerm = true + } } """.children @@ -373,7 +375,6 @@ abstract class CodeGenerator[InType <: AnyRef, OutType <: AnyRef] extends Loggin } else if (${eval2.primitiveTerm} == 0) $nullTerm = true else { - $nullTerm = false $primitiveTerm = ${eval1.primitiveTerm} / ${eval2.primitiveTerm} } """.children @@ -494,7 +495,6 @@ abstract class CodeGenerator[InType <: AnyRef, OutType <: AnyRef] extends Loggin $nullTerm = ${eval1.nullTerm} $primitiveTerm = ${eval1.primitiveTerm} } else { - $nullTerm = false if (${eval1.primitiveTerm} > ${eval2.primitiveTerm}) { $primitiveTerm = ${eval1.primitiveTerm} } else { From ddc7ba31cb1062acb182293b2698b1b20ea56a46 Mon Sep 17 00:00:00 2001 From: Takuya UESHIN Date: Tue, 16 Dec 2014 21:19:57 -0800 Subject: [PATCH 017/320] [SPARK-4720][SQL] Remainder should also return null if the divider is 0. This is a follow-up of SPARK-4593 (#3443). Author: Takuya UESHIN Closes #3581 from ueshin/issues/SPARK-4720 and squashes the following commits: c3959d4 [Takuya UESHIN] Make Remainder return null if the divider is 0. --- .../sql/catalyst/expressions/arithmetic.scala | 11 +++++++++-- .../expressions/codegen/CodeGenerator.scala | 19 +++++++++++++++++++ .../ExpressionEvaluationSuite.scala | 15 +++++++++++++++ 3 files changed, 43 insertions(+), 2 deletions(-) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala index 61c26c50a6662..79a742ad4b2ad 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala @@ -122,9 +122,16 @@ case class Divide(left: Expression, right: Expression) extends BinaryArithmetic case class Remainder(left: Expression, right: Expression) extends BinaryArithmetic { def symbol = "%" - override def nullable = left.nullable || right.nullable || dataType.isInstanceOf[DecimalType] + override def nullable = true - override def eval(input: Row): Any = i2(input, left, right, _.rem(_, _)) + override def eval(input: Row): Any = { + val evalE2 = right.eval(input) + dataType match { + case _ if evalE2 == null => null + case _ if evalE2 == 0 => null + case nt: NumericType => i1(input, left, _.rem(_, evalE2.asInstanceOf[nt.JvmType])) + } + } } /** diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala index 48727d5e90140..90c81b2631e59 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala @@ -379,6 +379,25 @@ abstract class CodeGenerator[InType <: AnyRef, OutType <: AnyRef] extends Loggin } """.children + case Remainder(e1, e2) => + val eval1 = expressionEvaluator(e1) + val eval2 = expressionEvaluator(e2) + + eval1.code ++ eval2.code ++ + q""" + var $nullTerm = false + var $primitiveTerm: ${termForType(e1.dataType)} = 0 + + if (${eval1.nullTerm} || ${eval2.nullTerm} ) { + $nullTerm = true + } else if (${eval2.primitiveTerm} == 0) + $nullTerm = true + else { + $nullTerm = false + $primitiveTerm = ${eval1.primitiveTerm} % ${eval2.primitiveTerm} + } + """.children + case IsNotNull(e) => val eval = expressionEvaluator(e) q""" diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala index b030483223d9e..1e371db315aac 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala @@ -179,6 +179,21 @@ class ExpressionEvaluationSuite extends FunSuite { checkEvaluation(Divide(Literal(null, IntegerType), Literal(null, IntegerType)), null) } + test("Remainder") { + checkEvaluation(Remainder(Literal(2), Literal(1)), 0) + checkEvaluation(Remainder(Literal(1.0), Literal(2.0)), 1.0) + checkEvaluation(Remainder(Literal(1), Literal(2)), 1) + checkEvaluation(Remainder(Literal(1), Literal(0)), null) + checkEvaluation(Remainder(Literal(1.0), Literal(0.0)), null) + checkEvaluation(Remainder(Literal(0.0), Literal(0.0)), null) + checkEvaluation(Remainder(Literal(0), Literal(null, IntegerType)), null) + checkEvaluation(Remainder(Literal(1), Literal(null, IntegerType)), null) + checkEvaluation(Remainder(Literal(null, IntegerType), Literal(0)), null) + checkEvaluation(Remainder(Literal(null, DoubleType), Literal(0.0)), null) + checkEvaluation(Remainder(Literal(null, IntegerType), Literal(1)), null) + checkEvaluation(Remainder(Literal(null, IntegerType), Literal(null, IntegerType)), null) + } + test("INSET") { val hS = HashSet[Any]() + 1 + 2 val nS = HashSet[Any]() + 1 + 2 + null From 770d8153a5fe400147cc597c8b4b703f0aa00c22 Mon Sep 17 00:00:00 2001 From: Cheng Hao Date: Tue, 16 Dec 2014 21:21:11 -0800 Subject: [PATCH 018/320] [SPARK-4375] [SQL] Add 0 argument support for udf Author: Cheng Hao Closes #3595 from chenghao-intel/udf0 and squashes the following commits: a858973 [Cheng Hao] Add 0 arguments support for udf --- .../org/apache/spark/sql/UdfRegistration.scala | 16 ++++++++++------ .../scala/org/apache/spark/sql/UDFSuite.scala | 5 +++++ 2 files changed, 15 insertions(+), 6 deletions(-) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/UdfRegistration.scala b/sql/core/src/main/scala/org/apache/spark/sql/UdfRegistration.scala index 00d6b43a57812..5fb472686c9e1 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/UdfRegistration.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/UdfRegistration.scala @@ -72,14 +72,13 @@ private[sql] trait UDFRegistration { functionRegistry.registerFunction(name, builder) } - /** registerFunction 1-22 were generated by this script + /** registerFunction 0-22 were generated by this script - (1 to 22).map { x => - val types = (1 to x).map(x => "_").reduce(_ + ", " + _) + (0 to 22).map { x => + val types = (1 to x).foldRight("T")((_, s) => {s"_, $s"}) s""" - def registerFunction[T: TypeTag](name: String, func: Function$x[$types, T]): Unit = { - def builder(e: Seq[Expression]) = - ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + def registerFunction[T: TypeTag](name: String, func: Function$x[$types]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) functionRegistry.registerFunction(name, builder) } """ @@ -87,6 +86,11 @@ private[sql] trait UDFRegistration { */ // scalastyle:off + def registerFunction[T: TypeTag](name: String, func: Function0[T]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + functionRegistry.registerFunction(name, builder) + } + def registerFunction[T: TypeTag](name: String, func: Function1[_, T]): Unit = { def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) functionRegistry.registerFunction(name, builder) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/UDFSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/UDFSuite.scala index ef9b76b1e251e..720953ae3765a 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/UDFSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/UDFSuite.scala @@ -31,6 +31,11 @@ class UDFSuite extends QueryTest { assert(sql("SELECT strLenScala('test')").first().getInt(0) === 4) } + test("ZeroArgument UDF") { + registerFunction("random0", () => { Math.random()}) + assert(sql("SELECT random0()").first().getDouble(0) >= 0.0) + } + test("TwoArgument UDF") { registerFunction("strLenScala", (_: String).length + (_:Int)) assert(sql("SELECT strLenScala('test', 1)").first().getInt(0) === 5) From ec5c4279edabd5ea2b187aff6662ac07ed825b08 Mon Sep 17 00:00:00 2001 From: Davies Liu Date: Tue, 16 Dec 2014 21:23:28 -0800 Subject: [PATCH 019/320] [SPARK-4866] support StructType as key in MapType This PR brings support of using StructType(and other hashable types) as key in MapType. Author: Davies Liu Closes #3714 from davies/fix_struct_in_map and squashes the following commits: 68585d7 [Davies Liu] fix primitive types in MapType 9601534 [Davies Liu] support StructType as key in MapType --- python/pyspark/sql.py | 17 ++++++++++------- python/pyspark/tests.py | 8 ++++++++ .../apache/spark/sql/execution/pythonUdfs.scala | 2 +- 3 files changed, 19 insertions(+), 8 deletions(-) diff --git a/python/pyspark/sql.py b/python/pyspark/sql.py index ae288471b0e51..1ee0b28a3256d 100644 --- a/python/pyspark/sql.py +++ b/python/pyspark/sql.py @@ -788,8 +788,9 @@ def _create_converter(dataType): return lambda row: map(conv, row) elif isinstance(dataType, MapType): - conv = _create_converter(dataType.valueType) - return lambda row: dict((k, conv(v)) for k, v in row.iteritems()) + kconv = _create_converter(dataType.keyType) + vconv = _create_converter(dataType.valueType) + return lambda row: dict((kconv(k), vconv(v)) for k, v in row.iteritems()) elif isinstance(dataType, NullType): return lambda x: None @@ -944,7 +945,7 @@ def _infer_schema_type(obj, dataType): elif isinstance(dataType, MapType): k, v = obj.iteritems().next() - return MapType(_infer_type(k), + return MapType(_infer_schema_type(k, dataType.keyType), _infer_schema_type(v, dataType.valueType)) elif isinstance(dataType, StructType): @@ -1085,7 +1086,7 @@ def _has_struct_or_date(dt): elif isinstance(dt, ArrayType): return _has_struct_or_date(dt.elementType) elif isinstance(dt, MapType): - return _has_struct_or_date(dt.valueType) + return _has_struct_or_date(dt.keyType) or _has_struct_or_date(dt.valueType) elif isinstance(dt, DateType): return True elif isinstance(dt, UserDefinedType): @@ -1148,12 +1149,13 @@ def List(l): return List elif isinstance(dataType, MapType): - cls = _create_cls(dataType.valueType) + kcls = _create_cls(dataType.keyType) + vcls = _create_cls(dataType.valueType) def Dict(d): if d is None: return - return dict((k, _create_object(cls, v)) for k, v in d.items()) + return dict((_create_object(kcls, k), _create_object(vcls, v)) for k, v in d.items()) return Dict @@ -1164,7 +1166,8 @@ def Dict(d): return lambda datum: dataType.deserialize(datum) elif not isinstance(dataType, StructType): - raise Exception("unexpected data type: %s" % dataType) + # no wrapper for primitive types + return lambda x: x class Row(tuple): diff --git a/python/pyspark/tests.py b/python/pyspark/tests.py index bca52a7ce6d58..b474fcf5bfb7e 100644 --- a/python/pyspark/tests.py +++ b/python/pyspark/tests.py @@ -923,6 +923,14 @@ def test_infer_schema(self): result = self.sqlCtx.sql("SELECT l[0].a from test2 where d['key'].d = '2'") self.assertEqual(1, result.first()[0]) + def test_struct_in_map(self): + d = [Row(m={Row(i=1): Row(s="")})] + rdd = self.sc.parallelize(d) + srdd = self.sqlCtx.inferSchema(rdd) + k, v = srdd.first().m.items()[0] + self.assertEqual(1, k.i) + self.assertEqual("", v.s) + def test_convert_row_to_dict(self): row = Row(l=[Row(a=1, b='s')], d={"key": Row(c=1.0, d="2")}) self.assertEqual(1, row.asDict()['l'][0].a) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/pythonUdfs.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/pythonUdfs.scala index 2b4a88d5e864e..5a41399971dda 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/pythonUdfs.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/pythonUdfs.scala @@ -132,7 +132,7 @@ object EvaluatePython { arr.asInstanceOf[Array[Any]].map(x => toJava(x, array.elementType)) case (obj: Map[_, _], mt: MapType) => obj.map { - case (k, v) => (k, toJava(v, mt.valueType)) // key should be primitive type + case (k, v) => (toJava(k, mt.keyType), toJava(v, mt.valueType)) }.asJava case (ud, udt: UserDefinedType[_]) => toJava(udt.serialize(ud), udt.sqlType) From 60698801ebc4c4947cfc7f46762a7cca2ed40452 Mon Sep 17 00:00:00 2001 From: scwf Date: Tue, 16 Dec 2014 21:26:36 -0800 Subject: [PATCH 020/320] [SPARK-4618][SQL] Make foreign DDL commands options case-insensitive Using lowercase for ```options``` key to make it case-insensitive, then we should use lower case to get value from parameters. So flowing cmd work ``` create temporary table normal_parquet USING org.apache.spark.sql.parquet OPTIONS ( PATH '/xxx/data' ) ``` Author: scwf Author: wangfei Closes #3470 from scwf/ddl-ulcase and squashes the following commits: ae78509 [scwf] address comments 8f4f585 [wangfei] address comments 3c132ef [scwf] minor fix a0fc20b [scwf] Merge branch 'master' of https://github.com/apache/spark into ddl-ulcase 4f86401 [scwf] adding CaseInsensitiveMap e244e8d [wangfei] using lower case in json e0cb017 [wangfei] make options in-casesensitive --- .../org/apache/spark/sql/sources/ddl.scala | 19 ++++++++++++++++++- .../apache/spark/sql/sources/interfaces.scala | 6 +++++- .../spark/sql/sources/TableScanSuite.scala | 6 +++--- 3 files changed, 26 insertions(+), 5 deletions(-) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala index ca510cb0b07e3..8a66ac31f2dfb 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala @@ -100,9 +100,26 @@ private[sql] case class CreateTableUsing( } } val dataSource = clazz.newInstance().asInstanceOf[org.apache.spark.sql.sources.RelationProvider] - val relation = dataSource.createRelation(sqlContext, options) + val relation = dataSource.createRelation(sqlContext, new CaseInsensitiveMap(options)) sqlContext.baseRelationToSchemaRDD(relation).registerTempTable(tableName) Seq.empty } } + +/** + * Builds a map in which keys are case insensitive + */ +protected class CaseInsensitiveMap(map: Map[String, String]) extends Map[String, String] { + + val baseMap = map.map(kv => kv.copy(_1 = kv._1.toLowerCase)) + + override def get(k: String): Option[String] = baseMap.get(k.toLowerCase) + + override def + [B1 >: String](kv: (String, B1)): Map[String, B1] = + baseMap + kv.copy(_1 = kv._1.toLowerCase) + + override def iterator: Iterator[(String, String)] = baseMap.iterator + + override def -(key: String): Map[String, String] = baseMap - key.toLowerCase() +} diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala index 939b4e15163a6..02eff80456dbe 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala @@ -36,7 +36,11 @@ import org.apache.spark.sql.catalyst.expressions.{Expression, Attribute} */ @DeveloperApi trait RelationProvider { - /** Returns a new base relation with the given parameters. */ + /** + * Returns a new base relation with the given parameters. + * Note: the parameters' keywords are case insensitive and this insensitivity is enforced + * by the Map that is passed to the function. + */ def createRelation(sqlContext: SQLContext, parameters: Map[String, String]): BaseRelation } diff --git a/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala index b254b0620c779..3cd7b0115d567 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala @@ -25,7 +25,7 @@ class SimpleScanSource extends RelationProvider { override def createRelation( sqlContext: SQLContext, parameters: Map[String, String]): BaseRelation = { - SimpleScan(parameters("from").toInt, parameters("to").toInt)(sqlContext) + SimpleScan(parameters("from").toInt, parameters("TO").toInt)(sqlContext) } } @@ -47,8 +47,8 @@ class TableScanSuite extends DataSourceTest { |CREATE TEMPORARY TABLE oneToTen |USING org.apache.spark.sql.sources.SimpleScanSource |OPTIONS ( - | from '1', - | to '10' + | From '1', + | To '10' |) """.stripMargin) } From 4e1112e7b0f52e7f59cc42025f300fa8124eb9b2 Mon Sep 17 00:00:00 2001 From: Andrew Or Date: Tue, 16 Dec 2014 22:11:03 -0800 Subject: [PATCH 021/320] [Release] Update contributors list format and sort it Additionally, we now warn the user when a duplicate author name arises, in which case he/she needs to resolve it manually. --- .gitignore | 2 +- .rat-excludes | 1 + dev/create-release/generate-contributors.py | 8 ++--- dev/create-release/translate-contributors.py | 34 ++++++++++++++------ 4 files changed, 30 insertions(+), 15 deletions(-) diff --git a/.gitignore b/.gitignore index 3b9086c7187dc..30b1e12bf1b03 100644 --- a/.gitignore +++ b/.gitignore @@ -51,7 +51,7 @@ checkpoint derby.log dist/ dev/create-release/*txt -dev/create-release/*new +dev/create-release/*final spark-*-bin-*.tgz unit-tests.log /lib/ diff --git a/.rat-excludes b/.rat-excludes index d8bee1f8e49c9..1bf97f0f8b0d7 100644 --- a/.rat-excludes +++ b/.rat-excludes @@ -64,3 +64,4 @@ dist/* logs .*scalastyle-output.xml .*dependency-reduced-pom.xml +dev/create-release/known_translations diff --git a/dev/create-release/generate-contributors.py b/dev/create-release/generate-contributors.py index e65c5d8233098..8aaa250bd7e29 100755 --- a/dev/create-release/generate-contributors.py +++ b/dev/create-release/generate-contributors.py @@ -192,9 +192,9 @@ def populate(issue_type, components): print "==================================================================================\n" # Write to contributors file ordered by author names -# Each line takes the format "Author name - semi-colon delimited contributions" -# e.g. Andrew Or - Bug fixes in Windows, Core, and Web UI; improvements in Core -# e.g. Tathagata Das - Bug fixes and new features in Streaming +# Each line takes the format " * Author name -- semi-colon delimited contributions" +# e.g. * Andrew Or -- Bug fixes in Windows, Core, and Web UI; improvements in Core +# e.g. * Tathagata Das -- Bug fixes and new features in Streaming contributors_file = open(contributors_file_name, "w") authors = author_info.keys() authors.sort() @@ -223,7 +223,7 @@ def populate(issue_type, components): # E.g. andrewor14/SPARK-3425/SPARK-1157/SPARK-6672 if author in invalid_authors and invalid_authors[author]: author = author + "/" + "/".join(invalid_authors[author]) - line = "%s - %s" % (author, contribution) + line = " * %s -- %s" % (author, contribution) contributors_file.write(line + "\n") contributors_file.close() print "Contributors list is successfully written to %s!" % contributors_file_name diff --git a/dev/create-release/translate-contributors.py b/dev/create-release/translate-contributors.py index f3b1efdd42785..86fa02d87b9a0 100755 --- a/dev/create-release/translate-contributors.py +++ b/dev/create-release/translate-contributors.py @@ -43,14 +43,12 @@ if not GITHUB_API_TOKEN: sys.exit("GITHUB_API_TOKEN must be set") -# Write new contributors list to .new +# Write new contributors list to .final if not os.path.isfile(contributors_file_name): print "Contributors file %s does not exist!" % contributors_file_name print "Have you run ./generate-contributors.py yet?" sys.exit(1) contributors_file = open(contributors_file_name, "r") -new_contributors_file_name = contributors_file_name + ".new" -new_contributors_file = open(new_contributors_file_name, "w") warnings = [] # In non-interactive mode, this script will choose the first replacement that is valid @@ -73,7 +71,7 @@ known_translations_file = open(known_translations_file_name, "r") for line in known_translations_file: if line.startswith("#"): continue - [old_name, new_name] = line.split(" - ") + [old_name, new_name] = line.strip("\n").split(" - ") known_translations[old_name] = new_name known_translations_file.close() @@ -147,16 +145,16 @@ def generate_candidates(author, issues): # If no such name exists, the original name is used (without the JIRA numbers). print "\n========================== Translating contributor list ==========================" lines = contributors_file.readlines() +contributions = [] for i, line in enumerate(lines): - temp_author = line.split(" - ")[0] + temp_author = line.strip(" * ").split(" -- ")[0] print "Processing author %s (%d/%d)" % (temp_author, i + 1, len(lines)) if not temp_author: - error_msg = " ERROR: Expected the following format - \n" + error_msg = " ERROR: Expected the following format \" * -- \"\n" error_msg += " ERROR: Actual = %s" % line print error_msg warnings.append(error_msg) - new_contributors_file.write(line) - new_contributors_file.flush() + contributions.append(line) continue author = temp_author.split("/")[0] # Use the local copy of known translations where possible @@ -222,10 +220,26 @@ def generate_candidates(author, issues): known_translations_file.write("%s - %s\n" % (author, new_author)) known_translations_file.flush() line = line.replace(temp_author, author) - new_contributors_file.write(line) - new_contributors_file.flush() + contributions.append(line) print "==================================================================================\n" contributors_file.close() +known_translations_file.close() + +# Sort the contributions before writing them to the new file. +# Additionally, check if there are any duplicate author rows. +# This could happen if the same user has both a valid full +# name (e.g. Andrew Or) and an invalid one (andrewor14). +# If so, warn the user about this at the end. +contributions.sort() +all_authors = set() +new_contributors_file_name = contributors_file_name + ".final" +new_contributors_file = open(new_contributors_file_name, "w") +for line in contributions: + author = line.strip(" * ").split(" -- ")[0] + if author in all_authors: + warnings.append("Detected duplicate author name %s. Please merge these manually." % author) + all_authors.add(author) + new_contributors_file.write(line) new_contributors_file.close() print "Translated contributors list successfully written to %s!" % new_contributors_file_name From 3d0c37b8118f6057a663f959321a79b8061132b6 Mon Sep 17 00:00:00 2001 From: Josh Rosen Date: Tue, 16 Dec 2014 23:00:25 -0800 Subject: [PATCH 022/320] [HOTFIX] Fix RAT exclusion for known_translations file Author: Josh Rosen Closes #3719 from JoshRosen/rat-fix and squashes the following commits: 1542886 [Josh Rosen] [HOTFIX] Fix RAT exclusion for known_translations file --- .rat-excludes | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.rat-excludes b/.rat-excludes index 1bf97f0f8b0d7..769defbac11b7 100644 --- a/.rat-excludes +++ b/.rat-excludes @@ -64,4 +64,4 @@ dist/* logs .*scalastyle-output.xml .*dependency-reduced-pom.xml -dev/create-release/known_translations +known_translations From cf50631a66500561ba44347711cdb6e963d9478f Mon Sep 17 00:00:00 2001 From: Saisai Shao Date: Wed, 17 Dec 2014 11:47:44 -0800 Subject: [PATCH 023/320] [SPARK-4595][Core] Fix MetricsServlet not work issue `MetricsServlet` handler should be added to the web UI after initialized by `MetricsSystem`, otherwise servlet handler cannot be attached. Author: Saisai Shao Author: Josh Rosen Author: jerryshao Closes #3444 from jerryshao/SPARK-4595 and squashes the following commits: 434d17e [Saisai Shao] Merge pull request #10 from JoshRosen/metrics-system-cleanup 87a2292 [Josh Rosen] Guard against misuse of MetricsSystem methods. f779fe0 [jerryshao] Fix MetricsServlet not work issue --- .../scala/org/apache/spark/SparkContext.scala | 2 ++ .../apache/spark/deploy/master/Master.scala | 4 +++ .../spark/deploy/master/ui/MasterWebUI.scala | 2 -- .../apache/spark/deploy/worker/Worker.scala | 2 ++ .../spark/deploy/worker/ui/WorkerWebUI.scala | 1 - .../apache/spark/metrics/MetricsSystem.scala | 26 ++++++++++++++----- .../scala/org/apache/spark/ui/SparkUI.scala | 2 -- 7 files changed, 28 insertions(+), 11 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala index 8e5378ecc08de..66e07d10132b8 100644 --- a/core/src/main/scala/org/apache/spark/SparkContext.scala +++ b/core/src/main/scala/org/apache/spark/SparkContext.scala @@ -344,6 +344,8 @@ class SparkContext(config: SparkConf) extends Logging { // The metrics system for Driver need to be set spark.app.id to app ID. // So it should start after we get app ID from the task scheduler and set spark.app.id. metricsSystem.start() + // Attach the driver metrics servlet handler to the web ui after the metrics system is started. + metricsSystem.getServletHandlers.foreach(handler => ui.foreach(_.attachHandler(handler))) // Optionally log Spark events private[spark] val eventLogger: Option[EventLoggingListener] = { diff --git a/core/src/main/scala/org/apache/spark/deploy/master/Master.scala b/core/src/main/scala/org/apache/spark/deploy/master/Master.scala index 7b32c505def9b..1f9f35d32059d 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/Master.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/Master.scala @@ -129,6 +129,10 @@ private[spark] class Master( masterMetricsSystem.registerSource(masterSource) masterMetricsSystem.start() applicationMetricsSystem.start() + // Attach the master and app metrics servlet handler to the web ui after the metrics systems are + // started. + masterMetricsSystem.getServletHandlers.foreach(webUi.attachHandler) + applicationMetricsSystem.getServletHandlers.foreach(webUi.attachHandler) val (persistenceEngine_, leaderElectionAgent_) = RECOVERY_MODE match { case "ZOOKEEPER" => diff --git a/core/src/main/scala/org/apache/spark/deploy/master/ui/MasterWebUI.scala b/core/src/main/scala/org/apache/spark/deploy/master/ui/MasterWebUI.scala index d86ec1e03e45c..73400c5affb5d 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/ui/MasterWebUI.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/ui/MasterWebUI.scala @@ -41,8 +41,6 @@ class MasterWebUI(val master: Master, requestedPort: Int) attachPage(new HistoryNotFoundPage(this)) attachPage(new MasterPage(this)) attachHandler(createStaticHandler(MasterWebUI.STATIC_RESOURCE_DIR, "/static")) - master.masterMetricsSystem.getServletHandlers.foreach(attachHandler) - master.applicationMetricsSystem.getServletHandlers.foreach(attachHandler) } /** Attach a reconstructed UI to this Master UI. Only valid after bind(). */ diff --git a/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala b/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala index eb11163538b20..6863b625514c6 100755 --- a/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala +++ b/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala @@ -163,6 +163,8 @@ private[spark] class Worker( metricsSystem.registerSource(workerSource) metricsSystem.start() + // Attach the worker metrics servlet handler to the web ui after the metrics system is started. + metricsSystem.getServletHandlers.foreach(webUi.attachHandler) } def changeMaster(url: String, uiUrl: String) { diff --git a/core/src/main/scala/org/apache/spark/deploy/worker/ui/WorkerWebUI.scala b/core/src/main/scala/org/apache/spark/deploy/worker/ui/WorkerWebUI.scala index b07942a9ca729..7ac81a2d87efd 100644 --- a/core/src/main/scala/org/apache/spark/deploy/worker/ui/WorkerWebUI.scala +++ b/core/src/main/scala/org/apache/spark/deploy/worker/ui/WorkerWebUI.scala @@ -50,7 +50,6 @@ class WorkerWebUI( attachHandler(createStaticHandler(WorkerWebUI.STATIC_RESOURCE_BASE, "/static")) attachHandler(createServletHandler("/log", (request: HttpServletRequest) => logPage.renderLog(request), worker.securityMgr)) - worker.metricsSystem.getServletHandlers.foreach(attachHandler) } } diff --git a/core/src/main/scala/org/apache/spark/metrics/MetricsSystem.scala b/core/src/main/scala/org/apache/spark/metrics/MetricsSystem.scala index 5dd67b0cbf683..45633e3de01dd 100644 --- a/core/src/main/scala/org/apache/spark/metrics/MetricsSystem.scala +++ b/core/src/main/scala/org/apache/spark/metrics/MetricsSystem.scala @@ -76,22 +76,36 @@ private[spark] class MetricsSystem private ( private val sources = new mutable.ArrayBuffer[Source] private val registry = new MetricRegistry() + private var running: Boolean = false + // Treat MetricsServlet as a special sink as it should be exposed to add handlers to web ui private var metricsServlet: Option[MetricsServlet] = None - /** Get any UI handlers used by this metrics system. */ - def getServletHandlers = metricsServlet.map(_.getHandlers).getOrElse(Array()) + /** + * Get any UI handlers used by this metrics system; can only be called after start(). + */ + def getServletHandlers = { + require(running, "Can only call getServletHandlers on a running MetricsSystem") + metricsServlet.map(_.getHandlers).getOrElse(Array()) + } metricsConfig.initialize() def start() { + require(!running, "Attempting to start a MetricsSystem that is already running") + running = true registerSources() registerSinks() sinks.foreach(_.start) } def stop() { - sinks.foreach(_.stop) + if (running) { + sinks.foreach(_.stop) + } else { + logWarning("Stopping a MetricsSystem that is not running") + } + running = false } def report() { @@ -107,7 +121,7 @@ private[spark] class MetricsSystem private ( * @return An unique metric name for each combination of * application, executor/driver and metric source. */ - def buildRegistryName(source: Source): String = { + private[spark] def buildRegistryName(source: Source): String = { val appId = conf.getOption("spark.app.id") val executorId = conf.getOption("spark.executor.id") val defaultName = MetricRegistry.name(source.sourceName) @@ -144,7 +158,7 @@ private[spark] class MetricsSystem private ( }) } - def registerSources() { + private def registerSources() { val instConfig = metricsConfig.getInstance(instance) val sourceConfigs = metricsConfig.subProperties(instConfig, MetricsSystem.SOURCE_REGEX) @@ -160,7 +174,7 @@ private[spark] class MetricsSystem private ( } } - def registerSinks() { + private def registerSinks() { val instConfig = metricsConfig.getInstance(instance) val sinkConfigs = metricsConfig.subProperties(instConfig, MetricsSystem.SINK_REGEX) diff --git a/core/src/main/scala/org/apache/spark/ui/SparkUI.scala b/core/src/main/scala/org/apache/spark/ui/SparkUI.scala index 176907dffa46a..0c24ad2760e08 100644 --- a/core/src/main/scala/org/apache/spark/ui/SparkUI.scala +++ b/core/src/main/scala/org/apache/spark/ui/SparkUI.scala @@ -57,8 +57,6 @@ private[spark] class SparkUI private ( attachHandler(createRedirectHandler("/", "/jobs", basePath = basePath)) attachHandler( createRedirectHandler("/stages/stage/kill", "/stages", stagesTab.handleKillRequest)) - // If the UI is live, then serve - sc.foreach { _.env.metricsSystem.getServletHandlers.foreach(attachHandler) } } initialize() From 5fdcbdc0c9f91be9380b09643a5db0f96c673ce8 Mon Sep 17 00:00:00 2001 From: Cheng Hao Date: Wed, 17 Dec 2014 12:01:57 -0800 Subject: [PATCH 024/320] [SPARK-4625] [SQL] Add sort by for DSL & SimpleSqlParser Add `sort by` support for both DSL & SqlParser. This PR is relevant with #3386, either one merged, will cause the other rebased. Author: Cheng Hao Closes #3481 from chenghao-intel/sortby and squashes the following commits: 041004f [Cheng Hao] Add sort by for DSL & SimpleSqlParser --- .../apache/spark/sql/catalyst/SqlParser.scala | 10 ++++++++-- .../spark/sql/catalyst/dsl/package.scala | 2 ++ .../scala/org/apache/spark/sql/SchemaRDD.scala | 13 +++++++++++++ .../org/apache/spark/sql/DslQuerySuite.scala | 18 ++++++++++++++++++ .../org/apache/spark/sql/SQLQuerySuite.scala | 7 +++++++ 5 files changed, 48 insertions(+), 2 deletions(-) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala index a2bcd73b6074f..d4fc9bbfd3118 100755 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala @@ -85,6 +85,7 @@ class SqlParser extends AbstractSparkSQLParser { protected val ON = Keyword("ON") protected val OR = Keyword("OR") protected val ORDER = Keyword("ORDER") + protected val SORT = Keyword("SORT") protected val OUTER = Keyword("OUTER") protected val OVERWRITE = Keyword("OVERWRITE") protected val REGEXP = Keyword("REGEXP") @@ -140,7 +141,7 @@ class SqlParser extends AbstractSparkSQLParser { (WHERE ~> expression).? ~ (GROUP ~ BY ~> rep1sep(expression, ",")).? ~ (HAVING ~> expression).? ~ - (ORDER ~ BY ~> ordering).? ~ + sortType.? ~ (LIMIT ~> expression).? ^^ { case d ~ p ~ r ~ f ~ g ~ h ~ o ~ l => val base = r.getOrElse(NoRelation) @@ -150,7 +151,7 @@ class SqlParser extends AbstractSparkSQLParser { .getOrElse(Project(assignAliases(p), withFilter)) val withDistinct = d.map(_ => Distinct(withProjection)).getOrElse(withProjection) val withHaving = h.map(Filter(_, withDistinct)).getOrElse(withDistinct) - val withOrder = o.map(Sort(_, withHaving)).getOrElse(withHaving) + val withOrder = o.map(_(withHaving)).getOrElse(withHaving) val withLimit = l.map(Limit(_, withOrder)).getOrElse(withOrder) withLimit } @@ -202,6 +203,11 @@ class SqlParser extends AbstractSparkSQLParser { | FULL ~ OUTER.? ^^^ FullOuter ) + protected lazy val sortType: Parser[LogicalPlan => LogicalPlan] = + ( ORDER ~ BY ~> ordering ^^ { case o => l: LogicalPlan => Sort(o, l) } + | SORT ~ BY ~> ordering ^^ { case o => l: LogicalPlan => SortPartitions(o, l) } + ) + protected lazy val ordering: Parser[Seq[SortOrder]] = ( rep1sep(singleOrder, ",") | rep1sep(expression, ",") ~ direction.? ^^ { diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala index 70dabc4e6c2e9..fb252cdf51534 100755 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala @@ -246,6 +246,8 @@ package object dsl { def orderBy(sortExprs: SortOrder*) = Sort(sortExprs, logicalPlan) + def sortBy(sortExprs: SortOrder*) = SortPartitions(sortExprs, logicalPlan) + def groupBy(groupingExprs: Expression*)(aggregateExprs: Expression*) = { val aliasedExprs = aggregateExprs.map { case ne: NamedExpression => ne diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala index a66af602a1064..7baf8ffcef787 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala @@ -216,6 +216,19 @@ class SchemaRDD( def orderBy(sortExprs: SortOrder*): SchemaRDD = new SchemaRDD(sqlContext, Sort(sortExprs, logicalPlan)) + /** + * Sorts the results by the given expressions within partition. + * {{{ + * schemaRDD.sortBy('a) + * schemaRDD.sortBy('a, 'b) + * schemaRDD.sortBy('a.asc, 'b.desc) + * }}} + * + * @group Query + */ + def sortBy(sortExprs: SortOrder*): SchemaRDD = + new SchemaRDD(sqlContext, SortPartitions(sortExprs, logicalPlan)) + @deprecated("use limit with integer argument", "1.1.0") def limit(limitExpr: Expression): SchemaRDD = new SchemaRDD(sqlContext, Limit(limitExpr, logicalPlan)) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala index 1a330a2bb6d46..e40d034ce4dc0 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala @@ -120,6 +120,24 @@ class DslQuerySuite extends QueryTest { mapData.collect().sortBy(_.data(1)).reverse.toSeq) } + test("sorting #2") { + checkAnswer( + testData2.sortBy('a.asc, 'b.asc), + Seq((1,1), (1,2), (2,1), (2,2), (3,1), (3,2))) + + checkAnswer( + testData2.sortBy('a.asc, 'b.desc), + Seq((1,2), (1,1), (2,2), (2,1), (3,2), (3,1))) + + checkAnswer( + testData2.sortBy('a.desc, 'b.desc), + Seq((3,2), (3,1), (2,2), (2,1), (1,2), (1,1))) + + checkAnswer( + testData2.sortBy('a.desc, 'b.asc), + Seq((3,1), (3,2), (2,1), (2,2), (1,1), (1,2))) + } + test("limit") { checkAnswer( testData.limit(10), diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala index bcebce7603f13..ddf4776ecf7ae 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala @@ -42,6 +42,13 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll { TimeZone.setDefault(origZone) } + test("SPARK-4625 support SORT BY in SimpleSQLParser & DSL") { + checkAnswer( + sql("SELECT a FROM testData2 SORT BY a"), + Seq(1, 1, 2 ,2 ,3 ,3).map(Seq(_)) + ) + } + test("grouping on nested fields") { jsonRDD(sparkContext.parallelize("""{"nested": {"attribute": 1}, "value": 2}""" :: Nil)) .registerTempTable("rows") From 4782def094fc5b5030a944290d2301f887f77a02 Mon Sep 17 00:00:00 2001 From: carlmartin Date: Wed, 17 Dec 2014 12:24:03 -0800 Subject: [PATCH 025/320] [SPARK-4694]Fix HiveThriftServer2 cann't stop In Yarn HA mode. HiveThriftServer2 can not exit automactic when changing the standy resource manager in Yarn HA mode. The scheduler backend was aware of the AM had been exited so it call sc.stop to exit the driver process but there was a user thread(HiveThriftServer2 ) which was still alive and cause this problem. To fix it, make a demo thread to detect the sparkContext is null or not.If the sc is stopped, call the ThriftServer.stop to stop the user thread. Author: carlmartin Closes #3576 from SaintBacchus/ThriftServer2ExitBug and squashes the following commits: 2890b4a [carlmartin] Use SparkListener instead of the demo thread to stop the hive server. c15da0e [carlmartin] HiveThriftServer2 can not exit automactic when changing the standy resource manager in Yarn HA mode --- .../sql/hive/thriftserver/HiveThriftServer2.scala | 14 +++++++++++++- 1 file changed, 13 insertions(+), 1 deletion(-) diff --git a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala index c5b73234fa1de..6e07df18b0e15 100644 --- a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala +++ b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala @@ -27,6 +27,7 @@ import org.apache.spark.Logging import org.apache.spark.annotation.DeveloperApi import org.apache.spark.sql.hive.HiveContext import org.apache.spark.sql.hive.thriftserver.ReflectionUtils._ +import org.apache.spark.scheduler.{SparkListenerApplicationEnd, SparkListener} /** * The main entry point for the Spark SQL port of HiveServer2. Starts up a `SparkSQLContext` and a @@ -44,9 +45,9 @@ object HiveThriftServer2 extends Logging { val server = new HiveThriftServer2(sqlContext) server.init(sqlContext.hiveconf) server.start() + sqlContext.sparkContext.addSparkListener(new HiveThriftServer2Listener(server)) } - def main(args: Array[String]) { val optionsProcessor = new ServerOptionsProcessor("HiveThriftServer2") if (!optionsProcessor.process(args)) { @@ -69,12 +70,23 @@ object HiveThriftServer2 extends Logging { server.init(SparkSQLEnv.hiveContext.hiveconf) server.start() logInfo("HiveThriftServer2 started") + SparkSQLEnv.sparkContext.addSparkListener(new HiveThriftServer2Listener(server)) } catch { case e: Exception => logError("Error starting HiveThriftServer2", e) System.exit(-1) } } + + /** + * A inner sparkListener called in sc.stop to clean up the HiveThriftServer2 + */ + class HiveThriftServer2Listener(val server: HiveServer2) extends SparkListener { + override def onApplicationEnd(applicationEnd: SparkListenerApplicationEnd): Unit = { + server.stop() + } + } + } private[hive] class HiveThriftServer2(hiveContext: HiveContext) From 7ad579ee972987863c09827554a6330aa54433b1 Mon Sep 17 00:00:00 2001 From: Michael Armbrust Date: Wed, 17 Dec 2014 12:43:51 -0800 Subject: [PATCH 026/320] [SPARK-3698][SQL] Fix case insensitive resolution of GetField. Based on #2543. Author: Michael Armbrust Closes #3724 from marmbrus/resolveGetField and squashes the following commits: 0a47aae [Michael Armbrust] Fix case insensitive resolution of GetField. --- .../apache/spark/sql/catalyst/analysis/Analyzer.scala | 10 ++++++++++ .../spark/sql/catalyst/expressions/complexTypes.scala | 8 +++++++- .../sql/hive/execution/HiveResolutionSuite.scala | 11 +++++++++++ 3 files changed, 28 insertions(+), 1 deletion(-) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala index ea9bb3978691a..3705fcc1f13f3 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala @@ -21,6 +21,7 @@ import org.apache.spark.sql.catalyst.errors.TreeNodeException import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.rules._ +import org.apache.spark.sql.catalyst.types.StructType /** * A trivial [[Analyzer]] with an [[EmptyCatalog]] and [[EmptyFunctionRegistry]]. Used for testing @@ -187,6 +188,15 @@ class Analyzer(catalog: Catalog, val result = q.resolveChildren(name, resolver).getOrElse(u) logDebug(s"Resolving $u to $result") result + + // Resolve field names using the resolver. + case f @ GetField(child, fieldName) if !f.resolved && child.resolved => + child.dataType match { + case StructType(fields) => + val resolvedFieldName = fields.map(_.name).find(resolver(_, fieldName)) + resolvedFieldName.map(n => f.copy(fieldName = n)).getOrElse(f) + case _ => f + } } } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala index 917b346086dcb..b12821d44b673 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala @@ -92,7 +92,13 @@ case class GetField(child: Expression, fieldName: String) extends UnaryExpressio lazy val ordinal = structType.fields.indexOf(field) - override lazy val resolved = childrenResolved && child.dataType.isInstanceOf[StructType] + override lazy val resolved = childrenResolved && fieldResolved + + /** Returns true only if the fieldName is found in the child struct. */ + private def fieldResolved = child.dataType match { + case StructType(fields) => fields.map(_.name).contains(fieldName) + case _ => false + } override def eval(input: Row): Any = { val baseValue = child.eval(input).asInstanceOf[Row] diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveResolutionSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveResolutionSuite.scala index ee9d08ff75450..422e843d2b0d2 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveResolutionSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveResolutionSuite.scala @@ -27,6 +27,17 @@ case class Data(a: Int, B: Int, n: Nested, nestedArray: Seq[Nested]) * A set of test cases expressed in Hive QL that are not covered by the tests included in the hive distribution. */ class HiveResolutionSuite extends HiveComparisonTest { + + case class NestedData(a: Seq[NestedData2], B: NestedData2) + case class NestedData2(a: NestedData3, B: NestedData3) + case class NestedData3(a: Int, B: Int) + + test("SPARK-3698: case insensitive test for nested data") { + sparkContext.makeRDD(Seq.empty[NestedData]).registerTempTable("nested") + // This should be successfully analyzed + sql("SELECT a[0].A.A from nested").queryExecution.analyzed + } + createQueryTest("table.attr", "SELECT src.key FROM src ORDER BY key LIMIT 1") From 62771353767b5eecf2ec6c732cab07369d784df5 Mon Sep 17 00:00:00 2001 From: Cheng Lian Date: Wed, 17 Dec 2014 12:48:04 -0800 Subject: [PATCH 027/320] [SPARK-4493][SQL] Don't pushdown Eq, NotEq, Lt, LtEq, Gt and GtEq predicates with nulls for Parquet Predicates like `a = NULL` and `a < NULL` can't be pushed down since Parquet `Lt`, `LtEq`, `Gt`, `GtEq` doesn't accept null value. Note that `Eq` and `NotEq` can only be used with `null` to represent predicates like `a IS NULL` and `a IS NOT NULL`. However, normally this issue doesn't cause NPE because any value compared to `NULL` results `NULL`, and Spark SQL automatically optimizes out `NULL` predicate in the `SimplifyFilters` rule. Only testing code that intentionally disables the optimizer may trigger this issue. (That's why this issue is not marked as blocker and I do **NOT** think we need to backport this to branch-1.1 This PR restricts `Lt`, `LtEq`, `Gt` and `GtEq` to non-null values only, and only uses `Eq` with null value to pushdown `IsNull` and `IsNotNull`. Also, added support for Parquet `NotEq` filter for completeness and (tiny) performance gain, it's also used to pushdown `IsNotNull`. [Review on Reviewable](https://reviewable.io/reviews/apache/spark/3367) Author: Cheng Lian Closes #3367 from liancheng/filters-with-null and squashes the following commits: cc41281 [Cheng Lian] Fixes several styling issues de7de28 [Cheng Lian] Adds stricter rules for Parquet filters with null --- .../sql/catalyst/expressions/literals.scala | 9 ++ .../spark/sql/parquet/ParquetFilters.scala | 68 +++++++-- .../spark/sql/parquet/ParquetQuerySuite.scala | 129 ++++++++++++++++-- 3 files changed, 183 insertions(+), 23 deletions(-) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala index 93c19325151bf..94e1d37c1c3ab 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala @@ -41,6 +41,15 @@ object Literal { } } +/** + * An extractor that matches non-null literal values + */ +object NonNullLiteral { + def unapply(literal: Literal): Option[(Any, DataType)] = { + Option(literal.value).map(_ => (literal.value, literal.dataType)) + } +} + /** * Extractor for retrieving Int literals. */ diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetFilters.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetFilters.scala index 6fb5f49b13668..56e7d11b2feea 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetFilters.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetFilters.scala @@ -50,12 +50,37 @@ private[sql] object ParquetFilters { (n: String, v: Any) => FilterApi.eq(floatColumn(n), v.asInstanceOf[java.lang.Float]) case DoubleType => (n: String, v: Any) => FilterApi.eq(doubleColumn(n), v.asInstanceOf[java.lang.Double]) + + // Binary.fromString and Binary.fromByteArray don't accept null values case StringType => - (n: String, v: Any) => - FilterApi.eq(binaryColumn(n), Binary.fromString(v.asInstanceOf[String])) + (n: String, v: Any) => FilterApi.eq( + binaryColumn(n), + Option(v).map(s => Binary.fromString(s.asInstanceOf[String])).orNull) case BinaryType => - (n: String, v: Any) => - FilterApi.eq(binaryColumn(n), Binary.fromByteArray(v.asInstanceOf[Array[Byte]])) + (n: String, v: Any) => FilterApi.eq( + binaryColumn(n), + Option(v).map(b => Binary.fromByteArray(v.asInstanceOf[Array[Byte]])).orNull) + } + + val makeNotEq: PartialFunction[DataType, (String, Any) => FilterPredicate] = { + case BooleanType => + (n: String, v: Any) => FilterApi.notEq(booleanColumn(n), v.asInstanceOf[java.lang.Boolean]) + case IntegerType => + (n: String, v: Any) => FilterApi.notEq(intColumn(n), v.asInstanceOf[Integer]) + case LongType => + (n: String, v: Any) => FilterApi.notEq(longColumn(n), v.asInstanceOf[java.lang.Long]) + case FloatType => + (n: String, v: Any) => FilterApi.notEq(floatColumn(n), v.asInstanceOf[java.lang.Float]) + case DoubleType => + (n: String, v: Any) => FilterApi.notEq(doubleColumn(n), v.asInstanceOf[java.lang.Double]) + case StringType => + (n: String, v: Any) => FilterApi.notEq( + binaryColumn(n), + Option(v).map(s => Binary.fromString(s.asInstanceOf[String])).orNull) + case BinaryType => + (n: String, v: Any) => FilterApi.notEq( + binaryColumn(n), + Option(v).map(b => Binary.fromByteArray(v.asInstanceOf[Array[Byte]])).orNull) } val makeLt: PartialFunction[DataType, (String, Any) => FilterPredicate] = { @@ -126,30 +151,45 @@ private[sql] object ParquetFilters { FilterApi.gtEq(binaryColumn(n), Binary.fromByteArray(v.asInstanceOf[Array[Byte]])) } + // NOTE: + // + // For any comparison operator `cmp`, both `a cmp NULL` and `NULL cmp a` evaluate to `NULL`, + // which can be casted to `false` implicitly. Please refer to the `eval` method of these + // operators and the `SimplifyFilters` rule for details. predicate match { - case EqualTo(NamedExpression(name, _), Literal(value, dataType)) if dataType != NullType => + case IsNull(NamedExpression(name, dataType)) => + makeEq.lift(dataType).map(_(name, null)) + case IsNotNull(NamedExpression(name, dataType)) => + makeNotEq.lift(dataType).map(_(name, null)) + + case EqualTo(NamedExpression(name, _), NonNullLiteral(value, dataType)) => makeEq.lift(dataType).map(_(name, value)) - case EqualTo(Literal(value, dataType), NamedExpression(name, _)) if dataType != NullType => + case EqualTo(NonNullLiteral(value, dataType), NamedExpression(name, _)) => makeEq.lift(dataType).map(_(name, value)) - case LessThan(NamedExpression(name, _), Literal(value, dataType)) => + case Not(EqualTo(NamedExpression(name, _), NonNullLiteral(value, dataType))) => + makeNotEq.lift(dataType).map(_(name, value)) + case Not(EqualTo(NonNullLiteral(value, dataType), NamedExpression(name, _))) => + makeNotEq.lift(dataType).map(_(name, value)) + + case LessThan(NamedExpression(name, _), NonNullLiteral(value, dataType)) => makeLt.lift(dataType).map(_(name, value)) - case LessThan(Literal(value, dataType), NamedExpression(name, _)) => + case LessThan(NonNullLiteral(value, dataType), NamedExpression(name, _)) => makeGt.lift(dataType).map(_(name, value)) - case LessThanOrEqual(NamedExpression(name, _), Literal(value, dataType)) => + case LessThanOrEqual(NamedExpression(name, _), NonNullLiteral(value, dataType)) => makeLtEq.lift(dataType).map(_(name, value)) - case LessThanOrEqual(Literal(value, dataType), NamedExpression(name, _)) => + case LessThanOrEqual(NonNullLiteral(value, dataType), NamedExpression(name, _)) => makeGtEq.lift(dataType).map(_(name, value)) - case GreaterThan(NamedExpression(name, _), Literal(value, dataType)) => + case GreaterThan(NamedExpression(name, _), NonNullLiteral(value, dataType)) => makeGt.lift(dataType).map(_(name, value)) - case GreaterThan(Literal(value, dataType), NamedExpression(name, _)) => + case GreaterThan(NonNullLiteral(value, dataType), NamedExpression(name, _)) => makeLt.lift(dataType).map(_(name, value)) - case GreaterThanOrEqual(NamedExpression(name, _), Literal(value, dataType)) => + case GreaterThanOrEqual(NamedExpression(name, _), NonNullLiteral(value, dataType)) => makeGtEq.lift(dataType).map(_(name, value)) - case GreaterThanOrEqual(Literal(value, dataType), NamedExpression(name, _)) => + case GreaterThanOrEqual(NonNullLiteral(value, dataType), NamedExpression(name, _)) => makeLtEq.lift(dataType).map(_(name, value)) case And(lhs, rhs) => diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala index 7ee4f3c1e93eb..0e5635d3e99dc 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala @@ -17,12 +17,13 @@ package org.apache.spark.sql.parquet -import _root_.parquet.filter2.predicate.{FilterPredicate, Operators} import org.apache.hadoop.fs.{FileSystem, Path} import org.apache.hadoop.mapreduce.Job import org.scalatest.{BeforeAndAfterAll, FunSuiteLike} +import parquet.filter2.predicate.{FilterPredicate, Operators} import parquet.hadoop.ParquetFileWriter import parquet.hadoop.util.ContextUtil +import parquet.io.api.Binary import org.apache.spark.sql._ import org.apache.spark.sql.catalyst.expressions._ @@ -84,7 +85,8 @@ case class NumericData(i: Int, d: Double) class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterAll { TestData // Load test data tables. - var testRDD: SchemaRDD = null + private var testRDD: SchemaRDD = null + private val originalParquetFilterPushdownEnabled = TestSQLContext.parquetFilterPushDown override def beforeAll() { ParquetTestData.writeFile() @@ -109,13 +111,17 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA Utils.deleteRecursively(ParquetTestData.testNestedDir3) Utils.deleteRecursively(ParquetTestData.testNestedDir4) // here we should also unregister the table?? + + setConf(SQLConf.PARQUET_FILTER_PUSHDOWN_ENABLED, originalParquetFilterPushdownEnabled.toString) } test("Read/Write All Types") { val tempDir = getTempFilePath("parquetTest").getCanonicalPath val range = (0 to 255) - val data = sparkContext.parallelize(range) - .map(x => AllDataTypes(s"$x", x, x.toLong, x.toFloat, x.toDouble, x.toShort, x.toByte, x % 2 == 0)) + val data = sparkContext.parallelize(range).map { x => + parquet.AllDataTypes( + s"$x", x, x.toLong, x.toFloat, x.toDouble, x.toShort, x.toByte, x % 2 == 0) + } data.saveAsParquetFile(tempDir) @@ -260,14 +266,15 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA test("Read/Write All Types with non-primitive type") { val tempDir = getTempFilePath("parquetTest").getCanonicalPath val range = (0 to 255) - val data = sparkContext.parallelize(range) - .map(x => AllDataTypesWithNonPrimitiveType( + val data = sparkContext.parallelize(range).map { x => + parquet.AllDataTypesWithNonPrimitiveType( s"$x", x, x.toLong, x.toFloat, x.toDouble, x.toShort, x.toByte, x % 2 == 0, (0 until x), (0 until x).map(Option(_).filter(_ % 3 == 0)), (0 until x).map(i => i -> i.toLong).toMap, (0 until x).map(i => i -> Option(i.toLong)).toMap + (x -> None), - Data((0 until x), Nested(x, s"$x")))) + parquet.Data((0 until x), parquet.Nested(x, s"$x"))) + } data.saveAsParquetFile(tempDir) checkAnswer( @@ -420,7 +427,7 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA } test("save and load case class RDD with nulls as parquet") { - val data = NullReflectData(null, null, null, null, null) + val data = parquet.NullReflectData(null, null, null, null, null) val rdd = sparkContext.parallelize(data :: Nil) val file = getTempFilePath("parquet") @@ -435,7 +442,7 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA } test("save and load case class RDD with Nones as parquet") { - val data = OptionalReflectData(None, None, None, None, None) + val data = parquet.OptionalReflectData(None, None, None, None, None) val rdd = sparkContext.parallelize(data :: Nil) val file = getTempFilePath("parquet") @@ -938,4 +945,108 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA checkAnswer(parquetFile(tempDir), data.toSchemaRDD.collect().toSeq) } } + + def checkFilter(predicate: Predicate, filterClass: Class[_ <: FilterPredicate]): Unit = { + val filter = ParquetFilters.createFilter(predicate) + assert(filter.isDefined) + assert(filter.get.getClass == filterClass) + } + + test("Pushdown IsNull predicate") { + checkFilter('a.int.isNull, classOf[Operators.Eq[Integer]]) + checkFilter('a.long.isNull, classOf[Operators.Eq[java.lang.Long]]) + checkFilter('a.float.isNull, classOf[Operators.Eq[java.lang.Float]]) + checkFilter('a.double.isNull, classOf[Operators.Eq[java.lang.Double]]) + checkFilter('a.string.isNull, classOf[Operators.Eq[Binary]]) + checkFilter('a.binary.isNull, classOf[Operators.Eq[Binary]]) + } + + test("Pushdown IsNotNull predicate") { + checkFilter('a.int.isNotNull, classOf[Operators.NotEq[Integer]]) + checkFilter('a.long.isNotNull, classOf[Operators.NotEq[java.lang.Long]]) + checkFilter('a.float.isNotNull, classOf[Operators.NotEq[java.lang.Float]]) + checkFilter('a.double.isNotNull, classOf[Operators.NotEq[java.lang.Double]]) + checkFilter('a.string.isNotNull, classOf[Operators.NotEq[Binary]]) + checkFilter('a.binary.isNotNull, classOf[Operators.NotEq[Binary]]) + } + + test("Pushdown EqualTo predicate") { + checkFilter('a.int === 0, classOf[Operators.Eq[Integer]]) + checkFilter('a.long === 0.toLong, classOf[Operators.Eq[java.lang.Long]]) + checkFilter('a.float === 0.toFloat, classOf[Operators.Eq[java.lang.Float]]) + checkFilter('a.double === 0.toDouble, classOf[Operators.Eq[java.lang.Double]]) + checkFilter('a.string === "foo", classOf[Operators.Eq[Binary]]) + checkFilter('a.binary === "foo".getBytes, classOf[Operators.Eq[Binary]]) + } + + test("Pushdown Not(EqualTo) predicate") { + checkFilter(!('a.int === 0), classOf[Operators.NotEq[Integer]]) + checkFilter(!('a.long === 0.toLong), classOf[Operators.NotEq[java.lang.Long]]) + checkFilter(!('a.float === 0.toFloat), classOf[Operators.NotEq[java.lang.Float]]) + checkFilter(!('a.double === 0.toDouble), classOf[Operators.NotEq[java.lang.Double]]) + checkFilter(!('a.string === "foo"), classOf[Operators.NotEq[Binary]]) + checkFilter(!('a.binary === "foo".getBytes), classOf[Operators.NotEq[Binary]]) + } + + test("Pushdown LessThan predicate") { + checkFilter('a.int < 0, classOf[Operators.Lt[Integer]]) + checkFilter('a.long < 0.toLong, classOf[Operators.Lt[java.lang.Long]]) + checkFilter('a.float < 0.toFloat, classOf[Operators.Lt[java.lang.Float]]) + checkFilter('a.double < 0.toDouble, classOf[Operators.Lt[java.lang.Double]]) + checkFilter('a.string < "foo", classOf[Operators.Lt[Binary]]) + checkFilter('a.binary < "foo".getBytes, classOf[Operators.Lt[Binary]]) + } + + test("Pushdown LessThanOrEqual predicate") { + checkFilter('a.int <= 0, classOf[Operators.LtEq[Integer]]) + checkFilter('a.long <= 0.toLong, classOf[Operators.LtEq[java.lang.Long]]) + checkFilter('a.float <= 0.toFloat, classOf[Operators.LtEq[java.lang.Float]]) + checkFilter('a.double <= 0.toDouble, classOf[Operators.LtEq[java.lang.Double]]) + checkFilter('a.string <= "foo", classOf[Operators.LtEq[Binary]]) + checkFilter('a.binary <= "foo".getBytes, classOf[Operators.LtEq[Binary]]) + } + + test("Pushdown GreaterThan predicate") { + checkFilter('a.int > 0, classOf[Operators.Gt[Integer]]) + checkFilter('a.long > 0.toLong, classOf[Operators.Gt[java.lang.Long]]) + checkFilter('a.float > 0.toFloat, classOf[Operators.Gt[java.lang.Float]]) + checkFilter('a.double > 0.toDouble, classOf[Operators.Gt[java.lang.Double]]) + checkFilter('a.string > "foo", classOf[Operators.Gt[Binary]]) + checkFilter('a.binary > "foo".getBytes, classOf[Operators.Gt[Binary]]) + } + + test("Pushdown GreaterThanOrEqual predicate") { + checkFilter('a.int >= 0, classOf[Operators.GtEq[Integer]]) + checkFilter('a.long >= 0.toLong, classOf[Operators.GtEq[java.lang.Long]]) + checkFilter('a.float >= 0.toFloat, classOf[Operators.GtEq[java.lang.Float]]) + checkFilter('a.double >= 0.toDouble, classOf[Operators.GtEq[java.lang.Double]]) + checkFilter('a.string >= "foo", classOf[Operators.GtEq[Binary]]) + checkFilter('a.binary >= "foo".getBytes, classOf[Operators.GtEq[Binary]]) + } + + test("Comparison with null should not be pushed down") { + val predicates = Seq( + 'a.int === null, + !('a.int === null), + + Literal(null) === 'a.int, + !(Literal(null) === 'a.int), + + 'a.int < null, + 'a.int <= null, + 'a.int > null, + 'a.int >= null, + + Literal(null) < 'a.int, + Literal(null) <= 'a.int, + Literal(null) > 'a.int, + Literal(null) >= 'a.int + ) + + predicates.foreach { p => + assert( + ParquetFilters.createFilter(p).isEmpty, + "Comparison predicate with null shouldn't be pushed down") + } + } } From 902e4d54acbc3c88163a5c6447aff68ed57475c1 Mon Sep 17 00:00:00 2001 From: Daoyuan Wang Date: Wed, 17 Dec 2014 12:51:27 -0800 Subject: [PATCH 028/320] [SPARK-4755] [SQL] sqrt(negative value) should return null Author: Daoyuan Wang Closes #3616 from adrian-wang/sqrt and squashes the following commits: d877439 [Daoyuan Wang] fix NULLTYPE 3effa2c [Daoyuan Wang] sqrt(negative value) should return null --- .../sql/catalyst/expressions/arithmetic.scala | 15 +++++++++++++-- .../expressions/ExpressionEvaluationSuite.scala | 2 ++ 2 files changed, 15 insertions(+), 2 deletions(-) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala index 79a742ad4b2ad..168a963e29c90 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala @@ -38,11 +38,22 @@ case class Sqrt(child: Expression) extends UnaryExpression { def dataType = DoubleType override def foldable = child.foldable - def nullable = child.nullable + def nullable = true override def toString = s"SQRT($child)" override def eval(input: Row): Any = { - n1(child, input, (na,a) => math.sqrt(na.toDouble(a))) + val evalE = child.eval(input) + if (evalE == null) { + null + } else { + child.dataType match { + case n: NumericType => + val value = n.numeric.toDouble(evalE.asInstanceOf[n.JvmType]) + if (value < 0) null + else math.sqrt(value) + case other => sys.error(s"Type $other does not support non-negative numeric operations") + } + } } } diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala index 1e371db315aac..4ba7d87ba8c5a 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala @@ -1037,6 +1037,8 @@ class ExpressionEvaluationSuite extends FunSuite { } checkEvaluation(Sqrt(Literal(null, DoubleType)), null, new GenericRow(Array[Any](null))) + checkEvaluation(Sqrt(-1), null, EmptyRow) + checkEvaluation(Sqrt(-1.5), null, EmptyRow) } test("Bitwise operations") { From 636d9fc450faaa0d8e82e0d34bb7b791e3812cb7 Mon Sep 17 00:00:00 2001 From: Cheng Hao Date: Wed, 17 Dec 2014 13:39:36 -0800 Subject: [PATCH 029/320] [SPARK-3739] [SQL] Update the split num base on block size for table scanning In local mode, Hadoop/Hive will ignore the "mapred.map.tasks", hence for small table file, it's always a single input split, however, SparkSQL doesn't honor that in table scanning, and we will get different result when do the Hive Compatibility test. This PR will fix that. Author: Cheng Hao Closes #2589 from chenghao-intel/source_split and squashes the following commits: dff38e7 [Cheng Hao] Remove the extra blank line 160a2b6 [Cheng Hao] fix the compiling bug 04d67f7 [Cheng Hao] Keep 1 split for small file in table scanning --- .../apache/spark/sql/hive/TableReader.scala | 13 +- ...l_table-0-7a45831bf96814d9a7fc3d78fb7bd8dc | 500 ++++++++++++++++++ .../hive/execution/HiveTableScanSuite.scala | 9 +- 3 files changed, 517 insertions(+), 5 deletions(-) create mode 100644 sql/hive/src/test/resources/golden/file_split_for_small_table-0-7a45831bf96814d9a7fc3d78fb7bd8dc diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala index f60bc3788e3e4..c368715f7c6f5 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala @@ -57,10 +57,15 @@ class HadoopTableReader( @transient hiveExtraConf: HiveConf) extends TableReader { - // Choose the minimum number of splits. If mapred.map.tasks is set, then use that unless - // it is smaller than what Spark suggests. - private val _minSplitsPerRDD = math.max( - sc.hiveconf.getInt("mapred.map.tasks", 1), sc.sparkContext.defaultMinPartitions) + // Hadoop honors "mapred.map.tasks" as hint, but will ignore when mapred.job.tracker is "local". + // https://hadoop.apache.org/docs/r1.0.4/mapred-default.html + // + // In order keep consistency with Hive, we will let it be 0 in local mode also. + private val _minSplitsPerRDD = if (sc.sparkContext.isLocal) { + 0 // will splitted based on block by default. + } else { + math.max(sc.hiveconf.getInt("mapred.map.tasks", 1), sc.sparkContext.defaultMinPartitions) + } // TODO: set aws s3 credentials. diff --git a/sql/hive/src/test/resources/golden/file_split_for_small_table-0-7a45831bf96814d9a7fc3d78fb7bd8dc b/sql/hive/src/test/resources/golden/file_split_for_small_table-0-7a45831bf96814d9a7fc3d78fb7bd8dc new file mode 100644 index 0000000000000..b70e127e82d05 --- /dev/null +++ b/sql/hive/src/test/resources/golden/file_split_for_small_table-0-7a45831bf96814d9a7fc3d78fb7bd8dc @@ -0,0 +1,500 @@ +0 val_0 +0 val_0 +0 val_0 +2 val_2 +4 val_4 +5 val_5 +5 val_5 +5 val_5 +8 val_8 +9 val_9 +10 val_10 +11 val_11 +12 val_12 +12 val_12 +15 val_15 +15 val_15 +17 val_17 +18 val_18 +18 val_18 +19 val_19 +20 val_20 +24 val_24 +24 val_24 +26 val_26 +26 val_26 +27 val_27 +28 val_28 +30 val_30 +33 val_33 +34 val_34 +35 val_35 +35 val_35 +35 val_35 +37 val_37 +37 val_37 +41 val_41 +42 val_42 +42 val_42 +43 val_43 +44 val_44 +47 val_47 +51 val_51 +51 val_51 +53 val_53 +54 val_54 +57 val_57 +58 val_58 +58 val_58 +64 val_64 +65 val_65 +66 val_66 +67 val_67 +67 val_67 +69 val_69 +70 val_70 +70 val_70 +70 val_70 +72 val_72 +72 val_72 +74 val_74 +76 val_76 +76 val_76 +77 val_77 +78 val_78 +80 val_80 +82 val_82 +83 val_83 +83 val_83 +84 val_84 +84 val_84 +85 val_85 +86 val_86 +87 val_87 +90 val_90 +90 val_90 +90 val_90 +92 val_92 +95 val_95 +95 val_95 +96 val_96 +97 val_97 +97 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val_469 +469 val_469 +470 val_470 +472 val_472 +475 val_475 +477 val_477 +478 val_478 +478 val_478 +479 val_479 +480 val_480 +480 val_480 +480 val_480 +481 val_481 +482 val_482 +483 val_483 +484 val_484 +485 val_485 +487 val_487 +489 val_489 +489 val_489 +489 val_489 +489 val_489 +490 val_490 +491 val_491 +492 val_492 +492 val_492 +493 val_493 +494 val_494 +495 val_495 +496 val_496 +497 val_497 +498 val_498 +498 val_498 +498 val_498 diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveTableScanSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveTableScanSuite.scala index 54c0f017d4cb6..a0ace91060a28 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveTableScanSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveTableScanSuite.scala @@ -44,6 +44,14 @@ class HiveTableScanSuite extends HiveComparisonTest { |SELECT * from part_scan_test; """.stripMargin) + // In unit test, kv1.txt is a small file and will be loaded as table src + // Since the small file will be considered as a single split, we assume + // Hive / SparkSQL HQL has the same output even for SORT BY + createQueryTest("file_split_for_small_table", + """ + |SELECT key, value FROM src SORT BY key, value + """.stripMargin) + test("Spark-4041: lowercase issue") { TestHive.sql("CREATE TABLE tb (KEY INT, VALUE STRING) STORED AS ORC") TestHive.sql("insert into table tb select key, value from src") @@ -68,5 +76,4 @@ class HiveTableScanSuite extends HiveComparisonTest { === Array(Row(java.sql.Timestamp.valueOf("2014-12-11 00:00:00")),Row(null))) TestHive.sql("DROP TABLE timestamp_query_null") } - } From affc3f460fc6172b6cea88a8779d6d40166c1c6b Mon Sep 17 00:00:00 2001 From: "Joseph K. Bradley" Date: Wed, 17 Dec 2014 14:12:46 -0800 Subject: [PATCH 030/320] [SPARK-4821] [mllib] [python] [docs] Fix for pyspark.mllib.rand doc + small doc edit + include edit to make IntelliJ happy CC: davies mengxr Note to davies -- this does not fix the "WARNING: Literal block expected; none found." warnings since that seems to involve spacing which IntelliJ does not like. (Those warnings occur when generating the Python docs.) Author: Joseph K. Bradley Closes #3669 from jkbradley/python-warnings and squashes the following commits: 4587868 [Joseph K. Bradley] fixed warning 8cb073c [Joseph K. Bradley] Updated based on davies recommendation c51eca4 [Joseph K. Bradley] Updated rst file for pyspark.mllib.rand doc. Small doc edit. Small include edit to make IntelliJ happy. --- python/docs/pyspark.streaming.rst | 2 +- python/pyspark/mllib/__init__.py | 27 +-------------------------- python/pyspark/mllib/feature.py | 6 +++--- 3 files changed, 5 insertions(+), 30 deletions(-) diff --git a/python/docs/pyspark.streaming.rst b/python/docs/pyspark.streaming.rst index 5024d694b668f..f08185627d0bc 100644 --- a/python/docs/pyspark.streaming.rst +++ b/python/docs/pyspark.streaming.rst @@ -1,5 +1,5 @@ pyspark.streaming module -================== +======================== Module contents --------------- diff --git a/python/pyspark/mllib/__init__.py b/python/pyspark/mllib/__init__.py index 5030a655fcbba..c3217620e3c4e 100644 --- a/python/pyspark/mllib/__init__.py +++ b/python/pyspark/mllib/__init__.py @@ -32,29 +32,4 @@ import rand as random random.__name__ = 'random' random.RandomRDDs.__module__ = __name__ + '.random' - - -class RandomModuleHook(object): - """ - Hook to import pyspark.mllib.random - """ - fullname = __name__ + '.random' - - def find_module(self, name, path=None): - # skip all other modules - if not name.startswith(self.fullname): - return - return self - - def load_module(self, name): - if name == self.fullname: - return random - - cname = name.rsplit('.', 1)[-1] - try: - return getattr(random, cname) - except AttributeError: - raise ImportError - - -sys.meta_path.append(RandomModuleHook()) +sys.modules[__name__ + '.random'] = random diff --git a/python/pyspark/mllib/feature.py b/python/pyspark/mllib/feature.py index 741c630cbd6eb..e46af208866a2 100644 --- a/python/pyspark/mllib/feature.py +++ b/python/pyspark/mllib/feature.py @@ -53,10 +53,10 @@ class Normalizer(VectorTransformer): """ :: Experimental :: - Normalizes samples individually to unit L\ :sup:`p`\ norm + Normalizes samples individually to unit L\ :sup:`p`\ norm - For any 1 <= `p` <= float('inf'), normalizes samples using - sum(abs(vector). :sup:`p`) :sup:`(1/p)` as norm. + For any 1 <= `p` < float('inf'), normalizes samples using + sum(abs(vector) :sup:`p`) :sup:`(1/p)` as norm. For `p` = float('inf'), max(abs(vector)) will be used as norm for normalization. From 19c0faad6d04349952ec25ce5ae94b718d7e8518 Mon Sep 17 00:00:00 2001 From: Michael Armbrust Date: Wed, 17 Dec 2014 14:27:02 -0800 Subject: [PATCH 031/320] [HOTFIX][SQL] Fix parquet filter suite Author: Michael Armbrust Closes #3727 from marmbrus/parquetNotEq and squashes the following commits: 2157bfc [Michael Armbrust] Fix parquet filter suite --- .../sql/parquet/ParquetFilterSuite.scala | 24 +++++++++---------- 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala index 111a459e6d27d..b17300475b6f6 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala @@ -87,14 +87,14 @@ class ParquetFilterSuite extends QueryTest with ParquetTest { test("filter pushdown - boolean") { withParquetRDD((true :: false :: Nil).map(Tuple1.apply)) { rdd => checkFilterPushdown(rdd, '_1)('_1 === true, classOf[Eq[java.lang.Boolean]])(true) - checkFilterPushdown(rdd, '_1)('_1 !== true, classOf[Operators.Not])(false) + checkFilterPushdown(rdd, '_1)('_1 !== true, classOf[Operators.NotEq[java.lang.Boolean]])(false) } } test("filter pushdown - integer") { withParquetRDD((1 to 4).map(Tuple1.apply)) { rdd => checkFilterPushdown(rdd, '_1)('_1 === 1, classOf[Eq[Integer]])(1) - checkFilterPushdown(rdd, '_1)('_1 !== 1, classOf[Operators.Not]) { + checkFilterPushdown(rdd, '_1)('_1 !== 1, classOf[Operators.NotEq[Integer]]) { (2 to 4).map(Row.apply(_)) } @@ -118,9 +118,9 @@ class ParquetFilterSuite extends QueryTest with ParquetTest { } test("filter pushdown - long") { - withParquetRDD((1 to 4).map(i => Tuple1.apply(i.toLong))) { rdd => + withParquetRDD((1 to 4).map(i => Tuple1(i.toLong))) { rdd => checkFilterPushdown(rdd, '_1)('_1 === 1, classOf[Eq[java.lang.Long]])(1) - checkFilterPushdown(rdd, '_1)('_1 !== 1, classOf[Operators.Not]) { + checkFilterPushdown(rdd, '_1)('_1 !== 1, classOf[Operators.NotEq[java.lang.Long]]) { (2 to 4).map(Row.apply(_)) } @@ -144,9 +144,9 @@ class ParquetFilterSuite extends QueryTest with ParquetTest { } test("filter pushdown - float") { - withParquetRDD((1 to 4).map(i => Tuple1.apply(i.toFloat))) { rdd => + withParquetRDD((1 to 4).map(i => Tuple1(i.toFloat))) { rdd => checkFilterPushdown(rdd, '_1)('_1 === 1, classOf[Eq[java.lang.Float]])(1) - checkFilterPushdown(rdd, '_1)('_1 !== 1, classOf[Operators.Not]) { + checkFilterPushdown(rdd, '_1)('_1 !== 1, classOf[Operators.NotEq[java.lang.Float]]) { (2 to 4).map(Row.apply(_)) } @@ -170,9 +170,9 @@ class ParquetFilterSuite extends QueryTest with ParquetTest { } test("filter pushdown - double") { - withParquetRDD((1 to 4).map(i => Tuple1.apply(i.toDouble))) { rdd => + withParquetRDD((1 to 4).map(i => Tuple1(i.toDouble))) { rdd => checkFilterPushdown(rdd, '_1)('_1 === 1, classOf[Eq[java.lang.Double]])(1) - checkFilterPushdown(rdd, '_1)('_1 !== 1, classOf[Operators.Not]) { + checkFilterPushdown(rdd, '_1)('_1 !== 1, classOf[Operators.NotEq[java.lang.Double]]) { (2 to 4).map(Row.apply(_)) } @@ -196,9 +196,9 @@ class ParquetFilterSuite extends QueryTest with ParquetTest { } test("filter pushdown - string") { - withParquetRDD((1 to 4).map(i => Tuple1.apply(i.toString))) { rdd => + withParquetRDD((1 to 4).map(i => Tuple1(i.toString))) { rdd => checkFilterPushdown(rdd, '_1)('_1 === "1", classOf[Eq[String]])("1") - checkFilterPushdown(rdd, '_1)('_1 !== "1", classOf[Operators.Not]) { + checkFilterPushdown(rdd, '_1)('_1 !== "1", classOf[Operators.NotEq[String]]) { (2 to 4).map(i => Row.apply(i.toString)) } @@ -226,9 +226,9 @@ class ParquetFilterSuite extends QueryTest with ParquetTest { def b: Array[Byte] = int.toString.getBytes("UTF-8") } - withParquetRDD((1 to 4).map(i => Tuple1.apply(i.b))) { rdd => + withParquetRDD((1 to 4).map(i => Tuple1(i.b))) { rdd => checkBinaryFilterPushdown(rdd, '_1)('_1 === 1.b, classOf[Eq[Array[Byte]]])(1.b) - checkBinaryFilterPushdown(rdd, '_1)('_1 !== 1.b, classOf[Operators.Not]) { + checkBinaryFilterPushdown(rdd, '_1)('_1 !== 1.b, classOf[Operators.NotEq[Array[Byte]]]) { (2 to 4).map(i => Row.apply(i.b)).toSeq } From 8d0d2a65eb3a7b1865f7fa7cc18b146fc6474620 Mon Sep 17 00:00:00 2001 From: Cheng Hao Date: Wed, 17 Dec 2014 15:01:59 -0800 Subject: [PATCH 032/320] [SPARK-4856] [SQL] NullType instead of StringType when sampling against empty string or nul... ``` TestSQLContext.sparkContext.parallelize( """{"ip":"27.31.100.29","headers":{"Host":"1.abc.com","Charset":"UTF-8"}}""" :: """{"ip":"27.31.100.29","headers":{}}""" :: """{"ip":"27.31.100.29","headers":""}""" :: Nil) ``` As empty string (the "headers") will be considered as String in the beginning (in line 2 and 3), it ignores the real nested data type (struct type "headers" in line 1), and also take the line 1 (the "headers") as String Type, which is not our expected. Author: Cheng Hao Closes #3708 from chenghao-intel/json and squashes the following commits: e7a72e9 [Cheng Hao] add more concise unit test 853de51 [Cheng Hao] NullType instead of StringType when sampling against empty string or null value --- .../org/apache/spark/sql/json/JsonRDD.scala | 4 +++- .../org/apache/spark/sql/json/JsonSuite.scala | 19 +++++++++++++++++++ .../apache/spark/sql/json/TestJsonData.scala | 7 +++++++ 3 files changed, 29 insertions(+), 1 deletion(-) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala index ffb9548356d1d..00449c200704a 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala @@ -263,6 +263,8 @@ private[sql] object JsonRDD extends Logging { val elementType = typeOfArray(array) buildKeyPathForInnerStructs(array, elementType) :+ (key, elementType) } + // we couldn't tell what the type is if the value is null or empty string + case (key: String, value) if value == "" || value == null => (key, NullType) :: Nil case (key: String, value) => (key, typeOfPrimitiveValue(value)) :: Nil } } @@ -400,13 +402,13 @@ private[sql] object JsonRDD extends Logging { } else { desiredType match { case StringType => toString(value) + case _ if value == null || value == "" => null // guard the non string type case IntegerType => value.asInstanceOf[IntegerType.JvmType] case LongType => toLong(value) case DoubleType => toDouble(value) case DecimalType() => toDecimal(value) case BooleanType => value.asInstanceOf[BooleanType.JvmType] case NullType => null - case ArrayType(elementType, _) => value.asInstanceOf[Seq[Any]].map(enforceCorrectType(_, elementType)) case struct: StructType => asRow(value.asInstanceOf[Map[String, Any]], struct) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala index f088d413257a9..8dce3372a8db3 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala @@ -193,6 +193,25 @@ class JsonSuite extends QueryTest { StringType) } + test("Complex field and type inferring with null in sampling") { + val jsonSchemaRDD = jsonRDD(jsonNullStruct) + val expectedSchema = StructType( + StructField("headers", StructType( + StructField("Charset", StringType, true) :: + StructField("Host", StringType, true) :: Nil) + , true) :: + StructField("ip", StringType, true) :: + StructField("nullstr", StringType, true):: Nil) + + assert(expectedSchema === jsonSchemaRDD.schema) + jsonSchemaRDD.registerTempTable("jsonTable") + + checkAnswer( + sql("select nullstr, headers.Host from jsonTable"), + Seq(Row("", "1.abc.com"), Row("", null), Row("", null), Row(null, null)) + ) + } + test("Primitive field and type inferring") { val jsonSchemaRDD = jsonRDD(primitiveFieldAndType) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/json/TestJsonData.scala b/sql/core/src/test/scala/org/apache/spark/sql/json/TestJsonData.scala index e5773a55875bc..3370b3c98b4be 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/json/TestJsonData.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/json/TestJsonData.scala @@ -43,6 +43,13 @@ object TestJsonData { """{"num_num_1":21474836570, "num_num_2":1.1, "num_num_3": 21474836470, "num_bool":null, "num_str":92233720368547758070, "str_bool":null}""" :: Nil) + val jsonNullStruct = + TestSQLContext.sparkContext.parallelize( + """{"nullstr":"","ip":"27.31.100.29","headers":{"Host":"1.abc.com","Charset":"UTF-8"}}""" :: + """{"nullstr":"","ip":"27.31.100.29","headers":{}}""" :: + """{"nullstr":"","ip":"27.31.100.29","headers":""}""" :: + """{"nullstr":null,"ip":"27.31.100.29","headers":null}""" :: Nil) + val complexFieldValueTypeConflict = TestSQLContext.sparkContext.parallelize( """{"num_struct":11, "str_array":[1, 2, 3], From f33d55046427b8594fd19bda5fd2214eeeab1a95 Mon Sep 17 00:00:00 2001 From: Venkata Ramana Gollamudi Date: Wed, 17 Dec 2014 15:41:35 -0800 Subject: [PATCH 033/320] [SPARK-3891][SQL] Add array support to percentile, percentile_approx and constant inspectors support Supported passing array to percentile and percentile_approx UDAFs To support percentile_approx, constant inspectors are supported for GenericUDAF Constant folding support added to CreateArray expression Avoided constant udf expression re-evaluation Author: Venkata Ramana G Author: Venkata Ramana Gollamudi Closes #2802 from gvramana/percentile_array_support and squashes the following commits: a0182e5 [Venkata Ramana Gollamudi] fixed review comment a18f917 [Venkata Ramana Gollamudi] avoid constant udf expression re-evaluation - fixes failure due to return iterator and value type mismatch c46db0f [Venkata Ramana Gollamudi] Removed TestHive reset 4d39105 [Venkata Ramana Gollamudi] Unified inspector creation, style check fixes f37fd69 [Venkata Ramana Gollamudi] Fixed review comments 47f6365 [Venkata Ramana Gollamudi] fixed test cb7c61e [Venkata Ramana Gollamudi] Supported ConstantInspector for UDAF Fixed HiveUdaf wrap object issue. 7f94aff [Venkata Ramana Gollamudi] Added foldable support to CreateArray --- .../catalyst/expressions/complexTypes.scala | 4 ++- .../org/apache/spark/sql/hive/hiveUdfs.scala | 35 +++++++++++++------ .../sql/hive/execution/HiveUdfSuite.scala | 13 ++++++- 3 files changed, 40 insertions(+), 12 deletions(-) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala index b12821d44b673..9aec601886efc 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala @@ -113,7 +113,9 @@ case class GetField(child: Expression, fieldName: String) extends UnaryExpressio */ case class CreateArray(children: Seq[Expression]) extends Expression { override type EvaluatedType = Any - + + override def foldable = !children.exists(!_.foldable) + lazy val childTypes = children.map(_.dataType).distinct override lazy val resolved = diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala index ed2e96df8ad77..93b6ef9fbc59b 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala @@ -158,6 +158,11 @@ private[hive] case class HiveGenericUdf(funcWrapper: HiveFunctionWrapper, childr override def foldable = isUDFDeterministic && returnInspector.isInstanceOf[ConstantObjectInspector] + @transient + protected def constantReturnValue = unwrap( + returnInspector.asInstanceOf[ConstantObjectInspector].getWritableConstantValue(), + returnInspector) + @transient protected lazy val deferedObjects = argumentInspectors.map(new DeferredObjectAdapter(_)).toArray[DeferredObject] @@ -166,6 +171,8 @@ private[hive] case class HiveGenericUdf(funcWrapper: HiveFunctionWrapper, childr override def eval(input: Row): Any = { returnInspector // Make sure initialized. + if(foldable) return constantReturnValue + var i = 0 while (i < children.length) { val idx = i @@ -193,12 +200,13 @@ private[hive] case class HiveGenericUdaf( @transient protected lazy val objectInspector = { - resolver.getEvaluator(children.map(_.dataType.toTypeInfo).toArray) + val parameterInfo = new SimpleGenericUDAFParameterInfo(inspectors.toArray, false, false) + resolver.getEvaluator(parameterInfo) .init(GenericUDAFEvaluator.Mode.COMPLETE, inspectors.toArray) } @transient - protected lazy val inspectors = children.map(_.dataType).map(toInspector) + protected lazy val inspectors = children.map(toInspector) def dataType: DataType = inspectorToDataType(objectInspector) @@ -223,12 +231,13 @@ private[hive] case class HiveUdaf( @transient protected lazy val objectInspector = { - resolver.getEvaluator(children.map(_.dataType.toTypeInfo).toArray) + val parameterInfo = new SimpleGenericUDAFParameterInfo(inspectors.toArray, false, false) + resolver.getEvaluator(parameterInfo) .init(GenericUDAFEvaluator.Mode.COMPLETE, inspectors.toArray) } @transient - protected lazy val inspectors = children.map(_.dataType).map(toInspector) + protected lazy val inspectors = children.map(toInspector) def dataType: DataType = inspectorToDataType(objectInspector) @@ -261,7 +270,7 @@ private[hive] case class HiveGenericUdtf( protected lazy val function: GenericUDTF = funcWrapper.createFunction() @transient - protected lazy val inputInspectors = children.map(_.dataType).map(toInspector) + protected lazy val inputInspectors = children.map(toInspector) @transient protected lazy val outputInspector = function.initialize(inputInspectors.toArray) @@ -334,10 +343,13 @@ private[hive] case class HiveUdafFunction( } else { funcWrapper.createFunction[AbstractGenericUDAFResolver]() } - - private val inspectors = exprs.map(_.dataType).map(toInspector).toArray - - private val function = resolver.getEvaluator(exprs.map(_.dataType.toTypeInfo).toArray) + + private val inspectors = exprs.map(toInspector).toArray + + private val function = { + val parameterInfo = new SimpleGenericUDAFParameterInfo(inspectors, false, false) + resolver.getEvaluator(parameterInfo) + } private val returnInspector = function.init(GenericUDAFEvaluator.Mode.COMPLETE, inspectors) @@ -350,9 +362,12 @@ private[hive] case class HiveUdafFunction( @transient val inputProjection = new InterpretedProjection(exprs) + @transient + protected lazy val cached = new Array[AnyRef](exprs.length) + def update(input: Row): Unit = { val inputs = inputProjection(input).asInstanceOf[Seq[AnyRef]].toArray - function.iterate(buffer, inputs) + function.iterate(buffer, wrap(inputs, inspectors, cached)) } } diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUdfSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUdfSuite.scala index 5fcaf671a80de..5fc8d8dbe3a9f 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUdfSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUdfSuite.scala @@ -92,10 +92,21 @@ class HiveUdfSuite extends QueryTest { } test("SPARK-2693 udaf aggregates test") { - checkAnswer(sql("SELECT percentile(key,1) FROM src LIMIT 1"), + checkAnswer(sql("SELECT percentile(key, 1) FROM src LIMIT 1"), sql("SELECT max(key) FROM src").collect().toSeq) + + checkAnswer(sql("SELECT percentile(key, array(1, 1)) FROM src LIMIT 1"), + sql("SELECT array(max(key), max(key)) FROM src").collect().toSeq) } + test("Generic UDAF aggregates") { + checkAnswer(sql("SELECT ceiling(percentile_approx(key, 0.99999)) FROM src LIMIT 1"), + sql("SELECT max(key) FROM src LIMIT 1").collect().toSeq) + + checkAnswer(sql("SELECT percentile_approx(100.0, array(0.9, 0.9)) FROM src LIMIT 1"), + sql("SELECT array(100, 100) FROM src LIMIT 1").collect().toSeq) + } + test("UDFIntegerToString") { val testData = TestHive.sparkContext.parallelize( IntegerCaseClass(1) :: IntegerCaseClass(2) :: Nil) From ca1260891adb87f4985d3cfc515b4756644630d0 Mon Sep 17 00:00:00 2001 From: Patrick Wendell Date: Wed, 17 Dec 2014 15:50:10 -0800 Subject: [PATCH 034/320] MAINTENANCE: Automated closing of pull requests. This commit exists to close the following pull requests on Github: Closes #3137 (close requested by 'marmbrus') Closes #3362 (close requested by 'marmbrus') Closes #2979 (close requested by 'JoshRosen') Closes #2223 (close requested by 'JoshRosen') Closes #2998 (close requested by 'marmbrus') Closes #3202 (close requested by 'marmbrus') Closes #3079 (close requested by 'marmbrus') Closes #3210 (close requested by 'marmbrus') Closes #2764 (close requested by 'marmbrus') Closes #3618 (close requested by 'marmbrus') Closes #3501 (close requested by 'marmbrus') Closes #2768 (close requested by 'marmbrus') Closes #3381 (close requested by 'marmbrus') Closes #3510 (close requested by 'marmbrus') Closes #3703 (close requested by 'marmbrus') Closes #2543 (close requested by 'marmbrus') Closes #2876 (close requested by 'marmbrus') Closes #1281 (close requested by 'JoshRosen') From 3cd516191baadf8496ccdae499771020e89acd7e Mon Sep 17 00:00:00 2001 From: lewuathe Date: Wed, 17 Dec 2014 17:31:24 -0800 Subject: [PATCH 035/320] [SPARK-4822] Use sphinx tags for Python doc annotations Modify python annotations for sphinx. There is no change to build process from. https://github.com/apache/spark/blob/master/docs/README.md Author: lewuathe Closes #3685 from Lewuathe/sphinx-tag-for-pydoc and squashes the following commits: 88a0fd9 [lewuathe] [SPARK-4822] Fix DevelopApi and WARN tags 3d7a398 [lewuathe] [SPARK-4822] Use sphinx tags for Python doc annotations --- python/pyspark/context.py | 4 ++-- python/pyspark/mllib/classification.py | 4 ++-- python/pyspark/mllib/feature.py | 12 ++++++------ python/pyspark/mllib/stat.py | 4 ++-- python/pyspark/rdd.py | 8 ++++---- python/pyspark/sql.py | 2 +- 6 files changed, 17 insertions(+), 17 deletions(-) diff --git a/python/pyspark/context.py b/python/pyspark/context.py index ed7351d60cff2..593d74bca5fff 100644 --- a/python/pyspark/context.py +++ b/python/pyspark/context.py @@ -407,7 +407,7 @@ def wholeTextFiles(self, path, minPartitions=None, use_unicode=True): def binaryFiles(self, path, minPartitions=None): """ - :: Experimental :: + .. note:: Experimental Read a directory of binary files from HDFS, a local file system (available on all nodes), or any Hadoop-supported file system URI @@ -424,7 +424,7 @@ def binaryFiles(self, path, minPartitions=None): def binaryRecords(self, path, recordLength): """ - :: Experimental :: + .. note:: Experimental Load data from a flat binary file, assuming each record is a set of numbers with the specified numerical format (see ByteBuffer), and the number of diff --git a/python/pyspark/mllib/classification.py b/python/pyspark/mllib/classification.py index f14d0ed11cbbb..00e2e76711e84 100644 --- a/python/pyspark/mllib/classification.py +++ b/python/pyspark/mllib/classification.py @@ -41,7 +41,7 @@ def __init__(self, weights, intercept): def setThreshold(self, value): """ - :: Experimental :: + .. note:: Experimental Sets the threshold that separates positive predictions from negative predictions. An example with prediction score greater than or equal @@ -51,7 +51,7 @@ def setThreshold(self, value): def clearThreshold(self): """ - :: Experimental :: + .. note:: Experimental Clears the threshold so that `predict` will output raw prediction scores. """ diff --git a/python/pyspark/mllib/feature.py b/python/pyspark/mllib/feature.py index e46af208866a2..10df6288065b8 100644 --- a/python/pyspark/mllib/feature.py +++ b/python/pyspark/mllib/feature.py @@ -36,7 +36,7 @@ class VectorTransformer(object): """ - :: DeveloperApi :: + .. note:: DeveloperApi Base class for transformation of a vector or RDD of vector """ @@ -51,7 +51,7 @@ def transform(self, vector): class Normalizer(VectorTransformer): """ - :: Experimental :: + .. note:: Experimental Normalizes samples individually to unit L\ :sup:`p`\ norm @@ -112,7 +112,7 @@ def transform(self, vector): class StandardScalerModel(JavaVectorTransformer): """ - :: Experimental :: + .. note:: Experimental Represents a StandardScaler model that can transform vectors. """ @@ -129,7 +129,7 @@ def transform(self, vector): class StandardScaler(object): """ - :: Experimental :: + .. note:: Experimental Standardizes features by removing the mean and scaling to unit variance using column summary statistics on the samples in the @@ -172,7 +172,7 @@ def fit(self, dataset): class HashingTF(object): """ - :: Experimental :: + .. note:: Experimental Maps a sequence of terms to their term frequencies using the hashing trick. @@ -232,7 +232,7 @@ def transform(self, x): class IDF(object): """ - :: Experimental :: + .. note:: Experimental Inverse document frequency (IDF). diff --git a/python/pyspark/mllib/stat.py b/python/pyspark/mllib/stat.py index 1980f5b03f430..c8af777a8b00d 100644 --- a/python/pyspark/mllib/stat.py +++ b/python/pyspark/mllib/stat.py @@ -55,7 +55,7 @@ def min(self): class ChiSqTestResult(JavaModelWrapper): """ - :: Experimental :: + .. note:: Experimental Object containing the test results for the chi-squared hypothesis test. """ @@ -200,7 +200,7 @@ def corr(x, y=None, method=None): @staticmethod def chiSqTest(observed, expected=None): """ - :: Experimental :: + .. note:: Experimental If `observed` is Vector, conduct Pearson's chi-squared goodness of fit test of the observed data against the expected distribution, diff --git a/python/pyspark/rdd.py b/python/pyspark/rdd.py index bd2ff00c0f1be..c1120cf781e5e 100644 --- a/python/pyspark/rdd.py +++ b/python/pyspark/rdd.py @@ -1964,7 +1964,7 @@ def _to_java_object_rdd(self): def countApprox(self, timeout, confidence=0.95): """ - :: Experimental :: + .. note:: Experimental Approximate version of count() that returns a potentially incomplete result within a timeout, even if not all tasks have finished. @@ -1977,7 +1977,7 @@ def countApprox(self, timeout, confidence=0.95): def sumApprox(self, timeout, confidence=0.95): """ - :: Experimental :: + .. note:: Experimental Approximate operation to return the sum within a timeout or meet the confidence. @@ -1993,7 +1993,7 @@ def sumApprox(self, timeout, confidence=0.95): def meanApprox(self, timeout, confidence=0.95): """ - :: Experimental :: + .. note:: Experimental Approximate operation to return the mean within a timeout or meet the confidence. @@ -2009,7 +2009,7 @@ def meanApprox(self, timeout, confidence=0.95): def countApproxDistinct(self, relativeSD=0.05): """ - :: Experimental :: + .. note:: Experimental Return approximate number of distinct elements in the RDD. The algorithm used is based on streamlib's implementation of diff --git a/python/pyspark/sql.py b/python/pyspark/sql.py index 1ee0b28a3256d..469f82473af97 100644 --- a/python/pyspark/sql.py +++ b/python/pyspark/sql.py @@ -420,7 +420,7 @@ def fromJson(cls, json): class UserDefinedType(DataType): """ - :: WARN: Spark Internal Use Only :: + .. note:: WARN: Spark Internal Use Only SQL User-Defined Type (UDT). """ From 3b764699ffc9c74b9597c855a0e8c04ac24fa3b7 Mon Sep 17 00:00:00 2001 From: Zhan Zhang Date: Thu, 18 Dec 2014 10:01:46 -0600 Subject: [PATCH 036/320] [SPARK-4461][YARN] pass extra java options to yarn application master Currently, there is no way to pass yarn am specific java options. It cause some potential issues when reading classpath from hadoop configuration file. Hadoop configuration actually replace variables in its property with the system property passed in java options. How to specify the value depends on different hadoop distribution. The new options are SPARK_YARN_JAVA_OPTS or spark.yarn.extraJavaOptions. I make it as spark global level, because typically we don't want user to specify this in their command line each time submitting spark job after it is setup in spark-defaults.conf. In addition, with this new extra options enabled to be passed to AM, it provides more flexibility. For example int the following valid mapred-site.xml file, we have the class path which specify values using system property. Hadoop can correctly handle it because it has java options passed in. This is the example, currently spark will break due to hadoop.version is not passed in. mapreduce.application.classpath /etc/hadoop/${hadoop.version}/mapreduce/* In the meantime, we cannot relies on mapreduce.admin.map.child.java.opts in mapred-site.xml, because it has its own extra java options specified, which does not apply to Spark. Author: Zhan Zhang Closes #3409 from zhzhan/Spark-4461 and squashes the following commits: daec3d0 [Zhan Zhang] solve review comments 08f44a7 [Zhan Zhang] add warning in driver mode if spark.yarn.am.extraJavaOptions is configured 5a505d3 [Zhan Zhang] solve review comments 4ed43ad [Zhan Zhang] solve review comments ad777ed [Zhan Zhang] Merge branch 'master' into Spark-4461 3e9e574 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark e3f9abe [Zhan Zhang] solve review comments 8963552 [Zhan Zhang] rebase f8f6700 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark dea1692 [Zhan Zhang] change the option key name to client mode specific 90d5dff [Zhan Zhang] rebase 8ac9254 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 092a25f [Zhan Zhang] solve review comments bc5a9ae [Zhan Zhang] solve review comments 782b014 [Zhan Zhang] add new configuration to docs/running-on-yarn.md and remove it from spark-defaults.conf.template 6faaa97 [Zhan Zhang] solve review comments 369863f [Zhan Zhang] clean up unnecessary var 733de9c [Zhan Zhang] Merge branch 'master' into Spark-4461 a68e7f0 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 864505a [Zhan Zhang] Add extra java options to be passed to Yarn application master 15830fc [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 685d911 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 03ebad3 [Zhan Zhang] Merge branch 'master' of https://github.com/zhzhan/spark 46d9e3d [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark ebb213a [Zhan Zhang] revert b983ef3 [Zhan Zhang] test c4efb9b [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 779d67b [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 4daae6d [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 12e1be5 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark ce0ca7b [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 93f3081 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 3764505 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark a9d372b [Zhan Zhang] Merge branch 'master' of https://github.com/zhzhan/spark a00f60f [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 497b0f4 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 4a2e36d [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark a72c0d4 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 301eb4a [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark cedcc6f [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark adf4924 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark d10bf00 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 7e0cc36 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 68deb11 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 3ee3b2b [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 2b0d513 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 1ccd7cc [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark af9feb9 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark e4c1982 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 921e914 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 789ea21 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark cb53a2c [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark f6a8a40 [Zhan Zhang] revert ba14f28 [Zhan Zhang] test --- docs/running-on-yarn.md | 8 ++++++++ .../apache/spark/deploy/yarn/ClientBase.scala | 19 +++++++++++++++++++ 2 files changed, 27 insertions(+) diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md index 62b317129b72a..b5fb077441468 100644 --- a/docs/running-on-yarn.md +++ b/docs/running-on-yarn.md @@ -139,6 +139,14 @@ Most of the configs are the same for Spark on YARN as for other deployment modes The maximum number of threads to use in the application master for launching executor containers. + + spark.yarn.am.extraJavaOptions + (none) + + A string of extra JVM options to pass to the Yarn ApplicationMaster in client mode. + In cluster mode, use spark.driver.extraJavaOptions instead. + + # Launching Spark on YARN diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientBase.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientBase.scala index f95d72379171c..5f0c67f05c9dd 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientBase.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientBase.scala @@ -352,12 +352,31 @@ private[spark] trait ClientBase extends Logging { if (isLaunchingDriver) { sparkConf.getOption("spark.driver.extraJavaOptions") .orElse(sys.env.get("SPARK_JAVA_OPTS")) + .map(Utils.splitCommandString).getOrElse(Seq.empty) .foreach(opts => javaOpts += opts) val libraryPaths = Seq(sys.props.get("spark.driver.extraLibraryPath"), sys.props.get("spark.driver.libraryPath")).flatten if (libraryPaths.nonEmpty) { prefixEnv = Some(Utils.libraryPathEnvPrefix(libraryPaths)) } + if (sparkConf.getOption("spark.yarn.am.extraJavaOptions").isDefined) { + logWarning("spark.yarn.am.extraJavaOptions will not take effect in cluster mode") + } + } else { + // Validate and include yarn am specific java options in yarn-client mode. + val amOptsKey = "spark.yarn.am.extraJavaOptions" + val amOpts = sparkConf.getOption(amOptsKey) + amOpts.foreach { opts => + if (opts.contains("-Dspark")) { + val msg = s"$amOptsKey is not allowed to set Spark options (was '$opts'). " + throw new SparkException(msg) + } + if (opts.contains("-Xmx") || opts.contains("-Xms")) { + val msg = s"$amOptsKey is not allowed to alter memory settings (was '$opts')." + throw new SparkException(msg) + } + javaOpts ++= Utils.splitCommandString(opts) + } } // For log4j configuration to reference From 253b72b56fe908bbab5d621eae8a5f359c639dfd Mon Sep 17 00:00:00 2001 From: Sandy Ryza Date: Thu, 18 Dec 2014 12:19:07 -0600 Subject: [PATCH 037/320] SPARK-3779. yarn spark.yarn.applicationMaster.waitTries config should be... ... changed to a time period Author: Sandy Ryza Closes #3471 from sryza/sandy-spark-3779 and squashes the following commits: 20b9887 [Sandy Ryza] Deprecate old property 42b5df7 [Sandy Ryza] Review feedback 9a959a1 [Sandy Ryza] SPARK-3779. yarn spark.yarn.applicationMaster.waitTries config should be changed to a time period --- docs/running-on-yarn.md | 8 ++-- .../spark/deploy/yarn/ApplicationMaster.scala | 48 +++++++++---------- 2 files changed, 29 insertions(+), 27 deletions(-) diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md index b5fb077441468..86276b1aa9cea 100644 --- a/docs/running-on-yarn.md +++ b/docs/running-on-yarn.md @@ -22,10 +22,12 @@ Most of the configs are the same for Spark on YARN as for other deployment modes - - + + diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala index 987b3373fb8ff..dc7a078446324 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala @@ -329,43 +329,43 @@ private[spark] class ApplicationMaster(args: ApplicationMasterArguments, private def waitForSparkContextInitialized(): SparkContext = { logInfo("Waiting for spark context initialization") - try { - sparkContextRef.synchronized { - var count = 0 - val waitTime = 10000L - val numTries = sparkConf.getInt("spark.yarn.applicationMaster.waitTries", 10) - while (sparkContextRef.get() == null && count < numTries && !finished) { - logInfo("Waiting for spark context initialization ... " + count) - count = count + 1 - sparkContextRef.wait(waitTime) - } + sparkContextRef.synchronized { + val waitTries = sparkConf.getOption("spark.yarn.applicationMaster.waitTries") + .map(_.toLong * 10000L) + if (waitTries.isDefined) { + logWarning( + "spark.yarn.applicationMaster.waitTries is deprecated, use spark.yarn.am.waitTime") + } + val totalWaitTime = sparkConf.getLong("spark.yarn.am.waitTime", waitTries.getOrElse(100000L)) + val deadline = System.currentTimeMillis() + totalWaitTime - val sparkContext = sparkContextRef.get() - if (sparkContext == null) { - logError(("SparkContext did not initialize after waiting for %d ms. Please check earlier" - + " log output for errors. Failing the application.").format(numTries * waitTime)) - } - sparkContext + while (sparkContextRef.get() == null && System.currentTimeMillis < deadline && !finished) { + logInfo("Waiting for spark context initialization ... ") + sparkContextRef.wait(10000L) + } + + val sparkContext = sparkContextRef.get() + if (sparkContext == null) { + logError(("SparkContext did not initialize after waiting for %d ms. Please check earlier" + + " log output for errors. Failing the application.").format(totalWaitTime)) } + sparkContext } } private def waitForSparkDriver(): ActorRef = { logInfo("Waiting for Spark driver to be reachable.") var driverUp = false - var count = 0 val hostport = args.userArgs(0) val (driverHost, driverPort) = Utils.parseHostPort(hostport) - // spark driver should already be up since it launched us, but we don't want to + // Spark driver should already be up since it launched us, but we don't want to // wait forever, so wait 100 seconds max to match the cluster mode setting. - // Leave this config unpublished for now. SPARK-3779 to investigating changing - // this config to be time based. - val numTries = sparkConf.getInt("spark.yarn.applicationMaster.waitTries", 1000) + val totalWaitTime = sparkConf.getLong("spark.yarn.am.waitTime", 100000L) + val deadline = System.currentTimeMillis + totalWaitTime - while (!driverUp && !finished && count < numTries) { + while (!driverUp && !finished && System.currentTimeMillis < deadline) { try { - count = count + 1 val socket = new Socket(driverHost, driverPort) socket.close() logInfo("Driver now available: %s:%s".format(driverHost, driverPort)) @@ -374,7 +374,7 @@ private[spark] class ApplicationMaster(args: ApplicationMasterArguments, case e: Exception => logError("Failed to connect to driver at %s:%s, retrying ...". format(driverHost, driverPort)) - Thread.sleep(100) + Thread.sleep(100L) } } From d9956f86ad7a937c5f2cfe39eacdcbdad9356c30 Mon Sep 17 00:00:00 2001 From: Timothy Chen Date: Thu, 18 Dec 2014 12:15:53 -0800 Subject: [PATCH 038/320] Add mesos specific configurations into doc Author: Timothy Chen Closes #3349 from tnachen/mesos_doc and squashes the following commits: 737ef49 [Timothy Chen] Add TOC 5ca546a [Timothy Chen] Update description around cores requested. 26283a5 [Timothy Chen] Add mesos specific configurations into doc --- docs/running-on-mesos.md | 45 ++++++++++++++++++++++++++++++++++++++++ 1 file changed, 45 insertions(+) diff --git a/docs/running-on-mesos.md b/docs/running-on-mesos.md index 1073abb202c56..78358499fd01f 100644 --- a/docs/running-on-mesos.md +++ b/docs/running-on-mesos.md @@ -2,6 +2,8 @@ layout: global title: Running Spark on Mesos --- +* This will become a table of contents (this text will be scraped). +{:toc} Spark can run on hardware clusters managed by [Apache Mesos](http://mesos.apache.org/). @@ -183,6 +185,49 @@ node. Please refer to [Hadoop on Mesos](https://github.com/mesos/hadoop). In either case, HDFS runs separately from Hadoop MapReduce, without being scheduled through Mesos. +# Configuration + +See the [configuration page](configuration.html) for information on Spark configurations. The following configs are specific for Spark on Mesos. + +#### Spark Properties + +
Property NameDefaultMeaning
spark.yarn.applicationMaster.waitTries10spark.yarn.am.waitTime100000 - Set the number of times the ApplicationMaster waits for the the Spark master and then also the number of tries it waits for the SparkContext to be initialized + In yarn-cluster mode, time in milliseconds for the application master to wait for the + SparkContext to be initialized. In yarn-client mode, time for the application master to wait + for the driver to connect to it.
+ + + + + + + + + + + + + + + + + + + + + +
Property NameDefaultMeaning
spark.mesos.coarsefalse + Set the run mode for Spark on Mesos. For more information about the run mode, refer to #Mesos Run Mode section above. +
spark.mesos.extra.cores0 + Set the extra amount of cpus to request per task. This setting is only used for Mesos coarse grain mode. + The total amount of cores requested per task is the number of cores in the offer plus the extra cores configured. + Note that total amount of cores the executor will request in total will not exceed the spark.cores.max setting. +
spark.mesos.executor.homeSPARK_HOME + The location where the mesos executor will look for Spark binaries to execute, and uses the SPARK_HOME setting on default. + This variable is only used when no spark.executor.uri is provided, and assumes Spark is installed on the specified location + on each slave. +
spark.mesos.executor.memoryOverhead384 + The amount of memory that Mesos executor will request for the task to account for the overhead of running the executor itself. + The final total amount of memory allocated is the maximum value between executor memory plus memoryOverhead, and overhead fraction (1.07) plus the executor memory. +
+ # Troubleshooting and Debugging A few places to look during debugging: From 3720057b8e7c15c2c0464b5bb7243bc22323f4e8 Mon Sep 17 00:00:00 2001 From: Ilya Ganelin Date: Thu, 18 Dec 2014 12:53:18 -0800 Subject: [PATCH 039/320] [SPARK-3607] ConnectionManager threads.max configs on the thread pools don't work Hi all - cleaned up the code to get rid of the unused parameter and added some discussion of the ThreadPoolExecutor parameters to explain why we can use a single threadCount instead of providing a min/max. Author: Ilya Ganelin Closes #3664 from ilganeli/SPARK-3607C and squashes the following commits: 3c05690 [Ilya Ganelin] Updated documentation and refactored code to extract shared variables --- .../spark/network/nio/ConnectionManager.scala | 27 ++++++++++++------- 1 file changed, 18 insertions(+), 9 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala b/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala index df4b085d2251e..243b71c980864 100644 --- a/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala +++ b/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala @@ -83,9 +83,21 @@ private[nio] class ConnectionManager( private val ackTimeout = conf.getInt("spark.core.connection.ack.wait.timeout", 60) + // Get the thread counts from the Spark Configuration. + // + // Even though the ThreadPoolExecutor constructor takes both a minimum and maximum value, + // we only query for the minimum value because we are using LinkedBlockingDeque. + // + // The JavaDoc for ThreadPoolExecutor points out that when using a LinkedBlockingDeque (which is + // an unbounded queue) no more than corePoolSize threads will ever be created, so only the "min" + // parameter is necessary. + private val handlerThreadCount = conf.getInt("spark.core.connection.handler.threads.min", 20) + private val ioThreadCount = conf.getInt("spark.core.connection.io.threads.min", 4) + private val connectThreadCount = conf.getInt("spark.core.connection.connect.threads.min", 1) + private val handleMessageExecutor = new ThreadPoolExecutor( - conf.getInt("spark.core.connection.handler.threads.min", 20), - conf.getInt("spark.core.connection.handler.threads.max", 60), + handlerThreadCount, + handlerThreadCount, conf.getInt("spark.core.connection.handler.threads.keepalive", 60), TimeUnit.SECONDS, new LinkedBlockingDeque[Runnable](), Utils.namedThreadFactory("handle-message-executor")) { @@ -96,12 +108,11 @@ private[nio] class ConnectionManager( logError("Error in handleMessageExecutor is not handled properly", t) } } - } private val handleReadWriteExecutor = new ThreadPoolExecutor( - conf.getInt("spark.core.connection.io.threads.min", 4), - conf.getInt("spark.core.connection.io.threads.max", 32), + ioThreadCount, + ioThreadCount, conf.getInt("spark.core.connection.io.threads.keepalive", 60), TimeUnit.SECONDS, new LinkedBlockingDeque[Runnable](), Utils.namedThreadFactory("handle-read-write-executor")) { @@ -112,14 +123,13 @@ private[nio] class ConnectionManager( logError("Error in handleReadWriteExecutor is not handled properly", t) } } - } // Use a different, yet smaller, thread pool - infrequently used with very short lived tasks : // which should be executed asap private val handleConnectExecutor = new ThreadPoolExecutor( - conf.getInt("spark.core.connection.connect.threads.min", 1), - conf.getInt("spark.core.connection.connect.threads.max", 8), + connectThreadCount, + connectThreadCount, conf.getInt("spark.core.connection.connect.threads.keepalive", 60), TimeUnit.SECONDS, new LinkedBlockingDeque[Runnable](), Utils.namedThreadFactory("handle-connect-executor")) { @@ -130,7 +140,6 @@ private[nio] class ConnectionManager( logError("Error in handleConnectExecutor is not handled properly", t) } } - } private val serverChannel = ServerSocketChannel.open() From 59a49db5982ecc487187fcd92399e08b4b4bea64 Mon Sep 17 00:00:00 2001 From: DB Tsai Date: Thu, 18 Dec 2014 13:55:49 -0800 Subject: [PATCH 040/320] [SPARK-4887][MLlib] Fix a bad unittest in LogisticRegressionSuite The original test doesn't make sense since if you step in, the lossSum is already NaN, and the coefficients are diverging. That's because the step size is too large for SGD, so it doesn't work. The correct behavior is that you should get smaller coefficients than the one without regularization. Comparing the values using 20000.0 relative error doesn't make sense as well. Author: DB Tsai Closes #3735 from dbtsai/mlortestfix and squashes the following commits: b1a3c42 [DB Tsai] first commit --- .../mllib/classification/LogisticRegressionSuite.scala | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala index 4e812994405b3..94b0e00f37267 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala @@ -178,15 +178,16 @@ class LogisticRegressionSuite extends FunSuite with MLlibTestSparkContext with M // Use half as many iterations as the previous test. val lr = new LogisticRegressionWithSGD().setIntercept(true) lr.optimizer. - setStepSize(10.0). + setStepSize(1.0). setNumIterations(10). setRegParam(1.0) val model = lr.run(testRDD, initialWeights) // Test the weights - assert(model.weights(0) ~== -430000.0 relTol 20000.0) - assert(model.intercept ~== 370000.0 relTol 20000.0) + // With regularization, the resulting weights will be smaller. + assert(model.weights(0) ~== -0.14 relTol 0.02) + assert(model.intercept ~== 0.25 relTol 0.02) val validationData = LogisticRegressionSuite.generateLogisticInput(A, B, nPoints, 17) val validationRDD = sc.parallelize(validationData, 2) From a7ed6f3cc537f57de87d28e8466ca88fbfff53b5 Mon Sep 17 00:00:00 2001 From: Ernest Date: Thu, 18 Dec 2014 15:42:26 -0800 Subject: [PATCH 041/320] [SPARK-4880] remove spark.locality.wait in Analytics spark.locality.wait set to 100000 in examples/graphx/Analytics.scala. Should be left to the user. Author: Ernest Closes #3730 from Earne/SPARK-4880 and squashes the following commits: d79ed04 [Ernest] remove spark.locality.wait in Analytics --- .../main/scala/org/apache/spark/examples/graphx/Analytics.scala | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala b/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala index 828cffb01ca1e..9cc47327f9a48 100644 --- a/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala +++ b/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala @@ -46,7 +46,7 @@ object Analytics extends Logging { } val options = mutable.Map(optionsList: _*) - val conf = new SparkConf().set("spark.locality.wait", "100000") + val conf = new SparkConf() GraphXUtils.registerKryoClasses(conf) val numEPart = options.remove("numEPart").map(_.toInt).getOrElse { From d5a596d4188bfa85ff49ee85039f54255c19a4de Mon Sep 17 00:00:00 2001 From: Madhu Siddalingaiah Date: Thu, 18 Dec 2014 16:00:53 -0800 Subject: [PATCH 042/320] [SPARK-4884]: Improve Partition docs Rewording was based on this discussion: http://apache-spark-developers-list.1001551.n3.nabble.com/RDD-data-flow-td9804.html This is the associated JIRA ticket: https://issues.apache.org/jira/browse/SPARK-4884 Author: Madhu Siddalingaiah Closes #3722 from msiddalingaiah/master and squashes the following commits: 79e679f [Madhu Siddalingaiah] [DOC]: improve documentation 51d14b9 [Madhu Siddalingaiah] Merge remote-tracking branch 'upstream/master' 38faca4 [Madhu Siddalingaiah] Merge remote-tracking branch 'upstream/master' cbccbfe [Madhu Siddalingaiah] Documentation: replace with (again) 332f7a2 [Madhu Siddalingaiah] Documentation: replace with cd2b05a [Madhu Siddalingaiah] Merge remote-tracking branch 'upstream/master' 0fc12d7 [Madhu Siddalingaiah] Documentation: add description for repartitionAndSortWithinPartitions --- core/src/main/scala/org/apache/spark/Partition.scala | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/Partition.scala b/core/src/main/scala/org/apache/spark/Partition.scala index 27892dbd2a0bc..dd3f28e4197e3 100644 --- a/core/src/main/scala/org/apache/spark/Partition.scala +++ b/core/src/main/scala/org/apache/spark/Partition.scala @@ -18,11 +18,11 @@ package org.apache.spark /** - * A partition of an RDD. + * An identifier for a partition in an RDD. */ trait Partition extends Serializable { /** - * Get the split's index within its parent RDD + * Get the partition's index within its parent RDD */ def index: Int From f9f58b9a01c4c7eaf0ce5055d6870e69a22297e3 Mon Sep 17 00:00:00 2001 From: Ivan Vergiliev Date: Thu, 18 Dec 2014 16:29:36 -0800 Subject: [PATCH 043/320] SPARK-4743 - Use SparkEnv.serializer instead of closureSerializer in aggregateByKey and foldByKey Author: Ivan Vergiliev Closes #3605 from IvanVergiliev/change-serializer and squashes the following commits: a49b7cf [Ivan Vergiliev] Use serializer instead of closureSerializer in aggregate/foldByKey. --- .../scala/org/apache/spark/rdd/PairRDDFunctions.scala | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala b/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala index b0434c9a3b6b3..fe3129b62f71e 100644 --- a/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala +++ b/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala @@ -123,11 +123,11 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)]) def aggregateByKey[U: ClassTag](zeroValue: U, partitioner: Partitioner)(seqOp: (U, V) => U, combOp: (U, U) => U): RDD[(K, U)] = { // Serialize the zero value to a byte array so that we can get a new clone of it on each key - val zeroBuffer = SparkEnv.get.closureSerializer.newInstance().serialize(zeroValue) + val zeroBuffer = SparkEnv.get.serializer.newInstance().serialize(zeroValue) val zeroArray = new Array[Byte](zeroBuffer.limit) zeroBuffer.get(zeroArray) - lazy val cachedSerializer = SparkEnv.get.closureSerializer.newInstance() + lazy val cachedSerializer = SparkEnv.get.serializer.newInstance() val createZero = () => cachedSerializer.deserialize[U](ByteBuffer.wrap(zeroArray)) combineByKey[U]((v: V) => seqOp(createZero(), v), seqOp, combOp, partitioner) @@ -168,12 +168,12 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)]) */ def foldByKey(zeroValue: V, partitioner: Partitioner)(func: (V, V) => V): RDD[(K, V)] = { // Serialize the zero value to a byte array so that we can get a new clone of it on each key - val zeroBuffer = SparkEnv.get.closureSerializer.newInstance().serialize(zeroValue) + val zeroBuffer = SparkEnv.get.serializer.newInstance().serialize(zeroValue) val zeroArray = new Array[Byte](zeroBuffer.limit) zeroBuffer.get(zeroArray) // When deserializing, use a lazy val to create just one instance of the serializer per task - lazy val cachedSerializer = SparkEnv.get.closureSerializer.newInstance() + lazy val cachedSerializer = SparkEnv.get.serializer.newInstance() val createZero = () => cachedSerializer.deserialize[V](ByteBuffer.wrap(zeroArray)) combineByKey[V]((v: V) => func(createZero(), v), func, func, partitioner) From 105293a7d06b26e7b179a0447eb802074ee9c218 Mon Sep 17 00:00:00 2001 From: Aaron Davidson Date: Thu, 18 Dec 2014 16:43:16 -0800 Subject: [PATCH 044/320] [SPARK-4837] NettyBlockTransferService should use spark.blockManager.port config This is used in NioBlockTransferService here: https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/network/nio/NioBlockTransferService.scala#L66 Author: Aaron Davidson Closes #3688 from aarondav/SPARK-4837 and squashes the following commits: ebd2007 [Aaron Davidson] [SPARK-4837] NettyBlockTransferService should use spark.blockManager.port config --- .../apache/spark/network/netty/NettyBlockTransferService.scala | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/core/src/main/scala/org/apache/spark/network/netty/NettyBlockTransferService.scala b/core/src/main/scala/org/apache/spark/network/netty/NettyBlockTransferService.scala index 0027cbb0ff1fb..3f0950dae1f24 100644 --- a/core/src/main/scala/org/apache/spark/network/netty/NettyBlockTransferService.scala +++ b/core/src/main/scala/org/apache/spark/network/netty/NettyBlockTransferService.scala @@ -60,7 +60,7 @@ class NettyBlockTransferService(conf: SparkConf, securityManager: SecurityManage } transportContext = new TransportContext(transportConf, rpcHandler) clientFactory = transportContext.createClientFactory(bootstrap.toList) - server = transportContext.createServer() + server = transportContext.createServer(conf.getInt("spark.blockManager.port", 0)) appId = conf.getAppId logInfo("Server created on " + server.getPort) } From 9804a759b68f56eceb8a2f4ea90f76a92b5f9f67 Mon Sep 17 00:00:00 2001 From: Andrew Or Date: Thu, 18 Dec 2014 17:37:42 -0800 Subject: [PATCH 045/320] [SPARK-4754] Refactor SparkContext into ExecutorAllocationClient This is such that the `ExecutorAllocationManager` does not take in the `SparkContext` with all of its dependencies as an argument. This prevents future developers of this class to tie down this class further with the `SparkContext`, which has really become quite a monstrous object. cc'ing pwendell who originally suggested this, and JoshRosen who may have thoughts about the trait mix-in style of `SparkContext`. Author: Andrew Or Closes #3614 from andrewor14/dynamic-allocation-sc and squashes the following commits: 187070d [Andrew Or] Merge branch 'master' of github.com:apache/spark into dynamic-allocation-sc 59baf6c [Andrew Or] Merge branch 'master' of github.com:apache/spark into dynamic-allocation-sc 347a348 [Andrew Or] Refactor SparkContext into ExecutorAllocationClient --- .../spark/ExecutorAllocationClient.scala | 42 +++++++++++++++++++ .../spark/ExecutorAllocationManager.scala | 14 ++++--- .../scala/org/apache/spark/SparkContext.scala | 10 ++--- .../CoarseGrainedSchedulerBackend.scala | 8 ++-- 4 files changed, 59 insertions(+), 15 deletions(-) create mode 100644 core/src/main/scala/org/apache/spark/ExecutorAllocationClient.scala diff --git a/core/src/main/scala/org/apache/spark/ExecutorAllocationClient.scala b/core/src/main/scala/org/apache/spark/ExecutorAllocationClient.scala new file mode 100644 index 0000000000000..a46a81eabd965 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/ExecutorAllocationClient.scala @@ -0,0 +1,42 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +/** + * A client that communicates with the cluster manager to request or kill executors. + */ +private[spark] trait ExecutorAllocationClient { + + /** + * Request an additional number of executors from the cluster manager. + * Return whether the request is acknowledged by the cluster manager. + */ + def requestExecutors(numAdditionalExecutors: Int): Boolean + + /** + * Request that the cluster manager kill the specified executors. + * Return whether the request is acknowledged by the cluster manager. + */ + def killExecutors(executorIds: Seq[String]): Boolean + + /** + * Request that the cluster manager kill the specified executor. + * Return whether the request is acknowledged by the cluster manager. + */ + def killExecutor(executorId: String): Boolean = killExecutors(Seq(executorId)) +} diff --git a/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala b/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala index 88adb892998af..e9e90e3f2f65a 100644 --- a/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala +++ b/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala @@ -60,11 +60,13 @@ import org.apache.spark.scheduler._ * spark.dynamicAllocation.executorIdleTimeout (K) - * If an executor has been idle for this duration, remove it */ -private[spark] class ExecutorAllocationManager(sc: SparkContext) extends Logging { +private[spark] class ExecutorAllocationManager( + client: ExecutorAllocationClient, + listenerBus: LiveListenerBus, + conf: SparkConf) + extends Logging { import ExecutorAllocationManager._ - private val conf = sc.conf - // Lower and upper bounds on the number of executors. These are required. private val minNumExecutors = conf.getInt("spark.dynamicAllocation.minExecutors", -1) private val maxNumExecutors = conf.getInt("spark.dynamicAllocation.maxExecutors", -1) @@ -168,7 +170,7 @@ private[spark] class ExecutorAllocationManager(sc: SparkContext) extends Logging * Register for scheduler callbacks to decide when to add and remove executors. */ def start(): Unit = { - sc.addSparkListener(listener) + listenerBus.addListener(listener) startPolling() } @@ -253,7 +255,7 @@ private[spark] class ExecutorAllocationManager(sc: SparkContext) extends Logging val actualNumExecutorsToAdd = math.min(numExecutorsToAdd, maxNumExecutorsToAdd) val newTotalExecutors = numExistingExecutors + actualNumExecutorsToAdd - val addRequestAcknowledged = testing || sc.requestExecutors(actualNumExecutorsToAdd) + val addRequestAcknowledged = testing || client.requestExecutors(actualNumExecutorsToAdd) if (addRequestAcknowledged) { logInfo(s"Requesting $actualNumExecutorsToAdd new executor(s) because " + s"tasks are backlogged (new desired total will be $newTotalExecutors)") @@ -295,7 +297,7 @@ private[spark] class ExecutorAllocationManager(sc: SparkContext) extends Logging } // Send a request to the backend to kill this executor - val removeRequestAcknowledged = testing || sc.killExecutor(executorId) + val removeRequestAcknowledged = testing || client.killExecutor(executorId) if (removeRequestAcknowledged) { logInfo(s"Removing executor $executorId because it has been idle for " + s"$executorIdleTimeout seconds (new desired total will be ${numExistingExecutors - 1})") diff --git a/core/src/main/scala/org/apache/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala index 66e07d10132b8..b1c6a90d182f6 100644 --- a/core/src/main/scala/org/apache/spark/SparkContext.scala +++ b/core/src/main/scala/org/apache/spark/SparkContext.scala @@ -64,7 +64,7 @@ import org.apache.spark.util._ * @param config a Spark Config object describing the application configuration. Any settings in * this config overrides the default configs as well as system properties. */ -class SparkContext(config: SparkConf) extends Logging { +class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationClient { // The call site where this SparkContext was constructed. private val creationSite: CallSite = Utils.getCallSite() @@ -365,7 +365,7 @@ class SparkContext(config: SparkConf) extends Logging { if (dynamicAllocationEnabled) { assert(master.contains("yarn") || dynamicAllocationTesting, "Dynamic allocation of executors is currently only supported in YARN mode") - Some(new ExecutorAllocationManager(this)) + Some(new ExecutorAllocationManager(this, listenerBus, conf)) } else { None } @@ -994,7 +994,7 @@ class SparkContext(config: SparkConf) extends Logging { * This is currently only supported in Yarn mode. Return whether the request is received. */ @DeveloperApi - def requestExecutors(numAdditionalExecutors: Int): Boolean = { + override def requestExecutors(numAdditionalExecutors: Int): Boolean = { assert(master.contains("yarn") || dynamicAllocationTesting, "Requesting executors is currently only supported in YARN mode") schedulerBackend match { @@ -1012,7 +1012,7 @@ class SparkContext(config: SparkConf) extends Logging { * This is currently only supported in Yarn mode. Return whether the request is received. */ @DeveloperApi - def killExecutors(executorIds: Seq[String]): Boolean = { + override def killExecutors(executorIds: Seq[String]): Boolean = { assert(master.contains("yarn") || dynamicAllocationTesting, "Killing executors is currently only supported in YARN mode") schedulerBackend match { @@ -1030,7 +1030,7 @@ class SparkContext(config: SparkConf) extends Logging { * This is currently only supported in Yarn mode. Return whether the request is received. */ @DeveloperApi - def killExecutor(executorId: String): Boolean = killExecutors(Seq(executorId)) + override def killExecutor(executorId: String): Boolean = super.killExecutor(executorId) /** The version of Spark on which this application is running. */ def version = SPARK_VERSION diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala index 29cd34429b881..fe9914b50bc54 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala @@ -27,7 +27,7 @@ import akka.actor._ import akka.pattern.ask import akka.remote.{DisassociatedEvent, RemotingLifecycleEvent} -import org.apache.spark.{SparkEnv, Logging, SparkException, TaskState} +import org.apache.spark.{ExecutorAllocationClient, Logging, SparkEnv, SparkException, TaskState} import org.apache.spark.scheduler.{SchedulerBackend, SlaveLost, TaskDescription, TaskSchedulerImpl, WorkerOffer} import org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages._ import org.apache.spark.util.{ActorLogReceive, SerializableBuffer, AkkaUtils, Utils} @@ -42,7 +42,7 @@ import org.apache.spark.util.{ActorLogReceive, SerializableBuffer, AkkaUtils, Ut */ private[spark] class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val actorSystem: ActorSystem) - extends SchedulerBackend with Logging + extends ExecutorAllocationClient with SchedulerBackend with Logging { // Use an atomic variable to track total number of cores in the cluster for simplicity and speed var totalCoreCount = new AtomicInteger(0) @@ -307,7 +307,7 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val actorSyste * Request an additional number of executors from the cluster manager. * Return whether the request is acknowledged. */ - final def requestExecutors(numAdditionalExecutors: Int): Boolean = synchronized { + final override def requestExecutors(numAdditionalExecutors: Int): Boolean = synchronized { logInfo(s"Requesting $numAdditionalExecutors additional executor(s) from the cluster manager") logDebug(s"Number of pending executors is now $numPendingExecutors") numPendingExecutors += numAdditionalExecutors @@ -334,7 +334,7 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val actorSyste * Request that the cluster manager kill the specified executors. * Return whether the kill request is acknowledged. */ - final def killExecutors(executorIds: Seq[String]): Boolean = synchronized { + final override def killExecutors(executorIds: Seq[String]): Boolean = synchronized { logInfo(s"Requesting to kill executor(s) ${executorIds.mkString(", ")}") val filteredExecutorIds = new ArrayBuffer[String] executorIds.foreach { id => From f728e0fe7e860fe6dd3437e248472a67a2d435f8 Mon Sep 17 00:00:00 2001 From: Cheng Hao Date: Thu, 18 Dec 2014 18:58:29 -0800 Subject: [PATCH 046/320] [SPARK-2663] [SQL] Support the Grouping Set Add support for `GROUPING SETS`, `ROLLUP`, `CUBE` and the the virtual column `GROUPING__ID`. More details on how to use the `GROUPING SETS" can be found at: https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation,+Cube,+Grouping+and+Rollup https://issues.apache.org/jira/secure/attachment/12676811/grouping_set.pdf The generic idea of the implementations are : 1 Replace the `ROLLUP`, `CUBE` with `GROUPING SETS` 2 Explode each of the input row, and then feed them to `Aggregate` * Each grouping set are represented as the bit mask for the `GroupBy Expression List`, for each bit, `1` means the expression is selected, otherwise `0` (left is the lower bit, and right is the higher bit in the `GroupBy Expression List`) * Several of projections are constructed according to the grouping sets, and within each projection(Seq[Expression), we replace those expressions with `Literal(null)` if it's not selected in the grouping set (based on the bit mask) * Output Schema of `Explode` is `child.output :+ grouping__id` * GroupBy Expressions of `Aggregate` is `GroupBy Expression List :+ grouping__id` * Keep the `Aggregation expressions` the same for the `Aggregate` The expressions substitutions happen in Logic Plan analyzing, so we will benefit from the Logical Plan optimization (e.g. expression constant folding, and map side aggregation etc.), Only an `Explosive` operator added for Physical Plan, which will explode the rows according the pre-set projections. A known issue will be done in the follow up PR: * Optimization `ColumnPruning` is not supported yet for `Explosive` node. Author: Cheng Hao Closes #1567 from chenghao-intel/grouping_sets and squashes the following commits: fe65fcc [Cheng Hao] Remove the extra space 3547056 [Cheng Hao] Add more doc and Simplify the Expand a7c869d [Cheng Hao] update code as feedbacks d23c672 [Cheng Hao] Add GroupingExpression to replace the Seq[Expression] 414b165 [Cheng Hao] revert the unnecessary changes ec276c6 [Cheng Hao] Support Rollup/Cube/GroupingSets --- .../sql/catalyst/analysis/Analyzer.scala | 95 +++++++++++++++++++ .../sql/catalyst/expressions/Expression.scala | 13 ++- .../expressions/namedExpressions.scala | 5 + .../plans/logical/basicOperators.scala | 83 ++++++++++++++++ .../apache/spark/sql/execution/Expand.scala | 79 +++++++++++++++ .../spark/sql/execution/SparkStrategies.scala | 2 + .../execution/HiveCompatibilitySuite.scala | 7 ++ .../org/apache/spark/sql/hive/HiveQl.scala | 79 +++++++++++++-- ...ing_id1-0-caf1c5fd299fdbdb655234d01d44caf2 | 0 ...ing_id1-1-b76bf9f6c92f83c9a5f351f8460d1e3b | 0 ...ing_id1-1-c0f14def6a135cc50cba364e810ce28e | 0 ...ing_id1-2-3dfbff77a9b56d44312814d3fb0d07fa | 18 ++++ ...ing_id1-3-d113d984a30ad7b98c50a46158605a51 | 12 +++ ...ing_id1-4-903a499840102e2cb722dd8b83820391 | 18 ++++ ...ing_id2-0-20539c642c514a590caca2f11395007e | 0 ...ing_id2-1-d1f3215e349f056c8de60b87a6a9855e | 0 ...ing_id2-1-d6fb6c164cda6a13a71290dbf95fcc6e | 0 ...ing_id2-2-a00d1791b7fa7ac5a0505d95c3d12257 | 1 + ...ing_id2-3-b3cb95405b1200603f40aaab24be7586 | 11 +++ ...ing_id2-4-9bdcf67baa5d7cf70cd2eb1a3ec6de74 | 3 + ...ing_id2-5-7dd97bda7e2a900dfc509a6133620b82 | 53 +++++++++++ ...ing_id2-6-a7dc16cb82c595b18d4258a38a304b1e | 1 + ...ing_id2-7-b3cb95405b1200603f40aaab24be7586 | 11 +++ ...ing_id2-8-9bdcf67baa5d7cf70cd2eb1a3ec6de74 | 3 + ...ing_id2-9-7dd97bda7e2a900dfc509a6133620b82 | 53 +++++++++++ ...g_sets1-0-91128722f50ec00b51e0bf6fe5695cd1 | 0 ...g_sets1-1-3673d61d0944adeba77438d882839de4 | 0 ...g_sets1-1-d1c300ea08361fb8237689c6cf8cc1b5 | 0 ...g_sets1-2-5c14fabebc5b4c526c459a6e867ec61a | 6 ++ ...g_sets1-3-9f501f293fe180bf6322e93d8dea025a | 15 +++ ...g_sets1-4-505ac6611b332d6cf4a364739075d49c | 15 +++ ...g_sets1-5-a33cc72bf5adee428eea079847034b62 | 11 +++ ...g_sets1-6-5f0c2e1d5489c867261e575625349542 | 14 +++ ...g_sets1-7-9b3bda02733476012e2cda434d936423 | 5 + ...g_sets1-8-1273ad6760f8c3ddad07819362dcc324 | 5 + ...g_sets2-0-bb96e87a0d6b0d1a6167e424b086acf6 | 1 + ...g_sets2-1-91128722f50ec00b51e0bf6fe5695cd1 | 0 ..._sets2-10-f39e49610430c91e5af3876d15fbdfe3 | 15 +++ ...g_sets2-2-3673d61d0944adeba77438d882839de4 | 0 ...g_sets2-2-d1c300ea08361fb8237689c6cf8cc1b5 | 0 ...g_sets2-3-59adefab34d80e8e185b2ad03877d381 | 0 ...g_sets2-4-9f501f293fe180bf6322e93d8dea025a | 15 +++ ...g_sets2-5-1163c486fd7e2c4346805fb035e2f268 | 0 ...g_sets2-6-9459dc3e8ab1f09d6d912b686e7f37fc | 15 +++ ...g_sets2-7-39db88427f92cb770b6daa38610c04e7 | 0 ...g_sets2-8-e464ec3d5461bda47eac3d1ef8617786 | 0 ...g_sets2-9-74126b100714164d13cbb3bff436c2ff | 0 ...g_sets3-0-4fe85ca1e68a895ef403afdcfbbf61bc | 0 ...g_sets3-1-38373b67d392924967a4695689d2164e | 0 ...g_sets3-1-e8964b2aaeb388064c9fdac5ec687824 | 0 ...ng_sets3-2-c1942a377b1a440d4ed3dd05fed445d | 0 ...g_sets3-2-d95cf9dfae402d369f338b8516845e02 | 0 ...g_sets3-3-b89ea2173180c8ae423d856f943e061f | 1 + ...g_sets3-4-77c57e1b4ca37c2dc715b65668cd0c59 | 1 + ...g_sets3-5-6623f95d90d929a6d2c8171a0698d4fd | 0 ...g_sets3-6-aec59088408cc57248851d3ce04e2eef | 16 ++++ ...g_sets3-7-bb96e87a0d6b0d1a6167e424b086acf6 | 1 + ...g_sets3-8-f32c4a191759237733a10cd721b49966 | 0 ...g_sets3-9-aec59088408cc57248851d3ce04e2eef | 16 ++++ ...g_sets4-0-d8ae5a3e613dd2dda392995b90d47565 | 1 + ...g_sets4-1-6ad4e855adb49babfa3ae6abac190be3 | 1 + ...g_sets4-2-1789808269c8bd0f6259227f07da1a6a | 0 ...g_sets4-3-3673d61d0944adeba77438d882839de4 | 0 ...g_sets4-3-d1c300ea08361fb8237689c6cf8cc1b5 | 0 ...g_sets4-4-b51d813d0c5a410d8cf9765d85005a01 | 0 ...g_sets4-5-9be98faf8588a3c8e7436f14c638e438 | 13 +++ ...g_sets4-6-bb96e87a0d6b0d1a6167e424b086acf6 | 1 + ...g_sets4-7-98f7522ce136cdffb0c14163e613c250 | 0 ...g_sets4-8-9be98faf8588a3c8e7436f14c638e438 | 13 +++ ...g_sets5-0-d8ae5a3e613dd2dda392995b90d47565 | 1 + ...g_sets5-1-6ad4e855adb49babfa3ae6abac190be3 | 1 + ...g_sets5-2-1789808269c8bd0f6259227f07da1a6a | 0 ...g_sets5-3-3673d61d0944adeba77438d882839de4 | 0 ...g_sets5-3-d1c300ea08361fb8237689c6cf8cc1b5 | 0 ...g_sets5-4-6a89a34347f1c0eb9e0763ecedddb6f9 | 0 ...g_sets5-5-af3569757b9f52fb9b1ead33130e1b4f | 15 +++ ...g_sets5-6-bb96e87a0d6b0d1a6167e424b086acf6 | 1 + ...g_sets5-7-6544a382d851f916616c4386fdcf0ed8 | 0 ...g_sets5-8-af3569757b9f52fb9b1ead33130e1b4f | 15 +++ 79 files changed, 750 insertions(+), 11 deletions(-) create mode 100644 sql/core/src/main/scala/org/apache/spark/sql/execution/Expand.scala create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_id1-0-caf1c5fd299fdbdb655234d01d44caf2 create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_id1-1-b76bf9f6c92f83c9a5f351f8460d1e3b create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_id1-1-c0f14def6a135cc50cba364e810ce28e create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_id1-2-3dfbff77a9b56d44312814d3fb0d07fa create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_id1-3-d113d984a30ad7b98c50a46158605a51 create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_id1-4-903a499840102e2cb722dd8b83820391 create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_id2-0-20539c642c514a590caca2f11395007e create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_id2-1-d1f3215e349f056c8de60b87a6a9855e create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_id2-1-d6fb6c164cda6a13a71290dbf95fcc6e create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_id2-2-a00d1791b7fa7ac5a0505d95c3d12257 create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_id2-3-b3cb95405b1200603f40aaab24be7586 create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_id2-4-9bdcf67baa5d7cf70cd2eb1a3ec6de74 create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_id2-5-7dd97bda7e2a900dfc509a6133620b82 create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_id2-6-a7dc16cb82c595b18d4258a38a304b1e create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_id2-7-b3cb95405b1200603f40aaab24be7586 create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_id2-8-9bdcf67baa5d7cf70cd2eb1a3ec6de74 create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_id2-9-7dd97bda7e2a900dfc509a6133620b82 create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_sets1-0-91128722f50ec00b51e0bf6fe5695cd1 create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_sets1-1-3673d61d0944adeba77438d882839de4 create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_sets1-1-d1c300ea08361fb8237689c6cf8cc1b5 create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_sets1-2-5c14fabebc5b4c526c459a6e867ec61a create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_sets1-3-9f501f293fe180bf6322e93d8dea025a create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_sets1-4-505ac6611b332d6cf4a364739075d49c create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_sets1-5-a33cc72bf5adee428eea079847034b62 create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_sets1-6-5f0c2e1d5489c867261e575625349542 create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_sets1-7-9b3bda02733476012e2cda434d936423 create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_sets1-8-1273ad6760f8c3ddad07819362dcc324 create mode 100644 sql/hive/src/test/resources/golden/groupby_grouping_sets2-0-bb96e87a0d6b0d1a6167e424b086acf6 create mode 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b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala index 3705fcc1f13f3..1c4088b8438e1 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala @@ -17,11 +17,13 @@ package org.apache.spark.sql.catalyst.analysis +import org.apache.spark.util.collection.OpenHashSet import org.apache.spark.sql.catalyst.errors.TreeNodeException import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.rules._ import org.apache.spark.sql.catalyst.types.StructType +import org.apache.spark.sql.catalyst.types.IntegerType /** * A trivial [[Analyzer]] with an [[EmptyCatalog]] and [[EmptyFunctionRegistry]]. Used for testing @@ -56,6 +58,7 @@ class Analyzer(catalog: Catalog, Batch("Resolution", fixedPoint, ResolveReferences :: ResolveRelations :: + ResolveGroupingAnalytics :: ResolveSortReferences :: NewRelationInstances :: ImplicitGenerate :: @@ -102,6 +105,93 @@ class Analyzer(catalog: Catalog, } } + object ResolveGroupingAnalytics extends Rule[LogicalPlan] { + /** + * Extract attribute set according to the grouping id + * @param bitmask bitmask to represent the selected of the attribute sequence + * @param exprs the attributes in sequence + * @return the attributes of non selected specified via bitmask (with the bit set to 1) + */ + private def buildNonSelectExprSet(bitmask: Int, exprs: Seq[Expression]) + : OpenHashSet[Expression] = { + val set = new OpenHashSet[Expression](2) + + var bit = exprs.length - 1 + while (bit >= 0) { + if (((bitmask >> bit) & 1) == 0) set.add(exprs(bit)) + bit -= 1 + } + + set + } + + /* + * GROUP BY a, b, c, WITH ROLLUP + * is equivalent to + * GROUP BY a, b, c GROUPING SETS ( (a, b, c), (a, b), (a), ( )). + * Group Count: N + 1 (N is the number of group expression) + * + * We need to get all of its subsets for the rule described above, the subset is + * represented as the bit masks. + */ + def bitmasks(r: Rollup): Seq[Int] = { + Seq.tabulate(r.groupByExprs.length + 1)(idx => {(1 << idx) - 1}) + } + + /* + * GROUP BY a, b, c, WITH CUBE + * is equivalent to + * GROUP BY a, b, c GROUPING SETS ( (a, b, c), (a, b), (b, c), (a, c), (a), (b), (c), ( ) ). + * Group Count: 2^N (N is the number of group expression) + * + * We need to get all of its sub sets for a given GROUPBY expressions, the subset is + * represented as the bit masks. + */ + def bitmasks(c: Cube): Seq[Int] = { + Seq.tabulate(1 << c.groupByExprs.length)(i => i) + } + + /** + * Create an array of Projections for the child projection, and replace the projections' + * expressions which equal GroupBy expressions with Literal(null), if those expressions + * are not set for this grouping set (according to the bit mask). + */ + private[this] def expand(g: GroupingSets): Seq[GroupExpression] = { + val result = new scala.collection.mutable.ArrayBuffer[GroupExpression] + + g.bitmasks.foreach { bitmask => + // get the non selected grouping attributes according to the bit mask + val nonSelectedGroupExprSet = buildNonSelectExprSet(bitmask, g.groupByExprs) + + val substitution = (g.child.output :+ g.gid).map(expr => expr transformDown { + case x: Expression if nonSelectedGroupExprSet.contains(x) => + // if the input attribute in the Invalid Grouping Expression set of for this group + // replace it with constant null + Literal(null, expr.dataType) + case x if x == g.gid => + // replace the groupingId with concrete value (the bit mask) + Literal(bitmask, IntegerType) + }) + + result += GroupExpression(substitution) + } + + result.toSeq + } + + def apply(plan: LogicalPlan): LogicalPlan = plan transform { + case a: Cube if a.resolved => + GroupingSets(bitmasks(a), a.groupByExprs, a.child, a.aggregations, a.gid) + case a: Rollup if a.resolved => + GroupingSets(bitmasks(a), a.groupByExprs, a.child, a.aggregations, a.gid) + case x: GroupingSets if x.resolved => + Aggregate( + x.groupByExprs :+ x.gid, + x.aggregations, + Expand(expand(x), x.child.output :+ x.gid, x.child)) + } + } + /** * Checks for non-aggregated attributes with aggregation */ @@ -183,6 +273,11 @@ class Analyzer(catalog: Catalog, case q: LogicalPlan => logTrace(s"Attempting to resolve ${q.simpleString}") q transformExpressions { + case u @ UnresolvedAttribute(name) + if resolver(name, VirtualColumn.groupingIdName) && + q.isInstanceOf[GroupingAnalytics] => + // Resolve the virtual column GROUPING__ID for the operator GroupingAnalytics + q.asInstanceOf[GroupingAnalytics].gid case u @ UnresolvedAttribute(name) => // Leave unchanged if resolution fails. Hopefully will be resolved next round. val result = q.resolveChildren(name, resolver).getOrElse(u) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Expression.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Expression.scala index bc45881e42748..ac5b02c2e6aed 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Expression.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Expression.scala @@ -284,6 +284,17 @@ abstract class LeafExpression extends Expression with trees.LeafNode[Expression] abstract class UnaryExpression extends Expression with trees.UnaryNode[Expression] { self: Product => +} - +// TODO Semantically we probably not need GroupExpression +// All we need is holding the Seq[Expression], and ONLY used in doing the +// expressions transformation correctly. Probably will be removed since it's +// not like a real expressions. +case class GroupExpression(children: Seq[Expression]) extends Expression { + self: Product => + type EvaluatedType = Seq[Any] + override def eval(input: Row): EvaluatedType = ??? + override def nullable = false + override def foldable = false + override def dataType = ??? } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/namedExpressions.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/namedExpressions.scala index 7634d392d4111..a3c300b5d90e9 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/namedExpressions.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/namedExpressions.scala @@ -187,3 +187,8 @@ case class AttributeReference( override def toString: String = s"$name#${exprId.id}$typeSuffix" } + +object VirtualColumn { + val groupingIdName = "grouping__id" + def newGroupingId = AttributeReference(groupingIdName, IntegerType, false)() +} diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala index 64b8d45ebbf42..a9282b98adfab 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala @@ -143,6 +143,89 @@ case class Aggregate( override def output = aggregateExpressions.map(_.toAttribute) } +/** + * Apply the all of the GroupExpressions to every input row, hence we will get + * multiple output rows for a input row. + * @param projections The group of expressions, all of the group expressions should + * output the same schema specified by the parameter `output` + * @param output The output Schema + * @param child Child operator + */ +case class Expand( + projections: Seq[GroupExpression], + output: Seq[Attribute], + child: LogicalPlan) extends UnaryNode + +trait GroupingAnalytics extends UnaryNode { + self: Product => + def gid: AttributeReference + def groupByExprs: Seq[Expression] + def aggregations: Seq[NamedExpression] + + override def output = aggregations.map(_.toAttribute) +} + +/** + * A GROUP BY clause with GROUPING SETS can generate a result set equivalent + * to generated by a UNION ALL of multiple simple GROUP BY clauses. + * + * We will transform GROUPING SETS into logical plan Aggregate(.., Expand) in Analyzer + * @param bitmasks A list of bitmasks, each of the bitmask indicates the selected + * GroupBy expressions + * @param groupByExprs The Group By expressions candidates, take effective only if the + * associated bit in the bitmask set to 1. + * @param child Child operator + * @param aggregations The Aggregation expressions, those non selected group by expressions + * will be considered as constant null if it appears in the expressions + * @param gid The attribute represents the virtual column GROUPING__ID, and it's also + * the bitmask indicates the selected GroupBy Expressions for each + * aggregating output row. + * The associated output will be one of the value in `bitmasks` + */ +case class GroupingSets( + bitmasks: Seq[Int], + groupByExprs: Seq[Expression], + child: LogicalPlan, + aggregations: Seq[NamedExpression], + gid: AttributeReference = VirtualColumn.newGroupingId) extends GroupingAnalytics + +/** + * Cube is a syntactic sugar for GROUPING SETS, and will be transformed to GroupingSets, + * and eventually will be transformed to Aggregate(.., Expand) in Analyzer + * + * @param groupByExprs The Group By expressions candidates. + * @param child Child operator + * @param aggregations The Aggregation expressions, those non selected group by expressions + * will be considered as constant null if it appears in the expressions + * @param gid The attribute represents the virtual column GROUPING__ID, and it's also + * the bitmask indicates the selected GroupBy Expressions for each + * aggregating output row. + */ +case class Cube( + groupByExprs: Seq[Expression], + child: LogicalPlan, + aggregations: Seq[NamedExpression], + gid: AttributeReference = VirtualColumn.newGroupingId) extends GroupingAnalytics + +/** + * Rollup is a syntactic sugar for GROUPING SETS, and will be transformed to GroupingSets, + * and eventually will be transformed to Aggregate(.., Expand) in Analyzer + * + * @param groupByExprs The Group By expressions candidates, take effective only if the + * associated bit in the bitmask set to 1. + * @param child Child operator + * @param aggregations The Aggregation expressions, those non selected group by expressions + * will be considered as constant null if it appears in the expressions + * @param gid The attribute represents the virtual column GROUPING__ID, and it's also + * the bitmask indicates the selected GroupBy Expressions for each + * aggregating output row. + */ +case class Rollup( + groupByExprs: Seq[Expression], + child: LogicalPlan, + aggregations: Seq[NamedExpression], + gid: AttributeReference = VirtualColumn.newGroupingId) extends GroupingAnalytics + case class Limit(limitExpr: Expression, child: LogicalPlan) extends UnaryNode { override def output = child.output diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/Expand.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/Expand.scala new file mode 100644 index 0000000000000..95172420608f9 --- /dev/null +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/Expand.scala @@ -0,0 +1,79 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.execution + +import org.apache.spark.annotation.DeveloperApi +import org.apache.spark.sql.SQLContext +import org.apache.spark.sql.catalyst.errors._ +import org.apache.spark.sql.catalyst.expressions._ +import org.apache.spark.sql.catalyst.plans.physical.{UnknownPartitioning, Partitioning} + +/** + * Apply the all of the GroupExpressions to every input row, hence we will get + * multiple output rows for a input row. + * @param projections The group of expressions, all of the group expressions should + * output the same schema specified bye the parameter `output` + * @param output The output Schema + * @param child Child operator + */ +@DeveloperApi +case class Expand( + projections: Seq[GroupExpression], + output: Seq[Attribute], + child: SparkPlan) + extends UnaryNode { + + // The GroupExpressions can output data with arbitrary partitioning, so set it + // as UNKNOWN partitioning + override def outputPartitioning: Partitioning = UnknownPartitioning(0) + + override def execute() = attachTree(this, "execute") { + child.execute().mapPartitions { iter => + // TODO Move out projection objects creation and transfer to + // workers via closure. However we can't assume the Projection + // is serializable because of the code gen, so we have to + // create the projections within each of the partition processing. + val groups = projections.map(ee => newProjection(ee.children, child.output)).toArray + + new Iterator[Row] { + private[this] var result: Row = _ + private[this] var idx = -1 // -1 means the initial state + private[this] var input: Row = _ + + override final def hasNext = (-1 < idx && idx < groups.length) || iter.hasNext + + override final def next(): Row = { + if (idx <= 0) { + // in the initial (-1) or beginning(0) of a new input row, fetch the next input tuple + input = iter.next() + idx = 0 + } + + result = groups(idx)(input) + idx += 1 + + if (idx == groups.length && iter.hasNext) { + idx = 0 + } + + result + } + } + } + } +} diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala index 1225d18857af2..6e04f26c84259 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala @@ -270,6 +270,8 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { execution.Project(projectList, planLater(child)) :: Nil case logical.Filter(condition, child) => execution.Filter(condition, planLater(child)) :: Nil + case logical.Expand(projections, output, child) => + execution.Expand(projections, output, planLater(child)) :: Nil case logical.Aggregate(group, agg, child) => execution.Aggregate(partial = false, group, agg, planLater(child)) :: Nil case logical.Sample(fraction, withReplacement, seed, child) => diff --git a/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala b/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala index 4302da5bfc7fc..1e44dd239458a 100644 --- a/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala +++ b/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala @@ -403,6 +403,13 @@ class HiveCompatibilitySuite extends HiveQueryFileTest with BeforeAndAfter { "groupby11", "groupby12", "groupby1_limit", + "groupby_grouping_id1", + "groupby_grouping_id2", + "groupby_grouping_sets1", + "groupby_grouping_sets2", + "groupby_grouping_sets3", + "groupby_grouping_sets4", + "groupby_grouping_sets5", "groupby1_map", "groupby1_map_nomap", "groupby1_map_skew", diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala index cd4e5a239ec66..5939276f6d65e 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala @@ -393,6 +393,42 @@ private[hive] object HiveQl { (db, tableName) } + /** + * SELECT MAX(value) FROM src GROUP BY k1, k2, k3 GROUPING SETS((k1, k2), (k2)) + * is equivalent to + * SELECT MAX(value) FROM src GROUP BY k1, k2 UNION SELECT MAX(value) FROM src GROUP BY k2 + * Check the following link for details. + * +https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C+Grouping+and+Rollup + * + * The bitmask denotes the grouping expressions validity for a grouping set, + * the bitmask also be called as grouping id (`GROUPING__ID`, the virtual column in Hive) + * e.g. In superset (k1, k2, k3), (bit 0: k1, bit 1: k2, and bit 2: k3), the grouping id of + * GROUPING SETS (k1, k2) and (k2) should be 3 and 2 respectively. + */ + protected def extractGroupingSet(children: Seq[ASTNode]): (Seq[Expression], Seq[Int]) = { + val (keyASTs, setASTs) = children.partition( n => n match { + case Token("TOK_GROUPING_SETS_EXPRESSION", children) => false // grouping sets + case _ => true // grouping keys + }) + + val keys = keyASTs.map(nodeToExpr).toSeq + val keyMap = keyASTs.map(_.toStringTree).zipWithIndex.toMap + + val bitmasks: Seq[Int] = setASTs.map(set => set match { + case Token("TOK_GROUPING_SETS_EXPRESSION", null) => 0 + case Token("TOK_GROUPING_SETS_EXPRESSION", children) => + children.foldLeft(0)((bitmap, col) => { + val colString = col.asInstanceOf[ASTNode].toStringTree() + require(keyMap.contains(colString), s"$colString doens't show up in the GROUP BY list") + bitmap | 1 << keyMap(colString) + }) + case _ => sys.error("Expect GROUPING SETS clause") + }) + + (keys, bitmasks) + } + protected def nodeToPlan(node: Node): LogicalPlan = node match { // Special drop table that also uncaches. case Token("TOK_DROPTABLE", @@ -520,6 +556,9 @@ private[hive] object HiveQl { selectDistinctClause :: whereClause :: groupByClause :: + rollupGroupByClause :: + cubeGroupByClause :: + groupingSetsClause :: orderByClause :: havingClause :: sortByClause :: @@ -535,6 +574,9 @@ private[hive] object HiveQl { "TOK_SELECTDI", "TOK_WHERE", "TOK_GROUPBY", + "TOK_ROLLUP_GROUPBY", + "TOK_CUBE_GROUPBY", + "TOK_GROUPING_SETS", "TOK_ORDERBY", "TOK_HAVING", "TOK_SORTBY", @@ -603,16 +645,33 @@ private[hive] object HiveQl { // The projection of the query can either be a normal projection, an aggregation // (if there is a group by) or a script transformation. - val withProject = transformation.getOrElse { - // Not a transformation so must be either project or aggregation. - val selectExpressions = nameExpressions(select.getChildren.flatMap(selExprNodeToExpr)) - - groupByClause match { - case Some(groupBy) => - Aggregate(groupBy.getChildren.map(nodeToExpr), selectExpressions, withLateralView) - case None => - Project(selectExpressions, withLateralView) - } + val withProject: LogicalPlan = transformation.getOrElse { + val selectExpressions = + nameExpressions(select.getChildren.flatMap(selExprNodeToExpr).toSeq) + Seq( + groupByClause.map(e => e match { + case Token("TOK_GROUPBY", children) => + // Not a transformation so must be either project or aggregation. + Aggregate(children.map(nodeToExpr), selectExpressions, withLateralView) + case _ => sys.error("Expect GROUP BY") + }), + groupingSetsClause.map(e => e match { + case Token("TOK_GROUPING_SETS", children) => + val(groupByExprs, masks) = extractGroupingSet(children) + GroupingSets(masks, groupByExprs, withLateralView, selectExpressions) + case _ => sys.error("Expect GROUPING SETS") + }), + rollupGroupByClause.map(e => e match { + case Token("TOK_ROLLUP_GROUPBY", children) => + Rollup(children.map(nodeToExpr), withLateralView, selectExpressions) + case _ => sys.error("Expect WITH ROLLUP") + }), + cubeGroupByClause.map(e => e match { + case Token("TOK_CUBE_GROUPBY", children) => + Cube(children.map(nodeToExpr), withLateralView, selectExpressions) + case _ => sys.error("Expect WITH CUBE") + }), + Some(Project(selectExpressions, withLateralView))).flatten.head } val withDistinct = diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_id1-0-caf1c5fd299fdbdb655234d01d44caf2 b/sql/hive/src/test/resources/golden/groupby_grouping_id1-0-caf1c5fd299fdbdb655234d01d44caf2 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_id1-1-b76bf9f6c92f83c9a5f351f8460d1e3b b/sql/hive/src/test/resources/golden/groupby_grouping_id1-1-b76bf9f6c92f83c9a5f351f8460d1e3b new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_id1-1-c0f14def6a135cc50cba364e810ce28e b/sql/hive/src/test/resources/golden/groupby_grouping_id1-1-c0f14def6a135cc50cba364e810ce28e new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_id1-2-3dfbff77a9b56d44312814d3fb0d07fa b/sql/hive/src/test/resources/golden/groupby_grouping_id1-2-3dfbff77a9b56d44312814d3fb0d07fa new file mode 100644 index 0000000000000..76280c6f3a1c8 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_id1-2-3dfbff77a9b56d44312814d3fb0d07fa @@ -0,0 +1,18 @@ +NULL NULL 0 +NULL 11 2 +NULL 12 2 +NULL 13 2 +NULL 17 2 +NULL 18 2 +NULL 28 2 +1 NULL 1 +1 11 3 +2 NULL 1 +2 12 3 +3 NULL 1 +3 13 3 +7 NULL 1 +7 17 3 +8 NULL 1 +8 18 3 +8 28 3 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_id1-3-d113d984a30ad7b98c50a46158605a51 b/sql/hive/src/test/resources/golden/groupby_grouping_id1-3-d113d984a30ad7b98c50a46158605a51 new file mode 100644 index 0000000000000..b18af4e5dd637 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_id1-3-d113d984a30ad7b98c50a46158605a51 @@ -0,0 +1,12 @@ +0 NULL NULL +1 1 NULL +3 1 11 +1 2 NULL +3 2 12 +1 3 NULL +3 3 13 +1 7 NULL +3 7 17 +1 8 NULL +3 8 18 +3 8 28 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_id1-4-903a499840102e2cb722dd8b83820391 b/sql/hive/src/test/resources/golden/groupby_grouping_id1-4-903a499840102e2cb722dd8b83820391 new file mode 100644 index 0000000000000..5a7ac193cb11b --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_id1-4-903a499840102e2cb722dd8b83820391 @@ -0,0 +1,18 @@ +NULL NULL 0 0 +NULL 11 2 2 +NULL 12 2 2 +NULL 13 2 2 +NULL 17 2 2 +NULL 18 2 2 +NULL 28 2 2 +1 NULL 1 1 +1 11 3 3 +2 NULL 1 1 +2 12 3 3 +3 NULL 1 1 +3 13 3 3 +7 NULL 1 1 +7 17 3 3 +8 NULL 1 1 +8 18 3 3 +8 28 3 3 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_id2-0-20539c642c514a590caca2f11395007e b/sql/hive/src/test/resources/golden/groupby_grouping_id2-0-20539c642c514a590caca2f11395007e new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_id2-1-d1f3215e349f056c8de60b87a6a9855e b/sql/hive/src/test/resources/golden/groupby_grouping_id2-1-d1f3215e349f056c8de60b87a6a9855e new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_id2-1-d6fb6c164cda6a13a71290dbf95fcc6e b/sql/hive/src/test/resources/golden/groupby_grouping_id2-1-d6fb6c164cda6a13a71290dbf95fcc6e new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_id2-2-a00d1791b7fa7ac5a0505d95c3d12257 b/sql/hive/src/test/resources/golden/groupby_grouping_id2-2-a00d1791b7fa7ac5a0505d95c3d12257 new file mode 100644 index 0000000000000..573541ac9702d --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_id2-2-a00d1791b7fa7ac5a0505d95c3d12257 @@ -0,0 +1 @@ +0 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_id2-3-b3cb95405b1200603f40aaab24be7586 b/sql/hive/src/test/resources/golden/groupby_grouping_id2-3-b3cb95405b1200603f40aaab24be7586 new file mode 100644 index 0000000000000..66ac2d65ce245 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_id2-3-b3cb95405b1200603f40aaab24be7586 @@ -0,0 +1,11 @@ +NULL NULL 0 6 +1 NULL 1 2 +1 NULL 3 1 +1 1 3 1 +2 NULL 1 1 +2 2 3 1 +3 NULL 1 2 +3 NULL 3 1 +3 3 3 1 +4 NULL 1 1 +4 5 3 1 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_id2-4-9bdcf67baa5d7cf70cd2eb1a3ec6de74 b/sql/hive/src/test/resources/golden/groupby_grouping_id2-4-9bdcf67baa5d7cf70cd2eb1a3ec6de74 new file mode 100644 index 0000000000000..8c1e9630ebfd7 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_id2-4-9bdcf67baa5d7cf70cd2eb1a3ec6de74 @@ -0,0 +1,3 @@ +0 1 +1 4 +3 6 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_id2-5-7dd97bda7e2a900dfc509a6133620b82 b/sql/hive/src/test/resources/golden/groupby_grouping_id2-5-7dd97bda7e2a900dfc509a6133620b82 new file mode 100644 index 0000000000000..42fc2290c2cba --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_id2-5-7dd97bda7e2a900dfc509a6133620b82 @@ -0,0 +1,53 @@ +0 0 +1 1 +1 1 +1 1 +1 1 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +1 1 +1 1 +1 1 +1 1 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +1 1 +1 1 +1 1 +1 1 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +1 1 +1 1 +1 1 +1 1 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_id2-6-a7dc16cb82c595b18d4258a38a304b1e b/sql/hive/src/test/resources/golden/groupby_grouping_id2-6-a7dc16cb82c595b18d4258a38a304b1e new file mode 100644 index 0000000000000..573541ac9702d --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_id2-6-a7dc16cb82c595b18d4258a38a304b1e @@ -0,0 +1 @@ +0 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_id2-7-b3cb95405b1200603f40aaab24be7586 b/sql/hive/src/test/resources/golden/groupby_grouping_id2-7-b3cb95405b1200603f40aaab24be7586 new file mode 100644 index 0000000000000..66ac2d65ce245 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_id2-7-b3cb95405b1200603f40aaab24be7586 @@ -0,0 +1,11 @@ +NULL NULL 0 6 +1 NULL 1 2 +1 NULL 3 1 +1 1 3 1 +2 NULL 1 1 +2 2 3 1 +3 NULL 1 2 +3 NULL 3 1 +3 3 3 1 +4 NULL 1 1 +4 5 3 1 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_id2-8-9bdcf67baa5d7cf70cd2eb1a3ec6de74 b/sql/hive/src/test/resources/golden/groupby_grouping_id2-8-9bdcf67baa5d7cf70cd2eb1a3ec6de74 new file mode 100644 index 0000000000000..8c1e9630ebfd7 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_id2-8-9bdcf67baa5d7cf70cd2eb1a3ec6de74 @@ -0,0 +1,3 @@ +0 1 +1 4 +3 6 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_id2-9-7dd97bda7e2a900dfc509a6133620b82 b/sql/hive/src/test/resources/golden/groupby_grouping_id2-9-7dd97bda7e2a900dfc509a6133620b82 new file mode 100644 index 0000000000000..42fc2290c2cba --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_id2-9-7dd97bda7e2a900dfc509a6133620b82 @@ -0,0 +1,53 @@ +0 0 +1 1 +1 1 +1 1 +1 1 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +1 1 +1 1 +1 1 +1 1 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +1 1 +1 1 +1 1 +1 1 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 +1 1 +1 1 +1 1 +1 1 +3 3 +3 3 +3 3 +3 3 +3 3 +3 3 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets1-0-91128722f50ec00b51e0bf6fe5695cd1 b/sql/hive/src/test/resources/golden/groupby_grouping_sets1-0-91128722f50ec00b51e0bf6fe5695cd1 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets1-1-3673d61d0944adeba77438d882839de4 b/sql/hive/src/test/resources/golden/groupby_grouping_sets1-1-3673d61d0944adeba77438d882839de4 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets1-1-d1c300ea08361fb8237689c6cf8cc1b5 b/sql/hive/src/test/resources/golden/groupby_grouping_sets1-1-d1c300ea08361fb8237689c6cf8cc1b5 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets1-2-5c14fabebc5b4c526c459a6e867ec61a b/sql/hive/src/test/resources/golden/groupby_grouping_sets1-2-5c14fabebc5b4c526c459a6e867ec61a new file mode 100644 index 0000000000000..7967c04c92149 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets1-2-5c14fabebc5b4c526c459a6e867ec61a @@ -0,0 +1,6 @@ +8 1 1 +5 2 2 +1 1 3 +2 2 4 +2 3 5 +3 2 8 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets1-3-9f501f293fe180bf6322e93d8dea025a b/sql/hive/src/test/resources/golden/groupby_grouping_sets1-3-9f501f293fe180bf6322e93d8dea025a new file mode 100644 index 0000000000000..da4a754efa0e0 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets1-3-9f501f293fe180bf6322e93d8dea025a @@ -0,0 +1,15 @@ +NULL NULL 6 +NULL 1 2 +NULL 2 3 +NULL 3 1 +1 NULL 1 +1 1 1 +2 NULL 2 +2 2 1 +2 3 1 +3 NULL 1 +3 2 1 +5 NULL 1 +5 2 1 +8 NULL 1 +8 1 1 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets1-4-505ac6611b332d6cf4a364739075d49c b/sql/hive/src/test/resources/golden/groupby_grouping_sets1-4-505ac6611b332d6cf4a364739075d49c new file mode 100644 index 0000000000000..da4a754efa0e0 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets1-4-505ac6611b332d6cf4a364739075d49c @@ -0,0 +1,15 @@ +NULL NULL 6 +NULL 1 2 +NULL 2 3 +NULL 3 1 +1 NULL 1 +1 1 1 +2 NULL 2 +2 2 1 +2 3 1 +3 NULL 1 +3 2 1 +5 NULL 1 +5 2 1 +8 NULL 1 +8 1 1 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets1-5-a33cc72bf5adee428eea079847034b62 b/sql/hive/src/test/resources/golden/groupby_grouping_sets1-5-a33cc72bf5adee428eea079847034b62 new file mode 100644 index 0000000000000..2d1b73d564955 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets1-5-a33cc72bf5adee428eea079847034b62 @@ -0,0 +1,11 @@ +1 NULL 1 +1 1 1 +2 NULL 2 +2 2 1 +2 3 1 +3 NULL 1 +3 2 1 +5 NULL 1 +5 2 1 +8 NULL 1 +8 1 1 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets1-6-5f0c2e1d5489c867261e575625349542 b/sql/hive/src/test/resources/golden/groupby_grouping_sets1-6-5f0c2e1d5489c867261e575625349542 new file mode 100644 index 0000000000000..fe6c4d001180a --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets1-6-5f0c2e1d5489c867261e575625349542 @@ -0,0 +1,14 @@ +NULL +NULL +NULL +NULL +NULL +NULL +NULL +NULL +NULL +1 +2 +3 +5 +8 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets1-7-9b3bda02733476012e2cda434d936423 b/sql/hive/src/test/resources/golden/groupby_grouping_sets1-7-9b3bda02733476012e2cda434d936423 new file mode 100644 index 0000000000000..24d5fc2851703 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets1-7-9b3bda02733476012e2cda434d936423 @@ -0,0 +1,5 @@ +1 +2 +3 +5 +8 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets1-8-1273ad6760f8c3ddad07819362dcc324 b/sql/hive/src/test/resources/golden/groupby_grouping_sets1-8-1273ad6760f8c3ddad07819362dcc324 new file mode 100644 index 0000000000000..8ba0d6d25a6f0 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets1-8-1273ad6760f8c3ddad07819362dcc324 @@ -0,0 +1,5 @@ +2.0 1 +4.0 1 +5.0 2 +7.0 1 +9.0 1 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets2-0-bb96e87a0d6b0d1a6167e424b086acf6 b/sql/hive/src/test/resources/golden/groupby_grouping_sets2-0-bb96e87a0d6b0d1a6167e424b086acf6 new file mode 100644 index 0000000000000..573541ac9702d --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets2-0-bb96e87a0d6b0d1a6167e424b086acf6 @@ -0,0 +1 @@ +0 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets2-1-91128722f50ec00b51e0bf6fe5695cd1 b/sql/hive/src/test/resources/golden/groupby_grouping_sets2-1-91128722f50ec00b51e0bf6fe5695cd1 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets2-10-f39e49610430c91e5af3876d15fbdfe3 b/sql/hive/src/test/resources/golden/groupby_grouping_sets2-10-f39e49610430c91e5af3876d15fbdfe3 new file mode 100644 index 0000000000000..cabc9bb1d918f --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets2-10-f39e49610430c91e5af3876d15fbdfe3 @@ -0,0 +1,15 @@ +NULL NULL 46 +NULL 1 8 +NULL 2 28 +NULL 3 10 +1 NULL 6 +1 1 6 +2 NULL 18 +2 2 8 +2 3 10 +3 NULL 16 +3 2 16 +5 NULL 4 +5 2 4 +8 NULL 2 +8 1 2 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets2-2-3673d61d0944adeba77438d882839de4 b/sql/hive/src/test/resources/golden/groupby_grouping_sets2-2-3673d61d0944adeba77438d882839de4 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets2-2-d1c300ea08361fb8237689c6cf8cc1b5 b/sql/hive/src/test/resources/golden/groupby_grouping_sets2-2-d1c300ea08361fb8237689c6cf8cc1b5 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets2-3-59adefab34d80e8e185b2ad03877d381 b/sql/hive/src/test/resources/golden/groupby_grouping_sets2-3-59adefab34d80e8e185b2ad03877d381 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets2-4-9f501f293fe180bf6322e93d8dea025a b/sql/hive/src/test/resources/golden/groupby_grouping_sets2-4-9f501f293fe180bf6322e93d8dea025a new file mode 100644 index 0000000000000..da4a754efa0e0 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets2-4-9f501f293fe180bf6322e93d8dea025a @@ -0,0 +1,15 @@ +NULL NULL 6 +NULL 1 2 +NULL 2 3 +NULL 3 1 +1 NULL 1 +1 1 1 +2 NULL 2 +2 2 1 +2 3 1 +3 NULL 1 +3 2 1 +5 NULL 1 +5 2 1 +8 NULL 1 +8 1 1 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets2-5-1163c486fd7e2c4346805fb035e2f268 b/sql/hive/src/test/resources/golden/groupby_grouping_sets2-5-1163c486fd7e2c4346805fb035e2f268 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets2-6-9459dc3e8ab1f09d6d912b686e7f37fc b/sql/hive/src/test/resources/golden/groupby_grouping_sets2-6-9459dc3e8ab1f09d6d912b686e7f37fc new file mode 100644 index 0000000000000..b20db4c79aa70 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets2-6-9459dc3e8ab1f09d6d912b686e7f37fc @@ -0,0 +1,15 @@ +NULL NULL 23.0 +NULL 1 4.0 +NULL 2 14.0 +NULL 3 5.0 +1 NULL 3.0 +1 1 3.0 +2 NULL 9.0 +2 2 4.0 +2 3 5.0 +3 NULL 8.0 +3 2 8.0 +5 NULL 2.0 +5 2 2.0 +8 NULL 1.0 +8 1 1.0 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets2-7-39db88427f92cb770b6daa38610c04e7 b/sql/hive/src/test/resources/golden/groupby_grouping_sets2-7-39db88427f92cb770b6daa38610c04e7 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets2-8-e464ec3d5461bda47eac3d1ef8617786 b/sql/hive/src/test/resources/golden/groupby_grouping_sets2-8-e464ec3d5461bda47eac3d1ef8617786 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets2-9-74126b100714164d13cbb3bff436c2ff b/sql/hive/src/test/resources/golden/groupby_grouping_sets2-9-74126b100714164d13cbb3bff436c2ff new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets3-0-4fe85ca1e68a895ef403afdcfbbf61bc b/sql/hive/src/test/resources/golden/groupby_grouping_sets3-0-4fe85ca1e68a895ef403afdcfbbf61bc new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets3-1-38373b67d392924967a4695689d2164e b/sql/hive/src/test/resources/golden/groupby_grouping_sets3-1-38373b67d392924967a4695689d2164e new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets3-1-e8964b2aaeb388064c9fdac5ec687824 b/sql/hive/src/test/resources/golden/groupby_grouping_sets3-1-e8964b2aaeb388064c9fdac5ec687824 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets3-2-c1942a377b1a440d4ed3dd05fed445d b/sql/hive/src/test/resources/golden/groupby_grouping_sets3-2-c1942a377b1a440d4ed3dd05fed445d new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets3-2-d95cf9dfae402d369f338b8516845e02 b/sql/hive/src/test/resources/golden/groupby_grouping_sets3-2-d95cf9dfae402d369f338b8516845e02 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets3-3-b89ea2173180c8ae423d856f943e061f b/sql/hive/src/test/resources/golden/groupby_grouping_sets3-3-b89ea2173180c8ae423d856f943e061f new file mode 100644 index 0000000000000..573541ac9702d --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets3-3-b89ea2173180c8ae423d856f943e061f @@ -0,0 +1 @@ +0 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets3-4-77c57e1b4ca37c2dc715b65668cd0c59 b/sql/hive/src/test/resources/golden/groupby_grouping_sets3-4-77c57e1b4ca37c2dc715b65668cd0c59 new file mode 100644 index 0000000000000..573541ac9702d --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets3-4-77c57e1b4ca37c2dc715b65668cd0c59 @@ -0,0 +1 @@ +0 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets3-5-6623f95d90d929a6d2c8171a0698d4fd b/sql/hive/src/test/resources/golden/groupby_grouping_sets3-5-6623f95d90d929a6d2c8171a0698d4fd new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets3-6-aec59088408cc57248851d3ce04e2eef b/sql/hive/src/test/resources/golden/groupby_grouping_sets3-6-aec59088408cc57248851d3ce04e2eef new file mode 100644 index 0000000000000..b2d08949e9795 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets3-6-aec59088408cc57248851d3ce04e2eef @@ -0,0 +1,16 @@ +NULL NULL 3.8333333333333335 12 +NULL 1 2.0 5 +NULL 2 5.2 5 +NULL 3 5.0 2 +1 NULL 2.6666666666666665 3 +1 1 3.0 2 +1 2 2.0 1 +2 NULL 5.2 5 +2 2 5.333333333333333 3 +2 3 5.0 2 +3 NULL 8.0 1 +3 2 8.0 1 +5 NULL 2.0 1 +5 1 2.0 1 +8 NULL 1.0 2 +8 1 1.0 2 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets3-7-bb96e87a0d6b0d1a6167e424b086acf6 b/sql/hive/src/test/resources/golden/groupby_grouping_sets3-7-bb96e87a0d6b0d1a6167e424b086acf6 new file mode 100644 index 0000000000000..573541ac9702d --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets3-7-bb96e87a0d6b0d1a6167e424b086acf6 @@ -0,0 +1 @@ +0 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets3-8-f32c4a191759237733a10cd721b49966 b/sql/hive/src/test/resources/golden/groupby_grouping_sets3-8-f32c4a191759237733a10cd721b49966 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets3-9-aec59088408cc57248851d3ce04e2eef b/sql/hive/src/test/resources/golden/groupby_grouping_sets3-9-aec59088408cc57248851d3ce04e2eef new file mode 100644 index 0000000000000..b2d08949e9795 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets3-9-aec59088408cc57248851d3ce04e2eef @@ -0,0 +1,16 @@ +NULL NULL 3.8333333333333335 12 +NULL 1 2.0 5 +NULL 2 5.2 5 +NULL 3 5.0 2 +1 NULL 2.6666666666666665 3 +1 1 3.0 2 +1 2 2.0 1 +2 NULL 5.2 5 +2 2 5.333333333333333 3 +2 3 5.0 2 +3 NULL 8.0 1 +3 2 8.0 1 +5 NULL 2.0 1 +5 1 2.0 1 +8 NULL 1.0 2 +8 1 1.0 2 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets4-0-d8ae5a3e613dd2dda392995b90d47565 b/sql/hive/src/test/resources/golden/groupby_grouping_sets4-0-d8ae5a3e613dd2dda392995b90d47565 new file mode 100644 index 0000000000000..573541ac9702d --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets4-0-d8ae5a3e613dd2dda392995b90d47565 @@ -0,0 +1 @@ +0 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets4-1-6ad4e855adb49babfa3ae6abac190be3 b/sql/hive/src/test/resources/golden/groupby_grouping_sets4-1-6ad4e855adb49babfa3ae6abac190be3 new file mode 100644 index 0000000000000..573541ac9702d --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets4-1-6ad4e855adb49babfa3ae6abac190be3 @@ -0,0 +1 @@ +0 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets4-2-1789808269c8bd0f6259227f07da1a6a b/sql/hive/src/test/resources/golden/groupby_grouping_sets4-2-1789808269c8bd0f6259227f07da1a6a new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets4-3-3673d61d0944adeba77438d882839de4 b/sql/hive/src/test/resources/golden/groupby_grouping_sets4-3-3673d61d0944adeba77438d882839de4 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets4-3-d1c300ea08361fb8237689c6cf8cc1b5 b/sql/hive/src/test/resources/golden/groupby_grouping_sets4-3-d1c300ea08361fb8237689c6cf8cc1b5 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets4-4-b51d813d0c5a410d8cf9765d85005a01 b/sql/hive/src/test/resources/golden/groupby_grouping_sets4-4-b51d813d0c5a410d8cf9765d85005a01 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets4-5-9be98faf8588a3c8e7436f14c638e438 b/sql/hive/src/test/resources/golden/groupby_grouping_sets4-5-9be98faf8588a3c8e7436f14c638e438 new file mode 100644 index 0000000000000..33060f0d51729 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets4-5-9be98faf8588a3c8e7436f14c638e438 @@ -0,0 +1,13 @@ +1 NULL 1 1 NULL 1 +1 NULL 1 1 1 1 +1 1 1 1 NULL 1 +1 1 1 1 1 1 +2 NULL 2 2 NULL 2 +2 NULL 2 2 2 1 +2 NULL 2 2 3 1 +2 2 1 2 NULL 2 +2 2 1 2 2 1 +2 2 1 2 3 1 +2 3 1 2 NULL 2 +2 3 1 2 2 1 +2 3 1 2 3 1 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets4-6-bb96e87a0d6b0d1a6167e424b086acf6 b/sql/hive/src/test/resources/golden/groupby_grouping_sets4-6-bb96e87a0d6b0d1a6167e424b086acf6 new file mode 100644 index 0000000000000..573541ac9702d --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets4-6-bb96e87a0d6b0d1a6167e424b086acf6 @@ -0,0 +1 @@ +0 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets4-7-98f7522ce136cdffb0c14163e613c250 b/sql/hive/src/test/resources/golden/groupby_grouping_sets4-7-98f7522ce136cdffb0c14163e613c250 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets4-8-9be98faf8588a3c8e7436f14c638e438 b/sql/hive/src/test/resources/golden/groupby_grouping_sets4-8-9be98faf8588a3c8e7436f14c638e438 new file mode 100644 index 0000000000000..33060f0d51729 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets4-8-9be98faf8588a3c8e7436f14c638e438 @@ -0,0 +1,13 @@ +1 NULL 1 1 NULL 1 +1 NULL 1 1 1 1 +1 1 1 1 NULL 1 +1 1 1 1 1 1 +2 NULL 2 2 NULL 2 +2 NULL 2 2 2 1 +2 NULL 2 2 3 1 +2 2 1 2 NULL 2 +2 2 1 2 2 1 +2 2 1 2 3 1 +2 3 1 2 NULL 2 +2 3 1 2 2 1 +2 3 1 2 3 1 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets5-0-d8ae5a3e613dd2dda392995b90d47565 b/sql/hive/src/test/resources/golden/groupby_grouping_sets5-0-d8ae5a3e613dd2dda392995b90d47565 new file mode 100644 index 0000000000000..573541ac9702d --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets5-0-d8ae5a3e613dd2dda392995b90d47565 @@ -0,0 +1 @@ +0 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets5-1-6ad4e855adb49babfa3ae6abac190be3 b/sql/hive/src/test/resources/golden/groupby_grouping_sets5-1-6ad4e855adb49babfa3ae6abac190be3 new file mode 100644 index 0000000000000..573541ac9702d --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets5-1-6ad4e855adb49babfa3ae6abac190be3 @@ -0,0 +1 @@ +0 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets5-2-1789808269c8bd0f6259227f07da1a6a b/sql/hive/src/test/resources/golden/groupby_grouping_sets5-2-1789808269c8bd0f6259227f07da1a6a new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets5-3-3673d61d0944adeba77438d882839de4 b/sql/hive/src/test/resources/golden/groupby_grouping_sets5-3-3673d61d0944adeba77438d882839de4 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets5-3-d1c300ea08361fb8237689c6cf8cc1b5 b/sql/hive/src/test/resources/golden/groupby_grouping_sets5-3-d1c300ea08361fb8237689c6cf8cc1b5 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets5-4-6a89a34347f1c0eb9e0763ecedddb6f9 b/sql/hive/src/test/resources/golden/groupby_grouping_sets5-4-6a89a34347f1c0eb9e0763ecedddb6f9 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets5-5-af3569757b9f52fb9b1ead33130e1b4f b/sql/hive/src/test/resources/golden/groupby_grouping_sets5-5-af3569757b9f52fb9b1ead33130e1b4f new file mode 100644 index 0000000000000..da4a754efa0e0 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets5-5-af3569757b9f52fb9b1ead33130e1b4f @@ -0,0 +1,15 @@ +NULL NULL 6 +NULL 1 2 +NULL 2 3 +NULL 3 1 +1 NULL 1 +1 1 1 +2 NULL 2 +2 2 1 +2 3 1 +3 NULL 1 +3 2 1 +5 NULL 1 +5 2 1 +8 NULL 1 +8 1 1 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets5-6-bb96e87a0d6b0d1a6167e424b086acf6 b/sql/hive/src/test/resources/golden/groupby_grouping_sets5-6-bb96e87a0d6b0d1a6167e424b086acf6 new file mode 100644 index 0000000000000..573541ac9702d --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets5-6-bb96e87a0d6b0d1a6167e424b086acf6 @@ -0,0 +1 @@ +0 diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets5-7-6544a382d851f916616c4386fdcf0ed8 b/sql/hive/src/test/resources/golden/groupby_grouping_sets5-7-6544a382d851f916616c4386fdcf0ed8 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/groupby_grouping_sets5-8-af3569757b9f52fb9b1ead33130e1b4f b/sql/hive/src/test/resources/golden/groupby_grouping_sets5-8-af3569757b9f52fb9b1ead33130e1b4f new file mode 100644 index 0000000000000..da4a754efa0e0 --- /dev/null +++ b/sql/hive/src/test/resources/golden/groupby_grouping_sets5-8-af3569757b9f52fb9b1ead33130e1b4f @@ -0,0 +1,15 @@ +NULL NULL 6 +NULL 1 2 +NULL 2 3 +NULL 3 1 +1 NULL 1 +1 1 1 +2 NULL 2 +2 2 1 +2 3 1 +3 NULL 1 +3 2 1 +5 NULL 1 +5 2 1 +8 NULL 1 +8 1 1 From b68bc6d2647f8a5caf8aa558e4115f9cc254f67c Mon Sep 17 00:00:00 2001 From: Thu Kyaw Date: Thu, 18 Dec 2014 20:08:32 -0800 Subject: [PATCH 047/320] [SPARK-3928][SQL] Support wildcard matches on Parquet files. ...arquetFile accept hadoop glob pattern in path. Author: Thu Kyaw Closes #3407 from tkyaw/master and squashes the following commits: 19115ad [Thu Kyaw] Merge https://github.com/apache/spark ceded32 [Thu Kyaw] [SPARK-3928][SQL] Support wildcard matches on Parquet files. d322c28 [Thu Kyaw] [SPARK-3928][SQL] Support wildcard matches on Parquet files. ce677c6 [Thu Kyaw] [SPARK-3928][SQL] Support wildcard matches on Parquet files. --- .../spark/sql/api/java/JavaSQLContext.scala | 4 ++- .../sql/parquet/ParquetTableOperations.scala | 4 ++- .../spark/sql/parquet/ParquetTestData.scala | 36 +++++++++++++++++++ .../spark/sql/parquet/ParquetTypes.scala | 12 ++++--- .../spark/sql/parquet/ParquetQuerySuite.scala | 26 ++++++++++++++ 5 files changed, 76 insertions(+), 6 deletions(-) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSQLContext.scala index 4c0869e05b029..8884204e5079f 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSQLContext.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSQLContext.scala @@ -133,7 +133,9 @@ class JavaSQLContext(val sqlContext: SQLContext) extends UDFRegistration { } /** - * Loads a parquet file, returning the result as a [[JavaSchemaRDD]]. + * Loads a parquet file from regular path or files that match file patterns in path, + * returning the result as a [[JavaSchemaRDD]]. + * Supported glob file pattern information at ([[http://tinyurl.com/kcqrzn8]]). */ def parquetFile(path: String): JavaSchemaRDD = new JavaSchemaRDD( diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala index 5a49384ade76f..96bace1769f71 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala @@ -621,7 +621,9 @@ private[parquet] object FileSystemHelper { throw new IllegalArgumentException( s"ParquetTableOperations: path $path does not exist or is not a directory") } - fs.listStatus(path).map(_.getPath) + fs.globStatus(path) + .flatMap { status => if(status.isDir) fs.listStatus(status.getPath) else List(status) } + .map(_.getPath) } /** diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTestData.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTestData.scala index c0918a40d136f..d5993656e0225 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTestData.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTestData.scala @@ -422,5 +422,41 @@ private[sql] object ParquetTestData { val first = reader.read() assert(first != null) } */ + + // to test golb pattern (wild card pattern matching for parquetFile input + val testGlobDir = Utils.createTempDir() + val testGlobSubDir1 = Utils.createTempDir(testGlobDir.getPath) + val testGlobSubDir2 = Utils.createTempDir(testGlobDir.getPath) + val testGlobSubDir3 = Utils.createTempDir(testGlobDir.getPath) + + def writeGlobFiles() = { + val subDirs = Array(testGlobSubDir1, testGlobSubDir2, testGlobSubDir3) + + subDirs.foreach { dir => + val path: Path = new Path(new Path(dir.toURI), new Path("part-r-0.parquet")) + val job = new Job() + val schema: MessageType = MessageTypeParser.parseMessageType(testSchema) + val writeSupport = new TestGroupWriteSupport(schema) + val writer = new ParquetWriter[Group](path, writeSupport) + + for(i <- 0 until 15) { + val record = new SimpleGroup(schema) + if(i % 3 == 0) { + record.add(0, true) + } else { + record.add(0, false) + } + if(i % 5 == 0) { + record.add(1, 5) + } + record.add(2, "abc") + record.add(3, i.toLong << 33) + record.add(4, 2.5F) + record.add(5, 4.5D) + writer.write(record) + } + writer.close() + } + } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTypes.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTypes.scala index fa37d1f2ae7e6..0e6fb57d57bca 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTypes.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTypes.scala @@ -437,10 +437,14 @@ private[parquet] object ParquetTypesConverter extends Logging { } val path = origPath.makeQualified(fs) - val children = fs.listStatus(path).filterNot { status => - val name = status.getPath.getName - (name(0) == '.' || name(0) == '_') && name != ParquetFileWriter.PARQUET_METADATA_FILE - } + val children = + fs + .globStatus(path) + .flatMap { status => if(status.isDir) fs.listStatus(status.getPath) else List(status) } + .filterNot { status => + val name = status.getPath.getName + (name(0) == '.' || name(0) == '_') && name != ParquetFileWriter.PARQUET_METADATA_FILE + } ParquetRelation.enableLogForwarding() diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala index 0e5635d3e99dc..074855389d746 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala @@ -95,6 +95,7 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA ParquetTestData.writeNestedFile2() ParquetTestData.writeNestedFile3() ParquetTestData.writeNestedFile4() + ParquetTestData.writeGlobFiles() testRDD = parquetFile(ParquetTestData.testDir.toString) testRDD.registerTempTable("testsource") parquetFile(ParquetTestData.testFilterDir.toString) @@ -110,6 +111,7 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA Utils.deleteRecursively(ParquetTestData.testNestedDir2) Utils.deleteRecursively(ParquetTestData.testNestedDir3) Utils.deleteRecursively(ParquetTestData.testNestedDir4) + Utils.deleteRecursively(ParquetTestData.testGlobDir) // here we should also unregister the table?? setConf(SQLConf.PARQUET_FILTER_PUSHDOWN_ENABLED, originalParquetFilterPushdownEnabled.toString) @@ -1049,4 +1051,28 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA "Comparison predicate with null shouldn't be pushed down") } } + + test("Import of simple Parquet files using glob wildcard pattern") { + val testGlobDir = ParquetTestData.testGlobDir.toString + val globPatterns = Array(testGlobDir + "/*/*", testGlobDir + "/spark-*/*", testGlobDir + "/?pa?k-*/*") + globPatterns.foreach { path => + val result = parquetFile(path).collect() + assert(result.size === 45) + result.zipWithIndex.foreach { + case (row, index) => { + val checkBoolean = + if ((index % 15) % 3 == 0) + row(0) == true + else + row(0) == false + assert(checkBoolean === true, s"boolean field value in line $index did not match") + if ((index % 15) % 5 == 0) assert(row(1) === 5, s"int field value in line $index did not match") + assert(row(2) === "abc", s"string field value in line $index did not match") + assert(row(3) === ((index.toLong % 15) << 33), s"long value in line $index did not match") + assert(row(4) === 2.5F, s"float field value in line $index did not match") + assert(row(5) === 4.5D, s"double field value in line $index did not match") + } + } + } + } } From 22ddb6e0338f4d101389a0655424a8fde6c4cff4 Mon Sep 17 00:00:00 2001 From: guowei2 Date: Thu, 18 Dec 2014 20:10:23 -0800 Subject: [PATCH 048/320] [SPARK-4756][SQL] FIX: sessionToActivePool grow infinitely, even as sessions expire **sessionToActivePool** in **SparkSQLOperationManager** grow infinitely, even as sessions expire. we should remove the pool value when the session closed, even though **sessionToActivePool** would not exist in all of sessions. Author: guowei2 Closes #3617 from guowei2/SPARK-4756 and squashes the following commits: e9b97b8 [guowei2] fix compile bug with Shim12 cf0f521 [guowei2] Merge remote-tracking branch 'apache/master' into SPARK-4756 e070998 [guowei2] fix: remove active pool of the session when it expired --- .../sql/hive/thriftserver/SparkSQLSessionManager.scala | 9 ++++++++- .../thriftserver/server/SparkSQLOperationManager.scala | 3 +-- .../org/apache/spark/sql/hive/thriftserver/Shim12.scala | 6 +++--- .../org/apache/spark/sql/hive/thriftserver/Shim13.scala | 6 +++--- 4 files changed, 15 insertions(+), 9 deletions(-) diff --git a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkSQLSessionManager.scala b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkSQLSessionManager.scala index 6b3275b4eaf04..89e9ede7261c9 100644 --- a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkSQLSessionManager.scala +++ b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkSQLSessionManager.scala @@ -27,11 +27,14 @@ import org.apache.hive.service.cli.session.SessionManager import org.apache.spark.sql.hive.HiveContext import org.apache.spark.sql.hive.thriftserver.ReflectionUtils._ import org.apache.spark.sql.hive.thriftserver.server.SparkSQLOperationManager +import org.apache.hive.service.cli.SessionHandle private[hive] class SparkSQLSessionManager(hiveContext: HiveContext) extends SessionManager with ReflectedCompositeService { + private lazy val sparkSqlOperationManager = new SparkSQLOperationManager(hiveContext) + override def init(hiveConf: HiveConf) { setSuperField(this, "hiveConf", hiveConf) @@ -40,10 +43,14 @@ private[hive] class SparkSQLSessionManager(hiveContext: HiveContext) getAncestorField[Log](this, 3, "LOG").info( s"HiveServer2: Async execution pool size $backgroundPoolSize") - val sparkSqlOperationManager = new SparkSQLOperationManager(hiveContext) setSuperField(this, "operationManager", sparkSqlOperationManager) addService(sparkSqlOperationManager) initCompositeService(hiveConf) } + + override def closeSession(sessionHandle: SessionHandle) { + super.closeSession(sessionHandle) + sparkSqlOperationManager.sessionToActivePool -= sessionHandle + } } diff --git a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/server/SparkSQLOperationManager.scala b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/server/SparkSQLOperationManager.scala index 99c4f46a82b8e..9c0bf02391e0e 100644 --- a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/server/SparkSQLOperationManager.scala +++ b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/server/SparkSQLOperationManager.scala @@ -36,8 +36,7 @@ private[thriftserver] class SparkSQLOperationManager(hiveContext: HiveContext) val handleToOperation = ReflectionUtils .getSuperField[JMap[OperationHandle, Operation]](this, "handleToOperation") - // TODO: Currenlty this will grow infinitely, even as sessions expire - val sessionToActivePool = Map[HiveSession, String]() + val sessionToActivePool = Map[SessionHandle, String]() override def newExecuteStatementOperation( parentSession: HiveSession, diff --git a/sql/hive-thriftserver/v0.12.0/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim12.scala b/sql/hive-thriftserver/v0.12.0/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim12.scala index 9258ad0cdf1d0..5550183621fb6 100644 --- a/sql/hive-thriftserver/v0.12.0/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim12.scala +++ b/sql/hive-thriftserver/v0.12.0/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim12.scala @@ -69,7 +69,7 @@ private[hive] class SparkExecuteStatementOperation( statement: String, confOverlay: JMap[String, String])( hiveContext: HiveContext, - sessionToActivePool: SMap[HiveSession, String]) + sessionToActivePool: SMap[SessionHandle, String]) extends ExecuteStatementOperation(parentSession, statement, confOverlay) with Logging { private var result: SchemaRDD = _ @@ -191,14 +191,14 @@ private[hive] class SparkExecuteStatementOperation( logDebug(result.queryExecution.toString()) result.queryExecution.logical match { case SetCommand(Some((SQLConf.THRIFTSERVER_POOL, Some(value)))) => - sessionToActivePool(parentSession) = value + sessionToActivePool(parentSession.getSessionHandle) = value logInfo(s"Setting spark.scheduler.pool=$value for future statements in this session.") case _ => } val groupId = round(random * 1000000).toString hiveContext.sparkContext.setJobGroup(groupId, statement) - sessionToActivePool.get(parentSession).foreach { pool => + sessionToActivePool.get(parentSession.getSessionHandle).foreach { pool => hiveContext.sparkContext.setLocalProperty("spark.scheduler.pool", pool) } iter = { diff --git a/sql/hive-thriftserver/v0.13.1/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim13.scala b/sql/hive-thriftserver/v0.13.1/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim13.scala index 17f1ad3e4690e..798a690a20427 100644 --- a/sql/hive-thriftserver/v0.13.1/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim13.scala +++ b/sql/hive-thriftserver/v0.13.1/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim13.scala @@ -69,7 +69,7 @@ private[hive] class SparkExecuteStatementOperation( confOverlay: JMap[String, String], runInBackground: Boolean = true)( hiveContext: HiveContext, - sessionToActivePool: SMap[HiveSession, String]) + sessionToActivePool: SMap[SessionHandle, String]) // NOTE: `runInBackground` is set to `false` intentionally to disable asynchronous execution extends ExecuteStatementOperation(parentSession, statement, confOverlay, false) with Logging { @@ -162,14 +162,14 @@ private[hive] class SparkExecuteStatementOperation( logDebug(result.queryExecution.toString()) result.queryExecution.logical match { case SetCommand(Some((SQLConf.THRIFTSERVER_POOL, Some(value)))) => - sessionToActivePool(parentSession) = value + sessionToActivePool(parentSession.getSessionHandle) = value logInfo(s"Setting spark.scheduler.pool=$value for future statements in this session.") case _ => } val groupId = round(random * 1000000).toString hiveContext.sparkContext.setJobGroup(groupId, statement) - sessionToActivePool.get(parentSession).foreach { pool => + sessionToActivePool.get(parentSession.getSessionHandle).foreach { pool => hiveContext.sparkContext.setLocalProperty("spark.scheduler.pool", pool) } iter = { From e7de7e5f46821e1ba3b070b21d6bcf6d5ec8a796 Mon Sep 17 00:00:00 2001 From: YanTangZhai Date: Thu, 18 Dec 2014 20:13:46 -0800 Subject: [PATCH 049/320] [SPARK-4693] [SQL] PruningPredicates may be wrong if predicates contains an empty AttributeSet() references The sql "select * from spark_test::for_test where abs(20141202) is not null" has predicates=List(IS NOT NULL HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFAbs(20141202)) and partitionKeyIds=AttributeSet(). PruningPredicates is List(IS NOT NULL HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFAbs(20141202)). Then the exception "java.lang.IllegalArgumentException: requirement failed: Partition pruning predicates only supported for partitioned tables." is thrown. The sql "select * from spark_test::for_test_partitioned_table where abs(20141202) is not null and type_id=11 and platform = 3" with partitioned key insert_date has predicates=List(IS NOT NULL HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFAbs(20141202), (type_id#12 = 11), (platform#8 = 3)) and partitionKeyIds=AttributeSet(insert_date#24). PruningPredicates is List(IS NOT NULL HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFAbs(20141202)). Author: YanTangZhai Author: yantangzhai Closes #3556 from YanTangZhai/SPARK-4693 and squashes the following commits: 620ebe3 [yantangzhai] [SPARK-4693] [SQL] PruningPredicates may be wrong if predicates contains an empty AttributeSet() references 37cfdf5 [yantangzhai] [SPARK-4693] [SQL] PruningPredicates may be wrong if predicates contains an empty AttributeSet() references 70a3544 [yantangzhai] [SPARK-4693] [SQL] PruningPredicates may be wrong if predicates contains an empty AttributeSet() references efa9b03 [YanTangZhai] Update HiveQuerySuite.scala 72accf1 [YanTangZhai] Update HiveQuerySuite.scala e572b9a [YanTangZhai] Update HiveStrategies.scala 6e643f8 [YanTangZhai] Merge pull request #11 from apache/master e249846 [YanTangZhai] Merge pull request #10 from apache/master d26d982 [YanTangZhai] Merge pull request #9 from apache/master 76d4027 [YanTangZhai] Merge pull request #8 from apache/master 03b62b0 [YanTangZhai] Merge pull request #7 from apache/master 8a00106 [YanTangZhai] Merge pull request #6 from apache/master cbcba66 [YanTangZhai] Merge pull request #3 from apache/master cdef539 [YanTangZhai] Merge pull request #1 from apache/master --- .../spark/sql/catalyst/expressions/AttributeSet.scala | 2 ++ .../scala/org/apache/spark/sql/hive/HiveStrategies.scala | 5 +++-- .../apache/spark/sql/hive/execution/HiveQuerySuite.scala | 9 +++++++++ 3 files changed, 14 insertions(+), 2 deletions(-) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/AttributeSet.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/AttributeSet.scala index 2b4969b7cfec0..171845ad14e3e 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/AttributeSet.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/AttributeSet.scala @@ -112,4 +112,6 @@ class AttributeSet private (val baseSet: Set[AttributeEquals]) override def toSeq: Seq[Attribute] = baseSet.map(_.a).toArray.toSeq override def toString = "{" + baseSet.map(_.a).mkString(", ") + "}" + + override def isEmpty: Boolean = baseSet.isEmpty } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala index 5f02e95ac3c34..4ebd59db83515 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala @@ -210,8 +210,9 @@ private[hive] trait HiveStrategies { // Filter out all predicates that only deal with partition keys, these are given to the // hive table scan operator to be used for partition pruning. val partitionKeyIds = AttributeSet(relation.partitionKeys) - val (pruningPredicates, otherPredicates) = predicates.partition { - _.references.subsetOf(partitionKeyIds) + val (pruningPredicates, otherPredicates) = predicates.partition { predicate => + !predicate.references.isEmpty && + predicate.references.subsetOf(partitionKeyIds) } pruneFilterProject( diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala index 63eb07c257501..4d81acc753a27 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala @@ -411,6 +411,15 @@ class HiveQuerySuite extends HiveComparisonTest with BeforeAndAfter { createQueryTest("select null from table", "SELECT null FROM src LIMIT 1") + test("predicates contains an empty AttributeSet() references") { + sql( + """ + |SELECT a FROM ( + | SELECT 1 AS a FROM src LIMIT 1 ) table + |WHERE abs(20141202) is not null + """.stripMargin).collect() + } + test("implement identity function using case statement") { val actual = sql("SELECT (CASE key WHEN key THEN key END) FROM src") .map { case Row(i: Int) => i } From 7687415c2578b5bdc79c9646c246e52da9a4dd4a Mon Sep 17 00:00:00 2001 From: ravipesala Date: Thu, 18 Dec 2014 20:19:10 -0800 Subject: [PATCH 050/320] [SPARK-2554][SQL] Supporting SumDistinct partial aggregation Adding support to the partial aggregation of SumDistinct Author: ravipesala Closes #3348 from ravipesala/SPARK-2554 and squashes the following commits: fd28e4d [ravipesala] Fixed review comments e60e67f [ravipesala] Fixed test cases and made it as nullable 32fe234 [ravipesala] Supporting SumDistinct partial aggregation Conflicts: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala --- .../sql/catalyst/expressions/aggregates.scala | 53 +++++++++++++++++-- .../sql/hive/execution/SQLQuerySuite.scala | 13 +++-- 2 files changed, 58 insertions(+), 8 deletions(-) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala index 0cd90866e14a2..5ea9868e9e846 100755 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala @@ -361,10 +361,10 @@ case class Sum(child: Expression) extends PartialAggregate with trees.UnaryNode[ } case class SumDistinct(child: Expression) - extends AggregateExpression with trees.UnaryNode[Expression] { + extends PartialAggregate with trees.UnaryNode[Expression] { + def this() = this(null) override def nullable = true - override def dataType = child.dataType match { case DecimalType.Fixed(precision, scale) => DecimalType(precision + 10, scale) // Add 10 digits left of decimal point, like Hive @@ -373,10 +373,55 @@ case class SumDistinct(child: Expression) case _ => child.dataType } + override def toString = s"SUM(DISTINCT ${child})" + override def newInstance() = new SumDistinctFunction(child, this) + + override def asPartial = { + val partialSet = Alias(CollectHashSet(child :: Nil), "partialSets")() + SplitEvaluation( + CombineSetsAndSum(partialSet.toAttribute, this), + partialSet :: Nil) + } +} - override def toString = s"SUM(DISTINCT $child)" +case class CombineSetsAndSum(inputSet: Expression, base: Expression) extends AggregateExpression { + def this() = this(null, null) - override def newInstance() = new SumDistinctFunction(child, this) + override def children = inputSet :: Nil + override def nullable = true + override def dataType = base.dataType + override def toString = s"CombineAndSum($inputSet)" + override def newInstance() = new CombineSetsAndSumFunction(inputSet, this) +} + +case class CombineSetsAndSumFunction( + @transient inputSet: Expression, + @transient base: AggregateExpression) + extends AggregateFunction { + + def this() = this(null, null) // Required for serialization. + + val seen = new OpenHashSet[Any]() + + override def update(input: Row): Unit = { + val inputSetEval = inputSet.eval(input).asInstanceOf[OpenHashSet[Any]] + val inputIterator = inputSetEval.iterator + while (inputIterator.hasNext) { + seen.add(inputIterator.next) + } + } + + override def eval(input: Row): Any = { + val casted = seen.asInstanceOf[OpenHashSet[Row]] + if (casted.size == 0) { + null + } else { + Cast(Literal( + casted.iterator.map(f => f.apply(0)).reduceLeft( + base.dataType.asInstanceOf[NumericType].numeric.asInstanceOf[Numeric[Any]].plus)), + base.dataType).eval(null) + } + } } case class First(child: Expression) extends PartialAggregate with trees.UnaryNode[Expression] { diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala index 96f3430207982..f57f31af15566 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala @@ -185,9 +185,14 @@ class SQLQuerySuite extends QueryTest { sql("SELECT case when ~1=-2 then 1 else 0 end FROM src"), sql("SELECT 1 FROM src").collect().toSeq) } - - test("SPARK-4154 Query does not work if it has 'not between' in Spark SQL and HQL") { - checkAnswer(sql("SELECT key FROM src WHERE key not between 0 and 10 order by key"), - sql("SELECT key FROM src WHERE key between 11 and 500 order by key").collect().toSeq) + + test("SPARK-4154 Query does not work if it has 'not between' in Spark SQL and HQL") { + checkAnswer(sql("SELECT key FROM src WHERE key not between 0 and 10 order by key"), + sql("SELECT key FROM src WHERE key between 11 and 500 order by key").collect().toSeq) + } + + test("SPARK-2554 SumDistinct partial aggregation") { + checkAnswer(sql("SELECT sum( distinct key) FROM src group by key order by key"), + sql("SELECT distinct key FROM src order by key").collect().toSeq) } } From ae9f128608f67cbee0a2fb24754783ee3b4f3098 Mon Sep 17 00:00:00 2001 From: Cheng Hao Date: Thu, 18 Dec 2014 20:21:52 -0800 Subject: [PATCH 051/320] [SPARK-4573] [SQL] Add SettableStructObjectInspector support in "wrap" function Hive UDAF may create an customized object constructed by SettableStructObjectInspector, this is critical when integrate Hive UDAF with the refactor-ed UDAF interface. Performance issue in `wrap/unwrap` since more match cases added, will do it in another PR. Author: Cheng Hao Closes #3429 from chenghao-intel/settable_oi and squashes the following commits: 9f0aff3 [Cheng Hao] update code style issues as feedbacks 2b0561d [Cheng Hao] Add more scala doc f5a40e8 [Cheng Hao] add scala doc 2977e9b [Cheng Hao] remove the timezone setting for test suite 3ed284c [Cheng Hao] fix the date type comparison f1b6749 [Cheng Hao] Update the comment 932940d [Cheng Hao] Add more unit test 72e4332 [Cheng Hao] Add settable StructObjectInspector support --- .../spark/sql/hive/HiveInspectors.scala | 346 +++++++++++++++--- .../spark/sql/hive/HiveInspectorSuite.scala | 220 +++++++++++ .../org/apache/spark/sql/hive/Shim12.scala | 87 +++-- .../org/apache/spark/sql/hive/Shim13.scala | 130 ++++--- 4 files changed, 659 insertions(+), 124 deletions(-) create mode 100644 sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala index 0eeac8620f01c..06189341f827c 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala @@ -18,9 +18,7 @@ package org.apache.spark.sql.hive import org.apache.hadoop.hive.common.`type`.{HiveDecimal, HiveVarchar} -import org.apache.hadoop.hive.serde2.typeinfo.TypeInfoFactory import org.apache.hadoop.hive.serde2.objectinspector._ -import org.apache.hadoop.hive.serde2.objectinspector.PrimitiveObjectInspector._ import org.apache.hadoop.hive.serde2.objectinspector.primitive._ import org.apache.hadoop.hive.serde2.{io => hiveIo} import org.apache.hadoop.{io => hadoopIo} @@ -33,6 +31,145 @@ import org.apache.spark.sql.catalyst.types.decimal.Decimal /* Implicit conversions */ import scala.collection.JavaConversions._ +/** + * 1. The Underlying data type in catalyst and in Hive + * In catalyst: + * Primitive => + * java.lang.String + * int / scala.Int + * boolean / scala.Boolean + * float / scala.Float + * double / scala.Double + * long / scala.Long + * short / scala.Short + * byte / scala.Byte + * org.apache.spark.sql.catalyst.types.decimal.Decimal + * Array[Byte] + * java.sql.Date + * java.sql.Timestamp + * Complex Types => + * Map: scala.collection.immutable.Map + * List: scala.collection.immutable.Seq + * Struct: + * org.apache.spark.sql.catalyst.expression.Row + * Union: NOT SUPPORTED YET + * The Complex types plays as a container, which can hold arbitrary data types. + * + * In Hive, the native data types are various, in UDF/UDAF/UDTF, and associated with + * Object Inspectors, in Hive expression evaluation framework, the underlying data are + * Primitive Type + * Java Boxed Primitives: + * org.apache.hadoop.hive.common.type.HiveVarchar + * java.lang.String + * java.lang.Integer + * java.lang.Boolean + * java.lang.Float + * java.lang.Double + * java.lang.Long + * java.lang.Short + * java.lang.Byte + * org.apache.hadoop.hive.common.`type`.HiveDecimal + * byte[] + * java.sql.Date + * java.sql.Timestamp + * Writables: + * org.apache.hadoop.hive.serde2.io.HiveVarcharWritable + * org.apache.hadoop.io.Text + * org.apache.hadoop.io.IntWritable + * org.apache.hadoop.hive.serde2.io.DoubleWritable + * org.apache.hadoop.io.BooleanWritable + * org.apache.hadoop.io.LongWritable + * org.apache.hadoop.io.FloatWritable + * org.apache.hadoop.hive.serde2.io.ShortWritable + * org.apache.hadoop.hive.serde2.io.ByteWritable + * org.apache.hadoop.io.BytesWritable + * org.apache.hadoop.hive.serde2.io.DateWritable + * org.apache.hadoop.hive.serde2.io.TimestampWritable + * org.apache.hadoop.hive.serde2.io.HiveDecimalWritable + * Complex Type + * List: Object[] / java.util.List + * Map: java.util.Map + * Struct: Object[] / java.util.List / java POJO + * Union: class StandardUnion { byte tag; Object object } + * + * NOTICE: HiveVarchar is not supported by catalyst, it will be simply considered as String type. + * + * + * 2. Hive ObjectInspector is a group of flexible APIs to inspect value in different data + * representation, and developers can extend those API as needed, so technically, + * object inspector supports arbitrary data type in java. + * + * Fortunately, only few built-in Hive Object Inspectors are used in generic udf/udaf/udtf + * evaluation. + * 1) Primitive Types (PrimitiveObjectInspector & its sub classes) + {{{ + public interface PrimitiveObjectInspector { + // Java Primitives (java.lang.Integer, java.lang.String etc.) + Object getPrimitiveWritableObject(Object o); + // Writables (hadoop.io.IntWritable, hadoop.io.Text etc.) + Object getPrimitiveJavaObject(Object o); + // ObjectInspector only inspect the `writable` always return true, we need to check it + // before invoking the methods above. + boolean preferWritable(); + ... + } + }}} + + * 2) Complex Types: + * ListObjectInspector: inspects java array or [[java.util.List]] + * MapObjectInspector: inspects [[java.util.Map]] + * Struct.StructObjectInspector: inspects java array, [[java.util.List]] and + * even a normal java object (POJO) + * UnionObjectInspector: (tag: Int, object data) (TODO: not supported by SparkSQL yet) + * + * 3) ConstantObjectInspector: + * Constant object inspector can be either primitive type or Complex type, and it bundles a + * constant value as its property, usually the value is created when the constant object inspector + * constructed. + * {{{ + public interface ConstantObjectInspector extends ObjectInspector { + Object getWritableConstantValue(); + ... + } + }}} + * Hive provides 3 built-in constant object inspectors: + * Primitive Object Inspectors: + * WritableConstantStringObjectInspector + * WritableConstantHiveVarcharObjectInspector + * WritableConstantHiveDecimalObjectInspector + * WritableConstantTimestampObjectInspector + * WritableConstantIntObjectInspector + * WritableConstantDoubleObjectInspector + * WritableConstantBooleanObjectInspector + * WritableConstantLongObjectInspector + * WritableConstantFloatObjectInspector + * WritableConstantShortObjectInspector + * WritableConstantByteObjectInspector + * WritableConstantBinaryObjectInspector + * WritableConstantDateObjectInspector + * Map Object Inspector: + * StandardConstantMapObjectInspector + * List Object Inspector: + * StandardConstantListObjectInspector]] + * Struct Object Inspector: Hive doesn't provide the built-in constant object inspector for Struct + * Union Object Inspector: Hive doesn't provide the built-in constant object inspector for Union + * + * + * 3. This trait facilitates: + * Data Unwrapping: Hive Data => Catalyst Data (unwrap) + * Data Wrapping: Catalyst Data => Hive Data (wrap) + * Binding the Object Inspector for Catalyst Data (toInspector) + * Retrieving the Catalyst Data Type from Object Inspector (inspectorToDataType) + * + * + * 4. Future Improvement (TODO) + * This implementation is quite ugly and inefficient: + * a. Pattern matching in runtime + * b. Small objects creation in catalyst data => writable + * c. Unnecessary unwrap / wrap for nested UDF invoking: + * e.g. date_add(printf("%s-%s-%s", a,b,c), 3) + * We don't need to unwrap the data for printf and wrap it again and passes in data_add + */ private[hive] trait HiveInspectors { def javaClassToDataType(clz: Class[_]): DataType = clz match { @@ -87,10 +224,23 @@ private[hive] trait HiveInspectors { * @param oi the ObjectInspector associated with the Hive Type * @return convert the data into catalyst type * TODO return the function of (data => Any) instead for performance consideration + * + * Strictly follows the following order in unwrapping (constant OI has the higher priority): + * Constant Null object inspector => + * return null + * Constant object inspector => + * extract the value from constant object inspector + * Check whether the `data` is null => + * return null if true + * If object inspector prefers writable => + * extract writable from `data` and then get the catalyst type from the writable + * Extract the java object directly from the object inspector + * + * NOTICE: the complex data type requires recursive unwrapping. */ def unwrap(data: Any, oi: ObjectInspector): Any = oi match { - case _ if data == null => null - case poi: VoidObjectInspector => null + case coi: ConstantObjectInspector if coi.getWritableConstantValue == null => null + case poi: WritableConstantStringObjectInspector => poi.getWritableConstantValue.toString case poi: WritableConstantHiveVarcharObjectInspector => poi.getWritableConstantValue.getHiveVarchar.getValue case poi: WritableConstantHiveDecimalObjectInspector => @@ -119,12 +269,44 @@ private[hive] trait HiveInspectors { System.arraycopy(writable.getBytes, 0, temp, 0, temp.length) temp case poi: WritableConstantDateObjectInspector => poi.getWritableConstantValue.get() - case hvoi: HiveVarcharObjectInspector => hvoi.getPrimitiveJavaObject(data).getValue - case hdoi: HiveDecimalObjectInspector => HiveShim.toCatalystDecimal(hdoi, data) - // org.apache.hadoop.hive.serde2.io.TimestampWritable.set will reset current time object - // if next timestamp is null, so Timestamp object is cloned - case ti: TimestampObjectInspector => ti.getPrimitiveJavaObject(data).clone() - case pi: PrimitiveObjectInspector => pi.getPrimitiveJavaObject(data) + case mi: StandardConstantMapObjectInspector => + // take the value from the map inspector object, rather than the input data + mi.getWritableConstantValue.map { case (k, v) => + (unwrap(k, mi.getMapKeyObjectInspector), + unwrap(v, mi.getMapValueObjectInspector)) + }.toMap + case li: StandardConstantListObjectInspector => + // take the value from the list inspector object, rather than the input data + li.getWritableConstantValue.map(unwrap(_, li.getListElementObjectInspector)).toSeq + // if the value is null, we don't care about the object inspector type + case _ if data == null => null + case poi: VoidObjectInspector => null // always be null for void object inspector + case pi: PrimitiveObjectInspector => pi match { + // We think HiveVarchar is also a String + case hvoi: HiveVarcharObjectInspector if hvoi.preferWritable() => + hvoi.getPrimitiveWritableObject(data).getHiveVarchar.getValue + case hvoi: HiveVarcharObjectInspector => hvoi.getPrimitiveJavaObject(data).getValue + case x: StringObjectInspector if x.preferWritable() => + x.getPrimitiveWritableObject(data).toString + case x: IntObjectInspector if x.preferWritable() => x.get(data) + case x: BooleanObjectInspector if x.preferWritable() => x.get(data) + case x: FloatObjectInspector if x.preferWritable() => x.get(data) + case x: DoubleObjectInspector if x.preferWritable() => x.get(data) + case x: LongObjectInspector if x.preferWritable() => x.get(data) + case x: ShortObjectInspector if x.preferWritable() => x.get(data) + case x: ByteObjectInspector if x.preferWritable() => x.get(data) + case x: HiveDecimalObjectInspector => HiveShim.toCatalystDecimal(x, data) + case x: BinaryObjectInspector if x.preferWritable() => + x.getPrimitiveWritableObject(data).copyBytes() + case x: DateObjectInspector if x.preferWritable() => + x.getPrimitiveWritableObject(data).get() + // org.apache.hadoop.hive.serde2.io.TimestampWritable.set will reset current time object + // if next timestamp is null, so Timestamp object is cloned + case x: TimestampObjectInspector if x.preferWritable() => + x.getPrimitiveWritableObject(data).getTimestamp.clone() + case ti: TimestampObjectInspector => ti.getPrimitiveJavaObject(data).clone() + case _ => pi.getPrimitiveJavaObject(data) + } case li: ListObjectInspector => Option(li.getList(data)) .map(_.map(unwrap(_, li.getListElementObjectInspector)).toSeq) @@ -132,10 +314,11 @@ private[hive] trait HiveInspectors { case mi: MapObjectInspector => Option(mi.getMap(data)).map( _.map { - case (k,v) => + case (k, v) => (unwrap(k, mi.getMapKeyObjectInspector), unwrap(v, mi.getMapValueObjectInspector)) }.toMap).orNull + // currently, hive doesn't provide the ConstantStructObjectInspector case si: StructObjectInspector => val allRefs = si.getAllStructFieldRefs new GenericRow( @@ -191,55 +374,89 @@ private[hive] trait HiveInspectors { * the ObjectInspector should also be consistent with those returned from * toInspector: DataType => ObjectInspector and * toInspector: Expression => ObjectInspector + * + * Strictly follows the following order in wrapping (constant OI has the higher priority): + * Constant object inspector => return the bundled value of Constant object inspector + * Check whether the `a` is null => return null if true + * If object inspector prefers writable object => return a Writable for the given data `a` + * Map the catalyst data to the boxed java primitive + * + * NOTICE: the complex data type requires recursive wrapping. */ - def wrap(a: Any, oi: ObjectInspector): AnyRef = if (a == null) { - null - } else { - oi match { - case x: ConstantObjectInspector => x.getWritableConstantValue - case x: PrimitiveObjectInspector => a match { - // TODO what if x.preferWritable() == true? reuse the writable? - case s: String => s: java.lang.String - case i: Int => i: java.lang.Integer - case b: Boolean => b: java.lang.Boolean - case f: Float => f: java.lang.Float - case d: Double => d: java.lang.Double - case l: Long => l: java.lang.Long - case l: Short => l: java.lang.Short - case l: Byte => l: java.lang.Byte - case b: BigDecimal => HiveShim.createDecimal(b.underlying()) - case d: Decimal => HiveShim.createDecimal(d.toBigDecimal.underlying()) - case b: Array[Byte] => b - case d: java.sql.Date => d - case t: java.sql.Timestamp => t + def wrap(a: Any, oi: ObjectInspector): AnyRef = oi match { + case x: ConstantObjectInspector => x.getWritableConstantValue + case _ if a == null => null + case x: PrimitiveObjectInspector => x match { + // TODO we don't support the HiveVarcharObjectInspector yet. + case _: StringObjectInspector if x.preferWritable() => HiveShim.getStringWritable(a) + case _: StringObjectInspector => a.asInstanceOf[java.lang.String] + case _: IntObjectInspector if x.preferWritable() => HiveShim.getIntWritable(a) + case _: IntObjectInspector => a.asInstanceOf[java.lang.Integer] + case _: BooleanObjectInspector if x.preferWritable() => HiveShim.getBooleanWritable(a) + case _: BooleanObjectInspector => a.asInstanceOf[java.lang.Boolean] + case _: FloatObjectInspector if x.preferWritable() => HiveShim.getFloatWritable(a) + case _: FloatObjectInspector => a.asInstanceOf[java.lang.Float] + case _: DoubleObjectInspector if x.preferWritable() => HiveShim.getDoubleWritable(a) + case _: DoubleObjectInspector => a.asInstanceOf[java.lang.Double] + case _: LongObjectInspector if x.preferWritable() => HiveShim.getLongWritable(a) + case _: LongObjectInspector => a.asInstanceOf[java.lang.Long] + case _: ShortObjectInspector if x.preferWritable() => HiveShim.getShortWritable(a) + case _: ShortObjectInspector => a.asInstanceOf[java.lang.Short] + case _: ByteObjectInspector if x.preferWritable() => HiveShim.getByteWritable(a) + case _: ByteObjectInspector => a.asInstanceOf[java.lang.Byte] + case _: HiveDecimalObjectInspector if x.preferWritable() => + HiveShim.getDecimalWritable(a.asInstanceOf[Decimal]) + case _: HiveDecimalObjectInspector => + HiveShim.createDecimal(a.asInstanceOf[Decimal].toBigDecimal.underlying()) + case _: BinaryObjectInspector if x.preferWritable() => HiveShim.getBinaryWritable(a) + case _: BinaryObjectInspector => a.asInstanceOf[Array[Byte]] + case _: DateObjectInspector if x.preferWritable() => HiveShim.getDateWritable(a) + case _: DateObjectInspector => a.asInstanceOf[java.sql.Date] + case _: TimestampObjectInspector if x.preferWritable() => HiveShim.getTimestampWritable(a) + case _: TimestampObjectInspector => a.asInstanceOf[java.sql.Timestamp] + } + case x: SettableStructObjectInspector => + val fieldRefs = x.getAllStructFieldRefs + val row = a.asInstanceOf[Seq[_]] + // 1. create the pojo (most likely) object + val result = x.create() + var i = 0 + while (i < fieldRefs.length) { + // 2. set the property for the pojo + x.setStructFieldData( + result, + fieldRefs.get(i), + wrap(row(i), fieldRefs.get(i).getFieldObjectInspector)) + i += 1 } - case x: StructObjectInspector => - val fieldRefs = x.getAllStructFieldRefs - val row = a.asInstanceOf[Seq[_]] - val result = new java.util.ArrayList[AnyRef](fieldRefs.length) - var i = 0 - while (i < fieldRefs.length) { - result.add(wrap(row(i), fieldRefs.get(i).getFieldObjectInspector)) - i += 1 - } - result - case x: ListObjectInspector => - val list = new java.util.ArrayList[Object] - a.asInstanceOf[Seq[_]].foreach { - v => list.add(wrap(v, x.getListElementObjectInspector)) - } - list - case x: MapObjectInspector => - // Some UDFs seem to assume we pass in a HashMap. - val hashMap = new java.util.HashMap[AnyRef, AnyRef]() - hashMap.putAll(a.asInstanceOf[Map[_, _]].map { - case (k, v) => - wrap(k, x.getMapKeyObjectInspector) -> wrap(v, x.getMapValueObjectInspector) - }) + result + case x: StructObjectInspector => + val fieldRefs = x.getAllStructFieldRefs + val row = a.asInstanceOf[Seq[_]] + val result = new java.util.ArrayList[AnyRef](fieldRefs.length) + var i = 0 + while (i < fieldRefs.length) { + result.add(wrap(row(i), fieldRefs.get(i).getFieldObjectInspector)) + i += 1 + } - hashMap - } + result + case x: ListObjectInspector => + val list = new java.util.ArrayList[Object] + a.asInstanceOf[Seq[_]].foreach { + v => list.add(wrap(v, x.getListElementObjectInspector)) + } + list + case x: MapObjectInspector => + // Some UDFs seem to assume we pass in a HashMap. + val hashMap = new java.util.HashMap[AnyRef, AnyRef]() + hashMap.putAll(a.asInstanceOf[Map[_, _]].map { + case (k, v) => + wrap(k, x.getMapKeyObjectInspector) -> wrap(v, x.getMapValueObjectInspector) + }) + + hashMap } def wrap( @@ -254,6 +471,11 @@ private[hive] trait HiveInspectors { cache } + /** + * @param dataType Catalyst data type + * @return Hive java object inspector (recursively), not the Writable ObjectInspector + * We can easily map to the Hive built-in object inspector according to the data type. + */ def toInspector(dataType: DataType): ObjectInspector = dataType match { case ArrayType(tpe, _) => ObjectInspectorFactory.getStandardListObjectInspector(toInspector(tpe)) @@ -272,12 +494,20 @@ private[hive] trait HiveInspectors { case BinaryType => PrimitiveObjectInspectorFactory.javaByteArrayObjectInspector case DateType => PrimitiveObjectInspectorFactory.javaDateObjectInspector case TimestampType => PrimitiveObjectInspectorFactory.javaTimestampObjectInspector + // TODO decimal precision? case DecimalType() => PrimitiveObjectInspectorFactory.javaHiveDecimalObjectInspector case StructType(fields) => ObjectInspectorFactory.getStandardStructObjectInspector( fields.map(f => f.name), fields.map(f => toInspector(f.dataType))) } + /** + * Map the catalyst expression to ObjectInspector, however, + * if the expression is [[Literal]] or foldable, a constant writable object inspector returns; + * Otherwise, we always get the object inspector according to its data type(in catalyst) + * @param expr Catalyst expression to be mapped + * @return Hive java objectinspector (recursively). + */ def toInspector(expr: Expression): ObjectInspector = expr match { case Literal(value, StringType) => HiveShim.getStringWritableConstantObjectInspector(value) @@ -326,8 +556,12 @@ private[hive] trait HiveInspectors { }) ObjectInspectorFactory.getStandardConstantMapObjectInspector(keyOI, valueOI, map) } + // We will enumerate all of the possible constant expressions, throw exception if we missed case Literal(_, dt) => sys.error(s"Hive doesn't support the constant type [$dt].") + // ideally, we don't test the foldable here(but in optimizer), however, some of the + // Hive UDF / UDAF requires its argument to be constant objectinspector, we do it eagerly. case _ if expr.foldable => toInspector(Literal(expr.eval(), expr.dataType)) + // For those non constant expression, map to object inspector according to its data type case _ => toInspector(expr.dataType) } diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala new file mode 100644 index 0000000000000..bfe608a51a30b --- /dev/null +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala @@ -0,0 +1,220 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.hive + +import java.sql.Date +import java.util + +import org.apache.hadoop.hive.serde2.io.DoubleWritable +import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory +import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.catalyst.types.decimal.Decimal +import org.scalatest.FunSuite + +import org.apache.hadoop.hive.ql.udf.UDAFPercentile +import org.apache.hadoop.hive.serde2.objectinspector.{ObjectInspector, StructObjectInspector, ObjectInspectorFactory} +import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory.ObjectInspectorOptions +import org.apache.hadoop.io.LongWritable + +import org.apache.spark.sql.catalyst.expressions.{Literal, Row} + +class HiveInspectorSuite extends FunSuite with HiveInspectors { + test("Test wrap SettableStructObjectInspector") { + val udaf = new UDAFPercentile.PercentileLongEvaluator() + udaf.init() + + udaf.iterate(new LongWritable(1), 0.1) + udaf.iterate(new LongWritable(1), 0.1) + + val state = udaf.terminatePartial() + + val soi = ObjectInspectorFactory.getReflectionObjectInspector( + classOf[UDAFPercentile.State], + ObjectInspectorOptions.JAVA).asInstanceOf[StructObjectInspector] + + val a = unwrap(state, soi).asInstanceOf[Row] + val b = wrap(a, soi).asInstanceOf[UDAFPercentile.State] + + val sfCounts = soi.getStructFieldRef("counts") + val sfPercentiles = soi.getStructFieldRef("percentiles") + + assert(2 === soi.getStructFieldData(b, sfCounts) + .asInstanceOf[util.Map[LongWritable, LongWritable]] + .get(new LongWritable(1L)) + .get()) + assert(0.1 === soi.getStructFieldData(b, sfPercentiles) + .asInstanceOf[util.ArrayList[DoubleWritable]] + .get(0) + .get()) + } + + val data = + Literal(true) :: + Literal(0.asInstanceOf[Byte]) :: + Literal(0.asInstanceOf[Short]) :: + Literal(0) :: + Literal(0.asInstanceOf[Long]) :: + Literal(0.asInstanceOf[Float]) :: + Literal(0.asInstanceOf[Double]) :: + Literal("0") :: + Literal(new Date(2014, 9, 23)) :: + Literal(Decimal(BigDecimal(123.123))) :: + Literal(new java.sql.Timestamp(123123)) :: + Literal(Array[Byte](1,2,3)) :: + Literal(Seq[Int](1,2,3), ArrayType(IntegerType)) :: + Literal(Map[Int, Int](1->2, 2->1), MapType(IntegerType, IntegerType)) :: + Literal(Row(1,2.0d,3.0f), + StructType(StructField("c1", IntegerType) :: + StructField("c2", DoubleType) :: + StructField("c3", FloatType) :: Nil)) :: + Nil + + val row = data.map(_.eval(null)) + val dataTypes = data.map(_.dataType) + + import scala.collection.JavaConversions._ + def toWritableInspector(dataType: DataType): ObjectInspector = dataType match { + case ArrayType(tpe, _) => + ObjectInspectorFactory.getStandardListObjectInspector(toWritableInspector(tpe)) + case MapType(keyType, valueType, _) => + ObjectInspectorFactory.getStandardMapObjectInspector( + toWritableInspector(keyType), toWritableInspector(valueType)) + case StringType => PrimitiveObjectInspectorFactory.writableStringObjectInspector + case IntegerType => PrimitiveObjectInspectorFactory.writableIntObjectInspector + case DoubleType => PrimitiveObjectInspectorFactory.writableDoubleObjectInspector + case BooleanType => PrimitiveObjectInspectorFactory.writableBooleanObjectInspector + case LongType => PrimitiveObjectInspectorFactory.writableLongObjectInspector + case FloatType => PrimitiveObjectInspectorFactory.writableFloatObjectInspector + case ShortType => PrimitiveObjectInspectorFactory.writableShortObjectInspector + case ByteType => PrimitiveObjectInspectorFactory.writableByteObjectInspector + case NullType => PrimitiveObjectInspectorFactory.writableVoidObjectInspector + case BinaryType => PrimitiveObjectInspectorFactory.writableBinaryObjectInspector + case DateType => PrimitiveObjectInspectorFactory.writableDateObjectInspector + case TimestampType => PrimitiveObjectInspectorFactory.writableTimestampObjectInspector + case DecimalType() => PrimitiveObjectInspectorFactory.writableHiveDecimalObjectInspector + case StructType(fields) => + ObjectInspectorFactory.getStandardStructObjectInspector( + fields.map(f => f.name), fields.map(f => toWritableInspector(f.dataType))) + } + + def checkDataType(dt1: Seq[DataType], dt2: Seq[DataType]): Unit = { + dt1.zip(dt2).map { + case (dd1, dd2) => + assert(dd1.getClass === dd2.getClass) // DecimalType doesn't has the default precision info + } + } + + def checkValues(row1: Seq[Any], row2: Seq[Any]): Unit = { + row1.zip(row2).map { + case (r1, r2) => checkValues(r1, r2) + } + } + + def checkValues(v1: Any, v2: Any): Unit = { + (v1, v2) match { + case (r1: Decimal, r2: Decimal) => + // Ignore the Decimal precision + assert(r1.compare(r2) === 0) + case (r1: Array[Byte], r2: Array[Byte]) + if r1 != null && r2 != null && r1.length == r2.length => + r1.zip(r2).map { case (b1, b2) => assert(b1 === b2) } + case (r1: Date, r2: Date) => assert(r1.compareTo(r2) === 0) + case (r1, r2) => assert(r1 === r2) + } + } + + test("oi => datatype => oi") { + val ois = dataTypes.map(toInspector) + + checkDataType(ois.map(inspectorToDataType), dataTypes) + checkDataType(dataTypes.map(toWritableInspector).map(inspectorToDataType), dataTypes) + } + + test("wrap / unwrap null, constant null and writables") { + val writableOIs = dataTypes.map(toWritableInspector) + val nullRow = data.map(d => null) + + checkValues(nullRow, nullRow.zip(writableOIs).map { + case (d, oi) => unwrap(wrap(d, oi), oi) + }) + + // struct couldn't be constant, sweep it out + val constantExprs = data.filter(!_.dataType.isInstanceOf[StructType]) + val constantData = constantExprs.map(_.eval()) + val constantNullData = constantData.map(_ => null) + val constantWritableOIs = constantExprs.map(e => toWritableInspector(e.dataType)) + val constantNullWritableOIs = constantExprs.map(e => toInspector(Literal(null, e.dataType))) + + checkValues(constantData, constantData.zip(constantWritableOIs).map { + case (d, oi) => unwrap(wrap(d, oi), oi) + }) + + checkValues(constantNullData, constantData.zip(constantNullWritableOIs).map { + case (d, oi) => unwrap(wrap(d, oi), oi) + }) + + checkValues(constantNullData, constantNullData.zip(constantWritableOIs).map { + case (d, oi) => unwrap(wrap(d, oi), oi) + }) + } + + test("wrap / unwrap primitive writable object inspector") { + val writableOIs = dataTypes.map(toWritableInspector) + + checkValues(row, row.zip(writableOIs).map { + case (data, oi) => unwrap(wrap(data, oi), oi) + }) + } + + test("wrap / unwrap primitive java object inspector") { + val ois = dataTypes.map(toInspector) + + checkValues(row, row.zip(ois).map { + case (data, oi) => unwrap(wrap(data, oi), oi) + }) + } + + test("wrap / unwrap Struct Type") { + val dt = StructType(dataTypes.zipWithIndex.map { + case (t, idx) => StructField(s"c_$idx", t) + }) + + checkValues(row, unwrap(wrap(row, toInspector(dt)), toInspector(dt)).asInstanceOf[Row]) + checkValues(null, unwrap(wrap(null, toInspector(dt)), toInspector(dt))) + } + + test("wrap / unwrap Array Type") { + val dt = ArrayType(dataTypes(0)) + + val d = row(0) :: row(0) :: Nil + checkValues(d, unwrap(wrap(d, toInspector(dt)), toInspector(dt))) + checkValues(null, unwrap(wrap(null, toInspector(dt)), toInspector(dt))) + checkValues(d, unwrap(wrap(d, toInspector(Literal(d, dt))), toInspector(Literal(d, dt)))) + checkValues(d, unwrap(wrap(null, toInspector(Literal(d, dt))), toInspector(Literal(d, dt)))) + } + + test("wrap / unwrap Map Type") { + val dt = MapType(dataTypes(0), dataTypes(1)) + + val d = Map(row(0) -> row(1)) + checkValues(d, unwrap(wrap(d, toInspector(dt)), toInspector(dt))) + checkValues(null, unwrap(wrap(null, toInspector(dt)), toInspector(dt))) + checkValues(d, unwrap(wrap(d, toInspector(Literal(d, dt))), toInspector(Literal(d, dt)))) + checkValues(d, unwrap(wrap(null, toInspector(Literal(d, dt))), toInspector(Literal(d, dt)))) + } +} diff --git a/sql/hive/v0.12.0/src/main/scala/org/apache/spark/sql/hive/Shim12.scala b/sql/hive/v0.12.0/src/main/scala/org/apache/spark/sql/hive/Shim12.scala index 67cc8865755c5..2d01a85067518 100644 --- a/sql/hive/v0.12.0/src/main/scala/org/apache/spark/sql/hive/Shim12.scala +++ b/sql/hive/v0.12.0/src/main/scala/org/apache/spark/sql/hive/Shim12.scala @@ -35,6 +35,7 @@ import org.apache.hadoop.hive.serde2.objectinspector.{PrimitiveObjectInspector, import org.apache.hadoop.hive.serde2.typeinfo.{TypeInfo, TypeInfoFactory} import org.apache.hadoop.hive.serde2.{Deserializer, ColumnProjectionUtils} import org.apache.hadoop.hive.serde2.{io => hiveIo} +import org.apache.hadoop.io.NullWritable import org.apache.hadoop.{io => hadoopIo} import org.apache.hadoop.mapred.InputFormat import org.apache.spark.sql.catalyst.types.decimal.Decimal @@ -71,76 +72,114 @@ private[hive] object HiveShim { def getStringWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( PrimitiveCategory.STRING, - if (value == null) null else new hadoopIo.Text(value.asInstanceOf[String])) + getStringWritable(value)) def getIntWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( PrimitiveCategory.INT, - if (value == null) null else new hadoopIo.IntWritable(value.asInstanceOf[Int])) + getIntWritable(value)) def getDoubleWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( PrimitiveCategory.DOUBLE, - if (value == null) null else new hiveIo.DoubleWritable(value.asInstanceOf[Double])) + getDoubleWritable(value)) def getBooleanWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( PrimitiveCategory.BOOLEAN, - if (value == null) null else new hadoopIo.BooleanWritable(value.asInstanceOf[Boolean])) + getBooleanWritable(value)) def getLongWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( PrimitiveCategory.LONG, - if (value == null) null else new hadoopIo.LongWritable(value.asInstanceOf[Long])) + getLongWritable(value)) def getFloatWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( PrimitiveCategory.FLOAT, - if (value == null) null else new hadoopIo.FloatWritable(value.asInstanceOf[Float])) + getFloatWritable(value)) def getShortWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( PrimitiveCategory.SHORT, - if (value == null) null else new hiveIo.ShortWritable(value.asInstanceOf[Short])) + getShortWritable(value)) def getByteWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( PrimitiveCategory.BYTE, - if (value == null) null else new hiveIo.ByteWritable(value.asInstanceOf[Byte])) + getByteWritable(value)) def getBinaryWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( PrimitiveCategory.BINARY, - if (value == null) null else new hadoopIo.BytesWritable(value.asInstanceOf[Array[Byte]])) + getBinaryWritable(value)) def getDateWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( PrimitiveCategory.DATE, - if (value == null) null else new hiveIo.DateWritable(value.asInstanceOf[java.sql.Date])) + getDateWritable(value)) def getTimestampWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( PrimitiveCategory.TIMESTAMP, - if (value == null) { - null - } else { - new hiveIo.TimestampWritable(value.asInstanceOf[java.sql.Timestamp]) - }) + getTimestampWritable(value)) def getDecimalWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( PrimitiveCategory.DECIMAL, - if (value == null) { - null - } else { - new hiveIo.HiveDecimalWritable( - HiveShim.createDecimal(value.asInstanceOf[Decimal].toBigDecimal.underlying())) - }) + getDecimalWritable(value)) def getPrimitiveNullWritableConstantObjectInspector: ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( PrimitiveCategory.VOID, null) + def getStringWritable(value: Any): hadoopIo.Text = + if (value == null) null else new hadoopIo.Text(value.asInstanceOf[String]) + + def getIntWritable(value: Any): hadoopIo.IntWritable = + if (value == null) null else new hadoopIo.IntWritable(value.asInstanceOf[Int]) + + def getDoubleWritable(value: Any): hiveIo.DoubleWritable = + if (value == null) null else new hiveIo.DoubleWritable(value.asInstanceOf[Double]) + + def getBooleanWritable(value: Any): hadoopIo.BooleanWritable = + if (value == null) null else new hadoopIo.BooleanWritable(value.asInstanceOf[Boolean]) + + def getLongWritable(value: Any): hadoopIo.LongWritable = + if (value == null) null else new hadoopIo.LongWritable(value.asInstanceOf[Long]) + + def getFloatWritable(value: Any): hadoopIo.FloatWritable = + if (value == null) null else new hadoopIo.FloatWritable(value.asInstanceOf[Float]) + + def getShortWritable(value: Any): hiveIo.ShortWritable = + if (value == null) null else new hiveIo.ShortWritable(value.asInstanceOf[Short]) + + def getByteWritable(value: Any): hiveIo.ByteWritable = + if (value == null) null else new hiveIo.ByteWritable(value.asInstanceOf[Byte]) + + def getBinaryWritable(value: Any): hadoopIo.BytesWritable = + if (value == null) null else new hadoopIo.BytesWritable(value.asInstanceOf[Array[Byte]]) + + def getDateWritable(value: Any): hiveIo.DateWritable = + if (value == null) null else new hiveIo.DateWritable(value.asInstanceOf[java.sql.Date]) + + def getTimestampWritable(value: Any): hiveIo.TimestampWritable = + if (value == null) { + null + } else { + new hiveIo.TimestampWritable(value.asInstanceOf[java.sql.Timestamp]) + } + + def getDecimalWritable(value: Any): hiveIo.HiveDecimalWritable = + if (value == null) { + null + } else { + new hiveIo.HiveDecimalWritable( + HiveShim.createDecimal(value.asInstanceOf[Decimal].toBigDecimal.underlying())) + } + + def getPrimitiveNullWritable: NullWritable = NullWritable.get() + def createDriverResultsArray = new JArrayList[String] def processResults(results: JArrayList[String]) = results @@ -197,7 +236,11 @@ private[hive] object HiveShim { } def toCatalystDecimal(hdoi: HiveDecimalObjectInspector, data: Any): Decimal = { - Decimal(hdoi.getPrimitiveJavaObject(data).bigDecimalValue()) + if (hdoi.preferWritable()) { + Decimal(hdoi.getPrimitiveWritableObject(data).getHiveDecimal().bigDecimalValue) + } else { + Decimal(hdoi.getPrimitiveJavaObject(data).bigDecimalValue()) + } } } diff --git a/sql/hive/v0.13.1/src/main/scala/org/apache/spark/sql/hive/Shim13.scala b/sql/hive/v0.13.1/src/main/scala/org/apache/spark/sql/hive/Shim13.scala index 7c8cbf10c1c30..b78c75798e988 100644 --- a/sql/hive/v0.13.1/src/main/scala/org/apache/spark/sql/hive/Shim13.scala +++ b/sql/hive/v0.13.1/src/main/scala/org/apache/spark/sql/hive/Shim13.scala @@ -22,6 +22,7 @@ import java.util.Properties import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.Path +import org.apache.hadoop.io.NullWritable import org.apache.hadoop.mapred.InputFormat import org.apache.hadoop.hive.common.StatsSetupConst import org.apache.hadoop.hive.common.`type`.{HiveDecimal} @@ -163,91 +164,123 @@ private[hive] object HiveShim { new TableDesc(inputFormatClass, outputFormatClass, properties) } + def getStringWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( - TypeInfoFactory.stringTypeInfo, - if (value == null) null else new hadoopIo.Text(value.asInstanceOf[String])) + TypeInfoFactory.stringTypeInfo, getStringWritable(value)) def getIntWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( - TypeInfoFactory.intTypeInfo, - if (value == null) null else new hadoopIo.IntWritable(value.asInstanceOf[Int])) + TypeInfoFactory.intTypeInfo, getIntWritable(value)) def getDoubleWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( - TypeInfoFactory.doubleTypeInfo, if (value == null) { - null - } else { - new hiveIo.DoubleWritable(value.asInstanceOf[Double]) - }) + TypeInfoFactory.doubleTypeInfo, getDoubleWritable(value)) def getBooleanWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( - TypeInfoFactory.booleanTypeInfo, if (value == null) { - null - } else { - new hadoopIo.BooleanWritable(value.asInstanceOf[Boolean]) - }) + TypeInfoFactory.booleanTypeInfo, getBooleanWritable(value)) def getLongWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( - TypeInfoFactory.longTypeInfo, - if (value == null) null else new hadoopIo.LongWritable(value.asInstanceOf[Long])) + TypeInfoFactory.longTypeInfo, getLongWritable(value)) def getFloatWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( - TypeInfoFactory.floatTypeInfo, if (value == null) { - null - } else { - new hadoopIo.FloatWritable(value.asInstanceOf[Float]) - }) + TypeInfoFactory.floatTypeInfo, getFloatWritable(value)) def getShortWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( - TypeInfoFactory.shortTypeInfo, - if (value == null) null else new hiveIo.ShortWritable(value.asInstanceOf[Short])) + TypeInfoFactory.shortTypeInfo, getShortWritable(value)) def getByteWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( - TypeInfoFactory.byteTypeInfo, - if (value == null) null else new hiveIo.ByteWritable(value.asInstanceOf[Byte])) + TypeInfoFactory.byteTypeInfo, getByteWritable(value)) def getBinaryWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( - TypeInfoFactory.binaryTypeInfo, if (value == null) { - null - } else { - new hadoopIo.BytesWritable(value.asInstanceOf[Array[Byte]]) - }) + TypeInfoFactory.binaryTypeInfo, getBinaryWritable(value)) def getDateWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( - TypeInfoFactory.dateTypeInfo, - if (value == null) null else new hiveIo.DateWritable(value.asInstanceOf[java.sql.Date])) + TypeInfoFactory.dateTypeInfo, getDateWritable(value)) def getTimestampWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( - TypeInfoFactory.timestampTypeInfo, if (value == null) { - null - } else { - new hiveIo.TimestampWritable(value.asInstanceOf[java.sql.Timestamp]) - }) + TypeInfoFactory.timestampTypeInfo, getTimestampWritable(value)) def getDecimalWritableConstantObjectInspector(value: Any): ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( - TypeInfoFactory.decimalTypeInfo, - if (value == null) { - null - } else { - // TODO precise, scale? - new hiveIo.HiveDecimalWritable( - HiveShim.createDecimal(value.asInstanceOf[Decimal].toBigDecimal.underlying())) - }) + TypeInfoFactory.decimalTypeInfo, getDecimalWritable(value)) def getPrimitiveNullWritableConstantObjectInspector: ObjectInspector = PrimitiveObjectInspectorFactory.getPrimitiveWritableConstantObjectInspector( TypeInfoFactory.voidTypeInfo, null) + def getStringWritable(value: Any): hadoopIo.Text = + if (value == null) null else new hadoopIo.Text(value.asInstanceOf[String]) + + def getIntWritable(value: Any): hadoopIo.IntWritable = + if (value == null) null else new hadoopIo.IntWritable(value.asInstanceOf[Int]) + + def getDoubleWritable(value: Any): hiveIo.DoubleWritable = + if (value == null) { + null + } else { + new hiveIo.DoubleWritable(value.asInstanceOf[Double]) + } + + def getBooleanWritable(value: Any): hadoopIo.BooleanWritable = + if (value == null) { + null + } else { + new hadoopIo.BooleanWritable(value.asInstanceOf[Boolean]) + } + + def getLongWritable(value: Any): hadoopIo.LongWritable = + if (value == null) null else new hadoopIo.LongWritable(value.asInstanceOf[Long]) + + def getFloatWritable(value: Any): hadoopIo.FloatWritable = + if (value == null) { + null + } else { + new hadoopIo.FloatWritable(value.asInstanceOf[Float]) + } + + def getShortWritable(value: Any): hiveIo.ShortWritable = + if (value == null) null else new hiveIo.ShortWritable(value.asInstanceOf[Short]) + + def getByteWritable(value: Any): hiveIo.ByteWritable = + if (value == null) null else new hiveIo.ByteWritable(value.asInstanceOf[Byte]) + + def getBinaryWritable(value: Any): hadoopIo.BytesWritable = + if (value == null) { + null + } else { + new hadoopIo.BytesWritable(value.asInstanceOf[Array[Byte]]) + } + + def getDateWritable(value: Any): hiveIo.DateWritable = + if (value == null) null else new hiveIo.DateWritable(value.asInstanceOf[java.sql.Date]) + + def getTimestampWritable(value: Any): hiveIo.TimestampWritable = + if (value == null) { + null + } else { + new hiveIo.TimestampWritable(value.asInstanceOf[java.sql.Timestamp]) + } + + def getDecimalWritable(value: Any): hiveIo.HiveDecimalWritable = + if (value == null) { + null + } else { + // TODO precise, scale? + new hiveIo.HiveDecimalWritable( + HiveShim.createDecimal(value.asInstanceOf[Decimal].toBigDecimal.underlying())) + } + + def getPrimitiveNullWritable: NullWritable = NullWritable.get() + def createDriverResultsArray = new JArrayList[Object] def processResults(results: JArrayList[Object]) = { @@ -355,7 +388,12 @@ private[hive] object HiveShim { } def toCatalystDecimal(hdoi: HiveDecimalObjectInspector, data: Any): Decimal = { - Decimal(hdoi.getPrimitiveJavaObject(data).bigDecimalValue(), hdoi.precision(), hdoi.scale()) + if (hdoi.preferWritable()) { + Decimal(hdoi.getPrimitiveWritableObject(data).getHiveDecimal().bigDecimalValue, + hdoi.precision(), hdoi.scale()) + } else { + Decimal(hdoi.getPrimitiveJavaObject(data).bigDecimalValue(), hdoi.precision(), hdoi.scale()) + } } } From c3d91da5ea8b85ca75444ec606f2e1eae376c4b2 Mon Sep 17 00:00:00 2001 From: wangfei Date: Thu, 18 Dec 2014 20:24:56 -0800 Subject: [PATCH 052/320] [SPARK-4861][SQL] Refactory command in spark sql Remove ```Command``` and use ```RunnableCommand``` instead. Author: wangfei Author: scwf Closes #3712 from scwf/cmd and squashes the following commits: 51a82f2 [wangfei] fix test failure 0e03be8 [wangfei] address comments 4033bed [scwf] remove CreateTableAsSelect in hivestrategy 5d20010 [wangfei] address comments 125f542 [scwf] factory command in spark sql --- .../sql/catalyst/plans/logical/commands.scala | 17 ---- .../org/apache/spark/sql/SQLContext.scala | 2 +- .../spark/sql/execution/SparkStrategies.scala | 13 +-- .../apache/spark/sql/execution/commands.scala | 85 +++++++------------ .../spark/sql/hive/ExtendedHiveQlParser.scala | 3 +- .../apache/spark/sql/hive/HiveContext.scala | 20 +++-- .../spark/sql/hive/HiveMetastoreCatalog.scala | 16 +++- .../org/apache/spark/sql/hive/HiveQl.scala | 13 +-- .../spark/sql/hive/HiveStrategies.scala | 39 ++------- .../org/apache/spark/sql/hive/TestHive.scala | 8 +- .../hive/execution/CreateTableAsSelect.scala | 38 +++------ .../execution/DescribeHiveTableCommand.scala | 23 ++--- ...eCommand.scala => HiveNativeCommand.scala} | 76 ++++++++--------- .../hive/execution/InsertIntoHiveTable.scala | 18 ++-- .../spark/sql/hive/execution/commands.scala | 39 ++++----- .../spark/sql/hive/StatisticsSuite.scala | 12 +-- .../hive/execution/HiveComparisonTest.scala | 5 +- 17 files changed, 172 insertions(+), 255 deletions(-) rename sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/{NativeCommand.scala => HiveNativeCommand.scala} (64%) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/commands.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/commands.scala index 1d513d7789763..5a1863953eae9 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/commands.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/commands.scala @@ -29,23 +29,6 @@ abstract class Command extends LeafNode { def output: Seq[Attribute] = Seq.empty } -/** - * Returned for commands supported by a given parser, but not catalyst. In general these are DDL - * commands that are passed directly to another system. - */ -case class NativeCommand(cmd: String) extends Command { - override def output = - Seq(AttributeReference("result", StringType, nullable = false)()) -} - -/** - * Commands of the form "SET [key [= value] ]". - */ -case class DFSCommand(kv: Option[(String, Option[String])]) extends Command { - override def output = Seq( - AttributeReference("DFS output", StringType, nullable = false)()) -} - /** * * Commands of the form "SET [key [= value] ]". diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala index ebd4cc920b1ad..7a13302229012 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala @@ -329,7 +329,7 @@ class SQLContext(@transient val sparkContext: SparkContext) def strategies: Seq[Strategy] = extraStrategies ++ ( - CommandStrategy(self) :: + CommandStrategy :: DataSourceStrategy :: TakeOrdered :: HashAggregation :: diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala index 6e04f26c84259..2954d4ce7d2d8 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala @@ -304,17 +304,20 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { } } - case class CommandStrategy(context: SQLContext) extends Strategy { + case object CommandStrategy extends Strategy { def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match { case r: RunnableCommand => ExecutedCommand(r) :: Nil case logical.SetCommand(kv) => - Seq(execution.SetCommand(kv, plan.output)(context)) + Seq(ExecutedCommand(execution.SetCommand(kv, plan.output))) case logical.ExplainCommand(logicalPlan, extended) => - Seq(execution.ExplainCommand(logicalPlan, plan.output, extended)(context)) + Seq(ExecutedCommand( + execution.ExplainCommand(logicalPlan, plan.output, extended))) case logical.CacheTableCommand(tableName, optPlan, isLazy) => - Seq(execution.CacheTableCommand(tableName, optPlan, isLazy)) + Seq(ExecutedCommand( + execution.CacheTableCommand(tableName, optPlan, isLazy))) case logical.UncacheTableCommand(tableName) => - Seq(execution.UncacheTableCommand(tableName)) + Seq(ExecutedCommand( + execution.UncacheTableCommand(tableName))) case _ => Nil } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala index afe3f3f07440c..b8fa4b019953e 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala @@ -26,34 +26,20 @@ import org.apache.spark.sql.catalyst.plans.logical import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan import org.apache.spark.sql.{SQLConf, SQLContext} -// TODO: DELETE ME... -trait Command { - this: SparkPlan => - - /** - * A concrete command should override this lazy field to wrap up any side effects caused by the - * command or any other computation that should be evaluated exactly once. The value of this field - * can be used as the contents of the corresponding RDD generated from the physical plan of this - * command. - * - * The `execute()` method of all the physical command classes should reference `sideEffectResult` - * so that the command can be executed eagerly right after the command query is created. - */ - protected lazy val sideEffectResult: Seq[Row] = Seq.empty[Row] - - override def executeCollect(): Array[Row] = sideEffectResult.toArray - - override def execute(): RDD[Row] = sqlContext.sparkContext.parallelize(sideEffectResult, 1) -} - -// TODO: Replace command with runnable command. +/** + * A logical command that is executed for its side-effects. `RunnableCommand`s are + * wrapped in `ExecutedCommand` during execution. + */ trait RunnableCommand extends logical.Command { self: Product => - def output: Seq[Attribute] def run(sqlContext: SQLContext): Seq[Row] } +/** + * A physical operator that executes the run method of a `RunnableCommand` and + * saves the result to prevent multiple executions. + */ case class ExecutedCommand(cmd: RunnableCommand) extends SparkPlan { /** * A concrete command should override this lazy field to wrap up any side effects caused by the @@ -79,43 +65,41 @@ case class ExecutedCommand(cmd: RunnableCommand) extends SparkPlan { * :: DeveloperApi :: */ @DeveloperApi -case class SetCommand(kv: Option[(String, Option[String])], output: Seq[Attribute])( - @transient context: SQLContext) - extends LeafNode with Command with Logging { +case class SetCommand( + kv: Option[(String, Option[String])], + override val output: Seq[Attribute]) extends RunnableCommand with Logging { - override protected lazy val sideEffectResult: Seq[Row] = kv match { + override def run(sqlContext: SQLContext) = kv match { // Configures the deprecated "mapred.reduce.tasks" property. case Some((SQLConf.Deprecated.MAPRED_REDUCE_TASKS, Some(value))) => logWarning( s"Property ${SQLConf.Deprecated.MAPRED_REDUCE_TASKS} is deprecated, " + s"automatically converted to ${SQLConf.SHUFFLE_PARTITIONS} instead.") - context.setConf(SQLConf.SHUFFLE_PARTITIONS, value) + sqlContext.setConf(SQLConf.SHUFFLE_PARTITIONS, value) Seq(Row(s"${SQLConf.SHUFFLE_PARTITIONS}=$value")) // Configures a single property. case Some((key, Some(value))) => - context.setConf(key, value) + sqlContext.setConf(key, value) Seq(Row(s"$key=$value")) - // Queries all key-value pairs that are set in the SQLConf of the context. Notice that different - // from Hive, here "SET -v" is an alias of "SET". (In Hive, "SET" returns all changed properties - // while "SET -v" returns all properties.) + // Queries all key-value pairs that are set in the SQLConf of the sqlContext. + // Notice that different from Hive, here "SET -v" is an alias of "SET". + // (In Hive, "SET" returns all changed properties while "SET -v" returns all properties.) case Some(("-v", None)) | None => - context.getAllConfs.map { case (k, v) => Row(s"$k=$v") }.toSeq + sqlContext.getAllConfs.map { case (k, v) => Row(s"$k=$v") }.toSeq // Queries the deprecated "mapred.reduce.tasks" property. case Some((SQLConf.Deprecated.MAPRED_REDUCE_TASKS, None)) => logWarning( s"Property ${SQLConf.Deprecated.MAPRED_REDUCE_TASKS} is deprecated, " + s"showing ${SQLConf.SHUFFLE_PARTITIONS} instead.") - Seq(Row(s"${SQLConf.SHUFFLE_PARTITIONS}=${context.numShufflePartitions}")) + Seq(Row(s"${SQLConf.SHUFFLE_PARTITIONS}=${sqlContext.numShufflePartitions}")) // Queries a single property. case Some((key, None)) => - Seq(Row(s"$key=${context.getConf(key, "")}")) + Seq(Row(s"$key=${sqlContext.getConf(key, "")}")) } - - override def otherCopyArgs = context :: Nil } /** @@ -128,22 +112,19 @@ case class SetCommand(kv: Option[(String, Option[String])], output: Seq[Attribut */ @DeveloperApi case class ExplainCommand( - logicalPlan: LogicalPlan, output: Seq[Attribute], extended: Boolean)( - @transient context: SQLContext) - extends LeafNode with Command { + logicalPlan: LogicalPlan, + override val output: Seq[Attribute], extended: Boolean) extends RunnableCommand { // Run through the optimizer to generate the physical plan. - override protected lazy val sideEffectResult: Seq[Row] = try { + override def run(sqlContext: SQLContext) = try { // TODO in Hive, the "extended" ExplainCommand prints the AST as well, and detailed properties. - val queryExecution = context.executePlan(logicalPlan) + val queryExecution = sqlContext.executePlan(logicalPlan) val outputString = if (extended) queryExecution.toString else queryExecution.simpleString outputString.split("\n").map(Row(_)) } catch { case cause: TreeNodeException[_] => ("Error occurred during query planning: \n" + cause.getMessage).split("\n").map(Row(_)) } - - override def otherCopyArgs = context :: Nil } /** @@ -153,10 +134,9 @@ case class ExplainCommand( case class CacheTableCommand( tableName: String, plan: Option[LogicalPlan], - isLazy: Boolean) - extends LeafNode with Command { + isLazy: Boolean) extends RunnableCommand { - override protected lazy val sideEffectResult = { + override def run(sqlContext: SQLContext) = { import sqlContext._ plan.foreach(_.registerTempTable(tableName)) @@ -178,8 +158,9 @@ case class CacheTableCommand( * :: DeveloperApi :: */ @DeveloperApi -case class UncacheTableCommand(tableName: String) extends LeafNode with Command { - override protected lazy val sideEffectResult: Seq[Row] = { +case class UncacheTableCommand(tableName: String) extends RunnableCommand { + + override def run(sqlContext: SQLContext) = { sqlContext.table(tableName).unpersist() Seq.empty[Row] } @@ -191,11 +172,11 @@ case class UncacheTableCommand(tableName: String) extends LeafNode with Command * :: DeveloperApi :: */ @DeveloperApi -case class DescribeCommand(child: SparkPlan, output: Seq[Attribute])( - @transient context: SQLContext) - extends LeafNode with Command { +case class DescribeCommand( + child: SparkPlan, + override val output: Seq[Attribute]) extends RunnableCommand { - override protected lazy val sideEffectResult: Seq[Row] = { + override def run(sqlContext: SQLContext) = { Row("# Registered as a temporary table", null, null) +: child.output.map(field => Row(field.name, field.dataType.toString, null)) } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/ExtendedHiveQlParser.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/ExtendedHiveQlParser.scala index 430ffb29989ea..ebf7003ff9e57 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/ExtendedHiveQlParser.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/ExtendedHiveQlParser.scala @@ -21,6 +21,7 @@ import scala.language.implicitConversions import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.{AbstractSparkSQLParser, SqlLexical} +import org.apache.spark.sql.hive.execution.{AddJar, AddFile, HiveNativeCommand} /** * A parser that recognizes all HiveQL constructs together with Spark SQL specific extensions. @@ -52,7 +53,7 @@ private[hive] class ExtendedHiveQlParser extends AbstractSparkSQLParser { protected lazy val dfs: Parser[LogicalPlan] = DFS ~> wholeInput ^^ { - case command => NativeCommand(command.trim) + case command => HiveNativeCommand(command.trim) } private lazy val addFile: Parser[LogicalPlan] = diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala index 7de440773023f..56fe27a77b838 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala @@ -39,8 +39,8 @@ import org.apache.spark.sql.catalyst.analysis.{Analyzer, EliminateAnalysisOperat import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.types.DecimalType import org.apache.spark.sql.catalyst.types.decimal.Decimal -import org.apache.spark.sql.execution.{ExtractPythonUdfs, QueryExecutionException, Command => PhysicalCommand} -import org.apache.spark.sql.hive.execution.DescribeHiveTableCommand +import org.apache.spark.sql.execution.{SparkPlan, ExecutedCommand, ExtractPythonUdfs, QueryExecutionException} +import org.apache.spark.sql.hive.execution.{HiveNativeCommand, DescribeHiveTableCommand} import org.apache.spark.sql.sources.DataSourceStrategy /** @@ -340,7 +340,7 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { override def strategies: Seq[Strategy] = extraStrategies ++ Seq( DataSourceStrategy, - CommandStrategy(self), + CommandStrategy, HiveCommandStrategy(self), TakeOrdered, ParquetOperations, @@ -369,11 +369,17 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { * execution is simply passed back to Hive. */ def stringResult(): Seq[String] = executedPlan match { - case describeHiveTableCommand: DescribeHiveTableCommand => + case ExecutedCommand(desc: DescribeHiveTableCommand) => // If it is a describe command for a Hive table, we want to have the output format // be similar with Hive. - describeHiveTableCommand.hiveString - case command: PhysicalCommand => + desc.run(self).map { + case Row(name: String, dataType: String, comment) => + Seq(name, dataType, + Option(comment.asInstanceOf[String]).getOrElse("")) + .map(s => String.format(s"%-20s", s)) + .mkString("\t") + } + case command: ExecutedCommand => command.executeCollect().map(_.head.toString) case other => @@ -386,7 +392,7 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { override def simpleString: String = logical match { - case _: NativeCommand => "" + case _: HiveNativeCommand => "" case _: SetCommand => "" case _ => super.simpleString } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala index d8b10b78c6c59..b31a3ec25096b 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala @@ -20,6 +20,8 @@ package org.apache.spark.sql.hive import java.io.IOException import java.util.{List => JList} +import org.apache.spark.sql.execution.SparkPlan + import scala.util.parsing.combinator.RegexParsers import org.apache.hadoop.util.ReflectionUtils @@ -286,14 +288,24 @@ private[hive] class HiveMetastoreCatalog(hive: HiveContext) extends Catalog with Some(sa.getQB().getTableDesc) } - CreateTableAsSelect(Some(databaseName), tblName, child, allowExisting, desc) + execution.CreateTableAsSelect( + databaseName, + tableName, + child, + allowExisting, + desc) case p: LogicalPlan if p.resolved => p case p @ CreateTableAsSelect(db, tableName, child, allowExisting, None) => val (dbName, tblName) = processDatabaseAndTableName(db, tableName) val databaseName = dbName.getOrElse(hive.sessionState.getCurrentDatabase) - CreateTableAsSelect(Some(databaseName), tblName, child, allowExisting, None) + execution.CreateTableAsSelect( + databaseName, + tableName, + child, + allowExisting, + None) } } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala index 5939276f6d65e..3f3d9e7cd4fbe 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala @@ -33,6 +33,7 @@ import org.apache.spark.sql.catalyst.plans.logical import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.types._ import org.apache.spark.sql.catalyst.types.decimal.Decimal +import org.apache.spark.sql.hive.execution.{HiveNativeCommand, DropTable, AnalyzeTable} /* Implicit conversions */ import scala.collection.JavaConversions._ @@ -44,14 +45,6 @@ import scala.collection.JavaConversions._ */ private[hive] case object NativePlaceholder extends Command -private[hive] case class AddFile(filePath: String) extends Command - -private[hive] case class AddJar(path: String) extends Command - -private[hive] case class DropTable(tableName: String, ifExists: Boolean) extends Command - -private[hive] case class AnalyzeTable(tableName: String) extends Command - /** Provides a mapping from HiveQL statements to catalyst logical plans and expression trees. */ private[hive] object HiveQl { protected val nativeCommands = Seq( @@ -239,10 +232,10 @@ private[hive] object HiveQl { try { val tree = getAst(sql) if (nativeCommands contains tree.getText) { - NativeCommand(sql) + HiveNativeCommand(sql) } else { nodeToPlan(tree) match { - case NativePlaceholder => NativeCommand(sql) + case NativePlaceholder => HiveNativeCommand(sql) case other => other } } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala index 4ebd59db83515..d3f6381b69a4d 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala @@ -17,9 +17,6 @@ package org.apache.spark.sql.hive -import org.apache.hadoop.hive.ql.parse.ASTNode -import org.apache.hadoop.hive.ql.plan.CreateTableDesc - import org.apache.spark.annotation.Experimental import org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute import org.apache.spark.sql.catalyst.expressions._ @@ -28,7 +25,7 @@ import org.apache.spark.sql.catalyst.planning._ import org.apache.spark.sql.catalyst.plans._ import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan import org.apache.spark.sql.catalyst.types.StringType -import org.apache.spark.sql.execution.{DescribeCommand, OutputFaker, SparkPlan, PhysicalRDD} +import org.apache.spark.sql.execution._ import org.apache.spark.sql.hive import org.apache.spark.sql.hive.execution._ import org.apache.spark.sql.parquet.ParquetRelation @@ -177,25 +174,10 @@ private[hive] trait HiveStrategies { def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match { case logical.InsertIntoTable(table: MetastoreRelation, partition, child, overwrite) => execution.InsertIntoHiveTable( - table, partition, planLater(child), overwrite)(hiveContext) :: Nil + table, partition, planLater(child), overwrite) :: Nil case hive.InsertIntoHiveTable(table: MetastoreRelation, partition, child, overwrite) => execution.InsertIntoHiveTable( - table, partition, planLater(child), overwrite)(hiveContext) :: Nil - case logical.CreateTableAsSelect( - Some(database), tableName, child, allowExisting, Some(desc: CreateTableDesc)) => - execution.CreateTableAsSelect( - database, - tableName, - child, - allowExisting, - Some(desc)) :: Nil - case logical.CreateTableAsSelect(Some(database), tableName, child, allowExisting, None) => - execution.CreateTableAsSelect( - database, - tableName, - child, - allowExisting, - None) :: Nil + table, partition, planLater(child), overwrite) :: Nil case _ => Nil } } @@ -227,23 +209,14 @@ private[hive] trait HiveStrategies { case class HiveCommandStrategy(context: HiveContext) extends Strategy { def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match { - case logical.NativeCommand(sql) => NativeCommand(sql, plan.output)(context) :: Nil - - case hive.DropTable(tableName, ifExists) => execution.DropTable(tableName, ifExists) :: Nil - - case hive.AddJar(path) => execution.AddJar(path) :: Nil - - case hive.AddFile(path) => execution.AddFile(path) :: Nil - - case hive.AnalyzeTable(tableName) => execution.AnalyzeTable(tableName) :: Nil - case describe: logical.DescribeCommand => val resolvedTable = context.executePlan(describe.table).analyzed resolvedTable match { case t: MetastoreRelation => - Seq(DescribeHiveTableCommand(t, describe.output, describe.isExtended)(context)) + ExecutedCommand( + DescribeHiveTableCommand(t, describe.output, describe.isExtended)) :: Nil case o: LogicalPlan => - Seq(DescribeCommand(planLater(o), describe.output)(context)) + ExecutedCommand(DescribeCommand(planLater(o), describe.output)) :: Nil } case _ => Nil diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala index eedb57de52ba9..b2149bd95a336 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala @@ -20,9 +20,6 @@ package org.apache.spark.sql.hive.test import java.io.File import java.util.{Set => JavaSet} -import org.apache.hadoop.hive.conf.HiveConf -import org.apache.hadoop.hive.ql.session.SessionState - import scala.collection.mutable import scala.language.implicitConversions @@ -37,10 +34,11 @@ import org.apache.hadoop.hive.serde2.avro.AvroSerDe import org.apache.spark.{SparkConf, SparkContext} import org.apache.spark.util.Utils import org.apache.spark.sql.catalyst.analysis._ -import org.apache.spark.sql.catalyst.plans.logical.{CacheTableCommand, LogicalPlan, NativeCommand} +import org.apache.spark.sql.catalyst.plans.logical.{CacheTableCommand, LogicalPlan} import org.apache.spark.sql.catalyst.util._ import org.apache.spark.sql.hive._ import org.apache.spark.sql.SQLConf +import org.apache.spark.sql.hive.execution.HiveNativeCommand /* Implicit conversions */ import scala.collection.JavaConversions._ @@ -161,7 +159,7 @@ class TestHiveContext(sc: SparkContext) extends HiveContext(sc) { abstract class QueryExecution extends super.QueryExecution { override lazy val analyzed = { val describedTables = logical match { - case NativeCommand(describedTable(tbl)) => tbl :: Nil + case HiveNativeCommand(describedTable(tbl)) => tbl :: Nil case CacheTableCommand(tbl, _, _) => tbl :: Nil case _ => Nil } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateTableAsSelect.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateTableAsSelect.scala index b83689ceabb84..fe21454e7fb38 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateTableAsSelect.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateTableAsSelect.scala @@ -20,10 +20,10 @@ package org.apache.spark.sql.hive.execution import org.apache.hadoop.hive.ql.plan.CreateTableDesc import org.apache.spark.annotation.Experimental -import org.apache.spark.rdd.RDD +import org.apache.spark.sql.SQLContext import org.apache.spark.sql.catalyst.expressions.Row import org.apache.spark.sql.catalyst.plans.logical.{InsertIntoTable, LogicalPlan} -import org.apache.spark.sql.execution.{SparkPlan, Command, LeafNode} +import org.apache.spark.sql.execution.RunnableCommand import org.apache.spark.sql.hive.HiveContext import org.apache.spark.sql.hive.MetastoreRelation @@ -44,28 +44,23 @@ case class CreateTableAsSelect( tableName: String, query: LogicalPlan, allowExisting: Boolean, - desc: Option[CreateTableDesc]) extends LeafNode with Command { + desc: Option[CreateTableDesc]) extends RunnableCommand { - def output = Seq.empty + override def run(sqlContext: SQLContext) = { + val hiveContext = sqlContext.asInstanceOf[HiveContext] + lazy val metastoreRelation: MetastoreRelation = { + // Create Hive Table + hiveContext.catalog.createTable(database, tableName, query.output, allowExisting, desc) - private[this] def sc = sqlContext.asInstanceOf[HiveContext] - - // A lazy computing of the metastoreRelation - private[this] lazy val metastoreRelation: MetastoreRelation = { - // Create Hive Table - sc.catalog.createTable(database, tableName, query.output, allowExisting, desc) - - // Get the Metastore Relation - sc.catalog.lookupRelation(Some(database), tableName, None) match { - case r: MetastoreRelation => r + // Get the Metastore Relation + hiveContext.catalog.lookupRelation(Some(database), tableName, None) match { + case r: MetastoreRelation => r + } } - } - - override protected[sql] lazy val sideEffectResult: Seq[Row] = { // TODO ideally, we should get the output data ready first and then // add the relation into catalog, just in case of failure occurs while data // processing. - if (sc.catalog.tableExists(Some(database), tableName)) { + if (hiveContext.catalog.tableExists(Some(database), tableName)) { if (allowExisting) { // table already exists, will do nothing, to keep consistent with Hive } else { @@ -73,17 +68,12 @@ case class CreateTableAsSelect( new org.apache.hadoop.hive.metastore.api.AlreadyExistsException(s"$database.$tableName") } } else { - sc.executePlan(InsertIntoTable(metastoreRelation, Map(), query, true)).toRdd + hiveContext.executePlan(InsertIntoTable(metastoreRelation, Map(), query, true)).toRdd } Seq.empty[Row] } - override def execute(): RDD[Row] = { - sideEffectResult - sparkContext.emptyRDD[Row] - } - override def argString: String = { s"[Database:$database, TableName: $tableName, InsertIntoHiveTable]\n" + query.toString } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/DescribeHiveTableCommand.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/DescribeHiveTableCommand.scala index 5d98834c6fb33..bfacc51ef57ab 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/DescribeHiveTableCommand.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/DescribeHiveTableCommand.scala @@ -22,11 +22,11 @@ import scala.collection.JavaConversions._ import org.apache.hadoop.hive.metastore.api.FieldSchema import org.apache.spark.annotation.DeveloperApi -import org.apache.spark.rdd.RDD import org.apache.spark.sql.catalyst.expressions.{Attribute, Row} -import org.apache.spark.sql.execution.{Command, LeafNode} +import org.apache.spark.sql.execution.{SparkPlan, RunnableCommand} import org.apache.spark.sql.hive.{HiveContext, MetastoreRelation} import org.apache.spark.sql.hive.HiveShim +import org.apache.spark.sql.SQLContext /** * Implementation for "describe [extended] table". @@ -36,21 +36,10 @@ import org.apache.spark.sql.hive.HiveShim @DeveloperApi case class DescribeHiveTableCommand( table: MetastoreRelation, - output: Seq[Attribute], - isExtended: Boolean)( - @transient context: HiveContext) - extends LeafNode with Command { + override val output: Seq[Attribute], + isExtended: Boolean) extends RunnableCommand { - // Strings with the format like Hive. It is used for result comparison in our unit tests. - lazy val hiveString: Seq[String] = sideEffectResult.map { - case Row(name: String, dataType: String, comment) => - Seq(name, dataType, - Option(comment.asInstanceOf[String]).getOrElse("")) - .map(s => String.format(s"%-20s", s)) - .mkString("\t") - } - - override protected lazy val sideEffectResult: Seq[Row] = { + override def run(sqlContext: SQLContext) = { // Trying to mimic the format of Hive's output. But not exactly the same. var results: Seq[(String, String, String)] = Nil @@ -75,6 +64,4 @@ case class DescribeHiveTableCommand( Row(name, dataType, comment) } } - - override def otherCopyArgs = context :: Nil } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/NativeCommand.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveNativeCommand.scala similarity index 64% rename from sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/NativeCommand.scala rename to sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveNativeCommand.scala index 6930c2babd117..8ba818af5f9d0 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/NativeCommand.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveNativeCommand.scala @@ -1,38 +1,38 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.hive.execution - -import org.apache.spark.annotation.DeveloperApi -import org.apache.spark.rdd.RDD -import org.apache.spark.sql.catalyst.expressions.{Attribute, GenericRow, Row} -import org.apache.spark.sql.execution.{Command, LeafNode} -import org.apache.spark.sql.hive.HiveContext - -/** - * :: DeveloperApi :: - */ -@DeveloperApi -case class NativeCommand( - sql: String, output: Seq[Attribute])( - @transient context: HiveContext) - extends LeafNode with Command { - - override protected lazy val sideEffectResult: Seq[Row] = context.runSqlHive(sql).map(Row(_)) - - override def otherCopyArgs = context :: Nil -} +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.hive.execution + +import org.apache.spark.annotation.DeveloperApi +import org.apache.spark.sql.catalyst.expressions.{AttributeReference, Row} +import org.apache.spark.sql.execution.RunnableCommand +import org.apache.spark.sql.hive.HiveContext +import org.apache.spark.sql.SQLContext +import org.apache.spark.sql.catalyst.types.StringType + +/** + * :: DeveloperApi :: + */ +@DeveloperApi +case class HiveNativeCommand(sql: String) extends RunnableCommand { + + override def output = + Seq(AttributeReference("result", StringType, nullable = false)()) + + override def run(sqlContext: SQLContext) = + sqlContext.asInstanceOf[HiveContext].runSqlHive(sql).map(Row(_)) +} diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala index 81390f626726c..ca0ec1513917f 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala @@ -21,7 +21,6 @@ import java.util import scala.collection.JavaConversions._ -import org.apache.hadoop.hive.common.`type`.HiveVarchar import org.apache.hadoop.hive.conf.HiveConf import org.apache.hadoop.hive.conf.HiveConf.ConfVars import org.apache.hadoop.hive.metastore.MetaStoreUtils @@ -31,14 +30,12 @@ import org.apache.hadoop.hive.ql.{Context, ErrorMsg} import org.apache.hadoop.hive.serde2.Serializer import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorUtils.ObjectInspectorCopyOption import org.apache.hadoop.hive.serde2.objectinspector._ -import org.apache.hadoop.hive.serde2.objectinspector.primitive.{JavaHiveDecimalObjectInspector, JavaHiveVarcharObjectInspector} import org.apache.hadoop.mapred.{FileOutputCommitter, FileOutputFormat, JobConf} import org.apache.spark.annotation.DeveloperApi import org.apache.spark.rdd.RDD import org.apache.spark.sql.catalyst.expressions.Row -import org.apache.spark.sql.catalyst.types.decimal.Decimal -import org.apache.spark.sql.execution.{Command, SparkPlan, UnaryNode} +import org.apache.spark.sql.execution.{UnaryNode, SparkPlan} import org.apache.spark.sql.hive._ import org.apache.spark.sql.hive.{ ShimFileSinkDesc => FileSinkDesc} import org.apache.spark.sql.hive.HiveShim._ @@ -52,10 +49,9 @@ case class InsertIntoHiveTable( table: MetastoreRelation, partition: Map[String, Option[String]], child: SparkPlan, - overwrite: Boolean) - (@transient sc: HiveContext) - extends UnaryNode with Command with HiveInspectors { + overwrite: Boolean) extends UnaryNode with HiveInspectors { + @transient val sc: HiveContext = sqlContext.asInstanceOf[HiveContext] @transient lazy val outputClass = newSerializer(table.tableDesc).getSerializedClass @transient private lazy val hiveContext = new Context(sc.hiveconf) @transient private lazy val db = Hive.get(sc.hiveconf) @@ -66,8 +62,6 @@ case class InsertIntoHiveTable( serializer } - override def otherCopyArgs = sc :: Nil - def output = child.output def saveAsHiveFile( @@ -134,7 +128,7 @@ case class InsertIntoHiveTable( * * Note: this is run once and then kept to avoid double insertions. */ - override protected[sql] lazy val sideEffectResult: Seq[Row] = { + protected[sql] lazy val sideEffectResult: Seq[Row] = { // Have to pass the TableDesc object to RDD.mapPartitions and then instantiate new serializer // instances within the closure, since Serializer is not serializable while TableDesc is. val tableDesc = table.tableDesc @@ -256,4 +250,8 @@ case class InsertIntoHiveTable( // TODO: implement hive compatibility as rules. Seq.empty[Row] } + + override def executeCollect(): Array[Row] = sideEffectResult.toArray + + override def execute(): RDD[Row] = sqlContext.sparkContext.parallelize(sideEffectResult, 1) } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala index 903075edf7e04..6fc4153f6a5df 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala @@ -18,10 +18,10 @@ package org.apache.spark.sql.hive.execution import org.apache.spark.annotation.DeveloperApi -import org.apache.spark.rdd.RDD import org.apache.spark.sql.catalyst.expressions.Row -import org.apache.spark.sql.execution.{Command, LeafNode} +import org.apache.spark.sql.execution.RunnableCommand import org.apache.spark.sql.hive.HiveContext +import org.apache.spark.sql.SQLContext /** * :: DeveloperApi :: @@ -32,13 +32,10 @@ import org.apache.spark.sql.hive.HiveContext * in the Hive metastore. */ @DeveloperApi -case class AnalyzeTable(tableName: String) extends LeafNode with Command { - def hiveContext = sqlContext.asInstanceOf[HiveContext] +case class AnalyzeTable(tableName: String) extends RunnableCommand { - def output = Seq.empty - - override protected lazy val sideEffectResult: Seq[Row] = { - hiveContext.analyze(tableName) + override def run(sqlContext: SQLContext) = { + sqlContext.asInstanceOf[HiveContext].analyze(tableName) Seq.empty[Row] } } @@ -48,12 +45,12 @@ case class AnalyzeTable(tableName: String) extends LeafNode with Command { * Drops a table from the metastore and removes it if it is cached. */ @DeveloperApi -case class DropTable(tableName: String, ifExists: Boolean) extends LeafNode with Command { - def hiveContext = sqlContext.asInstanceOf[HiveContext] - - def output = Seq.empty +case class DropTable( + tableName: String, + ifExists: Boolean) extends RunnableCommand { - override protected lazy val sideEffectResult: Seq[Row] = { + override def run(sqlContext: SQLContext) = { + val hiveContext = sqlContext.asInstanceOf[HiveContext] val ifExistsClause = if (ifExists) "IF EXISTS " else "" hiveContext.runSqlHive(s"DROP TABLE $ifExistsClause$tableName") hiveContext.catalog.unregisterTable(None, tableName) @@ -65,12 +62,10 @@ case class DropTable(tableName: String, ifExists: Boolean) extends LeafNode with * :: DeveloperApi :: */ @DeveloperApi -case class AddJar(path: String) extends LeafNode with Command { - def hiveContext = sqlContext.asInstanceOf[HiveContext] +case class AddJar(path: String) extends RunnableCommand { - override def output = Seq.empty - - override protected lazy val sideEffectResult: Seq[Row] = { + override def run(sqlContext: SQLContext) = { + val hiveContext = sqlContext.asInstanceOf[HiveContext] hiveContext.runSqlHive(s"ADD JAR $path") hiveContext.sparkContext.addJar(path) Seq.empty[Row] @@ -81,12 +76,10 @@ case class AddJar(path: String) extends LeafNode with Command { * :: DeveloperApi :: */ @DeveloperApi -case class AddFile(path: String) extends LeafNode with Command { - def hiveContext = sqlContext.asInstanceOf[HiveContext] - - override def output = Seq.empty +case class AddFile(path: String) extends RunnableCommand { - override protected lazy val sideEffectResult: Seq[Row] = { + override def run(sqlContext: SQLContext) = { + val hiveContext = sqlContext.asInstanceOf[HiveContext] hiveContext.runSqlHive(s"ADD FILE $path") hiveContext.sparkContext.addFile(path) Seq.empty[Row] diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala index a90fc023e67d8..ff4071d8e2f10 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala @@ -22,10 +22,10 @@ import org.scalatest.BeforeAndAfterAll import scala.reflect.ClassTag import org.apache.spark.sql.{SQLConf, QueryTest} -import org.apache.spark.sql.catalyst.plans.logical.NativeCommand import org.apache.spark.sql.execution.joins.{BroadcastHashJoin, ShuffledHashJoin} import org.apache.spark.sql.hive.test.TestHive import org.apache.spark.sql.hive.test.TestHive._ +import org.apache.spark.sql.hive.execution._ class StatisticsSuite extends QueryTest with BeforeAndAfterAll { TestHive.reset() @@ -51,19 +51,19 @@ class StatisticsSuite extends QueryTest with BeforeAndAfterAll { assertAnalyzeCommand( "ANALYZE TABLE Table1 COMPUTE STATISTICS", - classOf[NativeCommand]) + classOf[HiveNativeCommand]) assertAnalyzeCommand( "ANALYZE TABLE Table1 PARTITION(ds='2008-04-09', hr=11) COMPUTE STATISTICS", - classOf[NativeCommand]) + classOf[HiveNativeCommand]) assertAnalyzeCommand( "ANALYZE TABLE Table1 PARTITION(ds='2008-04-09', hr=11) COMPUTE STATISTICS noscan", - classOf[NativeCommand]) + classOf[HiveNativeCommand]) assertAnalyzeCommand( "ANALYZE TABLE Table1 PARTITION(ds, hr) COMPUTE STATISTICS", - classOf[NativeCommand]) + classOf[HiveNativeCommand]) assertAnalyzeCommand( "ANALYZE TABLE Table1 PARTITION(ds, hr) COMPUTE STATISTICS noscan", - classOf[NativeCommand]) + classOf[HiveNativeCommand]) assertAnalyzeCommand( "ANALYZE TABLE Table1 COMPUTE STATISTICS nOscAn", diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala index 44eb4cfa59335..8011f9b8773b3 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala @@ -24,7 +24,6 @@ import org.scalatest.{BeforeAndAfterAll, FunSuite, GivenWhenThen} import org.apache.spark.Logging import org.apache.spark.sql.catalyst.planning.PhysicalOperation import org.apache.spark.sql.catalyst.plans.logical._ -import org.apache.spark.sql.catalyst.plans.logical.{NativeCommand => LogicalNativeCommand} import org.apache.spark.sql.catalyst.util._ import org.apache.spark.sql.hive.test.TestHive @@ -142,14 +141,14 @@ abstract class HiveComparisonTest // Hack: Hive simply prints the result of a SET command to screen, // and does not return it as a query answer. case _: SetCommand => Seq("0") - case LogicalNativeCommand(c) if c.toLowerCase.contains("desc") => + case HiveNativeCommand(c) if c.toLowerCase.contains("desc") => answer .filterNot(nonDeterministicLine) .map(_.replaceAll("from deserializer", "")) .map(_.replaceAll("None", "")) .map(_.trim) .filterNot(_ == "") - case _: LogicalNativeCommand => answer.filterNot(nonDeterministicLine).filterNot(_ == "") + case _: HiveNativeCommand => answer.filterNot(nonDeterministicLine).filterNot(_ == "") case _: ExplainCommand => answer case _: DescribeCommand => // Filter out non-deterministic lines and lines which do not have actual results but From ee1fb97a97d5ac18cd2ad8028e84ecbd988fb811 Mon Sep 17 00:00:00 2001 From: RJ Nowling Date: Thu, 18 Dec 2014 21:00:49 -0800 Subject: [PATCH 053/320] [SPARK-4728][MLLib] Add exponential, gamma, and log normal sampling to MLlib da... ...ta generators This patch adds: * Exponential, gamma, and log normal generators that wrap Apache Commons math3 to the private API * Functions for generating exponential, gamma, and log normal RDDs and vector RDDs * Tests for the above Author: RJ Nowling Closes #3680 from rnowling/spark4728 and squashes the following commits: 455f50a [RJ Nowling] Add tests for exponential, gamma, and log normal samplers to JavaRandomRDDsSuite 3e1134a [RJ Nowling] Fix val/var, unncessary creation of Distribution objects when setting seeds, and import line longer than line wrap limits 58f5b97 [RJ Nowling] Fix bounds in tests so they scale with variance, not stdev 84fd98d [RJ Nowling] Add more values for testing distributions. 9f96232 [RJ Nowling] [SPARK-4728] Add exponential, gamma, and log normal sampling to MLlib data generators --- .../mllib/random/RandomDataGenerator.scala | 69 +++- .../spark/mllib/random/RandomRDDs.scala | 363 ++++++++++++++++++ .../mllib/random/JavaRandomRDDsSuite.java | 99 +++++ .../random/RandomDataGeneratorSuite.scala | 52 ++- .../spark/mllib/random/RandomRDDsSuite.scala | 43 +++ 5 files changed, 622 insertions(+), 4 deletions(-) diff --git a/mllib/src/main/scala/org/apache/spark/mllib/random/RandomDataGenerator.scala b/mllib/src/main/scala/org/apache/spark/mllib/random/RandomDataGenerator.scala index 51f9b8657c640..405bae62ee8b6 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/random/RandomDataGenerator.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/random/RandomDataGenerator.scala @@ -17,7 +17,8 @@ package org.apache.spark.mllib.random -import org.apache.commons.math3.distribution.PoissonDistribution +import org.apache.commons.math3.distribution.{ExponentialDistribution, + GammaDistribution, LogNormalDistribution, PoissonDistribution} import org.apache.spark.annotation.DeveloperApi import org.apache.spark.util.random.{XORShiftRandom, Pseudorandom} @@ -88,14 +89,76 @@ class StandardNormalGenerator extends RandomDataGenerator[Double] { @DeveloperApi class PoissonGenerator(val mean: Double) extends RandomDataGenerator[Double] { - private var rng = new PoissonDistribution(mean) + private val rng = new PoissonDistribution(mean) override def nextValue(): Double = rng.sample() override def setSeed(seed: Long) { - rng = new PoissonDistribution(mean) rng.reseedRandomGenerator(seed) } override def copy(): PoissonGenerator = new PoissonGenerator(mean) } + +/** + * :: DeveloperApi :: + * Generates i.i.d. samples from the exponential distribution with the given mean. + * + * @param mean mean for the exponential distribution. + */ +@DeveloperApi +class ExponentialGenerator(val mean: Double) extends RandomDataGenerator[Double] { + + private val rng = new ExponentialDistribution(mean) + + override def nextValue(): Double = rng.sample() + + override def setSeed(seed: Long) { + rng.reseedRandomGenerator(seed) + } + + override def copy(): ExponentialGenerator = new ExponentialGenerator(mean) +} + +/** + * :: DeveloperApi :: + * Generates i.i.d. samples from the gamma distribution with the given shape and scale. + * + * @param shape shape for the gamma distribution. + * @param scale scale for the gamma distribution + */ +@DeveloperApi +class GammaGenerator(val shape: Double, val scale: Double) extends RandomDataGenerator[Double] { + + private val rng = new GammaDistribution(shape, scale) + + override def nextValue(): Double = rng.sample() + + override def setSeed(seed: Long) { + rng.reseedRandomGenerator(seed) + } + + override def copy(): GammaGenerator = new GammaGenerator(shape, scale) +} + +/** + * :: DeveloperApi :: + * Generates i.i.d. samples from the log normal distribution with the + * given mean and standard deviation. + * + * @param mean mean for the log normal distribution. + * @param std standard deviation for the log normal distribution + */ +@DeveloperApi +class LogNormalGenerator(val mean: Double, val std: Double) extends RandomDataGenerator[Double] { + + private val rng = new LogNormalDistribution(mean, std) + + override def nextValue(): Double = rng.sample() + + override def setSeed(seed: Long) { + rng.reseedRandomGenerator(seed) + } + + override def copy(): LogNormalGenerator = new LogNormalGenerator(mean, std) +} diff --git a/mllib/src/main/scala/org/apache/spark/mllib/random/RandomRDDs.scala b/mllib/src/main/scala/org/apache/spark/mllib/random/RandomRDDs.scala index c5f4b084321f7..955c593a085d5 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/random/RandomRDDs.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/random/RandomRDDs.scala @@ -176,6 +176,176 @@ object RandomRDDs { JavaDoubleRDD.fromRDD(poissonRDD(jsc.sc, mean, size)) } + /** + * Generates an RDD comprised of i.i.d. samples from the exponential distribution with + * the input mean. + * + * @param sc SparkContext used to create the RDD. + * @param mean Mean, or 1 / lambda, for the exponential distribution. + * @param size Size of the RDD. + * @param numPartitions Number of partitions in the RDD (default: `sc.defaultParallelism`). + * @param seed Random seed (default: a random long integer). + * @return RDD[Double] comprised of i.i.d. samples ~ Pois(mean). + */ + def exponentialRDD( + sc: SparkContext, + mean: Double, + size: Long, + numPartitions: Int = 0, + seed: Long = Utils.random.nextLong()): RDD[Double] = { + val exponential = new ExponentialGenerator(mean) + randomRDD(sc, exponential, size, numPartitionsOrDefault(sc, numPartitions), seed) + } + + /** + * Java-friendly version of [[RandomRDDs#exponentialRDD]]. + */ + def exponentialJavaRDD( + jsc: JavaSparkContext, + mean: Double, + size: Long, + numPartitions: Int, + seed: Long): JavaDoubleRDD = { + JavaDoubleRDD.fromRDD(exponentialRDD(jsc.sc, mean, size, numPartitions, seed)) + } + + /** + * [[RandomRDDs#exponentialJavaRDD]] with the default seed. + */ + def exponentialJavaRDD( + jsc: JavaSparkContext, + mean: Double, + size: Long, + numPartitions: Int): JavaDoubleRDD = { + JavaDoubleRDD.fromRDD(exponentialRDD(jsc.sc, mean, size, numPartitions)) + } + + /** + * [[RandomRDDs#exponentialJavaRDD]] with the default number of partitions and the default seed. + */ + def exponentialJavaRDD(jsc: JavaSparkContext, mean: Double, size: Long): JavaDoubleRDD = { + JavaDoubleRDD.fromRDD(exponentialRDD(jsc.sc, mean, size)) + } + + /** + * Generates an RDD comprised of i.i.d. samples from the gamma distribution with the input + * shape and scale. + * + * @param sc SparkContext used to create the RDD. + * @param shape shape parameter (> 0) for the gamma distribution + * @param scale scale parameter (> 0) for the gamma distribution + * @param size Size of the RDD. + * @param numPartitions Number of partitions in the RDD (default: `sc.defaultParallelism`). + * @param seed Random seed (default: a random long integer). + * @return RDD[Double] comprised of i.i.d. samples ~ Pois(mean). + */ + def gammaRDD( + sc: SparkContext, + shape: Double, + scale: Double, + size: Long, + numPartitions: Int = 0, + seed: Long = Utils.random.nextLong()): RDD[Double] = { + val gamma = new GammaGenerator(shape, scale) + randomRDD(sc, gamma, size, numPartitionsOrDefault(sc, numPartitions), seed) + } + + /** + * Java-friendly version of [[RandomRDDs#gammaRDD]]. + */ + def gammaJavaRDD( + jsc: JavaSparkContext, + shape: Double, + scale: Double, + size: Long, + numPartitions: Int, + seed: Long): JavaDoubleRDD = { + JavaDoubleRDD.fromRDD(gammaRDD(jsc.sc, shape, scale, size, numPartitions, seed)) + } + + /** + * [[RandomRDDs#gammaJavaRDD]] with the default seed. + */ + def gammaJavaRDD( + jsc: JavaSparkContext, + shape: Double, + scale: Double, + size: Long, + numPartitions: Int): JavaDoubleRDD = { + JavaDoubleRDD.fromRDD(gammaRDD(jsc.sc, shape, scale, size, numPartitions)) + } + + /** + * [[RandomRDDs#gammaJavaRDD]] with the default number of partitions and the default seed. + */ + def gammaJavaRDD( + jsc: JavaSparkContext, + shape: Double, + scale: Double, + size: Long): JavaDoubleRDD = { + JavaDoubleRDD.fromRDD(gammaRDD(jsc.sc, shape, scale, size)) + } + + /** + * Generates an RDD comprised of i.i.d. samples from the log normal distribution with the input + * mean and standard deviation + * + * @param sc SparkContext used to create the RDD. + * @param mean mean for the log normal distribution + * @param std standard deviation for the log normal distribution + * @param size Size of the RDD. + * @param numPartitions Number of partitions in the RDD (default: `sc.defaultParallelism`). + * @param seed Random seed (default: a random long integer). + * @return RDD[Double] comprised of i.i.d. samples ~ Pois(mean). + */ + def logNormalRDD( + sc: SparkContext, + mean: Double, + std: Double, + size: Long, + numPartitions: Int = 0, + seed: Long = Utils.random.nextLong()): RDD[Double] = { + val logNormal = new LogNormalGenerator(mean, std) + randomRDD(sc, logNormal, size, numPartitionsOrDefault(sc, numPartitions), seed) + } + + /** + * Java-friendly version of [[RandomRDDs#logNormalRDD]]. + */ + def logNormalJavaRDD( + jsc: JavaSparkContext, + mean: Double, + std: Double, + size: Long, + numPartitions: Int, + seed: Long): JavaDoubleRDD = { + JavaDoubleRDD.fromRDD(logNormalRDD(jsc.sc, mean, std, size, numPartitions, seed)) + } + + /** + * [[RandomRDDs#logNormalJavaRDD]] with the default seed. + */ + def logNormalJavaRDD( + jsc: JavaSparkContext, + mean: Double, + std: Double, + size: Long, + numPartitions: Int): JavaDoubleRDD = { + JavaDoubleRDD.fromRDD(logNormalRDD(jsc.sc, mean, std, size, numPartitions)) + } + + /** + * [[RandomRDDs#logNormalJavaRDD]] with the default number of partitions and the default seed. + */ + def logNormalJavaRDD( + jsc: JavaSparkContext, + mean: Double, + std: Double, + size: Long): JavaDoubleRDD = { + JavaDoubleRDD.fromRDD(logNormalRDD(jsc.sc, mean, std, size)) + } + + /** * :: DeveloperApi :: * Generates an RDD comprised of i.i.d. samples produced by the input RandomDataGenerator. @@ -307,6 +477,72 @@ object RandomRDDs { normalVectorRDD(jsc.sc, numRows, numCols).toJavaRDD() } + /** + * Generates an RDD[Vector] with vectors containing i.i.d. samples drawn from a + * log normal distribution. + * + * @param sc SparkContext used to create the RDD. + * @param mean Mean of the log normal distribution. + * @param std Standard deviation of the log normal distribution. + * @param numRows Number of Vectors in the RDD. + * @param numCols Number of elements in each Vector. + * @param numPartitions Number of partitions in the RDD (default: `sc.defaultParallelism`). + * @param seed Random seed (default: a random long integer). + * @return RDD[Vector] with vectors containing i.i.d. samples. + */ + def logNormalVectorRDD( + sc: SparkContext, + mean: Double, + std: Double, + numRows: Long, + numCols: Int, + numPartitions: Int = 0, + seed: Long = Utils.random.nextLong()): RDD[Vector] = { + val logNormal = new LogNormalGenerator(mean, std) + randomVectorRDD(sc, logNormal, numRows, numCols, + numPartitionsOrDefault(sc, numPartitions), seed) + } + + /** + * Java-friendly version of [[RandomRDDs#logNormalVectorRDD]]. + */ + def logNormalJavaVectorRDD( + jsc: JavaSparkContext, + mean: Double, + std: Double, + numRows: Long, + numCols: Int, + numPartitions: Int, + seed: Long): JavaRDD[Vector] = { + logNormalVectorRDD(jsc.sc, mean, std, numRows, numCols, numPartitions, seed).toJavaRDD() + } + + /** + * [[RandomRDDs#logNormalJavaVectorRDD]] with the default seed. + */ + def logNormalJavaVectorRDD( + jsc: JavaSparkContext, + mean: Double, + std: Double, + numRows: Long, + numCols: Int, + numPartitions: Int): JavaRDD[Vector] = { + logNormalVectorRDD(jsc.sc, mean, std, numRows, numCols, numPartitions).toJavaRDD() + } + + /** + * [[RandomRDDs#logNormalJavaVectorRDD]] with the default number of partitions and + * the default seed. + */ + def logNormalJavaVectorRDD( + jsc: JavaSparkContext, + mean: Double, + std: Double, + numRows: Long, + numCols: Int): JavaRDD[Vector] = { + logNormalVectorRDD(jsc.sc, mean, std, numRows, numCols).toJavaRDD() + } + /** * Generates an RDD[Vector] with vectors containing i.i.d. samples drawn from the * Poisson distribution with the input mean. @@ -366,6 +602,133 @@ object RandomRDDs { poissonVectorRDD(jsc.sc, mean, numRows, numCols).toJavaRDD() } + /** + * Generates an RDD[Vector] with vectors containing i.i.d. samples drawn from the + * exponential distribution with the input mean. + * + * @param sc SparkContext used to create the RDD. + * @param mean Mean, or 1 / lambda, for the Exponential distribution. + * @param numRows Number of Vectors in the RDD. + * @param numCols Number of elements in each Vector. + * @param numPartitions Number of partitions in the RDD (default: `sc.defaultParallelism`) + * @param seed Random seed (default: a random long integer). + * @return RDD[Vector] with vectors containing i.i.d. samples ~ Exp(mean). + */ + def exponentialVectorRDD( + sc: SparkContext, + mean: Double, + numRows: Long, + numCols: Int, + numPartitions: Int = 0, + seed: Long = Utils.random.nextLong()): RDD[Vector] = { + val exponential = new ExponentialGenerator(mean) + randomVectorRDD(sc, exponential, numRows, numCols, + numPartitionsOrDefault(sc, numPartitions), seed) + } + + /** + * Java-friendly version of [[RandomRDDs#exponentialVectorRDD]]. + */ + def exponentialJavaVectorRDD( + jsc: JavaSparkContext, + mean: Double, + numRows: Long, + numCols: Int, + numPartitions: Int, + seed: Long): JavaRDD[Vector] = { + exponentialVectorRDD(jsc.sc, mean, numRows, numCols, numPartitions, seed).toJavaRDD() + } + + /** + * [[RandomRDDs#exponentialJavaVectorRDD]] with the default seed. + */ + def exponentialJavaVectorRDD( + jsc: JavaSparkContext, + mean: Double, + numRows: Long, + numCols: Int, + numPartitions: Int): JavaRDD[Vector] = { + exponentialVectorRDD(jsc.sc, mean, numRows, numCols, numPartitions).toJavaRDD() + } + + /** + * [[RandomRDDs#exponentialJavaVectorRDD]] with the default number of partitions + * and the default seed. + */ + def exponentialJavaVectorRDD( + jsc: JavaSparkContext, + mean: Double, + numRows: Long, + numCols: Int): JavaRDD[Vector] = { + exponentialVectorRDD(jsc.sc, mean, numRows, numCols).toJavaRDD() + } + + + /** + * Generates an RDD[Vector] with vectors containing i.i.d. samples drawn from the + * gamma distribution with the input shape and scale. + * + * @param sc SparkContext used to create the RDD. + * @param shape shape parameter (> 0) for the gamma distribution. + * @param scale scale parameter (> 0) for the gamma distribution. + * @param numRows Number of Vectors in the RDD. + * @param numCols Number of elements in each Vector. + * @param numPartitions Number of partitions in the RDD (default: `sc.defaultParallelism`) + * @param seed Random seed (default: a random long integer). + * @return RDD[Vector] with vectors containing i.i.d. samples ~ Exp(mean). + */ + def gammaVectorRDD( + sc: SparkContext, + shape: Double, + scale: Double, + numRows: Long, + numCols: Int, + numPartitions: Int = 0, + seed: Long = Utils.random.nextLong()): RDD[Vector] = { + val gamma = new GammaGenerator(shape, scale) + randomVectorRDD(sc, gamma, numRows, numCols, numPartitionsOrDefault(sc, numPartitions), seed) + } + + /** + * Java-friendly version of [[RandomRDDs#gammaVectorRDD]]. + */ + def gammaJavaVectorRDD( + jsc: JavaSparkContext, + shape: Double, + scale: Double, + numRows: Long, + numCols: Int, + numPartitions: Int, + seed: Long): JavaRDD[Vector] = { + gammaVectorRDD(jsc.sc, shape, scale, numRows, numCols, numPartitions, seed).toJavaRDD() + } + + /** + * [[RandomRDDs#gammaJavaVectorRDD]] with the default seed. + */ + def gammaJavaVectorRDD( + jsc: JavaSparkContext, + shape: Double, + scale: Double, + numRows: Long, + numCols: Int, + numPartitions: Int): JavaRDD[Vector] = { + gammaVectorRDD(jsc.sc, shape, scale, numRows, numCols, numPartitions).toJavaRDD() + } + + /** + * [[RandomRDDs#gammaJavaVectorRDD]] with the default number of partitions and the default seed. + */ + def gammaJavaVectorRDD( + jsc: JavaSparkContext, + shape: Double, + scale: Double, + numRows: Long, + numCols: Int): JavaRDD[Vector] = { + gammaVectorRDD(jsc.sc, shape, scale, numRows, numCols).toJavaRDD() + } + + /** * :: DeveloperApi :: * Generates an RDD[Vector] with vectors containing i.i.d. samples produced by the diff --git a/mllib/src/test/java/org/apache/spark/mllib/random/JavaRandomRDDsSuite.java b/mllib/src/test/java/org/apache/spark/mllib/random/JavaRandomRDDsSuite.java index a725736ca1a58..fcc13c00cbdc5 100644 --- a/mllib/src/test/java/org/apache/spark/mllib/random/JavaRandomRDDsSuite.java +++ b/mllib/src/test/java/org/apache/spark/mllib/random/JavaRandomRDDsSuite.java @@ -69,6 +69,21 @@ public void testNormalRDD() { } } + @Test + public void testLNormalRDD() { + double mean = 4.0; + double std = 2.0; + long m = 1000L; + int p = 2; + long seed = 1L; + JavaDoubleRDD rdd1 = logNormalJavaRDD(sc, mean, std, m); + JavaDoubleRDD rdd2 = logNormalJavaRDD(sc, mean, std, m, p); + JavaDoubleRDD rdd3 = logNormalJavaRDD(sc, mean, std, m, p, seed); + for (JavaDoubleRDD rdd: Lists.newArrayList(rdd1, rdd2, rdd3)) { + Assert.assertEquals(m, rdd.count()); + } + } + @Test public void testPoissonRDD() { double mean = 2.0; @@ -83,6 +98,36 @@ public void testPoissonRDD() { } } + @Test + public void testExponentialRDD() { + double mean = 2.0; + long m = 1000L; + int p = 2; + long seed = 1L; + JavaDoubleRDD rdd1 = exponentialJavaRDD(sc, mean, m); + JavaDoubleRDD rdd2 = exponentialJavaRDD(sc, mean, m, p); + JavaDoubleRDD rdd3 = exponentialJavaRDD(sc, mean, m, p, seed); + for (JavaDoubleRDD rdd: Lists.newArrayList(rdd1, rdd2, rdd3)) { + Assert.assertEquals(m, rdd.count()); + } + } + + @Test + public void testGammaRDD() { + double shape = 1.0; + double scale = 2.0; + long m = 1000L; + int p = 2; + long seed = 1L; + JavaDoubleRDD rdd1 = gammaJavaRDD(sc, shape, scale, m); + JavaDoubleRDD rdd2 = gammaJavaRDD(sc, shape, scale, m, p); + JavaDoubleRDD rdd3 = gammaJavaRDD(sc, shape, scale, m, p, seed); + for (JavaDoubleRDD rdd: Lists.newArrayList(rdd1, rdd2, rdd3)) { + Assert.assertEquals(m, rdd.count()); + } + } + + @Test @SuppressWarnings("unchecked") public void testUniformVectorRDD() { @@ -115,6 +160,24 @@ public void testNormalVectorRDD() { } } + @Test + @SuppressWarnings("unchecked") + public void testLogNormalVectorRDD() { + double mean = 4.0; + double std = 2.0; + long m = 100L; + int n = 10; + int p = 2; + long seed = 1L; + JavaRDD rdd1 = logNormalJavaVectorRDD(sc, mean, std, m, n); + JavaRDD rdd2 = logNormalJavaVectorRDD(sc, mean, std, m, n, p); + JavaRDD rdd3 = logNormalJavaVectorRDD(sc, mean, std, m, n, p, seed); + for (JavaRDD rdd: Lists.newArrayList(rdd1, rdd2, rdd3)) { + Assert.assertEquals(m, rdd.count()); + Assert.assertEquals(n, rdd.first().size()); + } + } + @Test @SuppressWarnings("unchecked") public void testPoissonVectorRDD() { @@ -131,4 +194,40 @@ public void testPoissonVectorRDD() { Assert.assertEquals(n, rdd.first().size()); } } + + @Test + @SuppressWarnings("unchecked") + public void testExponentialVectorRDD() { + double mean = 2.0; + long m = 100L; + int n = 10; + int p = 2; + long seed = 1L; + JavaRDD rdd1 = exponentialJavaVectorRDD(sc, mean, m, n); + JavaRDD rdd2 = exponentialJavaVectorRDD(sc, mean, m, n, p); + JavaRDD rdd3 = exponentialJavaVectorRDD(sc, mean, m, n, p, seed); + for (JavaRDD rdd: Lists.newArrayList(rdd1, rdd2, rdd3)) { + Assert.assertEquals(m, rdd.count()); + Assert.assertEquals(n, rdd.first().size()); + } + } + + @Test + @SuppressWarnings("unchecked") + public void testGammaVectorRDD() { + double shape = 1.0; + double scale = 2.0; + long m = 100L; + int n = 10; + int p = 2; + long seed = 1L; + JavaRDD rdd1 = gammaJavaVectorRDD(sc, shape, scale, m, n); + JavaRDD rdd2 = gammaJavaVectorRDD(sc, shape, scale, m, n, p); + JavaRDD rdd3 = gammaJavaVectorRDD(sc, shape, scale, m, n, p, seed); + for (JavaRDD rdd: Lists.newArrayList(rdd1, rdd2, rdd3)) { + Assert.assertEquals(m, rdd.count()); + Assert.assertEquals(n, rdd.first().size()); + } + } + } diff --git a/mllib/src/test/scala/org/apache/spark/mllib/random/RandomDataGeneratorSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/random/RandomDataGeneratorSuite.scala index 3df7c128af5ab..b792d819fdabb 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/random/RandomDataGeneratorSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/random/RandomDataGeneratorSuite.scala @@ -17,6 +17,8 @@ package org.apache.spark.mllib.random +import scala.math + import org.scalatest.FunSuite import org.apache.spark.util.StatCounter @@ -25,7 +27,6 @@ import org.apache.spark.util.StatCounter class RandomDataGeneratorSuite extends FunSuite { def apiChecks(gen: RandomDataGenerator[Double]) { - // resetting seed should generate the same sequence of random numbers gen.setSeed(42L) val array1 = (0 until 1000).map(_ => gen.nextValue()) @@ -79,6 +80,26 @@ class RandomDataGeneratorSuite extends FunSuite { distributionChecks(normal, 0.0, 1.0) } + test("LogNormalGenerator") { + List((0.0, 1.0), (0.0, 2.0), (2.0, 1.0), (2.0, 2.0)).map { + case (mean: Double, vari: Double) => + val normal = new LogNormalGenerator(mean, math.sqrt(vari)) + apiChecks(normal) + + // mean of log normal = e^(mean + var / 2) + val expectedMean = math.exp(mean + 0.5 * vari) + + // variance of log normal = (e^var - 1) * e^(2 * mean + var) + val expectedStd = math.sqrt((math.exp(vari) - 1.0) * math.exp(2.0 * mean + vari)) + + // since sampling error increases with variance, let's set + // the absolute tolerance as a percentage + val epsilon = 0.05 * expectedStd * expectedStd + + distributionChecks(normal, expectedMean, expectedStd, epsilon) + } + } + test("PoissonGenerator") { // mean = 0.0 will not pass the API checks since 0.0 is always deterministically produced. for (mean <- List(1.0, 5.0, 100.0)) { @@ -87,4 +108,33 @@ class RandomDataGeneratorSuite extends FunSuite { distributionChecks(poisson, mean, math.sqrt(mean), 0.1) } } + + test("ExponentialGenerator") { + // mean = 0.0 will not pass the API checks since 0.0 is always deterministically produced. + for (mean <- List(2.0, 5.0, 10.0, 50.0, 100.0)) { + val exponential = new ExponentialGenerator(mean) + apiChecks(exponential) + // var of exp = lambda^-2 = (1.0 / mean)^-2 = mean^2 + + // since sampling error increases with variance, let's set + // the absolute tolerance as a percentage + val epsilon = 0.05 * mean * mean + + distributionChecks(exponential, mean, mean, epsilon) + } + } + + test("GammaGenerator") { + // mean = 0.0 will not pass the API checks since 0.0 is always deterministically produced. + List((1.0, 2.0), (2.0, 2.0), (3.0, 2.0), (5.0, 1.0), (9.0, 0.5)).map { + case (shape: Double, scale: Double) => + val gamma = new GammaGenerator(shape, scale) + apiChecks(gamma) + // mean of gamma = shape * scale + val expectedMean = shape * scale + // var of gamma = shape * scale^2 + val expectedStd = math.sqrt(shape * scale * scale) + distributionChecks(gamma, expectedMean, expectedStd, 0.1) + } + } } diff --git a/mllib/src/test/scala/org/apache/spark/mllib/random/RandomRDDsSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/random/RandomRDDsSuite.scala index ea5889b3ecd5e..6395188a0842a 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/random/RandomRDDsSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/random/RandomRDDsSuite.scala @@ -110,7 +110,19 @@ class RandomRDDsSuite extends FunSuite with MLlibTestSparkContext with Serializa test("randomRDD for different distributions") { val size = 100000L val numPartitions = 10 + + // mean of log normal = e^(mean + var / 2) + val logNormalMean = math.exp(0.5) + // variance of log normal = (e^var - 1) * e^(2 * mean + var) + val logNormalStd = math.sqrt((math.E - 1.0) * math.E) + val gammaScale = 1.0 + val gammaShape = 2.0 + // mean of gamma = shape * scale + val gammaMean = gammaShape * gammaScale + // var of gamma = shape * scale^2 + val gammaStd = math.sqrt(gammaShape * gammaScale * gammaScale) val poissonMean = 100.0 + val exponentialMean = 1.0 for (seed <- 0 until 5) { val uniform = RandomRDDs.uniformRDD(sc, size, numPartitions, seed) @@ -119,8 +131,18 @@ class RandomRDDsSuite extends FunSuite with MLlibTestSparkContext with Serializa val normal = RandomRDDs.normalRDD(sc, size, numPartitions, seed) testGeneratedRDD(normal, size, numPartitions, 0.0, 1.0) + val logNormal = RandomRDDs.logNormalRDD(sc, 0.0, 1.0, size, numPartitions, seed) + testGeneratedRDD(logNormal, size, numPartitions, logNormalMean, logNormalStd, 0.1) + val poisson = RandomRDDs.poissonRDD(sc, poissonMean, size, numPartitions, seed) testGeneratedRDD(poisson, size, numPartitions, poissonMean, math.sqrt(poissonMean), 0.1) + + val exponential = RandomRDDs.exponentialRDD(sc, exponentialMean, size, numPartitions, seed) + testGeneratedRDD(exponential, size, numPartitions, exponentialMean, exponentialMean, 0.1) + + val gamma = RandomRDDs.gammaRDD(sc, gammaShape, gammaScale, size, numPartitions, seed) + testGeneratedRDD(gamma, size, numPartitions, gammaMean, gammaStd, 0.1) + } // mock distribution to check that partitions have unique seeds @@ -132,7 +154,19 @@ class RandomRDDsSuite extends FunSuite with MLlibTestSparkContext with Serializa val rows = 1000L val cols = 100 val parts = 10 + + // mean of log normal = e^(mean + var / 2) + val logNormalMean = math.exp(0.5) + // variance of log normal = (e^var - 1) * e^(2 * mean + var) + val logNormalStd = math.sqrt((math.E - 1.0) * math.E) + val gammaScale = 1.0 + val gammaShape = 2.0 + // mean of gamma = shape * scale + val gammaMean = gammaShape * gammaScale + // var of gamma = shape * scale^2 + val gammaStd = math.sqrt(gammaShape * gammaScale * gammaScale) val poissonMean = 100.0 + val exponentialMean = 1.0 for (seed <- 0 until 5) { val uniform = RandomRDDs.uniformVectorRDD(sc, rows, cols, parts, seed) @@ -141,8 +175,17 @@ class RandomRDDsSuite extends FunSuite with MLlibTestSparkContext with Serializa val normal = RandomRDDs.normalVectorRDD(sc, rows, cols, parts, seed) testGeneratedVectorRDD(normal, rows, cols, parts, 0.0, 1.0) + val logNormal = RandomRDDs.logNormalVectorRDD(sc, 0.0, 1.0, rows, cols, parts, seed) + testGeneratedVectorRDD(logNormal, rows, cols, parts, logNormalMean, logNormalStd, 0.1) + val poisson = RandomRDDs.poissonVectorRDD(sc, poissonMean, rows, cols, parts, seed) testGeneratedVectorRDD(poisson, rows, cols, parts, poissonMean, math.sqrt(poissonMean), 0.1) + + val exponential = RandomRDDs.exponentialVectorRDD(sc, exponentialMean, rows, cols, parts, seed) + testGeneratedVectorRDD(exponential, rows, cols, parts, exponentialMean, exponentialMean, 0.1) + + val gamma = RandomRDDs.gammaVectorRDD(sc, gammaShape, gammaScale, rows, cols, parts, seed) + testGeneratedVectorRDD(gamma, rows, cols, parts, gammaMean, gammaStd, 0.1) } } } From d7fc69a8b5c92b2bbb71f95027e5283968cd0679 Mon Sep 17 00:00:00 2001 From: Liang-Chi Hsieh Date: Thu, 18 Dec 2014 21:41:02 -0800 Subject: [PATCH 054/320] [SPARK-4674] Refactor getCallSite The current version of `getCallSite` visits the collection of `StackTraceElement` twice. However, it is unnecessary since we can perform our work with a single visit. We also do not need to keep filtered `StackTraceElement`. Author: Liang-Chi Hsieh Closes #3532 from viirya/refactor_getCallSite and squashes the following commits: 62aa124 [Liang-Chi Hsieh] Fix style. e741017 [Liang-Chi Hsieh] Refactor getCallSite. --- .../scala/org/apache/spark/util/Utils.scala | 44 +++++++++---------- 1 file changed, 22 insertions(+), 22 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/util/Utils.scala b/core/src/main/scala/org/apache/spark/util/Utils.scala index 9c04e45a58479..d16233a0bc760 100644 --- a/core/src/main/scala/org/apache/spark/util/Utils.scala +++ b/core/src/main/scala/org/apache/spark/util/Utils.scala @@ -1024,13 +1024,6 @@ private[spark] object Utils extends Logging { * @param skipClass Function that is used to exclude non-user-code classes. */ def getCallSite(skipClass: String => Boolean = coreExclusionFunction): CallSite = { - val trace = Thread.currentThread.getStackTrace().filterNot { ste: StackTraceElement => - // When running under some profilers, the current stack trace might contain some bogus - // frames. This is intended to ensure that we don't crash in these situations by - // ignoring any frames that we can't examine. - ste == null || ste.getMethodName == null || ste.getMethodName.contains("getStackTrace") - } - // Keep crawling up the stack trace until we find the first function not inside of the spark // package. We track the last (shallowest) contiguous Spark method. This might be an RDD // transformation, a SparkContext function (such as parallelize), or anything else that leads @@ -1040,27 +1033,34 @@ private[spark] object Utils extends Logging { var firstUserLine = 0 var insideSpark = true var callStack = new ArrayBuffer[String]() :+ "" - - for (el <- trace) { - if (insideSpark) { - if (skipClass(el.getClassName)) { - lastSparkMethod = if (el.getMethodName == "") { - // Spark method is a constructor; get its class name - el.getClassName.substring(el.getClassName.lastIndexOf('.') + 1) + + Thread.currentThread.getStackTrace().foreach { ste: StackTraceElement => + // When running under some profilers, the current stack trace might contain some bogus + // frames. This is intended to ensure that we don't crash in these situations by + // ignoring any frames that we can't examine. + if (ste != null && ste.getMethodName != null + && !ste.getMethodName.contains("getStackTrace")) { + if (insideSpark) { + if (skipClass(ste.getClassName)) { + lastSparkMethod = if (ste.getMethodName == "") { + // Spark method is a constructor; get its class name + ste.getClassName.substring(ste.getClassName.lastIndexOf('.') + 1) + } else { + ste.getMethodName + } + callStack(0) = ste.toString // Put last Spark method on top of the stack trace. } else { - el.getMethodName + firstUserLine = ste.getLineNumber + firstUserFile = ste.getFileName + callStack += ste.toString + insideSpark = false } - callStack(0) = el.toString // Put last Spark method on top of the stack trace. } else { - firstUserLine = el.getLineNumber - firstUserFile = el.getFileName - callStack += el.toString - insideSpark = false + callStack += ste.toString } - } else { - callStack += el.toString } } + val callStackDepth = System.getProperty("spark.callstack.depth", "20").toInt CallSite( shortForm = s"$lastSparkMethod at $firstUserFile:$firstUserLine", From 283263ffaa941e7e9ba147cf0ad377d9202d3761 Mon Sep 17 00:00:00 2001 From: Sandy Ryza Date: Thu, 18 Dec 2014 22:40:44 -0800 Subject: [PATCH 055/320] SPARK-3428. TaskMetrics for running tasks is missing GC time metrics Author: Sandy Ryza Closes #3684 from sryza/sandy-spark-3428 and squashes the following commits: cb827fe [Sandy Ryza] SPARK-3428. TaskMetrics for running tasks is missing GC time metrics --- .../main/scala/org/apache/spark/executor/Executor.scala | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/executor/Executor.scala b/core/src/main/scala/org/apache/spark/executor/Executor.scala index 52de6980ecbf8..da030f231fde8 100644 --- a/core/src/main/scala/org/apache/spark/executor/Executor.scala +++ b/core/src/main/scala/org/apache/spark/executor/Executor.scala @@ -145,6 +145,8 @@ private[spark] class Executor( } } + private def gcTime = ManagementFactory.getGarbageCollectorMXBeans.map(_.getCollectionTime).sum + class TaskRunner( execBackend: ExecutorBackend, val taskId: Long, taskName: String, serializedTask: ByteBuffer) extends Runnable { @@ -152,6 +154,7 @@ private[spark] class Executor( @volatile private var killed = false @volatile var task: Task[Any] = _ @volatile var attemptedTask: Option[Task[Any]] = None + @volatile var startGCTime: Long = _ def kill(interruptThread: Boolean) { logInfo(s"Executor is trying to kill $taskName (TID $taskId)") @@ -168,8 +171,7 @@ private[spark] class Executor( logInfo(s"Running $taskName (TID $taskId)") execBackend.statusUpdate(taskId, TaskState.RUNNING, EMPTY_BYTE_BUFFER) var taskStart: Long = 0 - def gcTime = ManagementFactory.getGarbageCollectorMXBeans.map(_.getCollectionTime).sum - val startGCTime = gcTime + startGCTime = gcTime try { val (taskFiles, taskJars, taskBytes) = Task.deserializeWithDependencies(serializedTask) @@ -376,10 +378,13 @@ private[spark] class Executor( while (!isStopped) { val tasksMetrics = new ArrayBuffer[(Long, TaskMetrics)]() + val curGCTime = gcTime + for (taskRunner <- runningTasks.values()) { if (!taskRunner.attemptedTask.isEmpty) { Option(taskRunner.task).flatMap(_.metrics).foreach { metrics => metrics.updateShuffleReadMetrics + metrics.jvmGCTime = curGCTime - taskRunner.startGCTime if (isLocal) { // JobProgressListener will hold an reference of it during // onExecutorMetricsUpdate(), then JobProgressListener can not see From 5479450c45038ddb4485cd676f945a961f2420d8 Mon Sep 17 00:00:00 2001 From: Cheng Hao Date: Fri, 19 Dec 2014 08:04:41 -0800 Subject: [PATCH 056/320] [SPARK-4901] [SQL] Hot fix for ByteWritables.copyBytes HiveInspectors.scala failed in compiling with Hadoop 1, as the BytesWritable.copyBytes is not available in Hadoop 1. Author: Cheng Hao Closes #3742 from chenghao-intel/settable_oi_hotfix and squashes the following commits: bb04d1f [Cheng Hao] hot fix for ByteWritables.copyBytes --- .../scala/org/apache/spark/sql/hive/HiveInspectors.scala | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala index 06189341f827c..e1147478130dd 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala @@ -297,7 +297,13 @@ private[hive] trait HiveInspectors { case x: ByteObjectInspector if x.preferWritable() => x.get(data) case x: HiveDecimalObjectInspector => HiveShim.toCatalystDecimal(x, data) case x: BinaryObjectInspector if x.preferWritable() => - x.getPrimitiveWritableObject(data).copyBytes() + // BytesWritable.copyBytes() only available since Hadoop2 + // In order to keep backward-compatible, we have to copy the + // bytes with old apis + val bw = x.getPrimitiveWritableObject(data) + val result = new Array[Byte](bw.getLength()) + System.arraycopy(bw.getBytes(), 0, result, 0, bw.getLength()) + result case x: DateObjectInspector if x.preferWritable() => x.getPrimitiveWritableObject(data).get() // org.apache.hadoop.hive.serde2.io.TimestampWritable.set will reset current time object From 8e253ebbf8c5867bd6b626ca8f20699d71aa6ddb Mon Sep 17 00:00:00 2001 From: scwf Date: Fri, 19 Dec 2014 08:29:38 -0800 Subject: [PATCH 057/320] [Build] Remove spark-staging-1038 Author: scwf Closes #3743 from scwf/abc and squashes the following commits: 7d98bc8 [scwf] removing spark-staging-1038 --- pom.xml | 12 ------------ project/SparkBuild.scala | 2 -- 2 files changed, 14 deletions(-) diff --git a/pom.xml b/pom.xml index 9e6fe09d95bbe..4be8c220223f8 100644 --- a/pom.xml +++ b/pom.xml @@ -230,18 +230,6 @@ false - - - spark-staging-1038 - Spark 1.2.0 Staging (1038) - https://repository.apache.org/content/repositories/orgapachespark-1038/ - - true - - - false - - diff --git a/project/SparkBuild.scala b/project/SparkBuild.scala index ff8cf81b286af..f52074282e1f7 100644 --- a/project/SparkBuild.scala +++ b/project/SparkBuild.scala @@ -214,8 +214,6 @@ object OldDeps { def oldDepsSettings() = Defaults.coreDefaultSettings ++ Seq( name := "old-deps", scalaVersion := "2.10.4", - // TODO: remove this as soon as 1.2.0 is published on Maven central. - resolvers += "spark-staging-1038" at "https://repository.apache.org/content/repositories/orgapachespark-1038/", retrieveManaged := true, retrievePattern := "[type]s/[artifact](-[revision])(-[classifier]).[ext]", libraryDependencies := Seq("spark-streaming-mqtt", "spark-streaming-zeromq", From 336cd341ee449098a1db594592a44f5ab9200fa0 Mon Sep 17 00:00:00 2001 From: Reynold Xin Date: Fri, 19 Dec 2014 12:51:12 -0800 Subject: [PATCH 058/320] Small refactoring to pass SparkEnv into Executor rather than creating SparkEnv in Executor. This consolidates some code path and makes constructor arguments simpler for a few classes. Author: Reynold Xin Closes #3738 from rxin/sparkEnvDepRefactor and squashes the following commits: 82e02cc [Reynold Xin] Fixed couple bugs. 217062a [Reynold Xin] Code review feedback. bd00af7 [Reynold Xin] Small refactoring to pass SparkEnv into Executor rather than creating SparkEnv in Executor. --- .../scala/org/apache/spark/SparkEnv.scala | 26 ++++++-------- .../CoarseGrainedExecutorBackend.scala | 32 +++++++++-------- .../org/apache/spark/executor/Executor.scala | 36 ++++++------------- .../spark/executor/MesosExecutorBackend.scala | 10 ++++-- .../spark/scheduler/local/LocalBackend.scala | 11 +++--- 5 files changed, 52 insertions(+), 63 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/SparkEnv.scala b/core/src/main/scala/org/apache/spark/SparkEnv.scala index f4215f268a0d3..6656df44d3599 100644 --- a/core/src/main/scala/org/apache/spark/SparkEnv.scala +++ b/core/src/main/scala/org/apache/spark/SparkEnv.scala @@ -177,18 +177,18 @@ object SparkEnv extends Logging { hostname: String, port: Int, numCores: Int, - isLocal: Boolean, - actorSystem: ActorSystem = null): SparkEnv = { - create( + isLocal: Boolean): SparkEnv = { + val env = create( conf, executorId, hostname, port, isDriver = false, isLocal = isLocal, - defaultActorSystem = actorSystem, numUsableCores = numCores ) + SparkEnv.set(env) + env } /** @@ -202,7 +202,6 @@ object SparkEnv extends Logging { isDriver: Boolean, isLocal: Boolean, listenerBus: LiveListenerBus = null, - defaultActorSystem: ActorSystem = null, numUsableCores: Int = 0): SparkEnv = { // Listener bus is only used on the driver @@ -212,20 +211,17 @@ object SparkEnv extends Logging { val securityManager = new SecurityManager(conf) - // If an existing actor system is already provided, use it. - // This is the case when an executor is launched in coarse-grained mode. - val (actorSystem, boundPort) = - Option(defaultActorSystem) match { - case Some(as) => (as, port) - case None => - val actorSystemName = if (isDriver) driverActorSystemName else executorActorSystemName - AkkaUtils.createActorSystem(actorSystemName, hostname, port, conf, securityManager) - } + // Create the ActorSystem for Akka and get the port it binds to. + val (actorSystem, boundPort) = { + val actorSystemName = if (isDriver) driverActorSystemName else executorActorSystemName + AkkaUtils.createActorSystem(actorSystemName, hostname, port, conf, securityManager) + } // Figure out which port Akka actually bound to in case the original port is 0 or occupied. - // This is so that we tell the executors the correct port to connect to. if (isDriver) { conf.set("spark.driver.port", boundPort.toString) + } else { + conf.set("spark.executor.port", boundPort.toString) } // Create an instance of the class with the given name, possibly initializing it with our conf diff --git a/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala b/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala index 5f46f3b1f085e..c794a7bc3599e 100644 --- a/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala +++ b/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala @@ -21,7 +21,7 @@ import java.nio.ByteBuffer import scala.concurrent.Await -import akka.actor.{Actor, ActorSelection, ActorSystem, Props} +import akka.actor.{Actor, ActorSelection, Props} import akka.pattern.Patterns import akka.remote.{RemotingLifecycleEvent, DisassociatedEvent} @@ -38,8 +38,7 @@ private[spark] class CoarseGrainedExecutorBackend( executorId: String, hostPort: String, cores: Int, - sparkProperties: Seq[(String, String)], - actorSystem: ActorSystem) + env: SparkEnv) extends Actor with ActorLogReceive with ExecutorBackend with Logging { Utils.checkHostPort(hostPort, "Expected hostport") @@ -58,8 +57,7 @@ private[spark] class CoarseGrainedExecutorBackend( case RegisteredExecutor => logInfo("Successfully registered with driver") val (hostname, _) = Utils.parseHostPort(hostPort) - executor = new Executor(executorId, hostname, sparkProperties, cores, isLocal = false, - actorSystem) + executor = new Executor(executorId, hostname, env, isLocal = false) case RegisterExecutorFailed(message) => logError("Slave registration failed: " + message) @@ -70,7 +68,7 @@ private[spark] class CoarseGrainedExecutorBackend( logError("Received LaunchTask command but executor was null") System.exit(1) } else { - val ser = SparkEnv.get.closureSerializer.newInstance() + val ser = env.closureSerializer.newInstance() val taskDesc = ser.deserialize[TaskDescription](data.value) logInfo("Got assigned task " + taskDesc.taskId) executor.launchTask(this, taskDesc.taskId, taskDesc.name, taskDesc.serializedTask) @@ -128,21 +126,25 @@ private[spark] object CoarseGrainedExecutorBackend extends Logging { Seq[(String, String)](("spark.app.id", appId)) fetcher.shutdown() - // Create a new ActorSystem using driver's Spark properties to run the backend. + // Create SparkEnv using properties we fetched from the driver. val driverConf = new SparkConf().setAll(props) - val (actorSystem, boundPort) = AkkaUtils.createActorSystem( - SparkEnv.executorActorSystemName, - hostname, port, driverConf, new SecurityManager(driverConf)) - // set it + val env = SparkEnv.createExecutorEnv( + driverConf, executorId, hostname, port, cores, isLocal = false) + + // SparkEnv sets spark.driver.port so it shouldn't be 0 anymore. + val boundPort = env.conf.getInt("spark.executor.port", 0) + assert(boundPort != 0) + + // Start the CoarseGrainedExecutorBackend actor. val sparkHostPort = hostname + ":" + boundPort - actorSystem.actorOf( + env.actorSystem.actorOf( Props(classOf[CoarseGrainedExecutorBackend], - driverUrl, executorId, sparkHostPort, cores, props, actorSystem), + driverUrl, executorId, sparkHostPort, cores, env), name = "Executor") workerUrl.foreach { url => - actorSystem.actorOf(Props(classOf[WorkerWatcher], url), name = "WorkerWatcher") + env.actorSystem.actorOf(Props(classOf[WorkerWatcher], url), name = "WorkerWatcher") } - actorSystem.awaitTermination() + env.actorSystem.awaitTermination() } } diff --git a/core/src/main/scala/org/apache/spark/executor/Executor.scala b/core/src/main/scala/org/apache/spark/executor/Executor.scala index da030f231fde8..0f99cd9f3b08a 100644 --- a/core/src/main/scala/org/apache/spark/executor/Executor.scala +++ b/core/src/main/scala/org/apache/spark/executor/Executor.scala @@ -26,7 +26,7 @@ import scala.collection.JavaConversions._ import scala.collection.mutable.{ArrayBuffer, HashMap} import scala.util.control.NonFatal -import akka.actor.{Props, ActorSystem} +import akka.actor.Props import org.apache.spark._ import org.apache.spark.deploy.SparkHadoopUtil @@ -42,10 +42,8 @@ import org.apache.spark.util.{SparkUncaughtExceptionHandler, AkkaUtils, Utils} private[spark] class Executor( executorId: String, slaveHostname: String, - properties: Seq[(String, String)], - numCores: Int, - isLocal: Boolean = false, - actorSystem: ActorSystem = null) + env: SparkEnv, + isLocal: Boolean = false) extends Logging { // Application dependencies (added through SparkContext) that we've fetched so far on this node. @@ -55,6 +53,8 @@ private[spark] class Executor( private val EMPTY_BYTE_BUFFER = ByteBuffer.wrap(new Array[Byte](0)) + private val conf = env.conf + @volatile private var isStopped = false // No ip or host:port - just hostname @@ -65,10 +65,6 @@ private[spark] class Executor( // Make sure the local hostname we report matches the cluster scheduler's name for this host Utils.setCustomHostname(slaveHostname) - // Set spark.* properties from executor arg - val conf = new SparkConf(true) - conf.setAll(properties) - if (!isLocal) { // Setup an uncaught exception handler for non-local mode. // Make any thread terminations due to uncaught exceptions kill the entire @@ -77,21 +73,11 @@ private[spark] class Executor( } val executorSource = new ExecutorSource(this, executorId) - - // Initialize Spark environment (using system properties read above) conf.set("spark.executor.id", executorId) - private val env = { - if (!isLocal) { - val port = conf.getInt("spark.executor.port", 0) - val _env = SparkEnv.createExecutorEnv( - conf, executorId, slaveHostname, port, numCores, isLocal, actorSystem) - SparkEnv.set(_env) - _env.metricsSystem.registerSource(executorSource) - _env.blockManager.initialize(conf.getAppId) - _env - } else { - SparkEnv.get - } + + if (!isLocal) { + env.metricsSystem.registerSource(executorSource) + env.blockManager.initialize(conf.getAppId) } // Create an actor for receiving RPCs from the driver @@ -167,7 +153,7 @@ private[spark] class Executor( override def run() { val deserializeStartTime = System.currentTimeMillis() Thread.currentThread.setContextClassLoader(replClassLoader) - val ser = SparkEnv.get.closureSerializer.newInstance() + val ser = env.closureSerializer.newInstance() logInfo(s"Running $taskName (TID $taskId)") execBackend.statusUpdate(taskId, TaskState.RUNNING, EMPTY_BYTE_BUFFER) var taskStart: Long = 0 @@ -202,7 +188,7 @@ private[spark] class Executor( throw new TaskKilledException } - val resultSer = SparkEnv.get.serializer.newInstance() + val resultSer = env.serializer.newInstance() val beforeSerialization = System.currentTimeMillis() val valueBytes = resultSer.serialize(value) val afterSerialization = System.currentTimeMillis() diff --git a/core/src/main/scala/org/apache/spark/executor/MesosExecutorBackend.scala b/core/src/main/scala/org/apache/spark/executor/MesosExecutorBackend.scala index f15e6bc33fb41..a098d07bd8659 100644 --- a/core/src/main/scala/org/apache/spark/executor/MesosExecutorBackend.scala +++ b/core/src/main/scala/org/apache/spark/executor/MesosExecutorBackend.scala @@ -25,7 +25,7 @@ import org.apache.mesos.protobuf.ByteString import org.apache.mesos.{Executor => MesosExecutor, ExecutorDriver, MesosExecutorDriver, MesosNativeLibrary} import org.apache.mesos.Protos.{TaskStatus => MesosTaskStatus, _} -import org.apache.spark.{Logging, TaskState} +import org.apache.spark.{Logging, TaskState, SparkConf, SparkEnv} import org.apache.spark.TaskState.TaskState import org.apache.spark.deploy.SparkHadoopUtil import org.apache.spark.util.{SignalLogger, Utils} @@ -64,11 +64,15 @@ private[spark] class MesosExecutorBackend this.driver = driver val properties = Utils.deserialize[Array[(String, String)]](executorInfo.getData.toByteArray) ++ Seq[(String, String)](("spark.app.id", frameworkInfo.getId.getValue)) + val conf = new SparkConf(loadDefaults = true).setAll(properties) + val port = conf.getInt("spark.executor.port", 0) + val env = SparkEnv.createExecutorEnv( + conf, executorId, slaveInfo.getHostname, port, cpusPerTask, isLocal = false) + executor = new Executor( executorId, slaveInfo.getHostname, - properties, - cpusPerTask) + env) } override def launchTask(d: ExecutorDriver, taskInfo: TaskInfo) { diff --git a/core/src/main/scala/org/apache/spark/scheduler/local/LocalBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/local/LocalBackend.scala index a2f1f14264a99..b3bd3110ac809 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/local/LocalBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/local/LocalBackend.scala @@ -41,17 +41,18 @@ private case class StopExecutor() * and the TaskSchedulerImpl. */ private[spark] class LocalActor( - scheduler: TaskSchedulerImpl, - executorBackend: LocalBackend, - private val totalCores: Int) extends Actor with ActorLogReceive with Logging { + scheduler: TaskSchedulerImpl, + executorBackend: LocalBackend, + private val totalCores: Int) + extends Actor with ActorLogReceive with Logging { private var freeCores = totalCores private val localExecutorId = SparkContext.DRIVER_IDENTIFIER private val localExecutorHostname = "localhost" - val executor = new Executor( - localExecutorId, localExecutorHostname, scheduler.conf.getAll, totalCores, isLocal = true) + private val executor = new Executor( + localExecutorId, localExecutorHostname, SparkEnv.get, isLocal = true) override def receiveWithLogging = { case ReviveOffers => From cdb2c645ab769a8678dd81cff44a809fcfa4420b Mon Sep 17 00:00:00 2001 From: Ryan Williams Date: Fri, 19 Dec 2014 13:56:04 -0800 Subject: [PATCH 059/320] [SPARK-4889] update history server example cmds Author: Ryan Williams Closes #3736 from ryan-williams/hist and squashes the following commits: 421d8ff [Ryan Williams] add another random typo fix 76d6a4c [Ryan Williams] remove hdfs example a2d0f82 [Ryan Williams] code review feedback 9ca7629 [Ryan Williams] [SPARK-4889] update history server example cmds --- conf/metrics.properties.template | 4 ++-- .../org/apache/spark/deploy/history/HistoryServer.scala | 9 +++++---- 2 files changed, 7 insertions(+), 6 deletions(-) diff --git a/conf/metrics.properties.template b/conf/metrics.properties.template index 30bcab0c93302..96b6844f0aabb 100644 --- a/conf/metrics.properties.template +++ b/conf/metrics.properties.template @@ -77,8 +77,8 @@ # sample false Whether to show entire set of samples for histograms ('false' or 'true') # # * Default path is /metrics/json for all instances except the master. The master has two paths: -# /metrics/aplications/json # App information -# /metrics/master/json # Master information +# /metrics/applications/json # App information +# /metrics/master/json # Master information # org.apache.spark.metrics.sink.GraphiteSink # Name: Default: Description: diff --git a/core/src/main/scala/org/apache/spark/deploy/history/HistoryServer.scala b/core/src/main/scala/org/apache/spark/deploy/history/HistoryServer.scala index ce00c0ffd21e0..fa9bfe5426b6c 100644 --- a/core/src/main/scala/org/apache/spark/deploy/history/HistoryServer.scala +++ b/core/src/main/scala/org/apache/spark/deploy/history/HistoryServer.scala @@ -158,11 +158,12 @@ class HistoryServer( /** * The recommended way of starting and stopping a HistoryServer is through the scripts - * start-history-server.sh and stop-history-server.sh. The path to a base log directory - * is must be specified, while the requested UI port is optional. For example: + * start-history-server.sh and stop-history-server.sh. The path to a base log directory, + * as well as any other relevant history server configuration, should be specified via + * the $SPARK_HISTORY_OPTS environment variable. For example: * - * ./sbin/spark-history-server.sh /tmp/spark-events - * ./sbin/spark-history-server.sh hdfs://1.2.3.4:9000/spark-events + * export SPARK_HISTORY_OPTS="-Dspark.history.fs.logDirectory=/tmp/spark-events" + * ./sbin/start-history-server.sh * * This launches the HistoryServer as a Spark daemon. */ From 7981f969762e77f1752ef8f86c546d4fc32a1a4f Mon Sep 17 00:00:00 2001 From: Ryan Williams Date: Fri, 19 Dec 2014 15:24:41 -0800 Subject: [PATCH 060/320] =?UTF-8?q?[SPARK-4896]=20don=E2=80=99t=20redundan?= =?UTF-8?q?tly=20overwrite=20executor=20JAR=20deps?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Author: Ryan Williams Closes #2848 from ryan-williams/fetch-file and squashes the following commits: c14daff [Ryan Williams] Fix copy that was changed to a move inadvertently 8e39c16 [Ryan Williams] code review feedback 788ed41 [Ryan Williams] don’t redundantly overwrite executor JAR deps --- .../scala/org/apache/spark/util/Utils.scala | 170 +++++++++++------- 1 file changed, 107 insertions(+), 63 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/util/Utils.scala b/core/src/main/scala/org/apache/spark/util/Utils.scala index d16233a0bc760..5e1cb0c7a7712 100644 --- a/core/src/main/scala/org/apache/spark/util/Utils.scala +++ b/core/src/main/scala/org/apache/spark/util/Utils.scala @@ -385,16 +385,12 @@ private[spark] object Utils extends Logging { } finally { lock.release() } - if (targetFile.exists && !Files.equal(cachedFile, targetFile)) { - if (conf.getBoolean("spark.files.overwrite", false)) { - targetFile.delete() - logInfo((s"File $targetFile exists and does not match contents of $url, " + - s"replacing it with $url")) - } else { - throw new SparkException(s"File $targetFile exists and does not match contents of $url") - } - } - Files.copy(cachedFile, targetFile) + copyFile( + url, + cachedFile, + targetFile, + conf.getBoolean("spark.files.overwrite", false) + ) } else { doFetchFile(url, targetDir, fileName, conf, securityMgr, hadoopConf) } @@ -411,6 +407,104 @@ private[spark] object Utils extends Logging { FileUtil.chmod(targetFile.getAbsolutePath, "a+x") } + /** + * Download `in` to `tempFile`, then move it to `destFile`. + * + * If `destFile` already exists: + * - no-op if its contents equal those of `sourceFile`, + * - throw an exception if `fileOverwrite` is false, + * - attempt to overwrite it otherwise. + * + * @param url URL that `sourceFile` originated from, for logging purposes. + * @param in InputStream to download. + * @param tempFile File path to download `in` to. + * @param destFile File path to move `tempFile` to. + * @param fileOverwrite Whether to delete/overwrite an existing `destFile` that does not match + * `sourceFile` + */ + private def downloadFile( + url: String, + in: InputStream, + tempFile: File, + destFile: File, + fileOverwrite: Boolean): Unit = { + + try { + val out = new FileOutputStream(tempFile) + Utils.copyStream(in, out, closeStreams = true) + copyFile(url, tempFile, destFile, fileOverwrite, removeSourceFile = true) + } finally { + // Catch-all for the couple of cases where for some reason we didn't move `tempFile` to + // `destFile`. + if (tempFile.exists()) { + tempFile.delete() + } + } + } + + /** + * Copy `sourceFile` to `destFile`. + * + * If `destFile` already exists: + * - no-op if its contents equal those of `sourceFile`, + * - throw an exception if `fileOverwrite` is false, + * - attempt to overwrite it otherwise. + * + * @param url URL that `sourceFile` originated from, for logging purposes. + * @param sourceFile File path to copy/move from. + * @param destFile File path to copy/move to. + * @param fileOverwrite Whether to delete/overwrite an existing `destFile` that does not match + * `sourceFile` + * @param removeSourceFile Whether to remove `sourceFile` after / as part of moving/copying it to + * `destFile`. + */ + private def copyFile( + url: String, + sourceFile: File, + destFile: File, + fileOverwrite: Boolean, + removeSourceFile: Boolean = false): Unit = { + + if (destFile.exists) { + if (!Files.equal(sourceFile, destFile)) { + if (fileOverwrite) { + logInfo( + s"File $destFile exists and does not match contents of $url, replacing it with $url" + ) + if (!destFile.delete()) { + throw new SparkException( + "Failed to delete %s while attempting to overwrite it with %s".format( + destFile.getAbsolutePath, + sourceFile.getAbsolutePath + ) + ) + } + } else { + throw new SparkException( + s"File $destFile exists and does not match contents of $url") + } + } else { + // Do nothing if the file contents are the same, i.e. this file has been copied + // previously. + logInfo( + "%s has been previously copied to %s".format( + sourceFile.getAbsolutePath, + destFile.getAbsolutePath + ) + ) + return + } + } + + // The file does not exist in the target directory. Copy or move it there. + if (removeSourceFile) { + Files.move(sourceFile, destFile) + } else { + logInfo(s"Copying ${sourceFile.getAbsolutePath} to ${destFile.getAbsolutePath}") + Files.copy(sourceFile, destFile) + } + } + /** * Download a file to target directory. Supports fetching the file in a variety of ways, * including HTTP, HDFS and files on a standard filesystem, based on the URL parameter. @@ -449,67 +543,17 @@ private[spark] object Utils extends Logging { uc.setReadTimeout(timeout) uc.connect() val in = uc.getInputStream() - val out = new FileOutputStream(tempFile) - Utils.copyStream(in, out, closeStreams = true) - if (targetFile.exists && !Files.equal(tempFile, targetFile)) { - if (fileOverwrite) { - targetFile.delete() - logInfo(("File %s exists and does not match contents of %s, " + - "replacing it with %s").format(targetFile, url, url)) - } else { - tempFile.delete() - throw new SparkException( - "File " + targetFile + " exists and does not match contents of" + " " + url) - } - } - Files.move(tempFile, targetFile) + downloadFile(url, in, tempFile, targetFile, fileOverwrite) case "file" => // In the case of a local file, copy the local file to the target directory. // Note the difference between uri vs url. val sourceFile = if (uri.isAbsolute) new File(uri) else new File(url) - var shouldCopy = true - if (targetFile.exists) { - if (!Files.equal(sourceFile, targetFile)) { - if (fileOverwrite) { - targetFile.delete() - logInfo(("File %s exists and does not match contents of %s, " + - "replacing it with %s").format(targetFile, url, url)) - } else { - throw new SparkException( - "File " + targetFile + " exists and does not match contents of" + " " + url) - } - } else { - // Do nothing if the file contents are the same, i.e. this file has been copied - // previously. - logInfo(sourceFile.getAbsolutePath + " has been previously copied to " - + targetFile.getAbsolutePath) - shouldCopy = false - } - } - - if (shouldCopy) { - // The file does not exist in the target directory. Copy it there. - logInfo("Copying " + sourceFile.getAbsolutePath + " to " + targetFile.getAbsolutePath) - Files.copy(sourceFile, targetFile) - } + copyFile(url, sourceFile, targetFile, fileOverwrite) case _ => // Use the Hadoop filesystem library, which supports file://, hdfs://, s3://, and others val fs = getHadoopFileSystem(uri, hadoopConf) val in = fs.open(new Path(uri)) - val out = new FileOutputStream(tempFile) - Utils.copyStream(in, out, closeStreams = true) - if (targetFile.exists && !Files.equal(tempFile, targetFile)) { - if (fileOverwrite) { - targetFile.delete() - logInfo(("File %s exists and does not match contents of %s, " + - "replacing it with %s").format(targetFile, url, url)) - } else { - tempFile.delete() - throw new SparkException( - "File " + targetFile + " exists and does not match contents of" + " " + url) - } - } - Files.move(tempFile, targetFile) + downloadFile(url, in, tempFile, targetFile, fileOverwrite) } } From c28083f468685d468c4daa5ce336ef04fbec3144 Mon Sep 17 00:00:00 2001 From: Josh Rosen Date: Fri, 19 Dec 2014 17:02:37 -0800 Subject: [PATCH 061/320] [SPARK-4890] Upgrade Boto to 2.34.0; automatically download Boto from PyPi instead of packaging it This patch upgrades `spark-ec2`'s Boto version to 2.34.0, since this is blocking several features. Newer versions of Boto don't work properly when they're loaded from a zipfile since they try to read a JSON file from a path relative to the Boto library sources. Therefore, this patch also changes spark-ec2 to automatically download Boto from PyPi if it's not present in `SPARK_EC2_DIR/lib`, similar to what we do in the `sbt/sbt` script. This shouldn't ben an issue for users since they already need to have an internet connection to launch an EC2 cluster. By performing the downloading in spark_ec2.py instead of the Bash script, this should also work for Windows users. I've tested this with Python 2.6, too. Author: Josh Rosen Closes #3737 from JoshRosen/update-boto and squashes the following commits: 0aa43cc [Josh Rosen] Remove unused setup_standalone_cluster() method. f02935d [Josh Rosen] Enable Python deprecation warnings and fix one Boto warning: 587ae89 [Josh Rosen] [SPARK-4890] Upgrade Boto to 2.34.0; automatically download Boto from PyPi instead of packaging it --- ec2/spark-ec2 | 3 +-- ec2/spark_ec2.py | 48 +++++++++++++++++++++++++-------- ec2/third_party/boto-2.4.1.zip | Bin 860195 -> 0 bytes 3 files changed, 38 insertions(+), 13 deletions(-) delete mode 100644 ec2/third_party/boto-2.4.1.zip diff --git a/ec2/spark-ec2 b/ec2/spark-ec2 index 4aa908242eeaa..3abd3f396f605 100755 --- a/ec2/spark-ec2 +++ b/ec2/spark-ec2 @@ -22,5 +22,4 @@ #+ the underlying Python script. SPARK_EC2_DIR="$(dirname $0)" -PYTHONPATH="${SPARK_EC2_DIR}/third_party/boto-2.4.1.zip/boto-2.4.1:$PYTHONPATH" \ - python "${SPARK_EC2_DIR}/spark_ec2.py" "$@" +python -Wdefault "${SPARK_EC2_DIR}/spark_ec2.py" "$@" diff --git a/ec2/spark_ec2.py b/ec2/spark_ec2.py index 4e8f5c1f44041..556d99d1027b8 100755 --- a/ec2/spark_ec2.py +++ b/ec2/spark_ec2.py @@ -21,6 +21,7 @@ from __future__ import with_statement +import hashlib import logging import os import pipes @@ -29,6 +30,7 @@ import string import subprocess import sys +import tarfile import tempfile import time import urllib2 @@ -36,9 +38,6 @@ from datetime import datetime from optparse import OptionParser from sys import stderr -import boto -from boto.ec2.blockdevicemapping import BlockDeviceMapping, BlockDeviceType, EBSBlockDeviceType -from boto import ec2 DEFAULT_SPARK_VERSION = "1.1.0" SPARK_EC2_DIR = os.path.dirname(os.path.realpath(__file__)) @@ -48,6 +47,39 @@ AMI_PREFIX = "https://raw.github.com/mesos/spark-ec2/{b}/ami-list".format(b=MESOS_SPARK_EC2_BRANCH) +def setup_boto(): + # Download Boto if it's not already present in the SPARK_EC2_DIR/lib folder: + version = "boto-2.34.0" + md5 = "5556223d2d0cc4d06dd4829e671dcecd" + url = "https://pypi.python.org/packages/source/b/boto/%s.tar.gz" % version + lib_dir = os.path.join(SPARK_EC2_DIR, "lib") + if not os.path.exists(lib_dir): + os.mkdir(lib_dir) + boto_lib_dir = os.path.join(lib_dir, version) + if not os.path.isdir(boto_lib_dir): + tgz_file_path = os.path.join(lib_dir, "%s.tar.gz" % version) + print "Downloading Boto from PyPi" + download_stream = urllib2.urlopen(url) + with open(tgz_file_path, "wb") as tgz_file: + tgz_file.write(download_stream.read()) + with open(tgz_file_path) as tar: + if hashlib.md5(tar.read()).hexdigest() != md5: + print >> stderr, "ERROR: Got wrong md5sum for Boto" + sys.exit(1) + tar = tarfile.open(tgz_file_path) + tar.extractall(path=lib_dir) + tar.close() + os.remove(tgz_file_path) + print "Finished downloading Boto" + sys.path.insert(0, boto_lib_dir) + + +setup_boto() +import boto +from boto.ec2.blockdevicemapping import BlockDeviceMapping, BlockDeviceType, EBSBlockDeviceType +from boto import ec2 + + class UsageError(Exception): pass @@ -452,7 +484,7 @@ def launch_cluster(conn, opts, cluster_name): active_instance_ids.append(id_to_req[i].instance_id) if len(active_instance_ids) == opts.slaves: print "All %d slaves granted" % opts.slaves - reservations = conn.get_all_instances(active_instance_ids) + reservations = conn.get_all_reservations(active_instance_ids) slave_nodes = [] for r in reservations: slave_nodes += r.instances @@ -541,7 +573,7 @@ def launch_cluster(conn, opts, cluster_name): def get_existing_cluster(conn, opts, cluster_name, die_on_error=True): print "Searching for existing cluster " + cluster_name + "..." - reservations = conn.get_all_instances() + reservations = conn.get_all_reservations() master_nodes = [] slave_nodes = [] for res in reservations: @@ -618,12 +650,6 @@ def setup_cluster(conn, master_nodes, slave_nodes, opts, deploy_ssh_key): print "Done!" -def setup_standalone_cluster(master, slave_nodes, opts): - slave_ips = '\n'.join([i.public_dns_name for i in slave_nodes]) - ssh(master, opts, "echo \"%s\" > spark/conf/slaves" % (slave_ips)) - ssh(master, opts, "/root/spark/sbin/start-all.sh") - - def setup_spark_cluster(master, opts): ssh(master, opts, "chmod u+x spark-ec2/setup.sh") ssh(master, opts, "spark-ec2/setup.sh") diff --git a/ec2/third_party/boto-2.4.1.zip b/ec2/third_party/boto-2.4.1.zip deleted file mode 100644 index 49886b89aeaeaa87524c7808563008b0b2e9cc92..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 860195 zcma&N1CS`)wyjyVZQC|>*|u%lwr$(Ct9H3+mu=g2Rqy}4?!IyEd3|1IL}p}UWXxPM zB6H^W##~EY3K#?m;GgZ2r~cP}o&4ViXaF1lLpx_XS|&OcI!1aGWk>*E?(QZz(SRj6 z7k6j?K#(Uu000n_zqiZ(zdWt|qyE zp7uY&QPJ6Z7(vld(K)%2t!VrAMkjU*X-2CP=8r*kc~tvo}r8^YipLT$^-B 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zDd8V6#=krB@H7XgD4MHYB@FH&SlS1MjcohciXvdv_4=Nrp?`}|oD7p5aMFBkrK9H% zt#=@hwjh!z+*?3S9v~x*dE=t-TpsEv=n|96xmvI6SNJYGPJK+%ah;Jezn1Oj^A-o2 z;rgfpv?e)wC}(x&I2GL|6Z1P+k{W_-PZ6uB`Ckz)?qr; Date: Fri, 19 Dec 2014 18:21:15 -0800 Subject: [PATCH 062/320] [SPARK-2261] Make event logger use a single file. Currently the event logger uses a directory and several files to describe an app's event log, all but one of which are empty. This is not very HDFS-friendly, since creating lots of nodes in HDFS (especially when they don't contain any data) is frowned upon due to the node metadata being kept in the NameNode's memory. Instead, add a header section to the event log file that contains metadata needed to read the events. This metadata includes things like the Spark version (for future code that may need it for backwards compatibility) and the compression codec used for the event data. With the new approach, aside from reducing the load on the NN, there's also a lot less remote calls needed when reading the log directory. Author: Marcelo Vanzin Closes #1222 from vanzin/hist-server-single-log and squashes the following commits: cc8f5de [Marcelo Vanzin] Store header in plain text. c7e6123 [Marcelo Vanzin] Update comment. 59c561c [Marcelo Vanzin] Review feedback. 216c5a3 [Marcelo Vanzin] Review comments. dce28e9 [Marcelo Vanzin] Fix log overwrite test. f91c13e [Marcelo Vanzin] Handle "spark.eventLog.overwrite", and add unit test. 346f0b4 [Marcelo Vanzin] Review feedback. ed0023e [Marcelo Vanzin] Merge branch 'master' into hist-server-single-log 3f4500f [Marcelo Vanzin] Unit test for SPARK-3697. 45c7a1f [Marcelo Vanzin] Version of SPARK-3697 for this branch. b3ee30b [Marcelo Vanzin] Merge branch 'master' into hist-server-single-log a6d5c50 [Marcelo Vanzin] Merge branch 'master' into hist-server-single-log 16fd491 [Marcelo Vanzin] Use unique log directory for each codec. 0ef3f70 [Marcelo Vanzin] Merge branch 'master' into hist-server-single-log d93c44a [Marcelo Vanzin] Add a newline to make the header more readable. 9e928ba [Marcelo Vanzin] Add types. bd6ba8c [Marcelo Vanzin] Review feedback. a624a89 [Marcelo Vanzin] Merge branch 'master' into hist-server-single-log 04364dc [Marcelo Vanzin] Merge branch 'master' into hist-server-single-log bb7c2d3 [Marcelo Vanzin] Fix scalastyle warning. 16661a3 [Marcelo Vanzin] Simplify some internal code. cc6bce4 [Marcelo Vanzin] Some review feedback. a722184 [Marcelo Vanzin] Do not encode metadata in log file name. 3700586 [Marcelo Vanzin] Restore log flushing. f677930 [Marcelo Vanzin] Fix botched rebase. ae571fa [Marcelo Vanzin] Fix end-to-end event logger test. 9db0efd [Marcelo Vanzin] Show prettier name in UI. 8f42274 [Marcelo Vanzin] Make history server parse old-style log directories. 6251dd7 [Marcelo Vanzin] Make event logger use a single file. --- .../spark/deploy/ApplicationDescription.scala | 2 +- .../deploy/history/FsHistoryProvider.scala | 194 +++++++---- .../apache/spark/deploy/master/Master.scala | 46 +-- .../scheduler/EventLoggingListener.scala | 291 ++++++++++------ .../spark/scheduler/ReplayListenerBus.scala | 77 ++--- .../org/apache/spark/util/FileLogger.scala | 237 ------------- .../history/FsHistoryProviderSuite.scala | 185 ++++++++++ .../scheduler/EventLoggingListenerSuite.scala | 321 +++++------------- .../spark/scheduler/ReplayListenerSuite.scala | 82 +++-- .../apache/spark/util/FileLoggerSuite.scala | 169 --------- 10 files changed, 675 insertions(+), 929 deletions(-) delete mode 100644 core/src/main/scala/org/apache/spark/util/FileLogger.scala create mode 100644 core/src/test/scala/org/apache/spark/deploy/history/FsHistoryProviderSuite.scala delete mode 100644 core/src/test/scala/org/apache/spark/util/FileLoggerSuite.scala diff --git a/core/src/main/scala/org/apache/spark/deploy/ApplicationDescription.scala b/core/src/main/scala/org/apache/spark/deploy/ApplicationDescription.scala index 65a1a8fd7e929..b10b7b8d32523 100644 --- a/core/src/main/scala/org/apache/spark/deploy/ApplicationDescription.scala +++ b/core/src/main/scala/org/apache/spark/deploy/ApplicationDescription.scala @@ -23,7 +23,7 @@ private[spark] class ApplicationDescription( val memoryPerSlave: Int, val command: Command, var appUiUrl: String, - val eventLogDir: Option[String] = None) + val eventLogFile: Option[String] = None) extends Serializable { val user = System.getProperty("user.name", "") diff --git a/core/src/main/scala/org/apache/spark/deploy/history/FsHistoryProvider.scala b/core/src/main/scala/org/apache/spark/deploy/history/FsHistoryProvider.scala index 82a54dbfb5330..792d15b99ea0d 100644 --- a/core/src/main/scala/org/apache/spark/deploy/history/FsHistoryProvider.scala +++ b/core/src/main/scala/org/apache/spark/deploy/history/FsHistoryProvider.scala @@ -17,14 +17,16 @@ package org.apache.spark.deploy.history -import java.io.FileNotFoundException +import java.io.{BufferedInputStream, FileNotFoundException, InputStream} import scala.collection.mutable import org.apache.hadoop.fs.{FileStatus, Path} +import org.apache.hadoop.fs.permission.AccessControlException import org.apache.spark.{Logging, SecurityManager, SparkConf} import org.apache.spark.deploy.SparkHadoopUtil +import org.apache.spark.io.CompressionCodec import org.apache.spark.scheduler._ import org.apache.spark.ui.SparkUI import org.apache.spark.util.Utils @@ -64,6 +66,12 @@ private[history] class FsHistoryProvider(conf: SparkConf) extends ApplicationHis @volatile private var applications: mutable.LinkedHashMap[String, FsApplicationHistoryInfo] = new mutable.LinkedHashMap() + // Constants used to parse Spark 1.0.0 log directories. + private[history] val LOG_PREFIX = "EVENT_LOG_" + private[history] val SPARK_VERSION_PREFIX = "SPARK_VERSION_" + private[history] val COMPRESSION_CODEC_PREFIX = "COMPRESSION_CODEC_" + private[history] val APPLICATION_COMPLETE = "APPLICATION_COMPLETE" + /** * A background thread that periodically checks for event log updates on disk. * @@ -90,7 +98,7 @@ private[history] class FsHistoryProvider(conf: SparkConf) extends ApplicationHis initialize() - private def initialize() { + private def initialize(): Unit = { // Validate the log directory. val path = new Path(logDir) if (!fs.exists(path)) { @@ -106,8 +114,12 @@ private[history] class FsHistoryProvider(conf: SparkConf) extends ApplicationHis } checkForLogs() - logCheckingThread.setDaemon(true) - logCheckingThread.start() + + // Disable the background thread during tests. + if (!conf.contains("spark.testing")) { + logCheckingThread.setDaemon(true) + logCheckingThread.start() + } } override def getListing() = applications.values @@ -115,8 +127,7 @@ private[history] class FsHistoryProvider(conf: SparkConf) extends ApplicationHis override def getAppUI(appId: String): Option[SparkUI] = { try { applications.get(appId).map { info => - val (replayBus, appListener) = createReplayBus(fs.getFileStatus( - new Path(logDir, info.logDir))) + val replayBus = new ReplayListenerBus() val ui = { val conf = this.conf.clone() val appSecManager = new SecurityManager(conf) @@ -125,15 +136,17 @@ private[history] class FsHistoryProvider(conf: SparkConf) extends ApplicationHis // Do not call ui.bind() to avoid creating a new server for each application } - replayBus.replay() + val appListener = new ApplicationEventListener() + replayBus.addListener(appListener) + val appInfo = replay(fs.getFileStatus(new Path(logDir, info.logPath)), replayBus) - ui.setAppName(s"${appListener.appName.getOrElse(NOT_STARTED)} ($appId)") + ui.setAppName(s"${appInfo.name} ($appId)") val uiAclsEnabled = conf.getBoolean("spark.history.ui.acls.enable", false) ui.getSecurityManager.setAcls(uiAclsEnabled) // make sure to set admin acls before view acls so they are properly picked up ui.getSecurityManager.setAdminAcls(appListener.adminAcls.getOrElse("")) - ui.getSecurityManager.setViewAcls(appListener.sparkUser.getOrElse(NOT_STARTED), + ui.getSecurityManager.setViewAcls(appInfo.sparkUser, appListener.viewAcls.getOrElse("")) ui } @@ -149,41 +162,45 @@ private[history] class FsHistoryProvider(conf: SparkConf) extends ApplicationHis * Tries to reuse as much of the data already in memory as possible, by not reading * applications that haven't been updated since last time the logs were checked. */ - private def checkForLogs() = { + private[history] def checkForLogs(): Unit = { lastLogCheckTimeMs = getMonotonicTimeMs() logDebug("Checking for logs. Time is now %d.".format(lastLogCheckTimeMs)) - try { - val logStatus = fs.listStatus(new Path(logDir)) - val logDirs = if (logStatus != null) logStatus.filter(_.isDir).toSeq else Seq[FileStatus]() - // Load all new logs from the log directory. Only directories that have a modification time - // later than the last known log directory will be loaded. + try { var newLastModifiedTime = lastModifiedTime - val logInfos = logDirs - .filter { dir => - if (fs.isFile(new Path(dir.getPath(), EventLoggingListener.APPLICATION_COMPLETE))) { - val modTime = getModificationTime(dir) - newLastModifiedTime = math.max(newLastModifiedTime, modTime) - modTime > lastModifiedTime - } else { - false + val statusList = Option(fs.listStatus(new Path(logDir))).map(_.toSeq) + .getOrElse(Seq[FileStatus]()) + val logInfos = statusList + .filter { entry => + try { + val isFinishedApplication = + if (isLegacyLogDirectory(entry)) { + fs.exists(new Path(entry.getPath(), APPLICATION_COMPLETE)) + } else { + !entry.getPath().getName().endsWith(EventLoggingListener.IN_PROGRESS) + } + + if (isFinishedApplication) { + val modTime = getModificationTime(entry) + newLastModifiedTime = math.max(newLastModifiedTime, modTime) + modTime >= lastModifiedTime + } else { + false + } + } catch { + case e: AccessControlException => + // Do not use "logInfo" since these messages can get pretty noisy if printed on + // every poll. + logDebug(s"No permission to read $entry, ignoring.") + false } } - .flatMap { dir => + .flatMap { entry => try { - val (replayBus, appListener) = createReplayBus(dir) - replayBus.replay() - Some(new FsApplicationHistoryInfo( - dir.getPath().getName(), - appListener.appId.getOrElse(dir.getPath().getName()), - appListener.appName.getOrElse(NOT_STARTED), - appListener.startTime.getOrElse(-1L), - appListener.endTime.getOrElse(-1L), - getModificationTime(dir), - appListener.sparkUser.getOrElse(NOT_STARTED))) + Some(replay(entry, new ReplayListenerBus())) } catch { case e: Exception => - logInfo(s"Failed to load application log data from $dir.", e) + logError(s"Failed to load application log data from $entry.", e) None } } @@ -217,37 +234,100 @@ private[history] class FsHistoryProvider(conf: SparkConf) extends ApplicationHis applications = newApps } } catch { - case t: Throwable => logError("Exception in checking for event log updates", t) + case e: Exception => logError("Exception in checking for event log updates", e) } } - private def createReplayBus(logDir: FileStatus): (ReplayListenerBus, ApplicationEventListener) = { - val path = logDir.getPath() - val elogInfo = EventLoggingListener.parseLoggingInfo(path, fs) - val replayBus = new ReplayListenerBus(elogInfo.logPaths, fs, elogInfo.compressionCodec) - val appListener = new ApplicationEventListener - replayBus.addListener(appListener) - (replayBus, appListener) + /** + * Replays the events in the specified log file and returns information about the associated + * application. + */ + private def replay(eventLog: FileStatus, bus: ReplayListenerBus): FsApplicationHistoryInfo = { + val logPath = eventLog.getPath() + val (logInput, sparkVersion) = + if (isLegacyLogDirectory(eventLog)) { + openLegacyEventLog(logPath) + } else { + EventLoggingListener.openEventLog(logPath, fs) + } + try { + val appListener = new ApplicationEventListener + bus.addListener(appListener) + bus.replay(logInput, sparkVersion) + new FsApplicationHistoryInfo( + logPath.getName(), + appListener.appId.getOrElse(logPath.getName()), + appListener.appName.getOrElse(NOT_STARTED), + appListener.startTime.getOrElse(-1L), + appListener.endTime.getOrElse(-1L), + getModificationTime(eventLog), + appListener.sparkUser.getOrElse(NOT_STARTED)) + } finally { + logInput.close() + } } - /** Return when this directory was last modified. */ - private def getModificationTime(dir: FileStatus): Long = { - try { - val logFiles = fs.listStatus(dir.getPath) - if (logFiles != null && !logFiles.isEmpty) { - logFiles.map(_.getModificationTime).max - } else { - dir.getModificationTime + /** + * Loads a legacy log directory. This assumes that the log directory contains a single event + * log file (along with other metadata files), which is the case for directories generated by + * the code in previous releases. + * + * @return 2-tuple of (input stream of the events, version of Spark which wrote the log) + */ + private[history] def openLegacyEventLog(dir: Path): (InputStream, String) = { + val children = fs.listStatus(dir) + var eventLogPath: Path = null + var codecName: Option[String] = None + var sparkVersion: String = null + + children.foreach { child => + child.getPath().getName() match { + case name if name.startsWith(LOG_PREFIX) => + eventLogPath = child.getPath() + + case codec if codec.startsWith(COMPRESSION_CODEC_PREFIX) => + codecName = Some(codec.substring(COMPRESSION_CODEC_PREFIX.length())) + + case version if version.startsWith(SPARK_VERSION_PREFIX) => + sparkVersion = version.substring(SPARK_VERSION_PREFIX.length()) + + case _ => } - } catch { - case t: Throwable => - logError("Exception in accessing modification time of %s".format(dir.getPath), t) - -1L + } + + if (eventLogPath == null || sparkVersion == null) { + throw new IllegalArgumentException(s"$dir is not a Spark application log directory.") + } + + val codec = try { + codecName.map { c => CompressionCodec.createCodec(conf, c) } + } catch { + case e: Exception => + throw new IllegalArgumentException(s"Unknown compression codec $codecName.") + } + + val in = new BufferedInputStream(fs.open(eventLogPath)) + (codec.map(_.compressedInputStream(in)).getOrElse(in), sparkVersion) + } + + /** + * Return whether the specified event log path contains a old directory-based event log. + * Previously, the event log of an application comprises of multiple files in a directory. + * As of Spark 1.3, these files are consolidated into a single one that replaces the directory. + * See SPARK-2261 for more detail. + */ + private def isLegacyLogDirectory(entry: FileStatus): Boolean = entry.isDir() + + private def getModificationTime(fsEntry: FileStatus): Long = { + if (fsEntry.isDir) { + fs.listStatus(fsEntry.getPath).map(_.getModificationTime()).max + } else { + fsEntry.getModificationTime() } } /** Returns the system's mononotically increasing time. */ - private def getMonotonicTimeMs() = System.nanoTime() / (1000 * 1000) + private def getMonotonicTimeMs(): Long = System.nanoTime() / (1000 * 1000) } @@ -256,7 +336,7 @@ private object FsHistoryProvider { } private class FsApplicationHistoryInfo( - val logDir: String, + val logPath: String, id: String, name: String, startTime: Long, diff --git a/core/src/main/scala/org/apache/spark/deploy/master/Master.scala b/core/src/main/scala/org/apache/spark/deploy/master/Master.scala index 1f9f35d32059d..ed5eab9f473ce 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/Master.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/Master.scala @@ -17,6 +17,7 @@ package org.apache.spark.deploy.master +import java.io.FileNotFoundException import java.net.URLEncoder import java.text.SimpleDateFormat import java.util.Date @@ -32,6 +33,7 @@ import akka.pattern.ask import akka.remote.{DisassociatedEvent, RemotingLifecycleEvent} import akka.serialization.Serialization import akka.serialization.SerializationExtension +import org.apache.hadoop.fs.Path import org.apache.spark.{Logging, SecurityManager, SparkConf, SparkException} import org.apache.spark.deploy.{ApplicationDescription, DriverDescription, @@ -56,6 +58,7 @@ private[spark] class Master( import context.dispatcher // to use Akka's scheduler.schedule() val conf = new SparkConf + val hadoopConf = SparkHadoopUtil.get.newConfiguration(conf) def createDateFormat = new SimpleDateFormat("yyyyMMddHHmmss") // For application IDs val WORKER_TIMEOUT = conf.getLong("spark.worker.timeout", 60) * 1000 @@ -514,7 +517,7 @@ private[spark] class Master( val shuffledAliveWorkers = Random.shuffle(workers.toSeq.filter(_.state == WorkerState.ALIVE)) val numWorkersAlive = shuffledAliveWorkers.size var curPos = 0 - + for (driver <- waitingDrivers.toList) { // iterate over a copy of waitingDrivers // We assign workers to each waiting driver in a round-robin fashion. For each driver, we // start from the last worker that was assigned a driver, and continue onwards until we have @@ -711,41 +714,38 @@ private[spark] class Master( def rebuildSparkUI(app: ApplicationInfo): Boolean = { val appName = app.desc.name val notFoundBasePath = HistoryServer.UI_PATH_PREFIX + "/not-found" - val eventLogDir = app.desc.eventLogDir.getOrElse { + val eventLogFile = app.desc.eventLogFile.getOrElse { // Event logging is not enabled for this application app.desc.appUiUrl = notFoundBasePath return false } - val appEventLogDir = EventLoggingListener.getLogDirPath(eventLogDir, app.id) - val fileSystem = Utils.getHadoopFileSystem(appEventLogDir, - SparkHadoopUtil.get.newConfiguration(conf)) - val eventLogInfo = EventLoggingListener.parseLoggingInfo(appEventLogDir, fileSystem) - val eventLogPaths = eventLogInfo.logPaths - val compressionCodec = eventLogInfo.compressionCodec - - if (eventLogPaths.isEmpty) { - // Event logging is enabled for this application, but no event logs are found - val title = s"Application history not found (${app.id})" - var msg = s"No event logs found for application $appName in $appEventLogDir." - logWarning(msg) - msg += " Did you specify the correct logging directory?" - msg = URLEncoder.encode(msg, "UTF-8") - app.desc.appUiUrl = notFoundBasePath + s"?msg=$msg&title=$title" - return false - } - try { - val replayBus = new ReplayListenerBus(eventLogPaths, fileSystem, compressionCodec) + val fs = Utils.getHadoopFileSystem(eventLogFile, hadoopConf) + val (logInput, sparkVersion) = EventLoggingListener.openEventLog(new Path(eventLogFile), fs) + val replayBus = new ReplayListenerBus() val ui = SparkUI.createHistoryUI(new SparkConf, replayBus, new SecurityManager(conf), appName + " (completed)", HistoryServer.UI_PATH_PREFIX + s"/${app.id}") - replayBus.replay() + try { + replayBus.replay(logInput, sparkVersion) + } finally { + logInput.close() + } appIdToUI(app.id) = ui webUi.attachSparkUI(ui) // Application UI is successfully rebuilt, so link the Master UI to it - app.desc.appUiUrl = ui.getBasePath + app.desc.appUiUrl = ui.basePath true } catch { + case fnf: FileNotFoundException => + // Event logging is enabled for this application, but no event logs are found + val title = s"Application history not found (${app.id})" + var msg = s"No event logs found for application $appName in $eventLogFile." + logWarning(msg) + msg += " Did you specify the correct logging directory?" + msg = URLEncoder.encode(msg, "UTF-8") + app.desc.appUiUrl = notFoundBasePath + s"?msg=$msg&title=$title" + false case e: Exception => // Relay exception message to application UI page val title = s"Application history load error (${app.id})" diff --git a/core/src/main/scala/org/apache/spark/scheduler/EventLoggingListener.scala b/core/src/main/scala/org/apache/spark/scheduler/EventLoggingListener.scala index 597dbc884913c..27bf4f1599076 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/EventLoggingListener.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/EventLoggingListener.scala @@ -17,20 +17,23 @@ package org.apache.spark.scheduler +import java.io._ +import java.net.URI + import scala.collection.mutable import scala.collection.mutable.ArrayBuffer +import com.google.common.base.Charsets import org.apache.hadoop.conf.Configuration -import org.apache.hadoop.fs.{FileSystem, Path} +import org.apache.hadoop.fs.{FileSystem, FSDataOutputStream, Path} import org.apache.hadoop.fs.permission.FsPermission import org.json4s.JsonAST.JValue import org.json4s.jackson.JsonMethods._ -import org.apache.spark.{Logging, SparkConf, SparkContext} +import org.apache.spark.{Logging, SparkConf, SPARK_VERSION} import org.apache.spark.deploy.SparkHadoopUtil import org.apache.spark.io.CompressionCodec -import org.apache.spark.SPARK_VERSION -import org.apache.spark.util.{FileLogger, JsonProtocol, Utils} +import org.apache.spark.util.{JsonProtocol, Utils} /** * A SparkListener that logs events to persistent storage. @@ -58,36 +61,78 @@ private[spark] class EventLoggingListener( private val shouldOverwrite = sparkConf.getBoolean("spark.eventLog.overwrite", false) private val testing = sparkConf.getBoolean("spark.eventLog.testing", false) private val outputBufferSize = sparkConf.getInt("spark.eventLog.buffer.kb", 100) * 1024 - val logDir = EventLoggingListener.getLogDirPath(logBaseDir, appId) - val logDirName: String = logDir.split("/").last - protected val logger = new FileLogger(logDir, sparkConf, hadoopConf, outputBufferSize, - shouldCompress, shouldOverwrite, Some(LOG_FILE_PERMISSIONS)) + private val fileSystem = Utils.getHadoopFileSystem(new URI(logBaseDir), hadoopConf) + + // Only defined if the file system scheme is not local + private var hadoopDataStream: Option[FSDataOutputStream] = None + + // The Hadoop APIs have changed over time, so we use reflection to figure out + // the correct method to use to flush a hadoop data stream. See SPARK-1518 + // for details. + private val hadoopFlushMethod = { + val cls = classOf[FSDataOutputStream] + scala.util.Try(cls.getMethod("hflush")).getOrElse(cls.getMethod("sync")) + } + + private var writer: Option[PrintWriter] = None // For testing. Keep track of all JSON serialized events that have been logged. private[scheduler] val loggedEvents = new ArrayBuffer[JValue] + // Visible for tests only. + private[scheduler] val logPath = getLogPath(logBaseDir, appId) + /** - * Begin logging events. - * If compression is used, log a file that indicates which compression library is used. + * Creates the log file in the configured log directory. */ def start() { - logger.start() - logInfo("Logging events to %s".format(logDir)) - if (shouldCompress) { - val codec = - sparkConf.get("spark.io.compression.codec", CompressionCodec.DEFAULT_COMPRESSION_CODEC) - logger.newFile(COMPRESSION_CODEC_PREFIX + codec) + if (!fileSystem.isDirectory(new Path(logBaseDir))) { + throw new IllegalArgumentException(s"Log directory $logBaseDir does not exist.") + } + + val workingPath = logPath + IN_PROGRESS + val uri = new URI(workingPath) + val path = new Path(workingPath) + val defaultFs = FileSystem.getDefaultUri(hadoopConf).getScheme + val isDefaultLocal = defaultFs == null || defaultFs == "file" + + if (shouldOverwrite && fileSystem.exists(path)) { + logWarning(s"Event log $path already exists. Overwriting...") + fileSystem.delete(path, true) } - logger.newFile(SPARK_VERSION_PREFIX + SPARK_VERSION) - logger.newFile(LOG_PREFIX + logger.fileIndex) + + /* The Hadoop LocalFileSystem (r1.0.4) has known issues with syncing (HADOOP-7844). + * Therefore, for local files, use FileOutputStream instead. */ + val dstream = + if ((isDefaultLocal && uri.getScheme == null) || uri.getScheme == "file") { + new FileOutputStream(uri.getPath) + } else { + hadoopDataStream = Some(fileSystem.create(path)) + hadoopDataStream.get + } + + val compressionCodec = + if (shouldCompress) { + Some(CompressionCodec.createCodec(sparkConf)) + } else { + None + } + + fileSystem.setPermission(path, LOG_FILE_PERMISSIONS) + val logStream = initEventLog(new BufferedOutputStream(dstream, outputBufferSize), + compressionCodec) + writer = Some(new PrintWriter(logStream)) + + logInfo("Logging events to %s".format(logPath)) } /** Log the event as JSON. */ private def logEvent(event: SparkListenerEvent, flushLogger: Boolean = false) { val eventJson = JsonProtocol.sparkEventToJson(event) - logger.logLine(compact(render(eventJson))) + writer.foreach(_.println(compact(render(eventJson)))) if (flushLogger) { - logger.flush() + writer.foreach(_.flush()) + hadoopDataStream.foreach(hadoopFlushMethod.invoke(_)) } if (testing) { loggedEvents += eventJson @@ -123,130 +168,164 @@ private[spark] class EventLoggingListener( logEvent(event, flushLogger = true) override def onApplicationEnd(event: SparkListenerApplicationEnd) = logEvent(event, flushLogger = true) + // No-op because logging every update would be overkill override def onExecutorMetricsUpdate(event: SparkListenerExecutorMetricsUpdate) { } /** - * Stop logging events. - * In addition, create an empty special file to indicate application completion. + * Stop logging events. The event log file will be renamed so that it loses the + * ".inprogress" suffix. */ def stop() = { - logger.newFile(APPLICATION_COMPLETE) - logger.stop() + writer.foreach(_.close()) + + val target = new Path(logPath) + if (fileSystem.exists(target)) { + if (shouldOverwrite) { + logWarning(s"Event log $target already exists. Overwriting...") + fileSystem.delete(target, true) + } else { + throw new IOException("Target log file already exists (%s)".format(logPath)) + } + } + fileSystem.rename(new Path(logPath + IN_PROGRESS), target) } + } private[spark] object EventLoggingListener extends Logging { + // Suffix applied to the names of files still being written by applications. + val IN_PROGRESS = ".inprogress" val DEFAULT_LOG_DIR = "/tmp/spark-events" - val LOG_PREFIX = "EVENT_LOG_" - val SPARK_VERSION_PREFIX = "SPARK_VERSION_" - val COMPRESSION_CODEC_PREFIX = "COMPRESSION_CODEC_" - val APPLICATION_COMPLETE = "APPLICATION_COMPLETE" - val LOG_FILE_PERMISSIONS = new FsPermission(Integer.parseInt("770", 8).toShort) - // A cache for compression codecs to avoid creating the same codec many times - private val codecMap = new mutable.HashMap[String, CompressionCodec] + private val LOG_FILE_PERMISSIONS = new FsPermission(Integer.parseInt("770", 8).toShort) - def isEventLogFile(fileName: String): Boolean = { - fileName.startsWith(LOG_PREFIX) - } + // Marker for the end of header data in a log file. After this marker, log data, potentially + // compressed, will be found. + private val HEADER_END_MARKER = "=== LOG_HEADER_END ===" - def isSparkVersionFile(fileName: String): Boolean = { - fileName.startsWith(SPARK_VERSION_PREFIX) - } + // To avoid corrupted files causing the heap to fill up. Value is arbitrary. + private val MAX_HEADER_LINE_LENGTH = 4096 - def isCompressionCodecFile(fileName: String): Boolean = { - fileName.startsWith(COMPRESSION_CODEC_PREFIX) - } + // A cache for compression codecs to avoid creating the same codec many times + private val codecMap = new mutable.HashMap[String, CompressionCodec] - def isApplicationCompleteFile(fileName: String): Boolean = { - fileName == APPLICATION_COMPLETE - } + /** + * Write metadata about the event log to the given stream. + * + * The header is a serialized version of a map, except it does not use Java serialization to + * avoid incompatibilities between different JDKs. It writes one map entry per line, in + * "key=value" format. + * + * The very last entry in the header is the `HEADER_END_MARKER` marker, so that the parsing code + * can know when to stop. + * + * The format needs to be kept in sync with the openEventLog() method below. Also, it cannot + * change in new Spark versions without some other way of detecting the change (like some + * metadata encoded in the file name). + * + * @param logStream Raw output stream to the even log file. + * @param compressionCodec Optional compression codec to use. + * @return A stream where to write event log data. This may be a wrapper around the original + * stream (for example, when compression is enabled). + */ + def initEventLog( + logStream: OutputStream, + compressionCodec: Option[CompressionCodec]): OutputStream = { + val meta = mutable.HashMap(("version" -> SPARK_VERSION)) + compressionCodec.foreach { codec => + meta += ("compressionCodec" -> codec.getClass().getName()) + } - def parseSparkVersion(fileName: String): String = { - if (isSparkVersionFile(fileName)) { - fileName.replaceAll(SPARK_VERSION_PREFIX, "") - } else "" - } + def write(entry: String) = { + val bytes = entry.getBytes(Charsets.UTF_8) + if (bytes.length > MAX_HEADER_LINE_LENGTH) { + throw new IOException(s"Header entry too long: ${entry}") + } + logStream.write(bytes, 0, bytes.length) + } - def parseCompressionCodec(fileName: String): String = { - if (isCompressionCodecFile(fileName)) { - fileName.replaceAll(COMPRESSION_CODEC_PREFIX, "") - } else "" + meta.foreach { case (k, v) => write(s"$k=$v\n") } + write(s"$HEADER_END_MARKER\n") + compressionCodec.map(_.compressedOutputStream(logStream)).getOrElse(logStream) } /** - * Return a file-system-safe path to the log directory for the given application. + * Return a file-system-safe path to the log file for the given application. * - * @param logBaseDir A base directory for the path to the log directory for given application. + * @param logBaseDir Directory where the log file will be written. * @param appId A unique app ID. * @return A path which consists of file-system-safe characters. */ - def getLogDirPath(logBaseDir: String, appId: String): String = { + def getLogPath(logBaseDir: String, appId: String): String = { val name = appId.replaceAll("[ :/]", "-").replaceAll("[${}'\"]", "_").toLowerCase Utils.resolveURI(logBaseDir) + "/" + name.stripSuffix("/") } /** - * Parse the event logging information associated with the logs in the given directory. + * Opens an event log file and returns an input stream to the event data. * - * Specifically, this looks for event log files, the Spark version file, the compression - * codec file (if event logs are compressed), and the application completion file (if the - * application has run to completion). + * @return 2-tuple (event input stream, Spark version of event data) */ - def parseLoggingInfo(logDir: Path, fileSystem: FileSystem): EventLoggingInfo = { + def openEventLog(log: Path, fs: FileSystem): (InputStream, String) = { + // It's not clear whether FileSystem.open() throws FileNotFoundException or just plain + // IOException when a file does not exist, so try our best to throw a proper exception. + if (!fs.exists(log)) { + throw new FileNotFoundException(s"File $log does not exist.") + } + + val in = new BufferedInputStream(fs.open(log)) + // Read a single line from the input stream without buffering. + // We cannot use BufferedReader because we must avoid reading + // beyond the end of the header, after which the content of the + // file may be compressed. + def readLine(): String = { + val bytes = new ByteArrayOutputStream() + var next = in.read() + var count = 0 + while (next != '\n') { + if (next == -1) { + throw new IOException("Unexpected end of file.") + } + bytes.write(next) + count = count + 1 + if (count > MAX_HEADER_LINE_LENGTH) { + throw new IOException("Maximum header line length exceeded.") + } + next = in.read() + } + new String(bytes.toByteArray(), Charsets.UTF_8) + } + + // Parse the header metadata in the form of k=v pairs + // This assumes that every line before the header end marker follows this format try { - val fileStatuses = fileSystem.listStatus(logDir) - val filePaths = - if (fileStatuses != null) { - fileStatuses.filter(!_.isDir).map(_.getPath).toSeq - } else { - Seq[Path]() + val meta = new mutable.HashMap[String, String]() + var foundEndMarker = false + while (!foundEndMarker) { + readLine() match { + case HEADER_END_MARKER => + foundEndMarker = true + case entry => + val prop = entry.split("=", 2) + if (prop.length != 2) { + throw new IllegalArgumentException("Invalid metadata in log file.") + } + meta += (prop(0) -> prop(1)) } - if (filePaths.isEmpty) { - logWarning("No files found in logging directory %s".format(logDir)) } - EventLoggingInfo( - logPaths = filePaths.filter { path => isEventLogFile(path.getName) }, - sparkVersion = filePaths - .find { path => isSparkVersionFile(path.getName) } - .map { path => parseSparkVersion(path.getName) } - .getOrElse(""), - compressionCodec = filePaths - .find { path => isCompressionCodecFile(path.getName) } - .map { path => - val codec = EventLoggingListener.parseCompressionCodec(path.getName) - val conf = new SparkConf - conf.set("spark.io.compression.codec", codec) - codecMap.getOrElseUpdate(codec, CompressionCodec.createCodec(conf)) - }, - applicationComplete = filePaths.exists { path => isApplicationCompleteFile(path.getName) } - ) + + val sparkVersion = meta.get("version").getOrElse( + throw new IllegalArgumentException("Missing Spark version in log metadata.")) + val codec = meta.get("compressionCodec").map { codecName => + codecMap.getOrElseUpdate(codecName, CompressionCodec.createCodec(new SparkConf, codecName)) + } + (codec.map(_.compressedInputStream(in)).getOrElse(in), sparkVersion) } catch { case e: Exception => - logError("Exception in parsing logging info from directory %s".format(logDir), e) - EventLoggingInfo.empty + in.close() + throw e } } - /** - * Parse the event logging information associated with the logs in the given directory. - */ - def parseLoggingInfo(logDir: String, fileSystem: FileSystem): EventLoggingInfo = { - parseLoggingInfo(new Path(logDir), fileSystem) - } -} - - -/** - * Information needed to process the event logs associated with an application. - */ -private[spark] case class EventLoggingInfo( - logPaths: Seq[Path], - sparkVersion: String, - compressionCodec: Option[CompressionCodec], - applicationComplete: Boolean = false) - -private[spark] object EventLoggingInfo { - def empty = EventLoggingInfo(Seq[Path](), "", None, applicationComplete = false) } diff --git a/core/src/main/scala/org/apache/spark/scheduler/ReplayListenerBus.scala b/core/src/main/scala/org/apache/spark/scheduler/ReplayListenerBus.scala index f89724d4ea196..584f4e7789d1a 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/ReplayListenerBus.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/ReplayListenerBus.scala @@ -17,74 +17,45 @@ package org.apache.spark.scheduler -import java.io.{BufferedInputStream, InputStream} +import java.io.{InputStream, IOException} import scala.io.Source -import org.apache.hadoop.fs.{Path, FileSystem} import org.json4s.jackson.JsonMethods._ import org.apache.spark.Logging -import org.apache.spark.io.CompressionCodec import org.apache.spark.util.JsonProtocol /** - * A SparkListenerBus that replays logged events from persisted storage. - * - * This assumes the given paths are valid log files, where each line can be deserialized into - * exactly one SparkListenerEvent. + * A SparkListenerBus that can be used to replay events from serialized event data. */ -private[spark] class ReplayListenerBus( - logPaths: Seq[Path], - fileSystem: FileSystem, - compressionCodec: Option[CompressionCodec]) - extends SparkListenerBus with Logging { - - private var replayed = false - - if (logPaths.length == 0) { - logWarning("Log path provided contains no log files.") - } +private[spark] class ReplayListenerBus extends SparkListenerBus with Logging { /** - * Replay each event in the order maintained in the given logs. - * This should only be called exactly once. + * Replay each event in the order maintained in the given stream. The stream is expected to + * contain one JSON-encoded SparkListenerEvent per line. + * + * This method can be called multiple times, but the listener behavior is undefined after any + * error is thrown by this method. + * + * @param logData Stream containing event log data. + * @param version Spark version that generated the events. */ - def replay() { - assert(!replayed, "ReplayListenerBus cannot replay events more than once") - logPaths.foreach { path => - // Keep track of input streams at all levels to close them later - // This is necessary because an exception can occur in between stream initializations - var fileStream: Option[InputStream] = None - var bufferedStream: Option[InputStream] = None - var compressStream: Option[InputStream] = None - var currentLine = "" - try { - fileStream = Some(fileSystem.open(path)) - bufferedStream = Some(new BufferedInputStream(fileStream.get)) - compressStream = Some(wrapForCompression(bufferedStream.get)) - - // Parse each line as an event and post the event to all attached listeners - val lines = Source.fromInputStream(compressStream.get).getLines() - lines.foreach { line => - currentLine = line - postToAll(JsonProtocol.sparkEventFromJson(parse(line))) - } - } catch { - case e: Exception => - logError("Exception in parsing Spark event log %s".format(path), e) - logError("Malformed line: %s\n".format(currentLine)) - } finally { - fileStream.foreach(_.close()) - bufferedStream.foreach(_.close()) - compressStream.foreach(_.close()) + def replay(logData: InputStream, version: String) { + var currentLine: String = null + try { + val lines = Source.fromInputStream(logData).getLines() + lines.foreach { line => + currentLine = line + postToAll(JsonProtocol.sparkEventFromJson(parse(line))) } + } catch { + case ioe: IOException => + throw ioe + case e: Exception => + logError("Exception in parsing Spark event log.", e) + logError("Malformed line: %s\n".format(currentLine)) } - replayed = true } - /** If a compression codec is specified, wrap the given stream in a compression stream. */ - private def wrapForCompression(stream: InputStream): InputStream = { - compressionCodec.map(_.compressedInputStream(stream)).getOrElse(stream) - } } diff --git a/core/src/main/scala/org/apache/spark/util/FileLogger.scala b/core/src/main/scala/org/apache/spark/util/FileLogger.scala deleted file mode 100644 index fdc73f08261a6..0000000000000 --- a/core/src/main/scala/org/apache/spark/util/FileLogger.scala +++ /dev/null @@ -1,237 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.util - -import java.io.{BufferedOutputStream, FileOutputStream, IOException, PrintWriter} -import java.net.URI -import java.text.SimpleDateFormat -import java.util.Date - -import org.apache.hadoop.conf.Configuration -import org.apache.hadoop.fs.{FileSystem, FSDataOutputStream, Path} -import org.apache.hadoop.fs.permission.FsPermission - -import org.apache.spark.{Logging, SparkConf} -import org.apache.spark.deploy.SparkHadoopUtil -import org.apache.spark.io.CompressionCodec - -/** - * A generic class for logging information to file. - * - * @param logDir Path to the directory in which files are logged - * @param outputBufferSize The buffer size to use when writing to an output stream in bytes - * @param compress Whether to compress output - * @param overwrite Whether to overwrite existing files - */ -private[spark] class FileLogger( - logDir: String, - sparkConf: SparkConf, - hadoopConf: Configuration, - outputBufferSize: Int = 8 * 1024, // 8 KB - compress: Boolean = false, - overwrite: Boolean = true, - dirPermissions: Option[FsPermission] = None) - extends Logging { - - def this( - logDir: String, - sparkConf: SparkConf, - compress: Boolean, - overwrite: Boolean) = { - this(logDir, sparkConf, SparkHadoopUtil.get.newConfiguration(sparkConf), compress = compress, - overwrite = overwrite) - } - - def this( - logDir: String, - sparkConf: SparkConf, - compress: Boolean) = { - this(logDir, sparkConf, SparkHadoopUtil.get.newConfiguration(sparkConf), compress = compress, - overwrite = true) - } - - def this( - logDir: String, - sparkConf: SparkConf) = { - this(logDir, sparkConf, SparkHadoopUtil.get.newConfiguration(sparkConf), compress = false, - overwrite = true) - } - - private val dateFormat = new ThreadLocal[SimpleDateFormat]() { - override def initialValue(): SimpleDateFormat = new SimpleDateFormat("yyyy/MM/dd HH:mm:ss") - } - - /** - * To avoid effects of FileSystem#close or FileSystem.closeAll called from other modules, - * create unique FileSystem instance only for FileLogger - */ - private val fileSystem = { - val conf = SparkHadoopUtil.get.newConfiguration(sparkConf) - val logUri = new URI(logDir) - val scheme = logUri.getScheme - if (scheme == "hdfs") { - conf.setBoolean("fs.hdfs.impl.disable.cache", true) - } - FileSystem.get(logUri, conf) - } - - var fileIndex = 0 - - // Only used if compression is enabled - private lazy val compressionCodec = CompressionCodec.createCodec(sparkConf) - - // Only defined if the file system scheme is not local - private var hadoopDataStream: Option[FSDataOutputStream] = None - - // The Hadoop APIs have changed over time, so we use reflection to figure out - // the correct method to use to flush a hadoop data stream. See SPARK-1518 - // for details. - private val hadoopFlushMethod = { - val cls = classOf[FSDataOutputStream] - scala.util.Try(cls.getMethod("hflush")).getOrElse(cls.getMethod("sync")) - } - - private var writer: Option[PrintWriter] = None - - /** - * Start this logger by creating the logging directory. - */ - def start() { - createLogDir() - } - - /** - * Create a logging directory with the given path. - */ - private def createLogDir() { - val path = new Path(logDir) - if (fileSystem.exists(path)) { - if (overwrite) { - logWarning("Log directory %s already exists. Overwriting...".format(logDir)) - // Second parameter is whether to delete recursively - fileSystem.delete(path, true) - } else { - throw new IOException("Log directory %s already exists!".format(logDir)) - } - } - if (!fileSystem.mkdirs(path)) { - throw new IOException("Error in creating log directory: %s".format(logDir)) - } - if (dirPermissions.isDefined) { - val fsStatus = fileSystem.getFileStatus(path) - if (fsStatus.getPermission.toShort != dirPermissions.get.toShort) { - fileSystem.setPermission(path, dirPermissions.get) - } - } - } - - /** - * Create a new writer for the file identified by the given path. - * If the permissions are not passed in, it will default to use the permissions - * (dirPermissions) used when class was instantiated. - */ - private def createWriter(fileName: String, perms: Option[FsPermission] = None): PrintWriter = { - val logPath = logDir + "/" + fileName - val uri = new URI(logPath) - val path = new Path(logPath) - val defaultFs = FileSystem.getDefaultUri(hadoopConf).getScheme - val isDefaultLocal = defaultFs == null || defaultFs == "file" - - /* The Hadoop LocalFileSystem (r1.0.4) has known issues with syncing (HADOOP-7844). - * Therefore, for local files, use FileOutputStream instead. */ - val dstream = - if ((isDefaultLocal && uri.getScheme == null) || uri.getScheme == "file") { - // Second parameter is whether to append - new FileOutputStream(uri.getPath, !overwrite) - } else { - hadoopDataStream = Some(fileSystem.create(path, overwrite)) - hadoopDataStream.get - } - - perms.orElse(dirPermissions).foreach { p => fileSystem.setPermission(path, p) } - val bstream = new BufferedOutputStream(dstream, outputBufferSize) - val cstream = if (compress) compressionCodec.compressedOutputStream(bstream) else bstream - new PrintWriter(cstream) - } - - /** - * Log the message to the given writer. - * @param msg The message to be logged - * @param withTime Whether to prepend message with a timestamp - */ - def log(msg: String, withTime: Boolean = false) { - val writeInfo = if (!withTime) { - msg - } else { - val date = new Date(System.currentTimeMillis) - dateFormat.get.format(date) + ": " + msg - } - writer.foreach(_.print(writeInfo)) - } - - /** - * Log the message to the given writer as a new line. - * @param msg The message to be logged - * @param withTime Whether to prepend message with a timestamp - */ - def logLine(msg: String, withTime: Boolean = false) = log(msg + "\n", withTime) - - /** - * Flush the writer to disk manually. - * - * When using a Hadoop filesystem, we need to invoke the hflush or sync - * method. In HDFS, hflush guarantees that the data gets to all the - * DataNodes. - */ - def flush() { - writer.foreach(_.flush()) - hadoopDataStream.foreach(hadoopFlushMethod.invoke(_)) - } - - /** - * Close the writer. Any subsequent calls to log or flush will have no effect. - */ - def close() { - writer.foreach(_.close()) - writer = None - } - - /** - * Start a writer for a new file, closing the existing one if it exists. - * @param fileName Name of the new file, defaulting to the file index if not provided. - * @param perms Permissions to put on the new file. - */ - def newFile(fileName: String = "", perms: Option[FsPermission] = None) { - fileIndex += 1 - writer.foreach(_.close()) - val name = fileName match { - case "" => fileIndex.toString - case _ => fileName - } - writer = Some(createWriter(name, perms)) - } - - /** - * Close all open writers, streams, and file systems. Any subsequent uses of this FileLogger - * instance will throw exceptions. - */ - def stop() { - hadoopDataStream.foreach(_.close()) - writer.foreach(_.close()) - } -} diff --git a/core/src/test/scala/org/apache/spark/deploy/history/FsHistoryProviderSuite.scala b/core/src/test/scala/org/apache/spark/deploy/history/FsHistoryProviderSuite.scala new file mode 100644 index 0000000000000..d719e9301f4fd --- /dev/null +++ b/core/src/test/scala/org/apache/spark/deploy/history/FsHistoryProviderSuite.scala @@ -0,0 +1,185 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.history + +import java.io.{File, FileOutputStream, OutputStreamWriter} + +import scala.io.Source + +import com.google.common.io.Files +import org.apache.hadoop.fs.Path +import org.json4s.jackson.JsonMethods._ +import org.scalatest.{BeforeAndAfter, FunSuite} +import org.scalatest.Matchers + +import org.apache.spark.{Logging, SparkConf} +import org.apache.spark.deploy.SparkHadoopUtil +import org.apache.spark.io._ +import org.apache.spark.scheduler._ +import org.apache.spark.util.{JsonProtocol, Utils} + +class FsHistoryProviderSuite extends FunSuite with BeforeAndAfter with Matchers with Logging { + + private var testDir: File = null + + private var provider: FsHistoryProvider = null + + before { + testDir = Utils.createTempDir() + provider = new FsHistoryProvider(new SparkConf() + .set("spark.history.fs.logDirectory", testDir.getAbsolutePath()) + .set("spark.history.fs.updateInterval", "0")) + } + + after { + Utils.deleteRecursively(testDir) + } + + test("Parse new and old application logs") { + val conf = new SparkConf() + .set("spark.history.fs.logDirectory", testDir.getAbsolutePath()) + .set("spark.history.fs.updateInterval", "0") + val provider = new FsHistoryProvider(conf) + + // Write a new-style application log. + val logFile1 = new File(testDir, "new1") + writeFile(logFile1, true, None, + SparkListenerApplicationStart("app1-1", None, 1L, "test"), + SparkListenerApplicationEnd(2L) + ) + + // Write an unfinished app, new-style. + writeFile(new File(testDir, "new2" + EventLoggingListener.IN_PROGRESS), true, None, + SparkListenerApplicationStart("app2-2", None, 1L, "test") + ) + + // Write an old-style application log. + val oldLog = new File(testDir, "old1") + oldLog.mkdir() + createEmptyFile(new File(oldLog, provider.SPARK_VERSION_PREFIX + "1.0")) + writeFile(new File(oldLog, provider.LOG_PREFIX + "1"), false, None, + SparkListenerApplicationStart("app3", None, 2L, "test"), + SparkListenerApplicationEnd(3L) + ) + createEmptyFile(new File(oldLog, provider.APPLICATION_COMPLETE)) + + // Write an unfinished app, old-style. + val oldLog2 = new File(testDir, "old2") + oldLog2.mkdir() + createEmptyFile(new File(oldLog2, provider.SPARK_VERSION_PREFIX + "1.0")) + writeFile(new File(oldLog2, provider.LOG_PREFIX + "1"), false, None, + SparkListenerApplicationStart("app4", None, 2L, "test") + ) + + // Force a reload of data from the log directory, and check that both logs are loaded. + // Take the opportunity to check that the offset checks work as expected. + provider.checkForLogs() + + val list = provider.getListing().toSeq + list should not be (null) + list.size should be (2) + + list(0) should be (ApplicationHistoryInfo(oldLog.getName(), "app3", 2L, 3L, + oldLog.lastModified(), "test")) + list(1) should be (ApplicationHistoryInfo(logFile1.getName(), "app1-1", 1L, 2L, + logFile1.lastModified(), "test")) + + // Make sure the UI can be rendered. + list.foreach { case info => + val appUi = provider.getAppUI(info.id) + appUi should not be null + } + } + + test("Parse legacy logs with compression codec set") { + val testCodecs = List((classOf[LZFCompressionCodec].getName(), true), + (classOf[SnappyCompressionCodec].getName(), true), + ("invalid.codec", false)) + + testCodecs.foreach { case (codecName, valid) => + val codec = if (valid) CompressionCodec.createCodec(new SparkConf(), codecName) else null + val logDir = new File(testDir, codecName) + logDir.mkdir() + createEmptyFile(new File(logDir, provider.SPARK_VERSION_PREFIX + "1.0")) + writeFile(new File(logDir, provider.LOG_PREFIX + "1"), false, Option(codec), + SparkListenerApplicationStart("app2", None, 2L, "test"), + SparkListenerApplicationEnd(3L) + ) + createEmptyFile(new File(logDir, provider.COMPRESSION_CODEC_PREFIX + codecName)) + + val logPath = new Path(logDir.getAbsolutePath()) + try { + val (logInput, sparkVersion) = provider.openLegacyEventLog(logPath) + try { + Source.fromInputStream(logInput).getLines().toSeq.size should be (2) + } finally { + logInput.close() + } + } catch { + case e: IllegalArgumentException => + valid should be (false) + } + } + } + + test("SPARK-3697: ignore directories that cannot be read.") { + val logFile1 = new File(testDir, "new1") + writeFile(logFile1, true, None, + SparkListenerApplicationStart("app1-1", None, 1L, "test"), + SparkListenerApplicationEnd(2L) + ) + val logFile2 = new File(testDir, "new2") + writeFile(logFile2, true, None, + SparkListenerApplicationStart("app1-2", None, 1L, "test"), + SparkListenerApplicationEnd(2L) + ) + logFile2.setReadable(false, false) + + val conf = new SparkConf() + .set("spark.history.fs.logDirectory", testDir.getAbsolutePath()) + .set("spark.history.fs.updateInterval", "0") + val provider = new FsHistoryProvider(conf) + provider.checkForLogs() + + val list = provider.getListing().toSeq + list should not be (null) + list.size should be (1) + } + + private def writeFile(file: File, isNewFormat: Boolean, codec: Option[CompressionCodec], + events: SparkListenerEvent*) = { + val out = + if (isNewFormat) { + EventLoggingListener.initEventLog(new FileOutputStream(file), codec) + } else { + val fileStream = new FileOutputStream(file) + codec.map(_.compressedOutputStream(fileStream)).getOrElse(fileStream) + } + val writer = new OutputStreamWriter(out, "UTF-8") + try { + events.foreach(e => writer.write(compact(render(JsonProtocol.sparkEventToJson(e))) + "\n")) + } finally { + writer.close() + } + } + + private def createEmptyFile(file: File) = { + new FileOutputStream(file).close() + } + +} diff --git a/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala index abc300fcffaf9..5909811c2034f 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala @@ -17,69 +17,59 @@ package org.apache.spark.scheduler +import java.io.{File, FileOutputStream, InputStream, IOException} + import scala.collection.mutable import scala.io.Source -import org.apache.hadoop.fs.{FileStatus, Path} +import org.apache.hadoop.fs.Path import org.json4s.jackson.JsonMethods._ import org.scalatest.{BeforeAndAfter, FunSuite} -import org.apache.spark.{SparkConf, SparkContext} +import org.apache.spark.{Logging, SparkConf, SparkContext} import org.apache.spark.deploy.SparkHadoopUtil -import org.apache.spark.io.CompressionCodec -import org.apache.spark.SPARK_VERSION +import org.apache.spark.io._ import org.apache.spark.util.{JsonProtocol, Utils} -import java.io.File - /** * Test whether EventLoggingListener logs events properly. * - * This tests whether EventLoggingListener actually creates special files while logging events, - * whether the parsing of these special files is correct, and whether the logged events can be - * read and deserialized into actual SparkListenerEvents. + * This tests whether EventLoggingListener actually log files with expected name patterns while + * logging events, whether the parsing of the file names is correct, and whether the logged events + * can be read and deserialized into actual SparkListenerEvents. */ -class EventLoggingListenerSuite extends FunSuite with BeforeAndAfter { +class EventLoggingListenerSuite extends FunSuite with BeforeAndAfter with Logging { + import EventLoggingListenerSuite._ + private val fileSystem = Utils.getHadoopFileSystem("/", SparkHadoopUtil.get.newConfiguration(new SparkConf())) - private val allCompressionCodecs = Seq[String]( - "org.apache.spark.io.LZFCompressionCodec", - "org.apache.spark.io.SnappyCompressionCodec" - ) private var testDir: File = _ - private var logDirPath: Path = _ + private var testDirPath: Path = _ before { testDir = Utils.createTempDir() - logDirPath = Utils.getFilePath(testDir, "spark-events") + testDir.deleteOnExit() + testDirPath = new Path(testDir.getAbsolutePath()) } after { Utils.deleteRecursively(testDir) } - test("Parse names of special files") { - testParsingFileName() - } - - test("Verify special files exist") { - testSpecialFilesExist() - } - - test("Verify special files exist with compression") { - allCompressionCodecs.foreach { codec => - testSpecialFilesExist(compressionCodec = Some(codec)) - } - } + test("Verify log file exist") { + // Verify logging directory exists + val conf = getLoggingConf(testDirPath) + val eventLogger = new EventLoggingListener("test", testDirPath.toUri().toString(), conf) + eventLogger.start() - test("Parse event logging info") { - testParsingLogInfo() - } + val logPath = new Path(eventLogger.logPath + EventLoggingListener.IN_PROGRESS) + assert(fileSystem.exists(logPath)) + val logStatus = fileSystem.getFileStatus(logPath) + assert(logStatus.isFile) - test("Parse event logging info with compression") { - allCompressionCodecs.foreach { codec => - testParsingLogInfo(compressionCodec = Some(codec)) - } + // Verify log is renamed after stop() + eventLogger.stop() + assert(fileSystem.getFileStatus(new Path(eventLogger.logPath)).isFile()) } test("Basic event logging") { @@ -87,7 +77,7 @@ class EventLoggingListenerSuite extends FunSuite with BeforeAndAfter { } test("Basic event logging with compression") { - allCompressionCodecs.foreach { codec => + CompressionCodec.ALL_COMPRESSION_CODECS.foreach { codec => testEventLogging(compressionCodec = Some(codec)) } } @@ -97,11 +87,25 @@ class EventLoggingListenerSuite extends FunSuite with BeforeAndAfter { } test("End-to-end event logging with compression") { - allCompressionCodecs.foreach { codec => + CompressionCodec.ALL_COMPRESSION_CODECS.foreach { codec => testApplicationEventLogging(compressionCodec = Some(codec)) } } + test("Log overwriting") { + val log = new FileOutputStream(new File(testDir, "test")) + log.close() + try { + testEventLogging() + assert(false) + } catch { + case e: IOException => + // Expected, since we haven't enabled log overwrite. + } + + // Try again, but enable overwriting. + testEventLogging(extraConf = Map("spark.eventLog.overwrite" -> "true")) + } /* ----------------- * * Actual test logic * @@ -109,130 +113,19 @@ class EventLoggingListenerSuite extends FunSuite with BeforeAndAfter { import EventLoggingListenerSuite._ - /** - * Test whether names of special files are correctly identified and parsed. - */ - private def testParsingFileName() { - val logPrefix = EventLoggingListener.LOG_PREFIX - val sparkVersionPrefix = EventLoggingListener.SPARK_VERSION_PREFIX - val compressionCodecPrefix = EventLoggingListener.COMPRESSION_CODEC_PREFIX - val applicationComplete = EventLoggingListener.APPLICATION_COMPLETE - assert(EventLoggingListener.isEventLogFile(logPrefix + "0")) - assert(EventLoggingListener.isEventLogFile(logPrefix + "100")) - assert(EventLoggingListener.isEventLogFile(logPrefix + "ANYTHING")) - assert(EventLoggingListener.isSparkVersionFile(sparkVersionPrefix + "0.9.1")) - assert(EventLoggingListener.isSparkVersionFile(sparkVersionPrefix + "1.0.0")) - assert(EventLoggingListener.isSparkVersionFile(sparkVersionPrefix + "ANYTHING")) - assert(EventLoggingListener.isApplicationCompleteFile(applicationComplete)) - allCompressionCodecs.foreach { codec => - assert(EventLoggingListener.isCompressionCodecFile(compressionCodecPrefix + codec)) - } - - // Negatives - assert(!EventLoggingListener.isEventLogFile("The greatest man of all mankind")) - assert(!EventLoggingListener.isSparkVersionFile("Will never falter in the face of death!")) - assert(!EventLoggingListener.isCompressionCodecFile("Unless he chooses to leave behind")) - assert(!EventLoggingListener.isApplicationCompleteFile("The very treasure he calls Macbeth")) - - // Verify that parsing is correct - assert(EventLoggingListener.parseSparkVersion(sparkVersionPrefix + "1.0.0") === "1.0.0") - allCompressionCodecs.foreach { codec => - assert(EventLoggingListener.parseCompressionCodec(compressionCodecPrefix + codec) === codec) - } - } - - /** - * Test whether the special files produced by EventLoggingListener exist. - * - * There should be exactly one event log and one spark version file throughout the entire - * execution. If a compression codec is specified, then the compression codec file should - * also exist. Only after the application has completed does the test expect the application - * completed file to be present. - */ - private def testSpecialFilesExist(compressionCodec: Option[String] = None) { - - def assertFilesExist(logFiles: Array[FileStatus], loggerStopped: Boolean) { - val numCompressionCodecFiles = if (compressionCodec.isDefined) 1 else 0 - val numApplicationCompleteFiles = if (loggerStopped) 1 else 0 - assert(logFiles.size === 2 + numCompressionCodecFiles + numApplicationCompleteFiles) - assert(eventLogsExist(logFiles)) - assert(sparkVersionExists(logFiles)) - assert(compressionCodecExists(logFiles) === compressionCodec.isDefined) - assert(applicationCompleteExists(logFiles) === loggerStopped) - assertSparkVersionIsValid(logFiles) - compressionCodec.foreach { codec => - assertCompressionCodecIsValid(logFiles, codec) - } - } - - // Verify logging directory exists - val conf = getLoggingConf(logDirPath, compressionCodec) - val logBaseDir = conf.get("spark.eventLog.dir") - val appId = EventLoggingListenerSuite.getUniqueApplicationId - val eventLogger = new EventLoggingListener(appId, logBaseDir, conf) - eventLogger.start() - val logPath = new Path(eventLogger.logDir) - assert(fileSystem.exists(logPath)) - val logDir = fileSystem.getFileStatus(logPath) - assert(logDir.isDir) - - // Verify special files are as expected before stop() - var logFiles = fileSystem.listStatus(logPath) - assert(logFiles != null) - assertFilesExist(logFiles, loggerStopped = false) - - // Verify special files are as expected after stop() - eventLogger.stop() - logFiles = fileSystem.listStatus(logPath) - assertFilesExist(logFiles, loggerStopped = true) - } - - /** - * Test whether EventLoggingListener correctly parses the correct information from the logs. - * - * This includes whether it returns the correct Spark version, compression codec (if any), - * and the application's completion status. - */ - private def testParsingLogInfo(compressionCodec: Option[String] = None) { - - def assertInfoCorrect(info: EventLoggingInfo, loggerStopped: Boolean) { - assert(info.logPaths.size > 0) - assert(info.sparkVersion === SPARK_VERSION) - assert(info.compressionCodec.isDefined === compressionCodec.isDefined) - info.compressionCodec.foreach { codec => - assert(compressionCodec.isDefined) - val expectedCodec = compressionCodec.get.split('.').last - assert(codec.getClass.getSimpleName === expectedCodec) - } - assert(info.applicationComplete === loggerStopped) - } - - // Verify that all information is correctly parsed before stop() - val conf = getLoggingConf(logDirPath, compressionCodec) - val logBaseDir = conf.get("spark.eventLog.dir") - val appId = EventLoggingListenerSuite.getUniqueApplicationId - val eventLogger = new EventLoggingListener(appId, logBaseDir, conf) - eventLogger.start() - var eventLoggingInfo = EventLoggingListener.parseLoggingInfo(eventLogger.logDir, fileSystem) - assertInfoCorrect(eventLoggingInfo, loggerStopped = false) - - // Verify that all information is correctly parsed after stop() - eventLogger.stop() - eventLoggingInfo = EventLoggingListener.parseLoggingInfo(eventLogger.logDir, fileSystem) - assertInfoCorrect(eventLoggingInfo, loggerStopped = true) - } - /** * Test basic event logging functionality. * * This creates two simple events, posts them to the EventLoggingListener, and verifies that * exactly these two events are logged in the expected file. */ - private def testEventLogging(compressionCodec: Option[String] = None) { - val conf = getLoggingConf(logDirPath, compressionCodec) - val logBaseDir = conf.get("spark.eventLog.dir") - val appId = EventLoggingListenerSuite.getUniqueApplicationId - val eventLogger = new EventLoggingListener(appId, logBaseDir, conf) + private def testEventLogging( + compressionCodec: Option[String] = None, + extraConf: Map[String, String] = Map()) { + val conf = getLoggingConf(testDirPath, compressionCodec) + extraConf.foreach { case (k, v) => conf.set(k, v) } + val logName = compressionCodec.map("test-" + _).getOrElse("test") + val eventLogger = new EventLoggingListener(logName, testDirPath.toUri().toString(), conf) val listenerBus = new LiveListenerBus val applicationStart = SparkListenerApplicationStart("Greatest App (N)ever", None, 125L, "Mickey") @@ -244,17 +137,21 @@ class EventLoggingListenerSuite extends FunSuite with BeforeAndAfter { listenerBus.addListener(eventLogger) listenerBus.postToAll(applicationStart) listenerBus.postToAll(applicationEnd) + eventLogger.stop() // Verify file contains exactly the two events logged - val eventLoggingInfo = EventLoggingListener.parseLoggingInfo(eventLogger.logDir, fileSystem) - assert(eventLoggingInfo.logPaths.size > 0) - val lines = readFileLines(eventLoggingInfo.logPaths.head, eventLoggingInfo.compressionCodec) - assert(lines.size === 2) - assert(lines(0).contains("SparkListenerApplicationStart")) - assert(lines(1).contains("SparkListenerApplicationEnd")) - assert(JsonProtocol.sparkEventFromJson(parse(lines(0))) === applicationStart) - assert(JsonProtocol.sparkEventFromJson(parse(lines(1))) === applicationEnd) - eventLogger.stop() + val (logData, version) = EventLoggingListener.openEventLog(new Path(eventLogger.logPath), + fileSystem) + try { + val lines = readLines(logData) + assert(lines.size === 2) + assert(lines(0).contains("SparkListenerApplicationStart")) + assert(lines(1).contains("SparkListenerApplicationEnd")) + assert(JsonProtocol.sparkEventFromJson(parse(lines(0))) === applicationStart) + assert(JsonProtocol.sparkEventFromJson(parse(lines(1))) === applicationEnd) + } finally { + logData.close() + } } /** @@ -262,12 +159,12 @@ class EventLoggingListenerSuite extends FunSuite with BeforeAndAfter { * This runs a simple Spark job and asserts that the expected events are logged when expected. */ private def testApplicationEventLogging(compressionCodec: Option[String] = None) { - val conf = getLoggingConf(logDirPath, compressionCodec) + val conf = getLoggingConf(testDirPath, compressionCodec) val sc = new SparkContext("local", "test", conf) assert(sc.eventLogger.isDefined) val eventLogger = sc.eventLogger.get - val expectedLogDir = logDirPath.toString - assert(eventLogger.logDir.contains(expectedLogDir)) + val expectedLogDir = testDir.toURI().toString() + assert(eventLogger.logPath.startsWith(expectedLogDir + "/")) // Begin listening for events that trigger asserts val eventExistenceListener = new EventExistenceListener(eventLogger) @@ -279,16 +176,22 @@ class EventLoggingListenerSuite extends FunSuite with BeforeAndAfter { // Ensure all asserts have actually been triggered eventExistenceListener.assertAllCallbacksInvoked() - } - /** - * Assert that all of the specified events are logged by the given EventLoggingListener. - */ - private def assertEventsExist(eventLogger: EventLoggingListener, events: Seq[String]) { - val eventLoggingInfo = EventLoggingListener.parseLoggingInfo(eventLogger.logDir, fileSystem) - assert(eventLoggingInfo.logPaths.size > 0) - val lines = readFileLines(eventLoggingInfo.logPaths.head, eventLoggingInfo.compressionCodec) - val eventSet = mutable.Set(events: _*) + // Make sure expected events exist in the log file. + val (logData, version) = EventLoggingListener.openEventLog(new Path(eventLogger.logPath), + fileSystem) + val lines = readLines(logData) + val eventSet = mutable.Set( + SparkListenerApplicationStart, + SparkListenerBlockManagerAdded, + SparkListenerEnvironmentUpdate, + SparkListenerJobStart, + SparkListenerJobEnd, + SparkListenerStageSubmitted, + SparkListenerStageCompleted, + SparkListenerTaskStart, + SparkListenerTaskEnd, + SparkListenerApplicationEnd).map(Utils.getFormattedClassName) lines.foreach { line => eventSet.foreach { event => if (line.contains(event)) { @@ -303,19 +206,8 @@ class EventLoggingListenerSuite extends FunSuite with BeforeAndAfter { assert(eventSet.isEmpty, "The following events are missing: " + eventSet.toSeq) } - /** - * Read all lines from the file specified by the given path. - * If a compression codec is specified, use it to read the file. - */ - private def readFileLines( - filePath: Path, - compressionCodec: Option[CompressionCodec]): Seq[String] = { - val fstream = fileSystem.open(filePath) - val cstream = - compressionCodec.map { codec => - codec.compressedInputStream(fstream) - }.getOrElse(fstream) - Source.fromInputStream(cstream).getLines().toSeq + private def readLines(in: InputStream): Seq[String] = { + Source.fromInputStream(in).getLines().toSeq } /** @@ -328,30 +220,14 @@ class EventLoggingListenerSuite extends FunSuite with BeforeAndAfter { var appEnded = false override def onJobStart(jobStart: SparkListenerJobStart) { - assertEventsExist(eventLogger, Seq[String]( - Utils.getFormattedClassName(SparkListenerApplicationStart), - Utils.getFormattedClassName(SparkListenerBlockManagerAdded), - Utils.getFormattedClassName(SparkListenerEnvironmentUpdate) - )) jobStarted = true } override def onJobEnd(jobEnd: SparkListenerJobEnd) { - assertEventsExist(eventLogger, Seq[String]( - Utils.getFormattedClassName(SparkListenerJobStart), - Utils.getFormattedClassName(SparkListenerJobEnd), - Utils.getFormattedClassName(SparkListenerStageSubmitted), - Utils.getFormattedClassName(SparkListenerStageCompleted), - Utils.getFormattedClassName(SparkListenerTaskStart), - Utils.getFormattedClassName(SparkListenerTaskEnd) - )) jobEnded = true } override def onApplicationEnd(applicationEnd: SparkListenerApplicationEnd) { - assertEventsExist(eventLogger, Seq[String]( - Utils.getFormattedClassName(SparkListenerApplicationEnd) - )) appEnded = true } @@ -362,39 +238,6 @@ class EventLoggingListenerSuite extends FunSuite with BeforeAndAfter { } } - - /* -------------------------------------------------------- * - * Helper methods for validating state of the special files * - * -------------------------------------------------------- */ - - private def eventLogsExist(logFiles: Array[FileStatus]): Boolean = { - logFiles.map(_.getPath.getName).exists(EventLoggingListener.isEventLogFile) - } - - private def sparkVersionExists(logFiles: Array[FileStatus]): Boolean = { - logFiles.map(_.getPath.getName).exists(EventLoggingListener.isSparkVersionFile) - } - - private def compressionCodecExists(logFiles: Array[FileStatus]): Boolean = { - logFiles.map(_.getPath.getName).exists(EventLoggingListener.isCompressionCodecFile) - } - - private def applicationCompleteExists(logFiles: Array[FileStatus]): Boolean = { - logFiles.map(_.getPath.getName).exists(EventLoggingListener.isApplicationCompleteFile) - } - - private def assertSparkVersionIsValid(logFiles: Array[FileStatus]) { - val file = logFiles.map(_.getPath.getName).find(EventLoggingListener.isSparkVersionFile) - assert(file.isDefined) - assert(EventLoggingListener.parseSparkVersion(file.get) === SPARK_VERSION) - } - - private def assertCompressionCodecIsValid(logFiles: Array[FileStatus], compressionCodec: String) { - val file = logFiles.map(_.getPath.getName).find(EventLoggingListener.isCompressionCodecFile) - assert(file.isDefined) - assert(EventLoggingListener.parseCompressionCodec(file.get) === compressionCodec) - } - } diff --git a/core/src/test/scala/org/apache/spark/scheduler/ReplayListenerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/ReplayListenerSuite.scala index 90bdfe07f61c9..7e635cb061441 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/ReplayListenerSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/ReplayListenerSuite.scala @@ -22,6 +22,7 @@ import java.io.{File, PrintWriter} import org.json4s.jackson.JsonMethods._ import org.scalatest.{BeforeAndAfter, FunSuite} +import org.apache.spark.{SparkConf, SparkContext, SPARK_VERSION} import org.apache.spark.{SparkConf, SparkContext} import org.apache.spark.deploy.SparkHadoopUtil import org.apache.spark.io.CompressionCodec @@ -33,7 +34,6 @@ import org.apache.spark.util.{JsonProtocol, Utils} class ReplayListenerSuite extends FunSuite with BeforeAndAfter { private val fileSystem = Utils.getHadoopFileSystem("/", SparkHadoopUtil.get.newConfiguration(new SparkConf())) - private val allCompressionCodecs = CompressionCodec.ALL_COMPRESSION_CODECS private var testDir: File = _ before { @@ -45,13 +45,29 @@ class ReplayListenerSuite extends FunSuite with BeforeAndAfter { } test("Simple replay") { - testSimpleReplay() - } + val logFilePath = Utils.getFilePath(testDir, "events.txt") + val fstream = fileSystem.create(logFilePath) + val writer = new PrintWriter(fstream) + val applicationStart = SparkListenerApplicationStart("Greatest App (N)ever", None, + 125L, "Mickey") + val applicationEnd = SparkListenerApplicationEnd(1000L) + writer.println(compact(render(JsonProtocol.sparkEventToJson(applicationStart)))) + writer.println(compact(render(JsonProtocol.sparkEventToJson(applicationEnd)))) + writer.close() - test("Simple replay with compression") { - allCompressionCodecs.foreach { codec => - testSimpleReplay(Some(codec)) + val conf = EventLoggingListenerSuite.getLoggingConf(logFilePath) + val logData = fileSystem.open(logFilePath) + val eventMonster = new EventMonster(conf) + try { + val replayer = new ReplayListenerBus() + replayer.addListener(eventMonster) + replayer.replay(logData, SPARK_VERSION) + } finally { + logData.close() } + assert(eventMonster.loggedEvents.size === 2) + assert(eventMonster.loggedEvents(0) === JsonProtocol.sparkEventToJson(applicationStart)) + assert(eventMonster.loggedEvents(1) === JsonProtocol.sparkEventToJson(applicationEnd)) } // This assumes the correctness of EventLoggingListener @@ -61,7 +77,7 @@ class ReplayListenerSuite extends FunSuite with BeforeAndAfter { // This assumes the correctness of EventLoggingListener test("End-to-end replay with compression") { - allCompressionCodecs.foreach { codec => + CompressionCodec.ALL_COMPRESSION_CODECS.foreach { codec => testApplicationReplay(Some(codec)) } } @@ -71,31 +87,6 @@ class ReplayListenerSuite extends FunSuite with BeforeAndAfter { * Actual test logic * * ----------------- */ - /** - * Test simple replaying of events. - */ - private def testSimpleReplay(codecName: Option[String] = None) { - val logFilePath = Utils.getFilePath(testDir, "events.txt") - val codec = codecName.map(getCompressionCodec) - val fstream = fileSystem.create(logFilePath) - val cstream = codec.map(_.compressedOutputStream(fstream)).getOrElse(fstream) - val writer = new PrintWriter(cstream) - val applicationStart = SparkListenerApplicationStart("Greatest App (N)ever", None, - 125L, "Mickey") - val applicationEnd = SparkListenerApplicationEnd(1000L) - writer.println(compact(render(JsonProtocol.sparkEventToJson(applicationStart)))) - writer.println(compact(render(JsonProtocol.sparkEventToJson(applicationEnd)))) - writer.close() - val replayer = new ReplayListenerBus(Seq(logFilePath), fileSystem, codec) - val conf = EventLoggingListenerSuite.getLoggingConf(logFilePath, codecName) - val eventMonster = new EventMonster(conf) - replayer.addListener(eventMonster) - replayer.replay() - assert(eventMonster.loggedEvents.size === 2) - assert(eventMonster.loggedEvents(0) === JsonProtocol.sparkEventToJson(applicationStart)) - assert(eventMonster.loggedEvents(1) === JsonProtocol.sparkEventToJson(applicationEnd)) - } - /** * Test end-to-end replaying of events. * @@ -105,6 +96,8 @@ class ReplayListenerSuite extends FunSuite with BeforeAndAfter { */ private def testApplicationReplay(codecName: Option[String] = None) { val logDirPath = Utils.getFilePath(testDir, "test-replay") + fileSystem.mkdirs(logDirPath) + val conf = EventLoggingListenerSuite.getLoggingConf(logDirPath, codecName) val sc = new SparkContext("local-cluster[2,1,512]", "Test replay", conf) @@ -116,22 +109,21 @@ class ReplayListenerSuite extends FunSuite with BeforeAndAfter { sc.stop() // Prepare information needed for replay - val codec = codecName.map(getCompressionCodec) val applications = fileSystem.listStatus(logDirPath) assert(applications != null && applications.size > 0) - val eventLogDir = applications.sortBy(_.getAccessTime).last - assert(eventLogDir.isDir) - val logFiles = fileSystem.listStatus(eventLogDir.getPath) - assert(logFiles != null && logFiles.size > 0) - val logFile = logFiles.find(_.getPath.getName.startsWith("EVENT_LOG_")) - assert(logFile.isDefined) - val logFilePath = logFile.get.getPath + val eventLog = applications.sortBy(_.getModificationTime).last + assert(eventLog.isFile) // Replay events - val replayer = new ReplayListenerBus(Seq(logFilePath), fileSystem, codec) + val (logData, version) = EventLoggingListener.openEventLog(eventLog.getPath(), fileSystem) val eventMonster = new EventMonster(conf) - replayer.addListener(eventMonster) - replayer.replay() + try { + val replayer = new ReplayListenerBus() + replayer.addListener(eventMonster) + replayer.replay(logData, version) + } finally { + logData.close() + } // Verify the same events are replayed in the same order assert(sc.eventLogger.isDefined) @@ -154,7 +146,9 @@ class ReplayListenerSuite extends FunSuite with BeforeAndAfter { */ private class EventMonster(conf: SparkConf) extends EventLoggingListener("test", "testdir", conf) { - logger.close() + + override def start() { } + } private def getCompressionCodec(codecName: String) = { diff --git a/core/src/test/scala/org/apache/spark/util/FileLoggerSuite.scala b/core/src/test/scala/org/apache/spark/util/FileLoggerSuite.scala deleted file mode 100644 index 72466a3aa1130..0000000000000 --- a/core/src/test/scala/org/apache/spark/util/FileLoggerSuite.scala +++ /dev/null @@ -1,169 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.util - -import java.io.{File, IOException} - -import scala.io.Source - -import org.apache.hadoop.fs.Path -import org.scalatest.{BeforeAndAfter, FunSuite} - -import org.apache.spark.SparkConf -import org.apache.spark.deploy.SparkHadoopUtil -import org.apache.spark.io.CompressionCodec - -/** - * Test writing files through the FileLogger. - */ -class FileLoggerSuite extends FunSuite with BeforeAndAfter { - private val fileSystem = Utils.getHadoopFileSystem("/", - SparkHadoopUtil.get.newConfiguration(new SparkConf())) - private val allCompressionCodecs = Seq[String]( - "org.apache.spark.io.LZFCompressionCodec", - "org.apache.spark.io.SnappyCompressionCodec" - ) - private var testDir: File = _ - private var logDirPath: Path = _ - private var logDirPathString: String = _ - - before { - testDir = Utils.createTempDir() - logDirPath = Utils.getFilePath(testDir, "test-file-logger") - logDirPathString = logDirPath.toString - } - - after { - Utils.deleteRecursively(testDir) - } - - test("Simple logging") { - testSingleFile() - } - - test ("Simple logging with compression") { - allCompressionCodecs.foreach { codec => - testSingleFile(Some(codec)) - } - } - - test("Logging multiple files") { - testMultipleFiles() - } - - test("Logging multiple files with compression") { - allCompressionCodecs.foreach { codec => - testMultipleFiles(Some(codec)) - } - } - - test("Logging when directory already exists") { - // Create the logging directory multiple times - new FileLogger(logDirPathString, new SparkConf, compress = false, overwrite = true).start() - new FileLogger(logDirPathString, new SparkConf, compress = false, overwrite = true).start() - new FileLogger(logDirPathString, new SparkConf, compress = false, overwrite = true).start() - - // If overwrite is not enabled, an exception should be thrown - intercept[IOException] { - new FileLogger(logDirPathString, new SparkConf, compress = false, overwrite = false).start() - } - } - - - /* ----------------- * - * Actual test logic * - * ----------------- */ - - /** - * Test logging to a single file. - */ - private def testSingleFile(codecName: Option[String] = None) { - val conf = getLoggingConf(codecName) - val codec = codecName.map { c => CompressionCodec.createCodec(conf) } - val logger = - if (codecName.isDefined) { - new FileLogger(logDirPathString, conf, compress = true) - } else { - new FileLogger(logDirPathString, conf) - } - logger.start() - assert(fileSystem.exists(logDirPath)) - assert(fileSystem.getFileStatus(logDirPath).isDir) - assert(fileSystem.listStatus(logDirPath).size === 0) - - logger.newFile() - val files = fileSystem.listStatus(logDirPath) - assert(files.size === 1) - val firstFile = files.head - val firstFilePath = firstFile.getPath - - logger.log("hello") - logger.flush() - assert(readFileContent(firstFilePath, codec) === "hello") - - logger.log(" world") - logger.close() - assert(readFileContent(firstFilePath, codec) === "hello world") - } - - /** - * Test logging to multiple files. - */ - private def testMultipleFiles(codecName: Option[String] = None) { - val conf = getLoggingConf(codecName) - val codec = codecName.map { c => CompressionCodec.createCodec(conf) } - val logger = - if (codecName.isDefined) { - new FileLogger(logDirPathString, conf, compress = true) - } else { - new FileLogger(logDirPathString, conf) - } - logger.start() - logger.newFile("Jean_Valjean") - logger.logLine("Who am I?") - logger.logLine("Destiny?") - logger.newFile("John_Valjohn") - logger.logLine("One") - logger.logLine("Two three...") - logger.newFile("Wolverine") - logger.logLine("There was a time") - logger.logLine("A time when our enemies knew honor.") - logger.close() - assert(readFileContent(new Path(logDirPath, "Jean_Valjean"), codec) === "Who am I?\nDestiny?") - assert(readFileContent(new Path(logDirPath, "John_Valjohn"), codec) === "One\nTwo three...") - assert(readFileContent(new Path(logDirPath, "Wolverine"), codec) === - "There was a time\nA time when our enemies knew honor.") - } - - /** - * Read the content of the file specified by the given path. - * If a compression codec is specified, use it to read the file. - */ - private def readFileContent(logPath: Path, codec: Option[CompressionCodec] = None): String = { - val fstream = fileSystem.open(logPath) - val cstream = codec.map(_.compressedInputStream(fstream)).getOrElse(fstream) - Source.fromInputStream(cstream).getLines().mkString("\n") - } - - private def getLoggingConf(codecName: Option[String]) = { - val conf = new SparkConf - codecName.foreach { c => conf.set("spark.io.compression.codec", c) } - conf - } - -} From c25c669d95293ce7f72f2758d6737fabd0d4390a Mon Sep 17 00:00:00 2001 From: Eran Medan Date: Fri, 19 Dec 2014 18:29:36 -0800 Subject: [PATCH 063/320] change signature of example to match released code the signature of registerKryoClasses is actually of Array[Class[_]] not Seq Author: Eran Medan Closes #3747 from eranation/patch-1 and squashes the following commits: ee9885d [Eran Medan] change signature of example to match released code --- docs/tuning.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/tuning.md b/docs/tuning.md index e2fdcfe6a37d9..efaac9d3d405f 100644 --- a/docs/tuning.md +++ b/docs/tuning.md @@ -51,7 +51,7 @@ To register your own custom classes with Kryo, use the `registerKryoClasses` met {% highlight scala %} val conf = new SparkConf().setMaster(...).setAppName(...) -conf.registerKryoClasses(Seq(classOf[MyClass1], classOf[MyClass2])) +conf.registerKryoClasses(Array(classOf[MyClass1], classOf[MyClass2])) val sc = new SparkContext(conf) {% endhighlight %} From 8d932475e6759e869c16ce6cac203a2e56558716 Mon Sep 17 00:00:00 2001 From: Masayoshi TSUZUKI Date: Fri, 19 Dec 2014 19:19:53 -0800 Subject: [PATCH 064/320] [SPARK-3060] spark-shell.cmd doesn't accept application options in Windows OS Added equivalent module as utils.sh and modified spark-shell2.cmd to use it to parse options. Now we can use application options. ex) `bin\spark-shell.cmd --master spark://master:7077 -i path\to\script.txt` Author: Masayoshi TSUZUKI Closes #3350 from tsudukim/feature/SPARK-3060 and squashes the following commits: 4551e56 [Masayoshi TSUZUKI] Modified too long line which defines the submission options to pass findstr command. 3a11361 [Masayoshi TSUZUKI] [SPARK-3060] spark-shell.cmd doesn't accept application options in Windows OS --- bin/spark-shell2.cmd | 21 ++++++++++++++- bin/windows-utils.cmd | 59 +++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 79 insertions(+), 1 deletion(-) create mode 100644 bin/windows-utils.cmd diff --git a/bin/spark-shell2.cmd b/bin/spark-shell2.cmd index 2ee60b4e2a2b3..1d1a40da315eb 100644 --- a/bin/spark-shell2.cmd +++ b/bin/spark-shell2.cmd @@ -19,4 +19,23 @@ rem set SPARK_HOME=%~dp0.. -cmd /V /E /C %SPARK_HOME%\bin\spark-submit.cmd --class org.apache.spark.repl.Main %* spark-shell +echo "%*" | findstr " --help -h" >nul +if %ERRORLEVEL% equ 0 ( + call :usage + exit /b 0 +) + +call %SPARK_HOME%\bin\windows-utils.cmd %* +if %ERRORLEVEL% equ 1 ( + call :usage + exit /b 1 +) + +cmd /V /E /C %SPARK_HOME%\bin\spark-submit.cmd --class org.apache.spark.repl.Main %SUBMISSION_OPTS% spark-shell %APPLICATION_OPTS% + +exit /b 0 + +:usage +echo "Usage: .\bin\spark-shell.cmd [options]" >&2 +%SPARK_HOME%\bin\spark-submit --help 2>&1 | findstr /V "Usage" 1>&2 +exit /b 0 diff --git a/bin/windows-utils.cmd b/bin/windows-utils.cmd new file mode 100644 index 0000000000000..1082a952dac99 --- /dev/null +++ b/bin/windows-utils.cmd @@ -0,0 +1,59 @@ +rem +rem Licensed to the Apache Software Foundation (ASF) under one or more +rem contributor license agreements. See the NOTICE file distributed with +rem this work for additional information regarding copyright ownership. +rem The ASF licenses this file to You under the Apache License, Version 2.0 +rem (the "License"); you may not use this file except in compliance with +rem the License. You may obtain a copy of the License at +rem +rem http://www.apache.org/licenses/LICENSE-2.0 +rem +rem Unless required by applicable law or agreed to in writing, software +rem distributed under the License is distributed on an "AS IS" BASIS, +rem WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +rem See the License for the specific language governing permissions and +rem limitations under the License. +rem + +rem Gather all spark-submit options into SUBMISSION_OPTS + +set SUBMISSION_OPTS= +set APPLICATION_OPTS= + +rem NOTE: If you add or remove spark-sumbmit options, +rem modify NOT ONLY this script but also SparkSubmitArgument.scala + +:OptsLoop +if "x%1"=="x" ( + goto :OptsLoopEnd +) + +SET opts="\<--master\> \<--deploy-mode\> \<--class\> \<--name\> \<--jars\> \<--py-files\> \<--files\>" +SET opts="%opts:~1,-1% \<--conf\> \<--properties-file\> \<--driver-memory\> \<--driver-java-options\>" +SET opts="%opts:~1,-1% \<--driver-library-path\> \<--driver-class-path\> \<--executor-memory\>" +SET opts="%opts:~1,-1% \<--driver-cores\> \<--total-executor-cores\> \<--executor-cores\> \<--queue\>" +SET opts="%opts:~1,-1% \<--num-executors\> \<--archives\>" + +echo %1 | findstr %opts% >nul +if %ERRORLEVEL% equ 0 ( + if "x%2"=="x" ( + echo "%1" requires an argument. >&2 + exit /b 1 + ) + set SUBMISSION_OPTS=%SUBMISSION_OPTS% %1 %2 + shift + shift + goto :OptsLoop +) +echo %1 | findstr "\<--verbose\> \<-v\> \<--supervise\>" >nul +if %ERRORLEVEL% equ 0 ( + set SUBMISSION_OPTS=%SUBMISSION_OPTS% %1 + shift + goto :OptsLoop +) +set APPLICATION_OPTS=%APPLICATION_OPTS% %1 +shift +goto :OptsLoop + +:OptsLoopEnd +exit /b 0 From 1d648123a77bbcd9b7a34cc0d66c14fa85edfecd Mon Sep 17 00:00:00 2001 From: Kanwaljit Singh Date: Fri, 19 Dec 2014 19:25:39 -0800 Subject: [PATCH 065/320] SPARK-2641: Passing num executors to spark arguments from properties file Since we can set spark executor memory and executor cores using property file, we must also be allowed to set the executor instances. Author: Kanwaljit Singh Closes #1657 from kjsingh/branch-1.0 and squashes the following commits: d8a5a12 [Kanwaljit Singh] SPARK-2641: Fixing how spark arguments are loaded from properties file for num executors Conflicts: core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala --- .../scala/org/apache/spark/deploy/SparkSubmitArguments.scala | 2 ++ 1 file changed, 2 insertions(+) diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala index f0e9ee67f6a67..958bd03617b3c 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala @@ -120,6 +120,8 @@ private[spark] class SparkSubmitArguments(args: Seq[String], env: Map[String, St name = Option(name).orElse(sparkProperties.get("spark.app.name")).orNull jars = Option(jars).orElse(sparkProperties.get("spark.jars")).orNull deployMode = Option(deployMode).orElse(env.get("DEPLOY_MODE")).orNull + numExecutors = Option(numExecutors) + .getOrElse(defaultProperties.get("spark.executor.instances").orNull) // Try to set main class from JAR if no --class argument is given if (mainClass == null && !isPython && primaryResource != null) { From 7cb3f54793124c527d62906c565aba2c3544e422 Mon Sep 17 00:00:00 2001 From: Daniel Darabos Date: Fri, 19 Dec 2014 19:32:39 -0800 Subject: [PATCH 066/320] [SPARK-4831] Do not include SPARK_CLASSPATH if empty My guess for fixing https://issues.apache.org/jira/browse/SPARK-4831. Author: Daniel Darabos Closes #3678 from darabos/patch-1 and squashes the following commits: 36e1243 [Daniel Darabos] Do not include SPARK_CLASSPATH if empty. --- bin/compute-classpath.sh | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/bin/compute-classpath.sh b/bin/compute-classpath.sh index 685051eeed9f1..a31ea73d3ce19 100755 --- a/bin/compute-classpath.sh +++ b/bin/compute-classpath.sh @@ -25,7 +25,11 @@ FWDIR="$(cd "`dirname "$0"`"/..; pwd)" . "$FWDIR"/bin/load-spark-env.sh -CLASSPATH="$SPARK_CLASSPATH:$SPARK_SUBMIT_CLASSPATH" +if [ -n "$SPARK_CLASSPATH" ]; then + CLASSPATH="$SPARK_CLASSPATH:$SPARK_SUBMIT_CLASSPATH" +else + CLASSPATH="$SPARK_SUBMIT_CLASSPATH" +fi # Build up classpath if [ -n "$SPARK_CONF_DIR" ]; then From 15c03e1e0efac29855f32984da7c6b0321f0e37a Mon Sep 17 00:00:00 2001 From: Andrew Or Date: Fri, 19 Dec 2014 19:36:20 -0800 Subject: [PATCH 067/320] [SPARK-4140] Document dynamic allocation Once the external shuffle service is also documented, the dynamic allocation section will link to it. Let me know if the whole dynamic allocation should be moved to its separate page; I personally think the organization might be cleaner that way. This patch builds on top of oza's work in #3689. aarondav pwendell Author: Andrew Or Author: Tsuyoshi Ozawa Closes #3731 from andrewor14/document-dynamic-allocation and squashes the following commits: 1281447 [Andrew Or] Address a few comments b9843f2 [Andrew Or] Document the configs as well 246fb44 [Andrew Or] Merge branch 'SPARK-4839' of github.com:oza/spark into document-dynamic-allocation 8c64004 [Andrew Or] Add documentation for dynamic allocation (without configs) 6827b56 [Tsuyoshi Ozawa] Fixing a documentation of spark.dynamicAllocation.enabled. 53cff58 [Tsuyoshi Ozawa] Adding a documentation about dynamic resource allocation. --- docs/configuration.md | 61 +++++++++++++++++++++++ docs/job-scheduling.md | 108 +++++++++++++++++++++++++++++++++++++++++ 2 files changed, 169 insertions(+) diff --git a/docs/configuration.md b/docs/configuration.md index 64aa94f622afa..2c8dea869b092 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -1008,6 +1008,67 @@ Apart from these, the following properties are also available, and may be useful +#### Dynamic allocation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Property NameDefaultMeaning
spark.dynamicAllocation.enabledfalse + Whether to use dynamic resource allocation, which scales the number of executors registered + with this application up and down based on the workload. Note that this is currently only + available on YARN mode. For more detail, see the description + here. +

+ This requires the following configurations to be set: + spark.dynamicAllocation.minExecutors, + spark.dynamicAllocation.maxExecutors, and + spark.shuffle.service.enabled +
spark.dynamicAllocation.minExecutors(none) + Lower bound for the number of executors if dynamic allocation is enabled (required). +
spark.dynamicAllocation.maxExecutors(none) + Upper bound for the number of executors if dynamic allocation is enabled (required). +
spark.dynamicAllocation.schedulerBacklogTimeout60 + If dynamic allocation is enabled and there have been pending tasks backlogged for more than + this duration (in seconds), new executors will be requested. For more detail, see this + description. +
spark.dynamicAllocation.sustainedSchedulerBacklogTimeoutschedulerBacklogTimeout + Same as spark.dynamicAllocation.schedulerBacklogTimeout, but used only for + subsequent executor requests. For more detail, see this + description. +
spark.dynamicAllocation.executorIdleTimeout600 + If dynamic allocation is enabled and an executor has been idle for more than this duration + (in seconds), the executor will be removed. For more detail, see this + description. +
+ #### Security diff --git a/docs/job-scheduling.md b/docs/job-scheduling.md index 94604f301dd46..dfbb871f01d2c 100644 --- a/docs/job-scheduling.md +++ b/docs/job-scheduling.md @@ -56,6 +56,114 @@ the same RDDs. For example, the [Shark](http://shark.cs.berkeley.edu) JDBC serve queries. In future releases, in-memory storage systems such as [Tachyon](http://tachyon-project.org) will provide another approach to share RDDs. +## Dynamic Resource Allocation + +Spark 1.2 introduces the ability to dynamically scale the set of cluster resources allocated to +your application up and down based on the workload. This means that your application may give +resources back to the cluster if they are no longer used and request them again later when there +is demand. This feature is particularly useful if multiple applications share resources in your +Spark cluster. If a subset of the resources allocated to an application becomes idle, it can be +returned to the cluster's pool of resources and acquired by other applications. In Spark, dynamic +resource allocation is performed on the granularity of the executor and can be enabled through +`spark.dynamicAllocation.enabled`. + +This feature is currently disabled by default and available only on [YARN](running-on-yarn.html). +A future release will extend this to [standalone mode](spark-standalone.html) and +[Mesos coarse-grained mode](running-on-mesos.html#mesos-run-modes). Note that although Spark on +Mesos already has a similar notion of dynamic resource sharing in fine-grained mode, enabling +dynamic allocation allows your Mesos application to take advantage of coarse-grained low-latency +scheduling while sharing cluster resources efficiently. + +### Configuration and Setup + +All configurations used by this feature live under the `spark.dynamicAllocation.*` namespace. +To enable this feature, your application must set `spark.dynamicAllocation.enabled` to `true` and +provide lower and upper bounds for the number of executors through +`spark.dynamicAllocation.minExecutors` and `spark.dynamicAllocation.maxExecutors`. Other relevant +configurations are described on the [configurations page](configuration.html#dynamic-allocation) +and in the subsequent sections in detail. + +Additionally, your application must use an external shuffle service. The purpose of the service is +to preserve the shuffle files written by executors so the executors can be safely removed (more +detail described [below](job-scheduling.html#graceful-decommission-of-executors)). To enable +this service, set `spark.shuffle.service.enabled` to `true`. In YARN, this external shuffle service +is implemented in `org.apache.spark.yarn.network.YarnShuffleService` that runs in each `NodeManager` +in your cluster. To start this service, follow these steps: + +1. Build Spark with the [YARN profile](building-spark.html). Skip this step if you are using a +pre-packaged distribution. +2. Locate the `spark--yarn-shuffle.jar`. This should be under +`$SPARK_HOME/network/yarn/target/scala-` if you are building Spark yourself, and under +`lib` if you are using a distribution. +2. Add this jar to the classpath of all `NodeManager`s in your cluster. +3. In the `yarn-site.xml` on each node, add `spark_shuffle` to `yarn.nodemanager.aux-services`, +then set `yarn.nodemanager.aux-services.spark_shuffle.class` to +`org.apache.spark.yarn.network.YarnShuffleService`. Additionally, set all relevant +`spark.shuffle.service.*` [configurations](configuration.html). +4. Restart all `NodeManager`s in your cluster. + +### Resource Allocation Policy + +At a high level, Spark should relinquish executors when they are no longer used and acquire +executors when they are needed. Since there is no definitive way to predict whether an executor +that is about to be removed will run a task in the near future, or whether a new executor that is +about to be added will actually be idle, we need a set of heuristics to determine when to remove +and request executors. + +#### Request Policy + +A Spark application with dynamic allocation enabled requests additional executors when it has +pending tasks waiting to be scheduled. This condition necessarily implies that the existing set +of executors is insufficient to simultaneously saturate all tasks that have been submitted but +not yet finished. + +Spark requests executors in rounds. The actual request is triggered when there have been pending +tasks for `spark.dynamicAllocation.schedulerBacklogTimeout` seconds, and then triggered again +every `spark.dynamicAllocation.sustainedSchedulerBacklogTimeout` seconds thereafter if the queue +of pending tasks persists. Additionally, the number of executors requested in each round increases +exponentially from the previous round. For instance, an application will add 1 executor in the +first round, and then 2, 4, 8 and so on executors in the subsequent rounds. + +The motivation for an exponential increase policy is twofold. First, an application should request +executors cautiously in the beginning in case it turns out that only a few additional executors is +sufficient. This echoes the justification for TCP slow start. Second, the application should be +able to ramp up its resource usage in a timely manner in case it turns out that many executors are +actually needed. + +#### Remove Policy + +The policy for removing executors is much simpler. A Spark application removes an executor when +it has been idle for more than `spark.dynamicAllocation.executorIdleTimeout` seconds. Note that, +under most circumstances, this condition is mutually exclusive with the request condition, in that +an executor should not be idle if there are still pending tasks to be scheduled. + +### Graceful Decommission of Executors + +Before dynamic allocation, a Spark executor exits either on failure or when the associated +application has also exited. In both scenarios, all state associated with the executor is no +longer needed and can be safely discarded. With dynamic allocation, however, the application +is still running when an executor is explicitly removed. If the application attempts to access +state stored in or written by the executor, it will have to perform a recompute the state. Thus, +Spark needs a mechanism to decommission an executor gracefully by preserving its state before +removing it. + +This requirement is especially important for shuffles. During a shuffle, the Spark executor first +writes its own map outputs locally to disk, and then acts as the server for those files when other +executors attempt to fetch them. In the event of stragglers, which are tasks that run for much +longer than their peers, dynamic allocation may remove an executor before the shuffle completes, +in which case the shuffle files written by that executor must be recomputed unnecessarily. + +The solution for preserving shuffle files is to use an external shuffle service, also introduced +in Spark 1.2. This service refers to a long-running process that runs on each node of your cluster +independently of your Spark applications and their executors. If the service is enabled, Spark +executors will fetch shuffle files from the service instead of from each other. This means any +shuffle state written by an executor may continue to be served beyond the executor's lifetime. + +In addition to writing shuffle files, executors also cache data either on disk or in memory. +When an executor is removed, however, all cached data will no longer be accessible. There is +currently not yet a solution for this in Spark 1.2. In future releases, the cached data may be +preserved through an off-heap storage similar in spirit to how shuffle files are preserved through +the external shuffle service. # Scheduling Within an Application From a764960b3b6d842eef7fa4777c8fa99d3f60fa1e Mon Sep 17 00:00:00 2001 From: huangzhaowei Date: Fri, 19 Dec 2014 23:32:56 -0800 Subject: [PATCH 068/320] [Minor] Build Failed: value defaultProperties not found Mvn Build Failed: value defaultProperties not found .Maybe related to this pr: https://github.com/apache/spark/commit/1d648123a77bbcd9b7a34cc0d66c14fa85edfecd andrewor14 can you look at this problem? Author: huangzhaowei Closes #3749 from SaintBacchus/Mvn-Build-Fail and squashes the following commits: 8e2917c [huangzhaowei] Build Failed: value defaultProperties not found --- .../scala/org/apache/spark/deploy/SparkSubmitArguments.scala | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala index 958bd03617b3c..607b4df73db99 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala @@ -121,7 +121,7 @@ private[spark] class SparkSubmitArguments(args: Seq[String], env: Map[String, St jars = Option(jars).orElse(sparkProperties.get("spark.jars")).orNull deployMode = Option(deployMode).orElse(env.get("DEPLOY_MODE")).orNull numExecutors = Option(numExecutors) - .getOrElse(defaultProperties.get("spark.executor.instances").orNull) + .getOrElse(sparkProperties.get("spark.executor.instances").orNull) // Try to set main class from JAR if no --class argument is given if (mainClass == null && !isPython && primaryResource != null) { From c6a3c0d5052e5bf6f981e5f91e05cba38b707237 Mon Sep 17 00:00:00 2001 From: Sean Owen Date: Sun, 21 Dec 2014 13:16:57 -0800 Subject: [PATCH 069/320] SPARK-4910 [CORE] build failed (use of FileStatus.isFile in Hadoop 1.x) Fix small Hadoop 1 compile error from SPARK-2261. In Hadoop 1.x, all we have is FileStatus.isDir, so these "is file" assertions are changed to "is not a dir". This is how similar checks are done so far in the code base. Author: Sean Owen Closes #3754 from srowen/SPARK-4910 and squashes the following commits: 52c5e4e [Sean Owen] Fix small Hadoop 1 compile error from SPARK-2261 --- .../apache/spark/scheduler/EventLoggingListenerSuite.scala | 4 ++-- .../org/apache/spark/scheduler/ReplayListenerSuite.scala | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala index 5909811c2034f..1de7e130039a5 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala @@ -65,11 +65,11 @@ class EventLoggingListenerSuite extends FunSuite with BeforeAndAfter with Loggin val logPath = new Path(eventLogger.logPath + EventLoggingListener.IN_PROGRESS) assert(fileSystem.exists(logPath)) val logStatus = fileSystem.getFileStatus(logPath) - assert(logStatus.isFile) + assert(!logStatus.isDir) // Verify log is renamed after stop() eventLogger.stop() - assert(fileSystem.getFileStatus(new Path(eventLogger.logPath)).isFile()) + assert(!fileSystem.getFileStatus(new Path(eventLogger.logPath)).isDir) } test("Basic event logging") { diff --git a/core/src/test/scala/org/apache/spark/scheduler/ReplayListenerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/ReplayListenerSuite.scala index 7e635cb061441..7e360cc6082ec 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/ReplayListenerSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/ReplayListenerSuite.scala @@ -112,7 +112,7 @@ class ReplayListenerSuite extends FunSuite with BeforeAndAfter { val applications = fileSystem.listStatus(logDirPath) assert(applications != null && applications.size > 0) val eventLog = applications.sortBy(_.getModificationTime).last - assert(eventLog.isFile) + assert(!eventLog.isDir) // Replay events val (logData, version) = EventLoggingListener.openEventLog(eventLog.getPath(), fileSystem) From 6ee6aa70b7d52408cc66bd1434cbeae3212e3f01 Mon Sep 17 00:00:00 2001 From: zsxwing Date: Sun, 21 Dec 2014 22:10:19 -0800 Subject: [PATCH 070/320] [SPARK-2075][Core] Make the compiler generate same bytes code for Hadoop 1.+ and Hadoop 2.+ `NullWritable` is a `Comparable` rather than `Comparable[NullWritable]` in Hadoop 1.+, so the compiler cannot find an implicit Ordering for it. It will generate different anonymous classes for `saveAsTextFile` in Hadoop 1.+ and Hadoop 2.+. Therefore, here we provide an Ordering for NullWritable so that the compiler will generate same codes. I used the following commands to confirm the generated byte codes are some. ``` mvn -Dhadoop.version=1.2.1 -DskipTests clean package -pl core -am javap -private -c -classpath core/target/scala-2.10/classes org.apache.spark.rdd.RDD > ~/hadoop1.txt mvn -Pyarn -Phadoop-2.2 -Dhadoop.version=2.2.0 -DskipTests clean package -pl core -am javap -private -c -classpath core/target/scala-2.10/classes org.apache.spark.rdd.RDD > ~/hadoop2.txt diff ~/hadoop1.txt ~/hadoop2.txt ``` However, the compiler will generate different codes for the classes which call methods of `JobContext/TaskAttemptContext`. `JobContext/TaskAttemptContext` is a class in Hadoop 1.+, and calling its method will use `invokevirtual`, while it's an interface in Hadoop 2.+, and will use `invokeinterface`. To fix it, we can use reflection to call `JobContext/TaskAttemptContext.getConfiguration`. Author: zsxwing Closes #3740 from zsxwing/SPARK-2075 and squashes the following commits: 39d9df2 [zsxwing] Fix the code style e4ad8b5 [zsxwing] Use null for the implicit Ordering 734bac9 [zsxwing] Explicitly set the implicit parameters ca03559 [zsxwing] Use reflection to access JobContext/TaskAttemptContext.getConfiguration fa40db0 [zsxwing] Add an Ordering for NullWritable to make the compiler generate same byte codes for RDD --- .../apache/spark/deploy/SparkHadoopUtil.scala | 12 +++++++++++ .../input/FixedLengthBinaryInputFormat.scala | 3 ++- .../input/FixedLengthBinaryRecordReader.scala | 3 ++- .../spark/input/PortableDataStream.scala | 4 +++- .../input/WholeTextFileRecordReader.scala | 4 +++- .../main/scala/org/apache/spark/rdd/RDD.scala | 21 +++++++++++++++++-- 6 files changed, 41 insertions(+), 6 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala b/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala index 60ee115e393ce..57f9faf5ddd1d 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala @@ -24,6 +24,7 @@ import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.{FileSystem, Path} import org.apache.hadoop.fs.FileSystem.Statistics import org.apache.hadoop.mapred.JobConf +import org.apache.hadoop.mapreduce.{JobContext, TaskAttemptContext} import org.apache.hadoop.security.Credentials import org.apache.hadoop.security.UserGroupInformation @@ -183,6 +184,17 @@ class SparkHadoopUtil extends Logging { Class.forName("org.apache.hadoop.fs.FileSystem$Statistics$StatisticsData") statisticsDataClass.getDeclaredMethod(methodName) } + + /** + * Using reflection to get the Configuration from JobContext/TaskAttemptContext. If we directly + * call `JobContext/TaskAttemptContext.getConfiguration`, it will generate different byte codes + * for Hadoop 1.+ and Hadoop 2.+ because JobContext/TaskAttemptContext is class in Hadoop 1.+ + * while it's interface in Hadoop 2.+. + */ + def getConfigurationFromJobContext(context: JobContext): Configuration = { + val method = context.getClass.getMethod("getConfiguration") + method.invoke(context).asInstanceOf[Configuration] + } } object SparkHadoopUtil { diff --git a/core/src/main/scala/org/apache/spark/input/FixedLengthBinaryInputFormat.scala b/core/src/main/scala/org/apache/spark/input/FixedLengthBinaryInputFormat.scala index 89b29af2000c8..c219d21fbefa9 100644 --- a/core/src/main/scala/org/apache/spark/input/FixedLengthBinaryInputFormat.scala +++ b/core/src/main/scala/org/apache/spark/input/FixedLengthBinaryInputFormat.scala @@ -21,6 +21,7 @@ import org.apache.hadoop.fs.Path import org.apache.hadoop.io.{BytesWritable, LongWritable} import org.apache.hadoop.mapreduce.lib.input.FileInputFormat import org.apache.hadoop.mapreduce.{InputSplit, JobContext, RecordReader, TaskAttemptContext} +import org.apache.spark.deploy.SparkHadoopUtil /** * Custom Input Format for reading and splitting flat binary files that contain records, @@ -33,7 +34,7 @@ private[spark] object FixedLengthBinaryInputFormat { /** Retrieves the record length property from a Hadoop configuration */ def getRecordLength(context: JobContext): Int = { - context.getConfiguration.get(RECORD_LENGTH_PROPERTY).toInt + SparkHadoopUtil.get.getConfigurationFromJobContext(context).get(RECORD_LENGTH_PROPERTY).toInt } } diff --git a/core/src/main/scala/org/apache/spark/input/FixedLengthBinaryRecordReader.scala b/core/src/main/scala/org/apache/spark/input/FixedLengthBinaryRecordReader.scala index 36a1e5d475f46..67a96925da019 100644 --- a/core/src/main/scala/org/apache/spark/input/FixedLengthBinaryRecordReader.scala +++ b/core/src/main/scala/org/apache/spark/input/FixedLengthBinaryRecordReader.scala @@ -24,6 +24,7 @@ import org.apache.hadoop.io.compress.CompressionCodecFactory import org.apache.hadoop.io.{BytesWritable, LongWritable} import org.apache.hadoop.mapreduce.{InputSplit, RecordReader, TaskAttemptContext} import org.apache.hadoop.mapreduce.lib.input.FileSplit +import org.apache.spark.deploy.SparkHadoopUtil /** * FixedLengthBinaryRecordReader is returned by FixedLengthBinaryInputFormat. @@ -82,7 +83,7 @@ private[spark] class FixedLengthBinaryRecordReader // the actual file we will be reading from val file = fileSplit.getPath // job configuration - val job = context.getConfiguration + val job = SparkHadoopUtil.get.getConfigurationFromJobContext(context) // check compression val codec = new CompressionCodecFactory(job).getCodec(file) if (codec != null) { diff --git a/core/src/main/scala/org/apache/spark/input/PortableDataStream.scala b/core/src/main/scala/org/apache/spark/input/PortableDataStream.scala index 457472547fcbb..593a62b3e3b32 100644 --- a/core/src/main/scala/org/apache/spark/input/PortableDataStream.scala +++ b/core/src/main/scala/org/apache/spark/input/PortableDataStream.scala @@ -28,6 +28,7 @@ import org.apache.hadoop.mapreduce.{InputSplit, JobContext, RecordReader, TaskAt import org.apache.hadoop.mapreduce.lib.input.{CombineFileInputFormat, CombineFileRecordReader, CombineFileSplit} import org.apache.spark.annotation.Experimental +import org.apache.spark.deploy.SparkHadoopUtil /** * A general format for reading whole files in as streams, byte arrays, @@ -145,7 +146,8 @@ class PortableDataStream( private val confBytes = { val baos = new ByteArrayOutputStream() - context.getConfiguration.write(new DataOutputStream(baos)) + SparkHadoopUtil.get.getConfigurationFromJobContext(context). + write(new DataOutputStream(baos)) baos.toByteArray } diff --git a/core/src/main/scala/org/apache/spark/input/WholeTextFileRecordReader.scala b/core/src/main/scala/org/apache/spark/input/WholeTextFileRecordReader.scala index 1b1131b9b8831..31bde8a78f3c6 100644 --- a/core/src/main/scala/org/apache/spark/input/WholeTextFileRecordReader.scala +++ b/core/src/main/scala/org/apache/spark/input/WholeTextFileRecordReader.scala @@ -26,6 +26,7 @@ import org.apache.hadoop.mapreduce.InputSplit import org.apache.hadoop.mapreduce.lib.input.{CombineFileSplit, CombineFileRecordReader} import org.apache.hadoop.mapreduce.RecordReader import org.apache.hadoop.mapreduce.TaskAttemptContext +import org.apache.spark.deploy.SparkHadoopUtil /** @@ -51,7 +52,8 @@ private[spark] class WholeTextFileRecordReader( extends RecordReader[String, String] with Configurable { private[this] val path = split.getPath(index) - private[this] val fs = path.getFileSystem(context.getConfiguration) + private[this] val fs = path.getFileSystem( + SparkHadoopUtil.get.getConfigurationFromJobContext(context)) // True means the current file has been processed, then skip it. private[this] var processed = false diff --git a/core/src/main/scala/org/apache/spark/rdd/RDD.scala b/core/src/main/scala/org/apache/spark/rdd/RDD.scala index 214f22bc5b603..a94206963b52f 100644 --- a/core/src/main/scala/org/apache/spark/rdd/RDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/RDD.scala @@ -1174,7 +1174,20 @@ abstract class RDD[T: ClassTag]( * Save this RDD as a text file, using string representations of elements. */ def saveAsTextFile(path: String) { - this.map(x => (NullWritable.get(), new Text(x.toString))) + // https://issues.apache.org/jira/browse/SPARK-2075 + // + // NullWritable is a `Comparable` in Hadoop 1.+, so the compiler cannot find an implicit + // Ordering for it and will use the default `null`. However, it's a `Comparable[NullWritable]` + // in Hadoop 2.+, so the compiler will call the implicit `Ordering.ordered` method to create an + // Ordering for `NullWritable`. That's why the compiler will generate different anonymous + // classes for `saveAsTextFile` in Hadoop 1.+ and Hadoop 2.+. + // + // Therefore, here we provide an explicit Ordering `null` to make sure the compiler generate + // same bytecodes for `saveAsTextFile`. + val nullWritableClassTag = implicitly[ClassTag[NullWritable]] + val textClassTag = implicitly[ClassTag[Text]] + val r = this.map(x => (NullWritable.get(), new Text(x.toString))) + RDD.rddToPairRDDFunctions(r)(nullWritableClassTag, textClassTag, null) .saveAsHadoopFile[TextOutputFormat[NullWritable, Text]](path) } @@ -1182,7 +1195,11 @@ abstract class RDD[T: ClassTag]( * Save this RDD as a compressed text file, using string representations of elements. */ def saveAsTextFile(path: String, codec: Class[_ <: CompressionCodec]) { - this.map(x => (NullWritable.get(), new Text(x.toString))) + // https://issues.apache.org/jira/browse/SPARK-2075 + val nullWritableClassTag = implicitly[ClassTag[NullWritable]] + val textClassTag = implicitly[ClassTag[Text]] + val r = this.map(x => (NullWritable.get(), new Text(x.toString))) + RDD.rddToPairRDDFunctions(r)(nullWritableClassTag, textClassTag, null) .saveAsHadoopFile[TextOutputFormat[NullWritable, Text]](path, codec) } From 93b2f3a8826e189f6398c9b30bc00de205a3c64a Mon Sep 17 00:00:00 2001 From: zsxwing Date: Mon, 22 Dec 2014 11:20:00 -0800 Subject: [PATCH 071/320] [SPARK-4918][Core] Reuse Text in saveAsTextFile Reuse Text in saveAsTextFile to reduce GC. /cc rxin Author: zsxwing Closes #3762 from zsxwing/SPARK-4918 and squashes the following commits: 59f03eb [zsxwing] Reuse Text in saveAsTextFile --- .../main/scala/org/apache/spark/rdd/RDD.scala | 16 ++++++++++++++-- 1 file changed, 14 insertions(+), 2 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/rdd/RDD.scala b/core/src/main/scala/org/apache/spark/rdd/RDD.scala index a94206963b52f..f47c2d1fcdcc7 100644 --- a/core/src/main/scala/org/apache/spark/rdd/RDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/RDD.scala @@ -1186,7 +1186,13 @@ abstract class RDD[T: ClassTag]( // same bytecodes for `saveAsTextFile`. val nullWritableClassTag = implicitly[ClassTag[NullWritable]] val textClassTag = implicitly[ClassTag[Text]] - val r = this.map(x => (NullWritable.get(), new Text(x.toString))) + val r = this.mapPartitions { iter => + val text = new Text() + iter.map { x => + text.set(x.toString) + (NullWritable.get(), text) + } + } RDD.rddToPairRDDFunctions(r)(nullWritableClassTag, textClassTag, null) .saveAsHadoopFile[TextOutputFormat[NullWritable, Text]](path) } @@ -1198,7 +1204,13 @@ abstract class RDD[T: ClassTag]( // https://issues.apache.org/jira/browse/SPARK-2075 val nullWritableClassTag = implicitly[ClassTag[NullWritable]] val textClassTag = implicitly[ClassTag[Text]] - val r = this.map(x => (NullWritable.get(), new Text(x.toString))) + val r = this.mapPartitions { iter => + val text = new Text() + iter.map { x => + text.set(x.toString) + (NullWritable.get(), text) + } + } RDD.rddToPairRDDFunctions(r)(nullWritableClassTag, textClassTag, null) .saveAsHadoopFile[TextOutputFormat[NullWritable, Text]](path, codec) } From 96606f69b7cd88edea5d4b6427f598a91ccb4c33 Mon Sep 17 00:00:00 2001 From: Tsuyoshi Ozawa Date: Mon, 22 Dec 2014 11:28:05 -0800 Subject: [PATCH 072/320] [SPARK-4915][YARN] Fix classname to be specified for external shuffle service. Author: Tsuyoshi Ozawa Closes #3757 from oza/SPARK-4915 and squashes the following commits: 3b0d6d6 [Tsuyoshi Ozawa] Fix classname to be specified for external shuffle service. --- docs/job-scheduling.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/job-scheduling.md b/docs/job-scheduling.md index dfbb871f01d2c..a5425eb3557b2 100644 --- a/docs/job-scheduling.md +++ b/docs/job-scheduling.md @@ -98,7 +98,7 @@ pre-packaged distribution. 2. Add this jar to the classpath of all `NodeManager`s in your cluster. 3. In the `yarn-site.xml` on each node, add `spark_shuffle` to `yarn.nodemanager.aux-services`, then set `yarn.nodemanager.aux-services.spark_shuffle.class` to -`org.apache.spark.yarn.network.YarnShuffleService`. Additionally, set all relevant +`org.apache.spark.network.yarn.YarnShuffleService`. Additionally, set all relevant `spark.shuffle.service.*` [configurations](configuration.html). 4. Restart all `NodeManager`s in your cluster. From 39272c8cdb3dc8ffbce44f6ee8055217d041e165 Mon Sep 17 00:00:00 2001 From: "Zhang, Liye" Date: Mon, 22 Dec 2014 11:36:49 -0800 Subject: [PATCH 073/320] [SPARK-4870] Add spark version to driver log Author: Zhang, Liye Closes #3717 from liyezhang556520/version2Log and squashes the following commits: ccd30d7 [Zhang, Liye] delete log in sparkConf 330f70c [Zhang, Liye] move the log from SaprkConf to SparkContext 96dc115 [Zhang, Liye] remove curly brace e833330 [Zhang, Liye] add spark version to driver log --- core/src/main/scala/org/apache/spark/SparkContext.scala | 3 +++ 1 file changed, 3 insertions(+) diff --git a/core/src/main/scala/org/apache/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala index b1c6a90d182f6..57bc3d4e4ae36 100644 --- a/core/src/main/scala/org/apache/spark/SparkContext.scala +++ b/core/src/main/scala/org/apache/spark/SparkContext.scala @@ -172,6 +172,9 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli private[spark] def this(master: String, appName: String, sparkHome: String, jars: Seq[String]) = this(master, appName, sparkHome, jars, Map(), Map()) + // log out Spark Version in Spark driver log + logInfo(s"Running Spark version $SPARK_VERSION") + private[spark] val conf = config.clone() conf.validateSettings() From 8773705fd4ab167bb06bee7f274b337560e3c293 Mon Sep 17 00:00:00 2001 From: zsxwing Date: Mon, 22 Dec 2014 12:11:36 -0800 Subject: [PATCH 074/320] [SPARK-4883][Shuffle] Add a name to the directoryCleaner thread Author: zsxwing Closes #3734 from zsxwing/SPARK-4883 and squashes the following commits: e6f2b61 [zsxwing] Fix the name cc74727 [zsxwing] Add a name to the directoryCleaner thread --- .../network/shuffle/ExternalShuffleBlockManager.java | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/network/shuffle/src/main/java/org/apache/spark/network/shuffle/ExternalShuffleBlockManager.java b/network/shuffle/src/main/java/org/apache/spark/network/shuffle/ExternalShuffleBlockManager.java index dfe0ba0595090..93e6fdd7161fa 100644 --- a/network/shuffle/src/main/java/org/apache/spark/network/shuffle/ExternalShuffleBlockManager.java +++ b/network/shuffle/src/main/java/org/apache/spark/network/shuffle/ExternalShuffleBlockManager.java @@ -37,6 +37,7 @@ import org.apache.spark.network.buffer.ManagedBuffer; import org.apache.spark.network.shuffle.protocol.ExecutorShuffleInfo; import org.apache.spark.network.util.JavaUtils; +import org.apache.spark.network.util.NettyUtils; import org.apache.spark.network.util.TransportConf; /** @@ -49,7 +50,7 @@ * the Executor's memory, unlike the IndexShuffleBlockManager. */ public class ExternalShuffleBlockManager { - private final Logger logger = LoggerFactory.getLogger(ExternalShuffleBlockManager.class); + private static final Logger logger = LoggerFactory.getLogger(ExternalShuffleBlockManager.class); // Map containing all registered executors' metadata. private final ConcurrentMap executors; @@ -60,8 +61,9 @@ public class ExternalShuffleBlockManager { private final TransportConf conf; public ExternalShuffleBlockManager(TransportConf conf) { - // TODO: Give this thread a name. - this(conf, Executors.newSingleThreadExecutor()); + this(conf, Executors.newSingleThreadExecutor( + // Add `spark` prefix because it will run in NM in Yarn mode. + NettyUtils.createThreadFactory("spark-shuffle-directory-cleaner"))); } // Allows tests to have more control over when directories are cleaned up. From 1d9788e42ec96407bd63da8f2a2abebc7253c671 Mon Sep 17 00:00:00 2001 From: carlmartin Date: Mon, 22 Dec 2014 12:13:53 -0800 Subject: [PATCH 075/320] [Minor] Improve some code in BroadcastTest for short Using val arr1 = (0 until num).toArray instead of val arr1 = new Array[Int](num) for (i <- 0 until arr1.length) { arr1(i) = i } for short. Author: carlmartin Closes #3750 from SaintBacchus/BroadcastTest and squashes the following commits: 43adb70 [carlmartin] Improve some code in BroadcastTest for short --- .../main/scala/org/apache/spark/examples/BroadcastTest.scala | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/examples/src/main/scala/org/apache/spark/examples/BroadcastTest.scala b/examples/src/main/scala/org/apache/spark/examples/BroadcastTest.scala index 973049b95a7bd..adecd934358c4 100644 --- a/examples/src/main/scala/org/apache/spark/examples/BroadcastTest.scala +++ b/examples/src/main/scala/org/apache/spark/examples/BroadcastTest.scala @@ -38,10 +38,7 @@ object BroadcastTest { val slices = if (args.length > 0) args(0).toInt else 2 val num = if (args.length > 1) args(1).toInt else 1000000 - val arr1 = new Array[Int](num) - for (i <- 0 until arr1.length) { - arr1(i) = i - } + val arr1 = (0 until num).toArray for (i <- 0 until 3) { println("Iteration " + i) From fb8e85e80e50904e1e93daf30dcadef62c3b7ca1 Mon Sep 17 00:00:00 2001 From: Takeshi Yamamuro Date: Mon, 22 Dec 2014 12:19:23 -0800 Subject: [PATCH 076/320] [SPARK-4733] Add missing prameter comments in ShuffleDependency Add missing Javadoc comments in ShuffleDependency. Author: Takeshi Yamamuro Closes #3594 from maropu/DependencyJavadocFix and squashes the following commits: 32129b4 [Takeshi Yamamuro] Fix comments in @aggregator and @mapSideCombine 303c75d [Takeshi Yamamuro] [SPARK-4733] Add missing prameter comments in ShuffleDependency --- core/src/main/scala/org/apache/spark/Dependency.scala | 3 +++ 1 file changed, 3 insertions(+) diff --git a/core/src/main/scala/org/apache/spark/Dependency.scala b/core/src/main/scala/org/apache/spark/Dependency.scala index ab2594cfc02eb..9a7cd4523e5ab 100644 --- a/core/src/main/scala/org/apache/spark/Dependency.scala +++ b/core/src/main/scala/org/apache/spark/Dependency.scala @@ -60,6 +60,9 @@ abstract class NarrowDependency[T](_rdd: RDD[T]) extends Dependency[T] { * @param serializer [[org.apache.spark.serializer.Serializer Serializer]] to use. If set to None, * the default serializer, as specified by `spark.serializer` config option, will * be used. + * @param keyOrdering key ordering for RDD's shuffles + * @param aggregator map/reduce-side aggregator for RDD's shuffle + * @param mapSideCombine whether to perform partial aggregation (also known as map-side combine) */ @DeveloperApi class ShuffleDependency[K, V, C]( From d62da642ace17b37283eab64149545723c8474a7 Mon Sep 17 00:00:00 2001 From: Sandy Ryza Date: Mon, 22 Dec 2014 12:23:43 -0800 Subject: [PATCH 077/320] SPARK-4447. Remove layers of abstraction in YARN code no longer needed after dropping yarn-alpha Author: Sandy Ryza Closes #3652 from sryza/sandy-spark-4447 and squashes the following commits: 2791158 [Sandy Ryza] Review feedback c23507b [Sandy Ryza] Strip margin from client arguments help string 18be7ba [Sandy Ryza] SPARK-4447 --- .../spark/deploy/yarn/ApplicationMaster.scala | 2 +- .../spark/deploy/yarn/ClientArguments.scala | 2 +- .../deploy/yarn/YarnAllocationHandler.scala | 213 ------------------ .../spark/deploy/yarn/YarnAllocator.scala | 201 ++++++++++++++--- .../spark/deploy/yarn/YarnRMClient.scala | 78 ++++++- .../spark/deploy/yarn/YarnRMClientImpl.scala | 110 --------- 6 files changed, 234 insertions(+), 372 deletions(-) delete mode 100644 yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala delete mode 100644 yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnRMClientImpl.scala diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala index dc7a078446324..b2e45435c4abb 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala @@ -511,7 +511,7 @@ object ApplicationMaster extends Logging { SignalLogger.register(log) val amArgs = new ApplicationMasterArguments(args) SparkHadoopUtil.get.runAsSparkUser { () => - master = new ApplicationMaster(amArgs, new YarnRMClientImpl(amArgs)) + master = new ApplicationMaster(amArgs, new YarnRMClient(amArgs)) System.exit(master.run()) } } diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala index c439969510fc9..7305249f80e83 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala @@ -197,6 +197,6 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf) | to work with. | --files files Comma separated list of files to be distributed with the job. | --archives archives Comma separated list of archives to be distributed with the job. - """ + """.stripMargin } } diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala deleted file mode 100644 index 2bbf5d7db8668..0000000000000 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala +++ /dev/null @@ -1,213 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.deploy.yarn - -import scala.collection.JavaConversions._ -import scala.collection.mutable.{ArrayBuffer, HashMap} - -import org.apache.spark.{SecurityManager, SparkConf} -import org.apache.spark.scheduler.SplitInfo - -import org.apache.hadoop.conf.Configuration -import org.apache.hadoop.yarn.api.records._ -import org.apache.hadoop.yarn.api.protocolrecords.AllocateResponse -import org.apache.hadoop.yarn.client.api.AMRMClient -import org.apache.hadoop.yarn.client.api.AMRMClient.ContainerRequest -import org.apache.hadoop.yarn.util.Records - -/** - * Acquires resources for executors from a ResourceManager and launches executors in new containers. - */ -private[yarn] class YarnAllocationHandler( - conf: Configuration, - sparkConf: SparkConf, - amClient: AMRMClient[ContainerRequest], - appAttemptId: ApplicationAttemptId, - args: ApplicationMasterArguments, - preferredNodes: collection.Map[String, collection.Set[SplitInfo]], - securityMgr: SecurityManager) - extends YarnAllocator(conf, sparkConf, appAttemptId, args, preferredNodes, securityMgr) { - - override protected def releaseContainer(container: Container) = { - amClient.releaseAssignedContainer(container.getId()) - } - - // pending isn't used on stable as the AMRMClient handles incremental asks - override protected def allocateContainers(count: Int, pending: Int): YarnAllocateResponse = { - addResourceRequests(count) - - // We have already set the container request. Poll the ResourceManager for a response. - // This doubles as a heartbeat if there are no pending container requests. - val progressIndicator = 0.1f - new StableAllocateResponse(amClient.allocate(progressIndicator)) - } - - private def createRackResourceRequests( - hostContainers: ArrayBuffer[ContainerRequest] - ): ArrayBuffer[ContainerRequest] = { - // Generate modified racks and new set of hosts under it before issuing requests. - val rackToCounts = new HashMap[String, Int]() - - for (container <- hostContainers) { - val candidateHost = container.getNodes.last - assert(YarnSparkHadoopUtil.ANY_HOST != candidateHost) - - val rack = YarnSparkHadoopUtil.lookupRack(conf, candidateHost) - if (rack != null) { - var count = rackToCounts.getOrElse(rack, 0) - count += 1 - rackToCounts.put(rack, count) - } - } - - val requestedContainers = new ArrayBuffer[ContainerRequest](rackToCounts.size) - for ((rack, count) <- rackToCounts) { - requestedContainers ++= createResourceRequests( - AllocationType.RACK, - rack, - count, - YarnSparkHadoopUtil.RM_REQUEST_PRIORITY) - } - - requestedContainers - } - - private def addResourceRequests(numExecutors: Int) { - val containerRequests: List[ContainerRequest] = - if (numExecutors <= 0) { - logDebug("numExecutors: " + numExecutors) - List() - } else if (preferredHostToCount.isEmpty) { - logDebug("host preferences is empty") - createResourceRequests( - AllocationType.ANY, - resource = null, - numExecutors, - YarnSparkHadoopUtil.RM_REQUEST_PRIORITY).toList - } else { - // Request for all hosts in preferred nodes and for numExecutors - - // candidates.size, request by default allocation policy. - val hostContainerRequests = new ArrayBuffer[ContainerRequest](preferredHostToCount.size) - for ((candidateHost, candidateCount) <- preferredHostToCount) { - val requiredCount = candidateCount - allocatedContainersOnHost(candidateHost) - - if (requiredCount > 0) { - hostContainerRequests ++= createResourceRequests( - AllocationType.HOST, - candidateHost, - requiredCount, - YarnSparkHadoopUtil.RM_REQUEST_PRIORITY) - } - } - val rackContainerRequests: List[ContainerRequest] = createRackResourceRequests( - hostContainerRequests).toList - - val anyContainerRequests = createResourceRequests( - AllocationType.ANY, - resource = null, - numExecutors, - YarnSparkHadoopUtil.RM_REQUEST_PRIORITY) - - val containerRequestBuffer = new ArrayBuffer[ContainerRequest]( - hostContainerRequests.size + rackContainerRequests.size() + anyContainerRequests.size) - - containerRequestBuffer ++= hostContainerRequests - containerRequestBuffer ++= rackContainerRequests - containerRequestBuffer ++= anyContainerRequests - containerRequestBuffer.toList - } - - for (request <- containerRequests) { - amClient.addContainerRequest(request) - } - - for (request <- containerRequests) { - val nodes = request.getNodes - var hostStr = if (nodes == null || nodes.isEmpty) { - "Any" - } else { - nodes.last - } - logInfo("Container request (host: %s, priority: %s, capability: %s".format( - hostStr, - request.getPriority().getPriority, - request.getCapability)) - } - } - - private def createResourceRequests( - requestType: AllocationType.AllocationType, - resource: String, - numExecutors: Int, - priority: Int - ): ArrayBuffer[ContainerRequest] = { - - // If hostname is specified, then we need at least two requests - node local and rack local. - // There must be a third request, which is ANY. That will be specially handled. - requestType match { - case AllocationType.HOST => { - assert(YarnSparkHadoopUtil.ANY_HOST != resource) - val hostname = resource - val nodeLocal = constructContainerRequests( - Array(hostname), - racks = null, - numExecutors, - priority) - - // Add `hostname` to the global (singleton) host->rack mapping in YarnAllocationHandler. - YarnSparkHadoopUtil.populateRackInfo(conf, hostname) - nodeLocal - } - case AllocationType.RACK => { - val rack = resource - constructContainerRequests(hosts = null, Array(rack), numExecutors, priority) - } - case AllocationType.ANY => constructContainerRequests( - hosts = null, racks = null, numExecutors, priority) - case _ => throw new IllegalArgumentException( - "Unexpected/unsupported request type: " + requestType) - } - } - - private def constructContainerRequests( - hosts: Array[String], - racks: Array[String], - numExecutors: Int, - priority: Int - ): ArrayBuffer[ContainerRequest] = { - - val memoryRequest = executorMemory + memoryOverhead - val resource = Resource.newInstance(memoryRequest, executorCores) - - val prioritySetting = Records.newRecord(classOf[Priority]) - prioritySetting.setPriority(priority) - - val requests = new ArrayBuffer[ContainerRequest]() - for (i <- 0 until numExecutors) { - requests += new ContainerRequest(resource, hosts, racks, prioritySetting) - } - requests - } - - private class StableAllocateResponse(response: AllocateResponse) extends YarnAllocateResponse { - override def getAllocatedContainers() = response.getAllocatedContainers() - override def getAvailableResources() = response.getAvailableResources() - override def getCompletedContainersStatuses() = response.getCompletedContainersStatuses() - } - -} diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala index b32e15738f28b..de65ef23ad1ce 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala @@ -17,7 +17,6 @@ package org.apache.spark.deploy.yarn -import java.util.{List => JList} import java.util.concurrent._ import java.util.concurrent.atomic.AtomicInteger import java.util.regex.Pattern @@ -25,17 +24,20 @@ import java.util.regex.Pattern import scala.collection.JavaConversions._ import scala.collection.mutable.{ArrayBuffer, HashMap, HashSet} +import com.google.common.util.concurrent.ThreadFactoryBuilder + import org.apache.hadoop.conf.Configuration import org.apache.hadoop.yarn.api.records._ import org.apache.hadoop.yarn.api.protocolrecords.AllocateResponse +import org.apache.hadoop.yarn.client.api.AMRMClient +import org.apache.hadoop.yarn.client.api.AMRMClient.ContainerRequest +import org.apache.hadoop.yarn.util.Records import org.apache.spark.{Logging, SecurityManager, SparkConf, SparkEnv} +import org.apache.spark.deploy.yarn.YarnSparkHadoopUtil._ import org.apache.spark.scheduler.{SplitInfo, TaskSchedulerImpl} import org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend -import com.google.common.util.concurrent.ThreadFactoryBuilder -import org.apache.spark.deploy.yarn.YarnSparkHadoopUtil._ - object AllocationType extends Enumeration { type AllocationType = Value val HOST, RACK, ANY = Value @@ -52,12 +54,12 @@ object AllocationType extends Enumeration { // more info on how we are requesting for containers. /** - * Common code for the Yarn container allocator. Contains all the version-agnostic code to - * manage container allocation for a running Spark application. + * Acquires resources for executors from a ResourceManager and launches executors in new containers. */ -private[yarn] abstract class YarnAllocator( +private[yarn] class YarnAllocator( conf: Configuration, sparkConf: SparkConf, + amClient: AMRMClient[ContainerRequest], appAttemptId: ApplicationAttemptId, args: ApplicationMasterArguments, preferredNodes: collection.Map[String, collection.Set[SplitInfo]], @@ -67,7 +69,7 @@ private[yarn] abstract class YarnAllocator( import YarnAllocator._ // These three are locked on allocatedHostToContainersMap. Complementary data structures - // allocatedHostToContainersMap : containers which are running : host, Set + // allocatedHostToContainersMap : containers which are running : host, Set // allocatedContainerToHostMap: container to host mapping. private val allocatedHostToContainersMap = new HashMap[String, collection.mutable.Set[ContainerId]]() @@ -161,8 +163,6 @@ private[yarn] abstract class YarnAllocator( def allocateResources(): Unit = synchronized { val missing = maxExecutors - numPendingAllocate.get() - numExecutorsRunning.get() - // this is needed by alpha, do it here since we add numPending right after this - val executorsPending = numPendingAllocate.get() if (missing > 0) { val totalExecutorMemory = executorMemory + memoryOverhead numPendingAllocate.addAndGet(missing) @@ -172,7 +172,7 @@ private[yarn] abstract class YarnAllocator( logDebug("Empty allocation request ...") } - val allocateResponse = allocateContainers(missing, executorsPending) + val allocateResponse = allocateContainers(missing) val allocatedContainers = allocateResponse.getAllocatedContainers() if (allocatedContainers.size > 0) { @@ -368,7 +368,7 @@ private[yarn] abstract class YarnAllocator( val containerId = completedContainer.getContainerId if (releasedContainers.containsKey(containerId)) { - // YarnAllocationHandler already marked the container for release, so remove it from + // Already marked the container for release, so remove it from // `releasedContainers`. releasedContainers.remove(containerId) } else { @@ -441,20 +441,16 @@ private[yarn] abstract class YarnAllocator( } } - protected def allocatedContainersOnHost(host: String): Int = { - var retval = 0 + private def allocatedContainersOnHost(host: String): Int = { allocatedHostToContainersMap.synchronized { - retval = allocatedHostToContainersMap.getOrElse(host, Set()).size + allocatedHostToContainersMap.getOrElse(host, Set()).size } - retval } - protected def allocatedContainersOnRack(rack: String): Int = { - var retval = 0 + private def allocatedContainersOnRack(rack: String): Int = { allocatedHostToContainersMap.synchronized { - retval = allocatedRackCount.getOrElse(rack, 0) + allocatedRackCount.getOrElse(rack, 0) } - retval } private def isResourceConstraintSatisfied(container: Container): Boolean = { @@ -464,9 +460,8 @@ private[yarn] abstract class YarnAllocator( // A simple method to copy the split info map. private def generateNodeToWeight( conf: Configuration, - input: collection.Map[String, collection.Set[SplitInfo]] - ): (Map[String, Int], Map[String, Int]) = { - + input: collection.Map[String, collection.Set[SplitInfo]]) + : (Map[String, Int], Map[String, Int]) = { if (input == null) { return (Map[String, Int](), Map[String, Int]()) } @@ -488,9 +483,9 @@ private[yarn] abstract class YarnAllocator( (hostToCount.toMap, rackToCount.toMap) } - private def internalReleaseContainer(container: Container) = { + private def internalReleaseContainer(container: Container): Unit = { releasedContainers.put(container.getId(), true) - releaseContainer(container) + amClient.releaseAssignedContainer(container.getId()) } /** @@ -498,26 +493,158 @@ private[yarn] abstract class YarnAllocator( * * @param count Number of containers to allocate. * If zero, should still contact RM (as a heartbeat). - * @param pending Number of containers pending allocate. Only used on alpha. * @return Response to the allocation request. */ - protected def allocateContainers(count: Int, pending: Int): YarnAllocateResponse + private def allocateContainers(count: Int): AllocateResponse = { + addResourceRequests(count) + + // We have already set the container request. Poll the ResourceManager for a response. + // This doubles as a heartbeat if there are no pending container requests. + val progressIndicator = 0.1f + amClient.allocate(progressIndicator) + } - /** Called to release a previously allocated container. */ - protected def releaseContainer(container: Container): Unit + private def createRackResourceRequests(hostContainers: ArrayBuffer[ContainerRequest]) + : ArrayBuffer[ContainerRequest] = { + // Generate modified racks and new set of hosts under it before issuing requests. + val rackToCounts = new HashMap[String, Int]() - /** - * Defines the interface for an allocate response from the RM. This is needed since the alpha - * and stable interfaces differ here in ways that cannot be fixed using other routes. - */ - protected trait YarnAllocateResponse { + for (container <- hostContainers) { + val candidateHost = container.getNodes.last + assert(YarnSparkHadoopUtil.ANY_HOST != candidateHost) + + val rack = YarnSparkHadoopUtil.lookupRack(conf, candidateHost) + if (rack != null) { + var count = rackToCounts.getOrElse(rack, 0) + count += 1 + rackToCounts.put(rack, count) + } + } + + val requestedContainers = new ArrayBuffer[ContainerRequest](rackToCounts.size) + for ((rack, count) <- rackToCounts) { + requestedContainers ++= createResourceRequests( + AllocationType.RACK, + rack, + count, + RM_REQUEST_PRIORITY) + } + + requestedContainers + } + + private def addResourceRequests(numExecutors: Int): Unit = { + val containerRequests: List[ContainerRequest] = + if (numExecutors <= 0) { + logDebug("numExecutors: " + numExecutors) + List() + } else if (preferredHostToCount.isEmpty) { + logDebug("host preferences is empty") + createResourceRequests( + AllocationType.ANY, + resource = null, + numExecutors, + RM_REQUEST_PRIORITY).toList + } else { + // Request for all hosts in preferred nodes and for numExecutors - + // candidates.size, request by default allocation policy. + val hostContainerRequests = new ArrayBuffer[ContainerRequest](preferredHostToCount.size) + for ((candidateHost, candidateCount) <- preferredHostToCount) { + val requiredCount = candidateCount - allocatedContainersOnHost(candidateHost) + + if (requiredCount > 0) { + hostContainerRequests ++= createResourceRequests( + AllocationType.HOST, + candidateHost, + requiredCount, + RM_REQUEST_PRIORITY) + } + } + val rackContainerRequests: List[ContainerRequest] = createRackResourceRequests( + hostContainerRequests).toList + + val anyContainerRequests = createResourceRequests( + AllocationType.ANY, + resource = null, + numExecutors, + RM_REQUEST_PRIORITY) + + val containerRequestBuffer = new ArrayBuffer[ContainerRequest]( + hostContainerRequests.size + rackContainerRequests.size + anyContainerRequests.size) + + containerRequestBuffer ++= hostContainerRequests + containerRequestBuffer ++= rackContainerRequests + containerRequestBuffer ++= anyContainerRequests + containerRequestBuffer.toList + } - def getAllocatedContainers(): JList[Container] + for (request <- containerRequests) { + amClient.addContainerRequest(request) + } - def getAvailableResources(): Resource + for (request <- containerRequests) { + val nodes = request.getNodes + val hostStr = if (nodes == null || nodes.isEmpty) { + "Any" + } else { + nodes.last + } + logInfo("Container request (host: %s, priority: %s, capability: %s".format( + hostStr, + request.getPriority().getPriority, + request.getCapability)) + } + } - def getCompletedContainersStatuses(): JList[ContainerStatus] + private def createResourceRequests( + requestType: AllocationType.AllocationType, + resource: String, + numExecutors: Int, + priority: Int): ArrayBuffer[ContainerRequest] = { + // If hostname is specified, then we need at least two requests - node local and rack local. + // There must be a third request, which is ANY. That will be specially handled. + requestType match { + case AllocationType.HOST => { + assert(YarnSparkHadoopUtil.ANY_HOST != resource) + val hostname = resource + val nodeLocal = constructContainerRequests( + Array(hostname), + racks = null, + numExecutors, + priority) + + // Add `hostname` to the global (singleton) host->rack mapping in YarnAllocationHandler. + YarnSparkHadoopUtil.populateRackInfo(conf, hostname) + nodeLocal + } + case AllocationType.RACK => { + val rack = resource + constructContainerRequests(hosts = null, Array(rack), numExecutors, priority) + } + case AllocationType.ANY => constructContainerRequests( + hosts = null, racks = null, numExecutors, priority) + case _ => throw new IllegalArgumentException( + "Unexpected/unsupported request type: " + requestType) + } + } + private def constructContainerRequests( + hosts: Array[String], + racks: Array[String], + numExecutors: Int, + priority: Int + ): ArrayBuffer[ContainerRequest] = { + val memoryRequest = executorMemory + memoryOverhead + val resource = Resource.newInstance(memoryRequest, executorCores) + + val prioritySetting = Records.newRecord(classOf[Priority]) + prioritySetting.setPriority(priority) + + val requests = new ArrayBuffer[ContainerRequest]() + for (i <- 0 until numExecutors) { + requests += new ContainerRequest(resource, hosts, racks, prioritySetting) + } + requests } } diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnRMClient.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnRMClient.scala index 2510b9c9cef68..bf4e15908bb46 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnRMClient.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnRMClient.scala @@ -17,19 +17,33 @@ package org.apache.spark.deploy.yarn +import java.util.{List => JList} + +import scala.collection.JavaConversions._ import scala.collection.{Map, Set} +import scala.util.Try -import org.apache.hadoop.yarn.conf.YarnConfiguration +import org.apache.hadoop.conf.Configuration +import org.apache.hadoop.yarn.api.ApplicationConstants import org.apache.hadoop.yarn.api.records._ +import org.apache.hadoop.yarn.client.api.AMRMClient +import org.apache.hadoop.yarn.client.api.AMRMClient.ContainerRequest +import org.apache.hadoop.yarn.conf.YarnConfiguration +import org.apache.hadoop.yarn.util.ConverterUtils +import org.apache.hadoop.yarn.webapp.util.WebAppUtils -import org.apache.spark.{SecurityManager, SparkConf, SparkContext} +import org.apache.spark.{Logging, SecurityManager, SparkConf} import org.apache.spark.scheduler.SplitInfo +import org.apache.spark.util.Utils /** - * Interface that defines a Yarn RM client. Abstracts away Yarn version-specific functionality that - * is used by Spark's AM. + * Handles registering and unregistering the application with the YARN ResourceManager. */ -trait YarnRMClient { +private[spark] class YarnRMClient(args: ApplicationMasterArguments) extends Logging { + + private var amClient: AMRMClient[ContainerRequest] = _ + private var uiHistoryAddress: String = _ + private var registered: Boolean = false /** * Registers the application master with the RM. @@ -46,7 +60,21 @@ trait YarnRMClient { preferredNodeLocations: Map[String, Set[SplitInfo]], uiAddress: String, uiHistoryAddress: String, - securityMgr: SecurityManager): YarnAllocator + securityMgr: SecurityManager + ): YarnAllocator = { + amClient = AMRMClient.createAMRMClient() + amClient.init(conf) + amClient.start() + this.uiHistoryAddress = uiHistoryAddress + + logInfo("Registering the ApplicationMaster") + synchronized { + amClient.registerApplicationMaster(Utils.localHostName(), 0, uiAddress) + registered = true + } + new YarnAllocator(conf, sparkConf, amClient, getAttemptId(), args, + preferredNodeLocations, securityMgr) + } /** * Unregister the AM. Guaranteed to only be called once. @@ -54,15 +82,45 @@ trait YarnRMClient { * @param status The final status of the AM. * @param diagnostics Diagnostics message to include in the final status. */ - def unregister(status: FinalApplicationStatus, diagnostics: String = ""): Unit + def unregister(status: FinalApplicationStatus, diagnostics: String = ""): Unit = synchronized { + if (registered) { + amClient.unregisterApplicationMaster(status, diagnostics, uiHistoryAddress) + } + } /** Returns the attempt ID. */ - def getAttemptId(): ApplicationAttemptId + def getAttemptId(): ApplicationAttemptId = { + val containerIdString = System.getenv(ApplicationConstants.Environment.CONTAINER_ID.name()) + val containerId = ConverterUtils.toContainerId(containerIdString) + containerId.getApplicationAttemptId() + } /** Returns the configuration for the AmIpFilter to add to the Spark UI. */ - def getAmIpFilterParams(conf: YarnConfiguration, proxyBase: String): Map[String, String] + def getAmIpFilterParams(conf: YarnConfiguration, proxyBase: String): Map[String, String] = { + // Figure out which scheme Yarn is using. Note the method seems to have been added after 2.2, + // so not all stable releases have it. + val prefix = Try(classOf[WebAppUtils].getMethod("getHttpSchemePrefix", classOf[Configuration]) + .invoke(null, conf).asInstanceOf[String]).getOrElse("http://") + + // If running a new enough Yarn, use the HA-aware API for retrieving the RM addresses. + try { + val method = classOf[WebAppUtils].getMethod("getProxyHostsAndPortsForAmFilter", + classOf[Configuration]) + val proxies = method.invoke(null, conf).asInstanceOf[JList[String]] + val hosts = proxies.map { proxy => proxy.split(":")(0) } + val uriBases = proxies.map { proxy => prefix + proxy + proxyBase } + Map("PROXY_HOSTS" -> hosts.mkString(","), "PROXY_URI_BASES" -> uriBases.mkString(",")) + } catch { + case e: NoSuchMethodException => + val proxy = WebAppUtils.getProxyHostAndPort(conf) + val parts = proxy.split(":") + val uriBase = prefix + proxy + proxyBase + Map("PROXY_HOST" -> parts(0), "PROXY_URI_BASE" -> uriBase) + } + } /** Returns the maximum number of attempts to register the AM. */ - def getMaxRegAttempts(conf: YarnConfiguration): Int + def getMaxRegAttempts(conf: YarnConfiguration): Int = + conf.getInt(YarnConfiguration.RM_AM_MAX_ATTEMPTS, YarnConfiguration.DEFAULT_RM_AM_MAX_ATTEMPTS) } diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnRMClientImpl.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnRMClientImpl.scala deleted file mode 100644 index 8d4b96ed79933..0000000000000 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnRMClientImpl.scala +++ /dev/null @@ -1,110 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.deploy.yarn - -import java.util.{List => JList} - -import scala.collection.{Map, Set} -import scala.collection.JavaConversions._ -import scala.util._ - -import org.apache.hadoop.conf.Configuration -import org.apache.hadoop.yarn.api._ -import org.apache.hadoop.yarn.api.protocolrecords._ -import org.apache.hadoop.yarn.api.records._ -import org.apache.hadoop.yarn.client.api.AMRMClient -import org.apache.hadoop.yarn.client.api.AMRMClient.ContainerRequest -import org.apache.hadoop.yarn.conf.YarnConfiguration -import org.apache.hadoop.yarn.util.ConverterUtils -import org.apache.hadoop.yarn.webapp.util.WebAppUtils - -import org.apache.spark.{Logging, SecurityManager, SparkConf} -import org.apache.spark.scheduler.SplitInfo -import org.apache.spark.util.Utils - - -/** - * YarnRMClient implementation for the Yarn stable API. - */ -private class YarnRMClientImpl(args: ApplicationMasterArguments) extends YarnRMClient with Logging { - - private var amClient: AMRMClient[ContainerRequest] = _ - private var uiHistoryAddress: String = _ - private var registered: Boolean = false - - override def register( - conf: YarnConfiguration, - sparkConf: SparkConf, - preferredNodeLocations: Map[String, Set[SplitInfo]], - uiAddress: String, - uiHistoryAddress: String, - securityMgr: SecurityManager) = { - amClient = AMRMClient.createAMRMClient() - amClient.init(conf) - amClient.start() - this.uiHistoryAddress = uiHistoryAddress - - logInfo("Registering the ApplicationMaster") - synchronized { - amClient.registerApplicationMaster(Utils.localHostName(), 0, uiAddress) - registered = true - } - new YarnAllocationHandler(conf, sparkConf, amClient, getAttemptId(), args, - preferredNodeLocations, securityMgr) - } - - override def unregister(status: FinalApplicationStatus, diagnostics: String = "") = synchronized { - if (registered) { - amClient.unregisterApplicationMaster(status, diagnostics, uiHistoryAddress) - } - } - - override def getAttemptId() = { - val containerIdString = System.getenv(ApplicationConstants.Environment.CONTAINER_ID.name()) - val containerId = ConverterUtils.toContainerId(containerIdString) - val appAttemptId = containerId.getApplicationAttemptId() - appAttemptId - } - - override def getAmIpFilterParams(conf: YarnConfiguration, proxyBase: String) = { - // Figure out which scheme Yarn is using. Note the method seems to have been added after 2.2, - // so not all stable releases have it. - val prefix = Try(classOf[WebAppUtils].getMethod("getHttpSchemePrefix", classOf[Configuration]) - .invoke(null, conf).asInstanceOf[String]).getOrElse("http://") - - // If running a new enough Yarn, use the HA-aware API for retrieving the RM addresses. - try { - val method = classOf[WebAppUtils].getMethod("getProxyHostsAndPortsForAmFilter", - classOf[Configuration]) - val proxies = method.invoke(null, conf).asInstanceOf[JList[String]] - val hosts = proxies.map { proxy => proxy.split(":")(0) } - val uriBases = proxies.map { proxy => prefix + proxy + proxyBase } - Map("PROXY_HOSTS" -> hosts.mkString(","), "PROXY_URI_BASES" -> uriBases.mkString(",")) - } catch { - case e: NoSuchMethodException => - val proxy = WebAppUtils.getProxyHostAndPort(conf) - val parts = proxy.split(":") - val uriBase = prefix + proxy + proxyBase - Map("PROXY_HOST" -> parts(0), "PROXY_URI_BASE" -> uriBase) - } - } - - override def getMaxRegAttempts(conf: YarnConfiguration) = - conf.getInt(YarnConfiguration.RM_AM_MAX_ATTEMPTS, YarnConfiguration.DEFAULT_RM_AM_MAX_ATTEMPTS) - -} From 7c0ed13d298d9cf66842c667602e2dccb8f5605b Mon Sep 17 00:00:00 2001 From: Kostas Sakellis Date: Mon, 22 Dec 2014 13:07:01 -0800 Subject: [PATCH 078/320] [SPARK-4079] [CORE] Consolidates Errors if a CompressionCodec is not available This commit consolidates some of the exceptions thrown if compression codecs are not available. If a bad configuration string was passed in, a ClassNotFoundException was through. Also, if Snappy was not available, it would throw an InvocationTargetException when the codec was being used (not when it was being initialized). Now, an IllegalArgumentException is thrown when a codec is not available at creation time - either because the class does not exist or the codec itself is not available in the system. This will allow us to have a better message and fail faster. Author: Kostas Sakellis Closes #3119 from ksakellis/kostas-spark-4079 and squashes the following commits: 9709c7c [Kostas Sakellis] Removed unnecessary Logging class 63bfdd0 [Kostas Sakellis] Removed isAvailable to preserve binary compatibility 1d0ef2f [Kostas Sakellis] [SPARK-4079] [CORE] Added more information to exception 64f3d27 [Kostas Sakellis] [SPARK-4079] [CORE] Code review feedback 52dfa8f [Kostas Sakellis] [SPARK-4079] [CORE] Default to LZF if Snappy not available --- .../apache/spark/io/CompressionCodec.scala | 27 ++++++++++++++----- .../spark/io/CompressionCodecSuite.scala | 6 +++++ 2 files changed, 27 insertions(+), 6 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/io/CompressionCodec.scala b/core/src/main/scala/org/apache/spark/io/CompressionCodec.scala index 1ac7f4e448eb1..f856890d279f4 100644 --- a/core/src/main/scala/org/apache/spark/io/CompressionCodec.scala +++ b/core/src/main/scala/org/apache/spark/io/CompressionCodec.scala @@ -21,11 +21,12 @@ import java.io.{InputStream, OutputStream} import com.ning.compress.lzf.{LZFInputStream, LZFOutputStream} import net.jpountz.lz4.{LZ4BlockInputStream, LZ4BlockOutputStream} -import org.xerial.snappy.{SnappyInputStream, SnappyOutputStream} +import org.xerial.snappy.{Snappy, SnappyInputStream, SnappyOutputStream} import org.apache.spark.SparkConf import org.apache.spark.annotation.DeveloperApi import org.apache.spark.util.Utils +import org.apache.spark.Logging /** * :: DeveloperApi :: @@ -44,25 +45,33 @@ trait CompressionCodec { def compressedInputStream(s: InputStream): InputStream } - private[spark] object CompressionCodec { + private val configKey = "spark.io.compression.codec" private val shortCompressionCodecNames = Map( "lz4" -> classOf[LZ4CompressionCodec].getName, "lzf" -> classOf[LZFCompressionCodec].getName, "snappy" -> classOf[SnappyCompressionCodec].getName) def createCodec(conf: SparkConf): CompressionCodec = { - createCodec(conf, conf.get("spark.io.compression.codec", DEFAULT_COMPRESSION_CODEC)) + createCodec(conf, conf.get(configKey, DEFAULT_COMPRESSION_CODEC)) } def createCodec(conf: SparkConf, codecName: String): CompressionCodec = { val codecClass = shortCompressionCodecNames.getOrElse(codecName.toLowerCase, codecName) - val ctor = Class.forName(codecClass, true, Utils.getContextOrSparkClassLoader) - .getConstructor(classOf[SparkConf]) - ctor.newInstance(conf).asInstanceOf[CompressionCodec] + val codec = try { + val ctor = Class.forName(codecClass, true, Utils.getContextOrSparkClassLoader) + .getConstructor(classOf[SparkConf]) + Some(ctor.newInstance(conf).asInstanceOf[CompressionCodec]) + } catch { + case e: ClassNotFoundException => None + case e: IllegalArgumentException => None + } + codec.getOrElse(throw new IllegalArgumentException(s"Codec [$codecName] is not available. " + + s"Consider setting $configKey=$FALLBACK_COMPRESSION_CODEC")) } + val FALLBACK_COMPRESSION_CODEC = "lzf" val DEFAULT_COMPRESSION_CODEC = "snappy" val ALL_COMPRESSION_CODECS = shortCompressionCodecNames.values.toSeq } @@ -120,6 +129,12 @@ class LZFCompressionCodec(conf: SparkConf) extends CompressionCodec { @DeveloperApi class SnappyCompressionCodec(conf: SparkConf) extends CompressionCodec { + try { + Snappy.getNativeLibraryVersion + } catch { + case e: Error => throw new IllegalArgumentException + } + override def compressedOutputStream(s: OutputStream): OutputStream = { val blockSize = conf.getInt("spark.io.compression.snappy.block.size", 32768) new SnappyOutputStream(s, blockSize) diff --git a/core/src/test/scala/org/apache/spark/io/CompressionCodecSuite.scala b/core/src/test/scala/org/apache/spark/io/CompressionCodecSuite.scala index 25be7f25c21bb..8c6035fb367fe 100644 --- a/core/src/test/scala/org/apache/spark/io/CompressionCodecSuite.scala +++ b/core/src/test/scala/org/apache/spark/io/CompressionCodecSuite.scala @@ -85,4 +85,10 @@ class CompressionCodecSuite extends FunSuite { assert(codec.getClass === classOf[SnappyCompressionCodec]) testCodec(codec) } + + test("bad compression codec") { + intercept[IllegalArgumentException] { + CompressionCodec.createCodec(conf, "foobar") + } + } } From fbca6b6ce293b1997b40abeb9ab77b8a969a5fc9 Mon Sep 17 00:00:00 2001 From: Aaron Davidson Date: Mon, 22 Dec 2014 13:09:22 -0800 Subject: [PATCH 079/320] [SPARK-4864] Add documentation to Netty-based configs Author: Aaron Davidson Closes #3713 from aarondav/netty-configs and squashes the following commits: 8a8b373 [Aaron Davidson] Address Patrick's comments 3b1f84e [Aaron Davidson] [SPARK-4864] Add documentation to Netty-based configs --- docs/configuration.md | 35 +++++++++++++++++++ .../spark/network/util/TransportConf.java | 2 +- 2 files changed, 36 insertions(+), 1 deletion(-) diff --git a/docs/configuration.md b/docs/configuration.md index 2c8dea869b092..2cc013c47fdbb 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -852,6 +852,41 @@ Apart from these, the following properties are also available, and may be useful between nodes leading to flooding the network with those. + + + + + + + + + + + + + + + + + + + +
Property NameDefaultMeaning
spark.shuffle.io.preferDirectBufstrue + (Netty only) Off-heap buffers are used to reduce garbage collection during shuffle and cache + block transfer. For environments where off-heap memory is tightly limited, users may wish to + turn this off to force all allocations from Netty to be on-heap. +
spark.shuffle.io.numConnectionsPerPeer1 + (Netty only) Connections between hosts are reused in order to reduce connection buildup for + large clusters. For clusters with many hard disks and few hosts, this may result in insufficient + concurrency to saturate all disks, and so users may consider increasing this value. +
spark.shuffle.io.maxRetries3 + (Netty only) Fetches that fail due to IO-related exceptions are automatically retried if this is + set to a non-zero value. This retry logic helps stabilize large shuffles in the face of long GC + pauses or transient network connectivity issues. +
spark.shuffle.io.retryWait5 + (Netty only) Seconds to wait between retries of fetches. The maximum delay caused by retrying + is simply maxRetries * retryWait, by default 15 seconds. +
#### Scheduling diff --git a/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java b/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java index 13b37f96f8ce2..7c9adf52af0f0 100644 --- a/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java +++ b/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java @@ -40,7 +40,7 @@ public int connectionTimeoutMs() { return conf.getInt("spark.shuffle.io.connectionTimeout", 120) * 1000; } - /** Number of concurrent connections between two nodes for fetching data. **/ + /** Number of concurrent connections between two nodes for fetching data. */ public int numConnectionsPerPeer() { return conf.getInt("spark.shuffle.io.numConnectionsPerPeer", 1); } From a61aa669af474b4b82976541cf3a6d2787014a0b Mon Sep 17 00:00:00 2001 From: Liang-Chi Hsieh Date: Mon, 22 Dec 2014 14:13:31 -0800 Subject: [PATCH 080/320] [Minor] Fix scala doc Minor fix for an obvious scala doc error. Author: Liang-Chi Hsieh Closes #3751 from viirya/fix_scaladoc and squashes the following commits: 03fddaa [Liang-Chi Hsieh] Fix scala doc. --- .../main/scala/org/apache/spark/sql/hive/HiveInspectors.scala | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala index e1147478130dd..a156d6f7e285d 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala @@ -105,9 +105,9 @@ import scala.collection.JavaConversions._ {{{ public interface PrimitiveObjectInspector { // Java Primitives (java.lang.Integer, java.lang.String etc.) - Object getPrimitiveWritableObject(Object o); + Object getPrimitiveJavaObject(Object o); // Writables (hadoop.io.IntWritable, hadoop.io.Text etc.) - Object getPrimitiveJavaObject(Object o); + Object getPrimitiveWritableObject(Object o); // ObjectInspector only inspect the `writable` always return true, we need to check it // before invoking the methods above. boolean preferWritable(); From de9d7d2b5b6d80963505571700e83779fd98f850 Mon Sep 17 00:00:00 2001 From: "genmao.ygm" Date: Mon, 22 Dec 2014 14:14:39 -0800 Subject: [PATCH 081/320] [SPARK-4920][UI]:current spark version in UI is not striking. It is not convenient to see the Spark version. We can keep the same style with Spark website. ![spark_version](https://cloud.githubusercontent.com/assets/7402327/5527025/1c8c721c-8a35-11e4-8d6a-2734f3c6bdf8.jpg) Author: genmao.ygm Closes #3763 from uncleGen/master-clean-141222 and squashes the following commits: 0dcb9a9 [genmao.ygm] [SPARK-4920][UI]:current spark version in UI is not striking. --- .../org/apache/spark/ui/static/webui.css | 10 ++++++++++ .../scala/org/apache/spark/ui/UIUtils.scala | 19 ++++++------------- 2 files changed, 16 insertions(+), 13 deletions(-) diff --git a/core/src/main/resources/org/apache/spark/ui/static/webui.css b/core/src/main/resources/org/apache/spark/ui/static/webui.css index 68c52ac09b55a..5751964b792ce 100644 --- a/core/src/main/resources/org/apache/spark/ui/static/webui.css +++ b/core/src/main/resources/org/apache/spark/ui/static/webui.css @@ -169,6 +169,16 @@ span.additional-metric-title { display: inline-block; } +.version { + line-height: 30px; + vertical-align: bottom; + font-size: 12px; + padding: 0; + margin: 0; + font-weight: bold; + color: #777; +} + /* Hide all additional metrics by default. This is done here rather than using JavaScript to * avoid slow page loads for stage pages with large numbers (e.g., thousands) of tasks. */ .scheduler_delay, .deserialization_time, .serialization_time, .getting_result_time { diff --git a/core/src/main/scala/org/apache/spark/ui/UIUtils.scala b/core/src/main/scala/org/apache/spark/ui/UIUtils.scala index d970fa30c1c35..7486cb6b1bbc0 100644 --- a/core/src/main/scala/org/apache/spark/ui/UIUtils.scala +++ b/core/src/main/scala/org/apache/spark/ui/UIUtils.scala @@ -194,9 +194,12 @@ private[spark] object UIUtils extends Logging {

- - - +
+ + + {org.apache.spark.SPARK_VERSION} + +
    {header}

{shortAppName} application UI @@ -214,11 +217,6 @@ private[spark] object UIUtils extends Logging {

{content}
- } @@ -245,11 +243,6 @@ private[spark] object UIUtils extends Logging { {content} - } From c233ab3d8d75a33495298964fe73dbf7dd8fe305 Mon Sep 17 00:00:00 2001 From: zsxwing Date: Mon, 22 Dec 2014 14:26:28 -0800 Subject: [PATCH 082/320] [SPARK-4818][Core] Add 'iterator' to reduce memory consumed by join In Scala, `map` and `flatMap` of `Iterable` will copy the contents of `Iterable` to a new `Seq`. Such as, ```Scala val iterable = Seq(1, 2, 3).map(v => { println(v) v }) println("Iterable map done") val iterator = Seq(1, 2, 3).iterator.map(v => { println(v) v }) println("Iterator map done") ``` outputed ``` 1 2 3 Iterable map done Iterator map done ``` So we should use 'iterator' to reduce memory consumed by join. Found by Johannes Simon in http://mail-archives.apache.org/mod_mbox/spark-user/201412.mbox/%3C5BE70814-9D03-4F61-AE2C-0D63F2DE4446%40mail.de%3E Author: zsxwing Closes #3671 from zsxwing/SPARK-4824 and squashes the following commits: 48ee7b9 [zsxwing] Remove the explicit types 95d59d6 [zsxwing] Add 'iterator' to reduce memory consumed by join --- .../org/apache/spark/rdd/PairRDDFunctions.scala | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala b/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala index fe3129b62f71e..4469c89e6bb1c 100644 --- a/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala +++ b/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala @@ -483,7 +483,7 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)]) */ def join[W](other: RDD[(K, W)], partitioner: Partitioner): RDD[(K, (V, W))] = { this.cogroup(other, partitioner).flatMapValues( pair => - for (v <- pair._1; w <- pair._2) yield (v, w) + for (v <- pair._1.iterator; w <- pair._2.iterator) yield (v, w) ) } @@ -496,9 +496,9 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)]) def leftOuterJoin[W](other: RDD[(K, W)], partitioner: Partitioner): RDD[(K, (V, Option[W]))] = { this.cogroup(other, partitioner).flatMapValues { pair => if (pair._2.isEmpty) { - pair._1.map(v => (v, None)) + pair._1.iterator.map(v => (v, None)) } else { - for (v <- pair._1; w <- pair._2) yield (v, Some(w)) + for (v <- pair._1.iterator; w <- pair._2.iterator) yield (v, Some(w)) } } } @@ -513,9 +513,9 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)]) : RDD[(K, (Option[V], W))] = { this.cogroup(other, partitioner).flatMapValues { pair => if (pair._1.isEmpty) { - pair._2.map(w => (None, w)) + pair._2.iterator.map(w => (None, w)) } else { - for (v <- pair._1; w <- pair._2) yield (Some(v), w) + for (v <- pair._1.iterator; w <- pair._2.iterator) yield (Some(v), w) } } } @@ -531,9 +531,9 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)]) def fullOuterJoin[W](other: RDD[(K, W)], partitioner: Partitioner) : RDD[(K, (Option[V], Option[W]))] = { this.cogroup(other, partitioner).flatMapValues { - case (vs, Seq()) => vs.map(v => (Some(v), None)) - case (Seq(), ws) => ws.map(w => (None, Some(w))) - case (vs, ws) => for (v <- vs; w <- ws) yield (Some(v), Some(w)) + case (vs, Seq()) => vs.iterator.map(v => (Some(v), None)) + case (Seq(), ws) => ws.iterator.map(w => (None, Some(w))) + case (vs, ws) => for (v <- vs.iterator; w <- ws.iterator) yield (Some(v), Some(w)) } } From a96b72781ae40bb303613990b8d8b4721b84e1c3 Mon Sep 17 00:00:00 2001 From: DB Tsai Date: Mon, 22 Dec 2014 16:42:55 -0800 Subject: [PATCH 083/320] [SPARK-4907][MLlib] Inconsistent loss and gradient in LeastSquaresGradient compared with R In most of the academic paper and algorithm implementations, people use L = 1/2n ||A weights-y||^2 instead of L = 1/n ||A weights-y||^2 for least-squared loss. See Eq. (1) in http://web.stanford.edu/~hastie/Papers/glmnet.pdf Since MLlib uses different convention, this will result different residuals and all the stats properties will be different from GLMNET package in R. The model coefficients will be still the same under this change. Author: DB Tsai Closes #3746 from dbtsai/lir and squashes the following commits: 19c2e85 [DB Tsai] make stepsize twice to converge to the same solution 0b2c29c [DB Tsai] first commit --- .../org/apache/spark/mllib/optimization/Gradient.scala | 10 +++++----- .../regression/StreamingLinearRegressionSuite.scala | 6 +++--- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/mllib/src/main/scala/org/apache/spark/mllib/optimization/Gradient.scala b/mllib/src/main/scala/org/apache/spark/mllib/optimization/Gradient.scala index 45dbf6044fcc5..5a419d1640292 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/optimization/Gradient.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/optimization/Gradient.scala @@ -94,16 +94,16 @@ class LogisticGradient extends Gradient { * :: DeveloperApi :: * Compute gradient and loss for a Least-squared loss function, as used in linear regression. * This is correct for the averaged least squares loss function (mean squared error) - * L = 1/n ||A weights-y||^2 + * L = 1/2n ||A weights-y||^2 * See also the documentation for the precise formulation. */ @DeveloperApi class LeastSquaresGradient extends Gradient { override def compute(data: Vector, label: Double, weights: Vector): (Vector, Double) = { val diff = dot(data, weights) - label - val loss = diff * diff + val loss = diff * diff / 2.0 val gradient = data.copy - scal(2.0 * diff, gradient) + scal(diff, gradient) (gradient, loss) } @@ -113,8 +113,8 @@ class LeastSquaresGradient extends Gradient { weights: Vector, cumGradient: Vector): Double = { val diff = dot(data, weights) - label - axpy(2.0 * diff, data, cumGradient) - diff * diff + axpy(diff, data, cumGradient) + diff * diff / 2.0 } } diff --git a/mllib/src/test/scala/org/apache/spark/mllib/regression/StreamingLinearRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/regression/StreamingLinearRegressionSuite.scala index 03b71301e9ab1..70b43ddb7daf5 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/regression/StreamingLinearRegressionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/regression/StreamingLinearRegressionSuite.scala @@ -52,7 +52,7 @@ class StreamingLinearRegressionSuite extends FunSuite with TestSuiteBase { // create model val model = new StreamingLinearRegressionWithSGD() .setInitialWeights(Vectors.dense(0.0, 0.0)) - .setStepSize(0.1) + .setStepSize(0.2) .setNumIterations(25) // generate sequence of simulated data @@ -84,7 +84,7 @@ class StreamingLinearRegressionSuite extends FunSuite with TestSuiteBase { // create model val model = new StreamingLinearRegressionWithSGD() .setInitialWeights(Vectors.dense(0.0)) - .setStepSize(0.1) + .setStepSize(0.2) .setNumIterations(25) // generate sequence of simulated data @@ -118,7 +118,7 @@ class StreamingLinearRegressionSuite extends FunSuite with TestSuiteBase { // create model initialized with true weights val model = new StreamingLinearRegressionWithSGD() .setInitialWeights(Vectors.dense(10.0, 10.0)) - .setStepSize(0.1) + .setStepSize(0.2) .setNumIterations(25) // generate sequence of simulated data for testing From 0e532ccb2b282ea5f7b818e67d521dc44d94c951 Mon Sep 17 00:00:00 2001 From: Nicholas Chammas Date: Mon, 22 Dec 2014 22:54:32 -0800 Subject: [PATCH 084/320] [Docs] Minor typo fixes Author: Nicholas Chammas Closes #3772 from nchammas/patch-1 and squashes the following commits: b7d9083 [Nicholas Chammas] [Docs] Minor typo fixes --- docs/submitting-applications.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/submitting-applications.md b/docs/submitting-applications.md index 2581c9f69fa37..3bd1deaccfafe 100644 --- a/docs/submitting-applications.md +++ b/docs/submitting-applications.md @@ -10,7 +10,7 @@ through a uniform interface so you don't have to configure your application spec # Bundling Your Application's Dependencies If your code depends on other projects, you will need to package them alongside your application in order to distribute the code to a Spark cluster. To do this, -to create an assembly jar (or "uber" jar) containing your code and its dependencies. Both +create an assembly jar (or "uber" jar) containing your code and its dependencies. Both [sbt](https://github.com/sbt/sbt-assembly) and [Maven](http://maven.apache.org/plugins/maven-shade-plugin/) have assembly plugins. When creating assembly jars, list Spark and Hadoop @@ -59,7 +59,7 @@ for applications that involve the REPL (e.g. Spark shell). Alternatively, if your application is submitted from a machine far from the worker machines (e.g. locally on your laptop), it is common to use `cluster` mode to minimize network latency between the drivers and the executors. Note that `cluster` mode is currently not supported for standalone -clusters, Mesos clusters, or python applications. +clusters, Mesos clusters, or Python applications. For Python applications, simply pass a `.py` file in the place of `` instead of a JAR, and add Python `.zip`, `.egg` or `.py` files to the search path with `--py-files`. @@ -174,7 +174,7 @@ This can use up a significant amount of space over time and will need to be clea is handled automatically, and with Spark standalone, automatic cleanup can be configured with the `spark.worker.cleanup.appDataTtl` property. -For python, the equivalent `--py-files` option can be used to distribute `.egg`, `.zip` and `.py` libraries +For Python, the equivalent `--py-files` option can be used to distribute `.egg`, `.zip` and `.py` libraries to executors. # More Information From 2823c7f021efd775a14049d6cd0a1f1789a31b6c Mon Sep 17 00:00:00 2001 From: Nicholas Chammas Date: Tue, 23 Dec 2014 11:12:16 -0800 Subject: [PATCH 085/320] [SPARK-4890] Ignore downloaded EC2 libs PR #3737 changed `spark-ec2` to automatically download boto from PyPI. This PR tell git to ignore those downloaded library files. Author: Nicholas Chammas Closes #3770 from nchammas/ignore-ec2-lib and squashes the following commits: 5c440d3 [Nicholas Chammas] gitignore downloaded EC2 libs --- .gitignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitignore b/.gitignore index 30b1e12bf1b03..20095dd97343e 100644 --- a/.gitignore +++ b/.gitignore @@ -55,6 +55,7 @@ dev/create-release/*final spark-*-bin-*.tgz unit-tests.log /lib/ +ec2/lib/ rat-results.txt scalastyle.txt scalastyle-output.xml From 2d215aebaad4b4596354f1543d997d06ef340bd5 Mon Sep 17 00:00:00 2001 From: zsxwing Date: Tue, 23 Dec 2014 11:18:06 -0800 Subject: [PATCH 086/320] [SPARK-4931][Yarn][Docs] Fix the format of running-on-yarn.md Currently, the format about log4j in running-on-yarn.md is a bit messy. ![running-on-yarn](https://cloud.githubusercontent.com/assets/1000778/5535248/204c4b64-8ab4-11e4-83c3-b4722ea0ad9d.png) Author: zsxwing Closes #3774 from zsxwing/SPARK-4931 and squashes the following commits: 4a5f853 [zsxwing] Fix the format of running-on-yarn.md --- docs/running-on-yarn.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md index 86276b1aa9cea..da1c8e8aa8667 100644 --- a/docs/running-on-yarn.md +++ b/docs/running-on-yarn.md @@ -211,18 +211,18 @@ settings and a restart of all node managers. Thus, this is not applicable to hos To use a custom log4j configuration for the application master or executors, there are two options: -- upload a custom log4j.properties using spark-submit, by adding it to the "--files" list of files +- upload a custom `log4j.properties` using `spark-submit`, by adding it to the `--files` list of files to be uploaded with the application. -- add "-Dlog4j.configuration=" to "spark.driver.extraJavaOptions" - (for the driver) or "spark.executor.extraJavaOptions" (for executors). Note that if using a file, - the "file:" protocol should be explicitly provided, and the file needs to exist locally on all +- add `-Dlog4j.configuration=` to `spark.driver.extraJavaOptions` + (for the driver) or `spark.executor.extraJavaOptions` (for executors). Note that if using a file, + the `file:` protocol should be explicitly provided, and the file needs to exist locally on all the nodes. Note that for the first option, both executors and the application master will share the same log4j configuration, which may cause issues when they run on the same node (e.g. trying to write to the same log file). -If you need a reference to the proper location to put log files in the YARN so that YARN can properly display and aggregate them, use "${spark.yarn.app.container.log.dir}" in your log4j.properties. For example, log4j.appender.file_appender.File=${spark.yarn.app.container.log.dir}/spark.log. For streaming application, configuring RollingFileAppender and setting file location to YARN's log directory will avoid disk overflow caused by large log file, and logs can be accessed using YARN's log utility. +If you need a reference to the proper location to put log files in the YARN so that YARN can properly display and aggregate them, use `spark.yarn.app.container.log.dir` in your log4j.properties. For example, `log4j.appender.file_appender.File=${spark.yarn.app.container.log.dir}/spark.log`. For streaming application, configuring `RollingFileAppender` and setting file location to YARN's log directory will avoid disk overflow caused by large log file, and logs can be accessed using YARN's log utility. # Important notes From dd155369a04d7dfbf6a5745cbb243e22218367dc Mon Sep 17 00:00:00 2001 From: Marcelo Vanzin Date: Tue, 23 Dec 2014 12:02:08 -0800 Subject: [PATCH 087/320] [SPARK-4834] [standalone] Clean up application files after app finishes. Commit 7aacb7bfa added support for sharing downloaded files among multiple executors of the same app. That works great in Yarn, since the app's directory is cleaned up after the app is done. But Spark standalone mode didn't do that, so the lock/cache files created by that change were left around and could eventually fill up the disk hosting /tmp. To solve that, create app-specific directories under the local dirs when launching executors. Multiple executors launched by the same Worker will use the same app directories, so they should be able to share the downloaded files. When the application finishes, a new message is sent to all workers telling them the application has finished; once that message has been received, and all executors registered for the application shut down, then those directories will be cleaned up by the Worker. Note: Unit testing this is hard (if even possible), since local-cluster mode doesn't seem to leave the Master/Worker daemons running long enough after `sc.stop()` is called for the clean up protocol to take effect. Author: Marcelo Vanzin Closes #3705 from vanzin/SPARK-4834 and squashes the following commits: b430534 [Marcelo Vanzin] Remove seemingly unnecessary synchronization. 50eb4b9 [Marcelo Vanzin] Review feedback. c0e5ea5 [Marcelo Vanzin] [SPARK-4834] [standalone] Clean up application files after app finishes. --- .../apache/spark/deploy/DeployMessage.scala | 3 ++ .../apache/spark/deploy/master/Master.scala | 5 +++ .../spark/deploy/worker/ExecutorRunner.scala | 4 ++- .../apache/spark/deploy/worker/Worker.scala | 36 +++++++++++++++++-- .../scala/org/apache/spark/util/Utils.scala | 16 +++++++-- .../spark/deploy/JsonProtocolSuite.scala | 2 +- .../deploy/worker/ExecutorRunnerTest.scala | 3 +- 7 files changed, 61 insertions(+), 8 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/deploy/DeployMessage.scala b/core/src/main/scala/org/apache/spark/deploy/DeployMessage.scala index c46f84de8444a..243d8edb72ed3 100644 --- a/core/src/main/scala/org/apache/spark/deploy/DeployMessage.scala +++ b/core/src/main/scala/org/apache/spark/deploy/DeployMessage.scala @@ -88,6 +88,8 @@ private[deploy] object DeployMessages { case class KillDriver(driverId: String) extends DeployMessage + case class ApplicationFinished(id: String) + // Worker internal case object WorkDirCleanup // Sent to Worker actor periodically for cleaning up app folders @@ -175,4 +177,5 @@ private[deploy] object DeployMessages { // Liveness checks in various places case object SendHeartbeat + } diff --git a/core/src/main/scala/org/apache/spark/deploy/master/Master.scala b/core/src/main/scala/org/apache/spark/deploy/master/Master.scala index ed5eab9f473ce..f8137bf93c124 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/Master.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/Master.scala @@ -704,6 +704,11 @@ private[spark] class Master( } persistenceEngine.removeApplication(app) schedule() + + // Tell all workers that the application has finished, so they can clean up any app state. + workers.foreach { w => + w.actor ! ApplicationFinished(app.id) + } } } diff --git a/core/src/main/scala/org/apache/spark/deploy/worker/ExecutorRunner.scala b/core/src/main/scala/org/apache/spark/deploy/worker/ExecutorRunner.scala index f4fedc6327ab9..acbdf0d8bd7bc 100644 --- a/core/src/main/scala/org/apache/spark/deploy/worker/ExecutorRunner.scala +++ b/core/src/main/scala/org/apache/spark/deploy/worker/ExecutorRunner.scala @@ -47,6 +47,7 @@ private[spark] class ExecutorRunner( val executorDir: File, val workerUrl: String, val conf: SparkConf, + val appLocalDirs: Seq[String], var state: ExecutorState.Value) extends Logging { @@ -77,7 +78,7 @@ private[spark] class ExecutorRunner( /** * Kill executor process, wait for exit and notify worker to update resource status. * - * @param message the exception message which caused the executor's death + * @param message the exception message which caused the executor's death */ private def killProcess(message: Option[String]) { var exitCode: Option[Int] = None @@ -129,6 +130,7 @@ private[spark] class ExecutorRunner( logInfo("Launch command: " + command.mkString("\"", "\" \"", "\"")) builder.directory(executorDir) + builder.environment.put("SPARK_LOCAL_DIRS", appLocalDirs.mkString(",")) // In case we are running this from within the Spark Shell, avoid creating a "scala" // parent process for the executor command builder.environment.put("SPARK_LAUNCH_WITH_SCALA", "0") diff --git a/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala b/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala index 6863b625514c6..86a87ec22235e 100755 --- a/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala +++ b/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala @@ -23,7 +23,7 @@ import java.text.SimpleDateFormat import java.util.{UUID, Date} import scala.collection.JavaConversions._ -import scala.collection.mutable.HashMap +import scala.collection.mutable.{HashMap, HashSet} import scala.concurrent.duration._ import scala.language.postfixOps import scala.util.Random @@ -109,6 +109,8 @@ private[spark] class Worker( val finishedExecutors = new HashMap[String, ExecutorRunner] val drivers = new HashMap[String, DriverRunner] val finishedDrivers = new HashMap[String, DriverRunner] + val appDirectories = new HashMap[String, Seq[String]] + val finishedApps = new HashSet[String] // The shuffle service is not actually started unless configured. val shuffleService = new StandaloneWorkerShuffleService(conf, securityMgr) @@ -294,7 +296,7 @@ private[spark] class Worker( val isAppStillRunning = executors.values.map(_.appId).contains(appIdFromDir) dir.isDirectory && !isAppStillRunning && !Utils.doesDirectoryContainAnyNewFiles(dir, APP_DATA_RETENTION_SECS) - }.foreach { dir => + }.foreach { dir => logInfo(s"Removing directory: ${dir.getPath}") Utils.deleteRecursively(dir) } @@ -339,8 +341,19 @@ private[spark] class Worker( throw new IOException("Failed to create directory " + executorDir) } + // Create local dirs for the executor. These are passed to the executor via the + // SPARK_LOCAL_DIRS environment variable, and deleted by the Worker when the + // application finishes. + val appLocalDirs = appDirectories.get(appId).getOrElse { + Utils.getOrCreateLocalRootDirs(conf).map { dir => + Utils.createDirectory(dir).getAbsolutePath() + }.toSeq + } + appDirectories(appId) = appLocalDirs + val manager = new ExecutorRunner(appId, execId, appDesc, cores_, memory_, - self, workerId, host, sparkHome, executorDir, akkaUrl, conf, ExecutorState.LOADING) + self, workerId, host, sparkHome, executorDir, akkaUrl, conf, appLocalDirs, + ExecutorState.LOADING) executors(appId + "/" + execId) = manager manager.start() coresUsed += cores_ @@ -377,6 +390,7 @@ private[spark] class Worker( message.map(" message " + _).getOrElse("") + exitStatus.map(" exitStatus " + _).getOrElse("")) } + maybeCleanupApplication(appId) } case KillExecutor(masterUrl, appId, execId) => @@ -446,6 +460,9 @@ private[spark] class Worker( case ReregisterWithMaster => reregisterWithMaster() + case ApplicationFinished(id) => + finishedApps += id + maybeCleanupApplication(id) } private def masterDisconnected() { @@ -454,6 +471,19 @@ private[spark] class Worker( registerWithMaster() } + private def maybeCleanupApplication(id: String): Unit = { + val shouldCleanup = finishedApps.contains(id) && !executors.values.exists(_.appId == id) + if (shouldCleanup) { + finishedApps -= id + appDirectories.remove(id).foreach { dirList => + logInfo(s"Cleaning up local directories for application $id") + dirList.foreach { dir => + Utils.deleteRecursively(new File(dir)) + } + } + } + } + def generateWorkerId(): String = { "worker-%s-%s-%d".format(createDateFormat.format(new Date), host, port) } diff --git a/core/src/main/scala/org/apache/spark/util/Utils.scala b/core/src/main/scala/org/apache/spark/util/Utils.scala index 5e1cb0c7a7712..8c00f2c36aed2 100644 --- a/core/src/main/scala/org/apache/spark/util/Utils.scala +++ b/core/src/main/scala/org/apache/spark/util/Utils.scala @@ -246,8 +246,11 @@ private[spark] object Utils extends Logging { retval } - /** Create a temporary directory inside the given parent directory */ - def createTempDir(root: String = System.getProperty("java.io.tmpdir")): File = { + /** + * Create a directory inside the given parent directory. The directory is guaranteed to be + * newly created, and is not marked for automatic deletion. + */ + def createDirectory(root: String): File = { var attempts = 0 val maxAttempts = 10 var dir: File = null @@ -265,6 +268,15 @@ private[spark] object Utils extends Logging { } catch { case e: SecurityException => dir = null; } } + dir + } + + /** + * Create a temporary directory inside the given parent directory. The directory will be + * automatically deleted when the VM shuts down. + */ + def createTempDir(root: String = System.getProperty("java.io.tmpdir")): File = { + val dir = createDirectory(root) registerShutdownDeleteDir(dir) dir } diff --git a/core/src/test/scala/org/apache/spark/deploy/JsonProtocolSuite.scala b/core/src/test/scala/org/apache/spark/deploy/JsonProtocolSuite.scala index 3f1cd0752e766..aa65f7e8915e6 100644 --- a/core/src/test/scala/org/apache/spark/deploy/JsonProtocolSuite.scala +++ b/core/src/test/scala/org/apache/spark/deploy/JsonProtocolSuite.scala @@ -119,7 +119,7 @@ class JsonProtocolSuite extends FunSuite { def createExecutorRunner(): ExecutorRunner = { new ExecutorRunner("appId", 123, createAppDesc(), 4, 1234, null, "workerId", "host", new File("sparkHome"), new File("workDir"), "akka://worker", - new SparkConf, ExecutorState.RUNNING) + new SparkConf, Seq("localDir"), ExecutorState.RUNNING) } def createDriverRunner(): DriverRunner = { diff --git a/core/src/test/scala/org/apache/spark/deploy/worker/ExecutorRunnerTest.scala b/core/src/test/scala/org/apache/spark/deploy/worker/ExecutorRunnerTest.scala index 196217062991e..6f233d7cf97aa 100644 --- a/core/src/test/scala/org/apache/spark/deploy/worker/ExecutorRunnerTest.scala +++ b/core/src/test/scala/org/apache/spark/deploy/worker/ExecutorRunnerTest.scala @@ -33,7 +33,8 @@ class ExecutorRunnerTest extends FunSuite { val appDesc = new ApplicationDescription("app name", Some(8), 500, Command("foo", Seq(appId), Map(), Seq(), Seq(), Seq()), "appUiUrl") val er = new ExecutorRunner(appId, 1, appDesc, 8, 500, null, "blah", "worker321", - new File(sparkHome), new File("ooga"), "blah", new SparkConf, ExecutorState.RUNNING) + new File(sparkHome), new File("ooga"), "blah", new SparkConf, Seq("localDir"), + ExecutorState.RUNNING) val builder = CommandUtils.buildProcessBuilder(appDesc.command, 512, sparkHome, er.substituteVariables) assert(builder.command().last === appId) } From 9c251c555f5ee527143d0cdb9e6c3cb7530fc8f8 Mon Sep 17 00:00:00 2001 From: Takeshi Yamamuro Date: Tue, 23 Dec 2014 12:39:41 -0800 Subject: [PATCH 088/320] [SPARK-4932] Add help comments in Analytics Trivial modifications for usability. Author: Takeshi Yamamuro Closes #3775 from maropu/AddHelpCommentInAnalytics and squashes the following commits: fbea8f5 [Takeshi Yamamuro] Add help comments in Analytics --- .../scala/org/apache/spark/examples/graphx/Analytics.scala | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala b/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala index 9cc47327f9a48..409721b01c8fd 100644 --- a/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala +++ b/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala @@ -33,6 +33,10 @@ object Analytics extends Logging { if (args.length < 2) { System.err.println( "Usage: Analytics --numEPart= [other options]") + System.err.println("Supported 'taskType' as follows:") + System.err.println(" pagerank Compute PageRank") + System.err.println(" cc Compute the connected components of vertices") + System.err.println(" triangles Count the number of triangles") System.exit(1) } From 395b771feed3fc90e5053defbe86dbd673fde582 Mon Sep 17 00:00:00 2001 From: Cheng Lian Date: Tue, 23 Dec 2014 12:54:20 -0800 Subject: [PATCH 089/320] [SPARK-4914][Build] Cleans lib_managed before compiling with Hive 0.13.1 This PR tries to fix the Hive tests failure encountered in PR #3157 by cleaning `lib_managed` before building assembly jar against Hive 0.13.1 in `dev/run-tests`. Otherwise two sets of datanucleus jars would be left in `lib_managed` and may mess up class paths while executing Hive test suites. Please refer to [this thread] [1] for details. A clean build would be even safer, but we only clean `lib_managed` here to save build time. This PR also takes the chance to clean up some minor typos and formatting issues in the comments. [1]: https://github.com/apache/spark/pull/3157#issuecomment-67656488 [Review on Reviewable](https://reviewable.io/reviews/apache/spark/3756) Author: Cheng Lian Closes #3756 from liancheng/clean-lib-managed and squashes the following commits: e2bd21d [Cheng Lian] Adds lib_managed to clean set c9f2f3e [Cheng Lian] Cleans lib_managed before compiling with Hive 0.13.1 --- dev/run-tests | 26 ++++++++++++++------------ pom.xml | 3 +++ 2 files changed, 17 insertions(+), 12 deletions(-) diff --git a/dev/run-tests b/dev/run-tests index 328a73bd8b26d..9192cb7e169f3 100755 --- a/dev/run-tests +++ b/dev/run-tests @@ -141,20 +141,22 @@ CURRENT_BLOCK=$BLOCK_BUILD { # NOTE: echo "q" is needed because sbt on encountering a build file with failure - #+ (either resolution or compilation) prompts the user for input either q, r, etc - #+ to quit or retry. This echo is there to make it not block. + # (either resolution or compilation) prompts the user for input either q, r, etc + # to quit or retry. This echo is there to make it not block. # NOTE: Do not quote $BUILD_MVN_PROFILE_ARGS or else it will be interpreted as a - #+ single argument! + # single argument! # QUESTION: Why doesn't 'yes "q"' work? # QUESTION: Why doesn't 'grep -v -e "^\[info\] Resolving"' work? - # First build with 0.12 to ensure patches do not break the hive 12 build + # First build with Hive 0.12.0 to ensure patches do not break the Hive 0.12.0 build HIVE_12_BUILD_ARGS="$SBT_MAVEN_PROFILES_ARGS -Phive -Phive-thriftserver -Phive-0.12.0" - echo "[info] Compile with hive 0.12" + echo "[info] Compile with Hive 0.12.0" echo -e "q\n" \ | sbt/sbt $HIVE_12_BUILD_ARGS clean hive/compile hive-thriftserver/compile \ | grep -v -e "info.*Resolving" -e "warn.*Merging" -e "info.*Including" - # Then build with default version(0.13.1) because tests are based on this version + # Then build with default Hive version (0.13.1) because tests are based on this version + echo "[info] Compile with Hive 0.13.1" + rm -rf lib_managed echo "[info] Building Spark with these arguments: $SBT_MAVEN_PROFILES_ARGS"\ " -Phive -Phive-thriftserver" echo -e "q\n" \ @@ -178,7 +180,7 @@ CURRENT_BLOCK=$BLOCK_SPARK_UNIT_TESTS if [ -n "$_SQL_TESTS_ONLY" ]; then # This must be an array of individual arguments. Otherwise, having one long string - #+ will be interpreted as a single test, which doesn't work. + # will be interpreted as a single test, which doesn't work. SBT_MAVEN_TEST_ARGS=("catalyst/test" "sql/test" "hive/test" "mllib/test") else SBT_MAVEN_TEST_ARGS=("test") @@ -187,11 +189,11 @@ CURRENT_BLOCK=$BLOCK_SPARK_UNIT_TESTS echo "[info] Running Spark tests with these arguments: $SBT_MAVEN_PROFILES_ARGS ${SBT_MAVEN_TEST_ARGS[@]}" # NOTE: echo "q" is needed because sbt on encountering a build file with failure - #+ (either resolution or compilation) prompts the user for input either q, r, etc - #+ to quit or retry. This echo is there to make it not block. + # (either resolution or compilation) prompts the user for input either q, r, etc + # to quit or retry. This echo is there to make it not block. # NOTE: Do not quote $SBT_MAVEN_PROFILES_ARGS or else it will be interpreted as a - #+ single argument! - #+ "${SBT_MAVEN_TEST_ARGS[@]}" is cool because it's an array. + # single argument! + # "${SBT_MAVEN_TEST_ARGS[@]}" is cool because it's an array. # QUESTION: Why doesn't 'yes "q"' work? # QUESTION: Why doesn't 'grep -v -e "^\[info\] Resolving"' work? echo -e "q\n" \ @@ -210,7 +212,7 @@ CURRENT_BLOCK=$BLOCK_PYSPARK_UNIT_TESTS echo "" echo "=========================================================================" -echo "Detecting binary incompatibilites with MiMa" +echo "Detecting binary incompatibilities with MiMa" echo "=========================================================================" CURRENT_BLOCK=$BLOCK_MIMA diff --git a/pom.xml b/pom.xml index 4be8c220223f8..e4db1393ba9cf 100644 --- a/pom.xml +++ b/pom.xml @@ -1010,6 +1010,9 @@ checkpoint + + lib_managed + From 27c5399f4dd542e36ea579956b8cb0613de25c6d Mon Sep 17 00:00:00 2001 From: Andrew Or Date: Tue, 23 Dec 2014 14:28:36 -0800 Subject: [PATCH 090/320] [SPARK-4730][YARN] Warn against deprecated YARN settings See https://issues.apache.org/jira/browse/SPARK-4730. Author: Andrew Or Closes #3590 from andrewor14/yarn-settings and squashes the following commits: 36e0753 [Andrew Or] Merge branch 'master' of github.com:apache/spark into yarn-settings dcd1316 [Andrew Or] Warn against deprecated YARN settings --- .../spark/deploy/SparkSubmitArguments.scala | 5 ++++- .../cluster/YarnClientSchedulerBackend.scala | 17 ++++++++++++++++- 2 files changed, 20 insertions(+), 2 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala index 607b4df73db99..f174bc1af59b4 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala @@ -214,7 +214,10 @@ private[spark] class SparkSubmitArguments(args: Seq[String], env: Map[String, St """.stripMargin } - /** Fill in values by parsing user options. */ + /** + * Fill in values by parsing user options. + * NOTE: Any changes here must be reflected in YarnClientSchedulerBackend. + */ private def parseOpts(opts: Seq[String]): Unit = { val EQ_SEPARATED_OPT="""(--[^=]+)=(.+)""".r diff --git a/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala b/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala index 2923e6729cd6b..09597bd0e6ab9 100644 --- a/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala +++ b/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala @@ -65,7 +65,8 @@ private[spark] class YarnClientSchedulerBackend( */ private def getExtraClientArguments: Seq[String] = { val extraArgs = new ArrayBuffer[String] - val optionTuples = // List of (target Client argument, environment variable, Spark property) + // List of (target Client argument, environment variable, Spark property) + val optionTuples = List( ("--driver-memory", "SPARK_MASTER_MEMORY", "spark.master.memory"), ("--driver-memory", "SPARK_DRIVER_MEMORY", "spark.driver.memory"), @@ -78,11 +79,25 @@ private[spark] class YarnClientSchedulerBackend( ("--queue", "SPARK_YARN_QUEUE", "spark.yarn.queue"), ("--name", "SPARK_YARN_APP_NAME", "spark.app.name") ) + // Warn against the following deprecated environment variables: env var -> suggestion + val deprecatedEnvVars = Map( + "SPARK_MASTER_MEMORY" -> "SPARK_DRIVER_MEMORY or --driver-memory through spark-submit", + "SPARK_WORKER_INSTANCES" -> "SPARK_WORKER_INSTANCES or --num-executors through spark-submit", + "SPARK_WORKER_MEMORY" -> "SPARK_EXECUTOR_MEMORY or --executor-memory through spark-submit", + "SPARK_WORKER_CORES" -> "SPARK_EXECUTOR_CORES or --executor-cores through spark-submit") + // Do the same for deprecated properties: property -> suggestion + val deprecatedProps = Map("spark.master.memory" -> "--driver-memory through spark-submit") optionTuples.foreach { case (optionName, envVar, sparkProp) => if (System.getenv(envVar) != null) { extraArgs += (optionName, System.getenv(envVar)) + if (deprecatedEnvVars.contains(envVar)) { + logWarning(s"NOTE: $envVar is deprecated. Use ${deprecatedEnvVars(envVar)} instead.") + } } else if (sc.getConf.contains(sparkProp)) { extraArgs += (optionName, sc.getConf.get(sparkProp)) + if (deprecatedProps.contains(sparkProp)) { + logWarning(s"NOTE: $sparkProp is deprecated. Use ${deprecatedProps(sparkProp)} instead.") + } } } extraArgs From 96281cd0c3ffb4c0fbdb64b8f7b705f863d46b33 Mon Sep 17 00:00:00 2001 From: Liang-Chi Hsieh Date: Tue, 23 Dec 2014 14:58:33 -0800 Subject: [PATCH 091/320] [SPARK-4913] Fix incorrect event log path SPARK-2261 uses a single file to log events for an app. `eventLogDir` in `ApplicationDescription` is replaced with `eventLogFile`. However, `ApplicationDescription` in `SparkDeploySchedulerBackend` is initialized with `SparkContext`'s `eventLogDir`. It is just the log directory, not the actual log file path. `Master.rebuildSparkUI` can not correctly rebuild a new SparkUI for the app. Because the `ApplicationDescription` is remotely registered with `Master` and the app's id is then generated in `Master`, we can not get the app id in advance before registration. So the received description needs to be modified with correct `eventLogFile` value. Author: Liang-Chi Hsieh Closes #3755 from viirya/fix_app_logdir and squashes the following commits: 5e0ea35 [Liang-Chi Hsieh] Revision for comment. b5730a1 [Liang-Chi Hsieh] Fix incorrect event log path. Closes #3777 (a duplicate PR for the same JIRA) --- .../spark/deploy/ApplicationDescription.scala | 2 +- .../apache/spark/deploy/master/Master.scala | 20 +++++++++++++++---- 2 files changed, 17 insertions(+), 5 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/deploy/ApplicationDescription.scala b/core/src/main/scala/org/apache/spark/deploy/ApplicationDescription.scala index b10b7b8d32523..65a1a8fd7e929 100644 --- a/core/src/main/scala/org/apache/spark/deploy/ApplicationDescription.scala +++ b/core/src/main/scala/org/apache/spark/deploy/ApplicationDescription.scala @@ -23,7 +23,7 @@ private[spark] class ApplicationDescription( val memoryPerSlave: Int, val command: Command, var appUiUrl: String, - val eventLogFile: Option[String] = None) + val eventLogDir: Option[String] = None) extends Serializable { val user = System.getProperty("user.name", "") diff --git a/core/src/main/scala/org/apache/spark/deploy/master/Master.scala b/core/src/main/scala/org/apache/spark/deploy/master/Master.scala index f8137bf93c124..81fa0770bbaf9 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/Master.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/Master.scala @@ -719,14 +719,26 @@ private[spark] class Master( def rebuildSparkUI(app: ApplicationInfo): Boolean = { val appName = app.desc.name val notFoundBasePath = HistoryServer.UI_PATH_PREFIX + "/not-found" - val eventLogFile = app.desc.eventLogFile.getOrElse { - // Event logging is not enabled for this application - app.desc.appUiUrl = notFoundBasePath + val eventLogFile = app.desc.eventLogDir + .map { dir => EventLoggingListener.getLogPath(dir, app.id) } + .getOrElse { + // Event logging is not enabled for this application + app.desc.appUiUrl = notFoundBasePath + return false + } + val fs = Utils.getHadoopFileSystem(eventLogFile, hadoopConf) + + if (fs.exists(new Path(eventLogFile + EventLoggingListener.IN_PROGRESS))) { + // Event logging is enabled for this application, but the application is still in progress + val title = s"Application history not found (${app.id})" + var msg = s"Application $appName is still in progress." + logWarning(msg) + msg = URLEncoder.encode(msg, "UTF-8") + app.desc.appUiUrl = notFoundBasePath + s"?msg=$msg&title=$title" return false } try { - val fs = Utils.getHadoopFileSystem(eventLogFile, hadoopConf) val (logInput, sparkVersion) = EventLoggingListener.openEventLog(new Path(eventLogFile), fs) val replayBus = new ReplayListenerBus() val ui = SparkUI.createHistoryUI(new SparkConf, replayBus, new SecurityManager(conf), From 10d69e9cbfdabe95d0e513176d5347d7b59da0ee Mon Sep 17 00:00:00 2001 From: Ilayaperumal Gopinathan Date: Tue, 23 Dec 2014 15:14:54 -0800 Subject: [PATCH 092/320] [SPARK-4802] [streaming] Remove receiverInfo once receiver is de-registered Once the streaming receiver is de-registered at executor, the `ReceiverTrackerActor` needs to remove the corresponding reveiverInfo from the `receiverInfo` map at `ReceiverTracker`. Author: Ilayaperumal Gopinathan Closes #3647 from ilayaperumalg/receiverInfo-RTracker and squashes the following commits: 6eb97d5 [Ilayaperumal Gopinathan] Polishing based on the review 3640c86 [Ilayaperumal Gopinathan] Remove receiverInfo once receiver is de-registered --- .../apache/spark/streaming/scheduler/ReceiverTracker.scala | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceiverTracker.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceiverTracker.scala index 32e481dabc8ca..1f0e442a12283 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceiverTracker.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceiverTracker.scala @@ -150,8 +150,8 @@ class ReceiverTracker(ssc: StreamingContext, skipReceiverLaunch: Boolean = false logWarning("No prior receiver info") ReceiverInfo(streamId, "", null, false, "", lastErrorMessage = message, lastError = error) } - receiverInfo(streamId) = newReceiverInfo - listenerBus.post(StreamingListenerReceiverStopped(receiverInfo(streamId))) + receiverInfo -= streamId + listenerBus.post(StreamingListenerReceiverStopped(newReceiverInfo)) val messageWithError = if (error != null && !error.isEmpty) { s"$message - $error" } else { From 3f5f4cc4e7b3bc458e0579d247a0652dca365853 Mon Sep 17 00:00:00 2001 From: jerryshao Date: Tue, 23 Dec 2014 15:45:53 -0800 Subject: [PATCH 093/320] [SPARK-4671][Streaming]Do not replicate streaming block when WAL is enabled Currently streaming block will be replicated when specific storage level is set, since WAL is already fault tolerant, so replication is needless and will hurt the throughput of streaming application. Hi tdas , as per discussed about this issue, I fixed with this implementation, I'm not is this the way you want, would you mind taking a look at it? Thanks a lot. Author: jerryshao Closes #3534 from jerryshao/SPARK-4671 and squashes the following commits: 500b456 [jerryshao] Do not replicate streaming block when WAL is enabled --- .../receiver/ReceivedBlockHandler.scala | 20 ++++++++++++++++++- 1 file changed, 19 insertions(+), 1 deletion(-) diff --git a/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala b/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala index fdf995320beb4..c0670e22a7aee 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala @@ -121,6 +121,24 @@ private[streaming] class WriteAheadLogBasedBlockHandler( private val maxFailures = conf.getInt( "spark.streaming.receiver.writeAheadLog.maxFailures", 3) + private val effectiveStorageLevel = { + if (storageLevel.deserialized) { + logWarning(s"Storage level serialization ${storageLevel.deserialized} is not supported when" + + s" write ahead log is enabled, change to serialization false") + } + if (storageLevel.replication > 1) { + logWarning(s"Storage level replication ${storageLevel.replication} is unnecessary when " + + s"write ahead log is enabled, change to replication 1") + } + + StorageLevel(storageLevel.useDisk, storageLevel.useMemory, storageLevel.useOffHeap, false, 1) + } + + if (storageLevel != effectiveStorageLevel) { + logWarning(s"User defined storage level $storageLevel is changed to effective storage level " + + s"$effectiveStorageLevel when write ahead log is enabled") + } + // Manages rolling log files private val logManager = new WriteAheadLogManager( checkpointDirToLogDir(checkpointDir, streamId), @@ -156,7 +174,7 @@ private[streaming] class WriteAheadLogBasedBlockHandler( // Store the block in block manager val storeInBlockManagerFuture = Future { val putResult = - blockManager.putBytes(blockId, serializedBlock, storageLevel, tellMaster = true) + blockManager.putBytes(blockId, serializedBlock, effectiveStorageLevel, tellMaster = true) if (!putResult.map { _._1 }.contains(blockId)) { throw new SparkException( s"Could not store $blockId to block manager with storage level $storageLevel") From 7e2deb71c4239564631b19c748e95c3d1aa1c77d Mon Sep 17 00:00:00 2001 From: Marcelo Vanzin Date: Tue, 23 Dec 2014 16:02:59 -0800 Subject: [PATCH 094/320] [SPARK-4606] Send EOF to child JVM when there's no more data to read. Author: Marcelo Vanzin Closes #3460 from vanzin/SPARK-4606 and squashes the following commits: 031207d [Marcelo Vanzin] [SPARK-4606] Send EOF to child JVM when there's no more data to read. --- .../SparkSubmitDriverBootstrapper.scala | 3 ++- .../scala/org/apache/spark/util/Utils.scala | 24 +++++++++++++------ 2 files changed, 19 insertions(+), 8 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitDriverBootstrapper.scala b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitDriverBootstrapper.scala index d2687faad62b1..2eab9981845e8 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitDriverBootstrapper.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitDriverBootstrapper.scala @@ -151,7 +151,8 @@ private[spark] object SparkSubmitDriverBootstrapper { val isWindows = Utils.isWindows val isSubprocess = sys.env.contains("IS_SUBPROCESS") if (!isWindows) { - val stdinThread = new RedirectThread(System.in, process.getOutputStream, "redirect stdin") + val stdinThread = new RedirectThread(System.in, process.getOutputStream, "redirect stdin", + propagateEof = true) stdinThread.start() // Spark submit (JVM) may run as a subprocess, and so this JVM should terminate on // broken pipe, signaling that the parent process has exited. This is the case if the diff --git a/core/src/main/scala/org/apache/spark/util/Utils.scala b/core/src/main/scala/org/apache/spark/util/Utils.scala index 8c00f2c36aed2..0d771baaa6abc 100644 --- a/core/src/main/scala/org/apache/spark/util/Utils.scala +++ b/core/src/main/scala/org/apache/spark/util/Utils.scala @@ -1847,19 +1847,29 @@ private[spark] object Utils extends Logging { /** * A utility class to redirect the child process's stdout or stderr. */ -private[spark] class RedirectThread(in: InputStream, out: OutputStream, name: String) +private[spark] class RedirectThread( + in: InputStream, + out: OutputStream, + name: String, + propagateEof: Boolean = false) extends Thread(name) { setDaemon(true) override def run() { scala.util.control.Exception.ignoring(classOf[IOException]) { // FIXME: We copy the stream on the level of bytes to avoid encoding problems. - val buf = new Array[Byte](1024) - var len = in.read(buf) - while (len != -1) { - out.write(buf, 0, len) - out.flush() - len = in.read(buf) + try { + val buf = new Array[Byte](1024) + var len = in.read(buf) + while (len != -1) { + out.write(buf, 0, len) + out.flush() + len = in.read(buf) + } + } finally { + if (propagateEof) { + out.close() + } } } } From fd41eb9574280b5cfee9b94b4f92e4c44363fb14 Mon Sep 17 00:00:00 2001 From: jbencook Date: Tue, 23 Dec 2014 17:46:24 -0800 Subject: [PATCH 095/320] [SPARK-4860][pyspark][sql] speeding up `sample()` and `takeSample()` This PR modifies the python `SchemaRDD` to use `sample()` and `takeSample()` from Scala instead of the slower python implementations from `rdd.py`. This is worthwhile because the `Row`'s are already serialized as Java objects. In order to use the faster `takeSample()`, a `takeSampleToPython()` method was implemented in `SchemaRDD.scala` following the pattern of `collectToPython()`. Author: jbencook Author: J. Benjamin Cook Closes #3764 from jbencook/master and squashes the following commits: 6fbc769 [J. Benjamin Cook] [SPARK-4860][pyspark][sql] fixing sloppy indentation for takeSampleToPython() arguments 5170da2 [J. Benjamin Cook] [SPARK-4860][pyspark][sql] fixing typo: from RDD to SchemaRDD de22f70 [jbencook] [SPARK-4860][pyspark][sql] using sample() method from JavaSchemaRDD b916442 [jbencook] [SPARK-4860][pyspark][sql] adding sample() to JavaSchemaRDD 020cbdf [jbencook] [SPARK-4860][pyspark][sql] using Scala implementations of `sample()` and `takeSample()` --- python/pyspark/sql.py | 28 +++++++++++++++++++ .../org/apache/spark/sql/SchemaRDD.scala | 15 ++++++++++ .../spark/sql/api/java/JavaSchemaRDD.scala | 6 ++++ 3 files changed, 49 insertions(+) diff --git a/python/pyspark/sql.py b/python/pyspark/sql.py index 469f82473af97..9807a84a66f11 100644 --- a/python/pyspark/sql.py +++ b/python/pyspark/sql.py @@ -2085,6 +2085,34 @@ def subtract(self, other, numPartitions=None): else: raise ValueError("Can only subtract another SchemaRDD") + def sample(self, withReplacement, fraction, seed=None): + """ + Return a sampled subset of this SchemaRDD. + + >>> srdd = sqlCtx.inferSchema(rdd) + >>> srdd.sample(False, 0.5, 97).count() + 2L + """ + assert fraction >= 0.0, "Negative fraction value: %s" % fraction + seed = seed if seed is not None else random.randint(0, sys.maxint) + rdd = self._jschema_rdd.sample(withReplacement, fraction, long(seed)) + return SchemaRDD(rdd, self.sql_ctx) + + def takeSample(self, withReplacement, num, seed=None): + """Return a fixed-size sampled subset of this SchemaRDD. + + >>> srdd = sqlCtx.inferSchema(rdd) + >>> srdd.takeSample(False, 2, 97) + [Row(field1=3, field2=u'row3'), Row(field1=1, field2=u'row1')] + """ + seed = seed if seed is not None else random.randint(0, sys.maxint) + with SCCallSiteSync(self.context) as css: + bytesInJava = self._jschema_rdd.baseSchemaRDD() \ + .takeSampleToPython(withReplacement, num, long(seed)) \ + .iterator() + cls = _create_cls(self.schema()) + return map(cls, self._collect_iterator_through_file(bytesInJava)) + def _test(): import doctest diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala index 7baf8ffcef787..856b10f1a8fd8 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala @@ -437,6 +437,21 @@ class SchemaRDD( }.grouped(100).map(batched => pickle.dumps(batched.toArray)).toIterable) } + /** + * Serializes the Array[Row] returned by SchemaRDD's takeSample(), using the same + * format as javaToPython and collectToPython. It is used by pyspark. + */ + private[sql] def takeSampleToPython( + withReplacement: Boolean, + num: Int, + seed: Long): JList[Array[Byte]] = { + val fieldTypes = schema.fields.map(_.dataType) + val pickle = new Pickler + new java.util.ArrayList(this.takeSample(withReplacement, num, seed).map { row => + EvaluatePython.rowToArray(row, fieldTypes) + }.grouped(100).map(batched => pickle.dumps(batched.toArray)).toIterable) + } + /** * Creates SchemaRDD by applying own schema to derived RDD. Typically used to wrap return value * of base RDD functions that do not change schema. diff --git a/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSchemaRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSchemaRDD.scala index ac4844f9b9290..5b9c612487ace 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSchemaRDD.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSchemaRDD.scala @@ -218,4 +218,10 @@ class JavaSchemaRDD( */ def subtract(other: JavaSchemaRDD, p: Partitioner): JavaSchemaRDD = this.baseSchemaRDD.subtract(other.baseSchemaRDD, p).toJavaSchemaRDD + + /** + * Return a SchemaRDD with a sampled version of the underlying dataset. + */ + def sample(withReplacement: Boolean, fraction: Double, seed: Long): JavaSchemaRDD = + this.baseSchemaRDD.sample(withReplacement, fraction, seed).toJavaSchemaRDD } From 199e59aacd540e17b31f38e0e32a3618870e9055 Mon Sep 17 00:00:00 2001 From: Kousuke Saruta Date: Tue, 23 Dec 2014 19:14:34 -0800 Subject: [PATCH 096/320] [SPARK-4881][Minor] Use SparkConf#getBoolean instead of get().toBoolean It's really a minor issue. In ApplicationMaster, there is code like as follows. val preserveFiles = sparkConf.get("spark.yarn.preserve.staging.files", "false").toBoolean I think, the code can be simplified like as follows. val preserveFiles = sparkConf.getBoolean("spark.yarn.preserve.staging.files", false) Author: Kousuke Saruta Closes #3733 from sarutak/SPARK-4881 and squashes the following commits: 1771430 [Kousuke Saruta] Modified the code like sparkConf.get(...).toBoolean to sparkConf.getBoolean(...) c63daa0 [Kousuke Saruta] Simplified code --- core/src/main/scala/org/apache/spark/SecurityManager.scala | 4 ++-- core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala | 2 +- .../org/apache/spark/deploy/yarn/ApplicationMaster.scala | 2 +- .../main/scala/org/apache/spark/deploy/yarn/ClientBase.scala | 2 +- 4 files changed, 5 insertions(+), 5 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/SecurityManager.scala b/core/src/main/scala/org/apache/spark/SecurityManager.scala index 49dae5231a92c..ec82d09cd079b 100644 --- a/core/src/main/scala/org/apache/spark/SecurityManager.scala +++ b/core/src/main/scala/org/apache/spark/SecurityManager.scala @@ -151,8 +151,8 @@ private[spark] class SecurityManager(sparkConf: SparkConf) extends Logging with private val authOn = sparkConf.getBoolean("spark.authenticate", false) // keep spark.ui.acls.enable for backwards compatibility with 1.0 - private var aclsOn = sparkConf.getOption("spark.acls.enable").getOrElse( - sparkConf.get("spark.ui.acls.enable", "false")).toBoolean + private var aclsOn = + sparkConf.getBoolean("spark.acls.enable", sparkConf.getBoolean("spark.ui.acls.enable", false)) // admin acls should be set before view or modify acls private var adminAcls: Set[String] = diff --git a/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala b/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala index a157e36e2286e..0001c2329c83a 100644 --- a/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala @@ -131,7 +131,7 @@ class HadoopRDD[K, V]( // used to build JobTracker ID private val createTime = new Date() - private val shouldCloneJobConf = sc.conf.get("spark.hadoop.cloneConf", "false").toBoolean + private val shouldCloneJobConf = sc.conf.getBoolean("spark.hadoop.cloneConf", false) // Returns a JobConf that will be used on slaves to obtain input splits for Hadoop reads. protected def getJobConf(): JobConf = { diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala index b2e45435c4abb..9c77dff48dc8b 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala @@ -311,7 +311,7 @@ private[spark] class ApplicationMaster(args: ApplicationMasterArguments, private def cleanupStagingDir(fs: FileSystem) { var stagingDirPath: Path = null try { - val preserveFiles = sparkConf.get("spark.yarn.preserve.staging.files", "false").toBoolean + val preserveFiles = sparkConf.getBoolean("spark.yarn.preserve.staging.files", false) if (!preserveFiles) { stagingDirPath = new Path(System.getenv("SPARK_YARN_STAGING_DIR")) if (stagingDirPath == null) { diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientBase.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientBase.scala index 5f0c67f05c9dd..eb97a7b3c59a4 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientBase.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientBase.scala @@ -693,7 +693,7 @@ private[spark] object ClientBase extends Logging { addClasspathEntry(Environment.PWD.$(), env) // Normally the users app.jar is last in case conflicts with spark jars - if (sparkConf.get("spark.yarn.user.classpath.first", "false").toBoolean) { + if (sparkConf.getBoolean("spark.yarn.user.classpath.first", false)) { addUserClasspath(args, sparkConf, env) addFileToClasspath(sparkJar(sparkConf), SPARK_JAR, env) populateHadoopClasspath(conf, env) From 29fabb1b528e60b2f65132a9ab64f2fd95b729ba Mon Sep 17 00:00:00 2001 From: Sean Owen Date: Wed, 24 Dec 2014 13:32:51 -0800 Subject: [PATCH 097/320] SPARK-4297 [BUILD] Build warning fixes omnibus There are a number of warnings generated in a normal, successful build right now. They're mostly Java unchecked cast warnings, which can be suppressed. But there's a grab bag of other Scala language warnings and so on that can all be easily fixed. The forthcoming PR fixes about 90% of the build warnings I see now. Author: Sean Owen Closes #3157 from srowen/SPARK-4297 and squashes the following commits: 8c9e469 [Sean Owen] Suppress unchecked cast warnings, and several other build warning fixes --- core/pom.xml | 4 ++-- .../spark/scheduler/TaskResultGetter.scala | 1 + .../java/org/apache/spark/JavaAPISuite.java | 4 +++- .../metrics/InputOutputMetricsSuite.scala | 4 ++-- .../spark/scheduler/DAGSchedulerSuite.scala | 2 +- .../spark/mllib/feature/JavaTfIdfSuite.java | 2 ++ .../spark/sql/api/java/UserDefinedType.java | 1 + .../spark/sql/parquet/ParquetTypes.scala | 4 ++-- .../spark/sql/api/java/JavaRowSuite.java | 1 + .../org/apache/spark/sql/DslQuerySuite.scala | 2 ++ .../spark/sql/parquet/ParquetQuerySuite.scala | 14 ++++++++++--- .../sql/hive/parquet/FakeParquetSerDe.scala | 2 +- .../sql/hive/execution/UDFListListInt.java | 20 ++++++++----------- .../apache/spark/streaming/JavaAPISuite.java | 16 +++++++-------- 14 files changed, 45 insertions(+), 32 deletions(-) diff --git a/core/pom.xml b/core/pom.xml index 1feb00b3a7fb8..c5c41b2b5de42 100644 --- a/core/pom.xml +++ b/core/pom.xml @@ -352,9 +352,9 @@ - + - + diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskResultGetter.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskResultGetter.scala index 819b51e12ad8c..4896ec845bbc9 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/TaskResultGetter.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/TaskResultGetter.scala @@ -19,6 +19,7 @@ package org.apache.spark.scheduler import java.nio.ByteBuffer +import scala.language.existentials import scala.util.control.NonFatal import org.apache.spark._ diff --git a/core/src/test/java/org/apache/spark/JavaAPISuite.java b/core/src/test/java/org/apache/spark/JavaAPISuite.java index e5bdad6bda2fa..5ce299d05824b 100644 --- a/core/src/test/java/org/apache/spark/JavaAPISuite.java +++ b/core/src/test/java/org/apache/spark/JavaAPISuite.java @@ -184,6 +184,7 @@ public void sortByKey() { Assert.assertEquals(new Tuple2(3, 2), sortedPairs.get(2)); } + @SuppressWarnings("unchecked") @Test public void repartitionAndSortWithinPartitions() { List> pairs = new ArrayList>(); @@ -491,6 +492,7 @@ public Integer call(Integer a, Integer b) { Assert.assertEquals(33, sum); } + @SuppressWarnings("unchecked") @Test public void aggregateByKey() { JavaPairRDD pairs = sc.parallelizePairs( @@ -1556,7 +1558,7 @@ static class Class2 {} @Test public void testRegisterKryoClasses() { SparkConf conf = new SparkConf(); - conf.registerKryoClasses(new Class[]{ Class1.class, Class2.class }); + conf.registerKryoClasses(new Class[]{ Class1.class, Class2.class }); Assert.assertEquals( Class1.class.getName() + "," + Class2.class.getName(), conf.get("spark.kryo.classesToRegister")); diff --git a/core/src/test/scala/org/apache/spark/metrics/InputOutputMetricsSuite.scala b/core/src/test/scala/org/apache/spark/metrics/InputOutputMetricsSuite.scala index ca226fd4e694f..f8bcde12a371a 100644 --- a/core/src/test/scala/org/apache/spark/metrics/InputOutputMetricsSuite.scala +++ b/core/src/test/scala/org/apache/spark/metrics/InputOutputMetricsSuite.scala @@ -24,14 +24,14 @@ import org.apache.spark.deploy.SparkHadoopUtil import org.apache.spark.scheduler.{SparkListenerTaskEnd, SparkListener} import org.scalatest.FunSuite -import org.scalatest.matchers.ShouldMatchers +import org.scalatest.Matchers import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.{Path, FileSystem} import scala.collection.mutable.ArrayBuffer -class InputOutputMetricsSuite extends FunSuite with SharedSparkContext with ShouldMatchers { +class InputOutputMetricsSuite extends FunSuite with SharedSparkContext with Matchers { test("input metrics when reading text file with single split") { val file = new File(getClass.getSimpleName + ".txt") val pw = new PrintWriter(new FileWriter(file)) diff --git a/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala index 436eea4f1fdcf..d6ec9e129cceb 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala @@ -739,7 +739,7 @@ class DAGSchedulerSuite extends TestKit(ActorSystem("DAGSchedulerSuite")) with F test("accumulator not calculated for resubmitted result stage") { //just for register - val accum = new Accumulator[Int](0, SparkContext.IntAccumulatorParam) + val accum = new Accumulator[Int](0, AccumulatorParam.IntAccumulatorParam) val finalRdd = new MyRDD(sc, 1, Nil) submit(finalRdd, Array(0)) completeWithAccumulator(accum.id, taskSets(0), Seq((Success, 42))) diff --git a/mllib/src/test/java/org/apache/spark/mllib/feature/JavaTfIdfSuite.java b/mllib/src/test/java/org/apache/spark/mllib/feature/JavaTfIdfSuite.java index 064263e02cd11..fbc26167ce66f 100644 --- a/mllib/src/test/java/org/apache/spark/mllib/feature/JavaTfIdfSuite.java +++ b/mllib/src/test/java/org/apache/spark/mllib/feature/JavaTfIdfSuite.java @@ -49,6 +49,7 @@ public void tearDown() { public void tfIdf() { // The tests are to check Java compatibility. HashingTF tf = new HashingTF(); + @SuppressWarnings("unchecked") JavaRDD> documents = sc.parallelize(Lists.newArrayList( Lists.newArrayList("this is a sentence".split(" ")), Lists.newArrayList("this is another sentence".split(" ")), @@ -68,6 +69,7 @@ public void tfIdf() { public void tfIdfMinimumDocumentFrequency() { // The tests are to check Java compatibility. HashingTF tf = new HashingTF(); + @SuppressWarnings("unchecked") JavaRDD> documents = sc.parallelize(Lists.newArrayList( Lists.newArrayList("this is a sentence".split(" ")), Lists.newArrayList("this is another sentence".split(" ")), diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/UserDefinedType.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/UserDefinedType.java index b751847b464fd..f0d079d25b5d4 100644 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/UserDefinedType.java +++ b/sql/core/src/main/java/org/apache/spark/sql/api/java/UserDefinedType.java @@ -35,6 +35,7 @@ protected UserDefinedType() { } public boolean equals(Object o) { if (this == o) return true; if (o == null || getClass() != o.getClass()) return false; + @SuppressWarnings("unchecked") UserDefinedType that = (UserDefinedType) o; return this.sqlType().equals(that.sqlType()); } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTypes.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTypes.scala index 0e6fb57d57bca..97447871a11ee 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTypes.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTypes.scala @@ -24,8 +24,8 @@ import scala.util.Try import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.{FileSystem, Path} import org.apache.hadoop.mapreduce.Job -import org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter +import parquet.format.converter.ParquetMetadataConverter import parquet.hadoop.{ParquetFileReader, Footer, ParquetFileWriter} import parquet.hadoop.metadata.{ParquetMetadata, FileMetaData} import parquet.hadoop.util.ContextUtil @@ -458,7 +458,7 @@ private[parquet] object ParquetTypesConverter extends Logging { // ... and fallback to "_metadata" if no such file exists (which implies the Parquet file is // empty, thus normally the "_metadata" file is expected to be fairly small). .orElse(children.find(_.getPath.getName == ParquetFileWriter.PARQUET_METADATA_FILE)) - .map(ParquetFileReader.readFooter(conf, _)) + .map(ParquetFileReader.readFooter(conf, _, ParquetMetadataConverter.NO_FILTER)) .getOrElse( throw new IllegalArgumentException(s"Could not find Parquet metadata at path $path")) } diff --git a/sql/core/src/test/java/org/apache/spark/sql/api/java/JavaRowSuite.java b/sql/core/src/test/java/org/apache/spark/sql/api/java/JavaRowSuite.java index bc5cd66482add..2b5812159d07d 100644 --- a/sql/core/src/test/java/org/apache/spark/sql/api/java/JavaRowSuite.java +++ b/sql/core/src/test/java/org/apache/spark/sql/api/java/JavaRowSuite.java @@ -141,6 +141,7 @@ public void constructComplexRow() { doubleValue, stringValue, timestampValue, null); // Complex array + @SuppressWarnings("unchecked") List> arrayOfMaps = Arrays.asList(simpleMap); List arrayOfRows = Arrays.asList(simpleStruct); diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala index e40d034ce4dc0..691c4b38287bf 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala @@ -24,6 +24,8 @@ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.dsl._ import org.apache.spark.sql.test.TestSQLContext._ +import scala.language.postfixOps + class DslQuerySuite extends QueryTest { import org.apache.spark.sql.TestData._ diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala index 074855389d746..a5fe2e8da2840 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala @@ -17,6 +17,8 @@ package org.apache.spark.sql.parquet +import scala.reflect.ClassTag + import org.apache.hadoop.fs.{FileSystem, Path} import org.apache.hadoop.mapreduce.Job import org.scalatest.{BeforeAndAfterAll, FunSuiteLike} @@ -459,11 +461,17 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA } test("make RecordFilter for simple predicates") { - def checkFilter[T <: FilterPredicate](predicate: Expression, defined: Boolean = true): Unit = { + def checkFilter[T <: FilterPredicate : ClassTag]( + predicate: Expression, + defined: Boolean = true): Unit = { val filter = ParquetFilters.createFilter(predicate) if (defined) { assert(filter.isDefined) - assert(filter.get.isInstanceOf[T]) + val tClass = implicitly[ClassTag[T]].runtimeClass + val filterGet = filter.get + assert( + tClass.isInstance(filterGet), + s"$filterGet of type ${filterGet.getClass} is not an instance of $tClass") } else { assert(filter.isEmpty) } @@ -484,7 +492,7 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA checkFilter[Operators.And]('a.int === 1 && 'a.int < 4) checkFilter[Operators.Or]('a.int === 1 || 'a.int < 4) - checkFilter[Operators.Not](!('a.int === 1)) + checkFilter[Operators.NotEq[Integer]](!('a.int === 1)) checkFilter('a.int > 'b.int, defined = false) checkFilter(('a.int > 'b.int) && ('a.int > 'b.int), defined = false) diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/parquet/FakeParquetSerDe.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/parquet/FakeParquetSerDe.scala index abed299cd957f..2a16c9d1a27c9 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/parquet/FakeParquetSerDe.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/parquet/FakeParquetSerDe.scala @@ -32,7 +32,7 @@ import org.apache.hadoop.io.Writable * when "spark.sql.hive.convertMetastoreParquet" is set to true. */ @deprecated("No code should depend on FakeParquetHiveSerDe as it is only intended as a " + - "placeholder in the Hive MetaStore") + "placeholder in the Hive MetaStore", "1.2.0") class FakeParquetSerDe extends SerDe { override def getObjectInspector: ObjectInspector = new ObjectInspector { override def getCategory: Category = Category.PRIMITIVE diff --git a/sql/hive/src/test/java/org/apache/spark/sql/hive/execution/UDFListListInt.java b/sql/hive/src/test/java/org/apache/spark/sql/hive/execution/UDFListListInt.java index d2d39a8c4dc28..808e2986d3b77 100644 --- a/sql/hive/src/test/java/org/apache/spark/sql/hive/execution/UDFListListInt.java +++ b/sql/hive/src/test/java/org/apache/spark/sql/hive/execution/UDFListListInt.java @@ -23,25 +23,21 @@ public class UDFListListInt extends UDF { /** - * * @param obj - * SQL schema: array> - * Java Type: List> - * @return + * SQL schema: array<struct<x: int, y: int, z: int>> + * Java Type: List<List<Integer>> */ + @SuppressWarnings("unchecked") public long evaluate(Object obj) { if (obj == null) { - return 0l; + return 0L; } - List listList = (List) obj; + List> listList = (List>) obj; long retVal = 0; - for (List aList : listList) { - @SuppressWarnings("unchecked") - List list = (List) aList; - @SuppressWarnings("unchecked") - Integer someInt = (Integer) list.get(1); + for (List aList : listList) { + Number someInt = (Number) aList.get(1); try { - retVal += (long) (someInt.intValue()); + retVal += someInt.longValue(); } catch (NullPointerException e) { System.out.println(e); } diff --git a/streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java b/streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java index ce645fccba1d0..12cc0de7509d6 100644 --- a/streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java +++ b/streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java @@ -57,7 +57,7 @@ public void equalIterable(Iterable a, Iterable b) { @Test public void testInitialization() { - Assert.assertNotNull(ssc.sc()); + Assert.assertNotNull(ssc.sparkContext()); } @SuppressWarnings("unchecked") @@ -662,7 +662,7 @@ public void testStreamingContextTransform(){ listOfDStreams1, new Function2>, Time, JavaRDD>() { public JavaRDD call(List> listOfRDDs, Time time) { - assert(listOfRDDs.size() == 2); + Assert.assertEquals(2, listOfRDDs.size()); return null; } } @@ -675,7 +675,7 @@ public JavaRDD call(List> listOfRDDs, Time time) { listOfDStreams2, new Function2>, Time, JavaPairRDD>>() { public JavaPairRDD> call(List> listOfRDDs, Time time) { - assert(listOfRDDs.size() == 3); + Assert.assertEquals(3, listOfRDDs.size()); JavaRDD rdd1 = (JavaRDD)listOfRDDs.get(0); JavaRDD rdd2 = (JavaRDD)listOfRDDs.get(1); JavaRDD> rdd3 = (JavaRDD>)listOfRDDs.get(2); @@ -969,7 +969,7 @@ public Integer call(Tuple2 in) throws Exception { }); JavaTestUtils.attachTestOutputStream(reversed); - List>> result = JavaTestUtils.runStreams(ssc, 2, 2); + List> result = JavaTestUtils.runStreams(ssc, 2, 2); Assert.assertEquals(expected, result); } @@ -1012,7 +1012,7 @@ public Iterable> call(Tuple2 in) throws } }); JavaTestUtils.attachTestOutputStream(flatMapped); - List>> result = JavaTestUtils.runStreams(ssc, 2, 2); + List>> result = JavaTestUtils.runStreams(ssc, 2, 2); Assert.assertEquals(expected, result); } @@ -1163,9 +1163,9 @@ public void testGroupByKeyAndWindow() { JavaTestUtils.attachTestOutputStream(groupWindowed); List>>> result = JavaTestUtils.runStreams(ssc, 3, 3); - assert(result.size() == expected.size()); + Assert.assertEquals(expected.size(), result.size()); for (int i = 0; i < result.size(); i++) { - assert(convert(result.get(i)).equals(convert(expected.get(i)))); + Assert.assertEquals(convert(expected.get(i)), convert(result.get(i))); } } @@ -1383,7 +1383,7 @@ public JavaPairRDD call(JavaPairRDD in) thro }); JavaTestUtils.attachTestOutputStream(sorted); - List>> result = JavaTestUtils.runStreams(ssc, 2, 2); + List>> result = JavaTestUtils.runStreams(ssc, 2, 2); Assert.assertEquals(expected, result); } From b4d0db80a0bfba7f1e045d4edb9357b4b2c0a557 Mon Sep 17 00:00:00 2001 From: zsxwing Date: Wed, 24 Dec 2014 19:49:41 -0800 Subject: [PATCH 098/320] [SPARK-4873][Streaming] Use `Future.zip` instead of `Future.flatMap`(for-loop) in WriteAheadLogBasedBlockHandler Use `Future.zip` instead of `Future.flatMap`(for-loop). `zip` implies these two Futures will run concurrently, while `flatMap` usually means one Future depends on the other one. Author: zsxwing Closes #3721 from zsxwing/SPARK-4873 and squashes the following commits: 46a2cd9 [zsxwing] Use Future.zip instead of Future.flatMap(for-loop) --- .../spark/streaming/receiver/ReceivedBlockHandler.scala | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala b/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala index c0670e22a7aee..8b97db8dd36f1 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala @@ -187,10 +187,7 @@ private[streaming] class WriteAheadLogBasedBlockHandler( } // Combine the futures, wait for both to complete, and return the write ahead log segment - val combinedFuture = for { - _ <- storeInBlockManagerFuture - fileSegment <- storeInWriteAheadLogFuture - } yield fileSegment + val combinedFuture = storeInBlockManagerFuture.zip(storeInWriteAheadLogFuture).map(_._2) val segment = Await.result(combinedFuture, blockStoreTimeout) WriteAheadLogBasedStoreResult(blockId, segment) } From 11dd99317b1b0bcd18a0a0cc3c4eb79d3aaa4a2b Mon Sep 17 00:00:00 2001 From: Kousuke Saruta Date: Thu, 25 Dec 2014 07:05:43 -0800 Subject: [PATCH 099/320] [SPARK-4953][Doc] Fix the description of building Spark with YARN At the section "Specifying the Hadoop Version" In building-spark.md, there is description about building with YARN with Hadoop 0.23. Spark 1.3.0 will not support Hadoop 0.23 so we should fix the description. Author: Kousuke Saruta Closes #3787 from sarutak/SPARK-4953 and squashes the following commits: ee9c355 [Kousuke Saruta] Removed description related to a specific vendor 9ab0c24 [Kousuke Saruta] Fix the description about building SPARK with YARN --- docs/building-spark.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/building-spark.md b/docs/building-spark.md index 70165eabca435..dab3d2aef497e 100644 --- a/docs/building-spark.md +++ b/docs/building-spark.md @@ -60,7 +60,7 @@ mvn -Dhadoop.version=2.0.0-mr1-cdh4.2.0 -DskipTests clean package mvn -Phadoop-0.23 -Dhadoop.version=0.23.7 -DskipTests clean package {% endhighlight %} -For Apache Hadoop 2.x, 0.23.x, Cloudera CDH, and other Hadoop versions with YARN, you can enable the "yarn" profile and optionally set the "yarn.version" property if it is different from "hadoop.version". As of Spark 1.3, Spark only supports YARN versions 2.2.0 and later. +You can enable the "yarn" profile and optionally set the "yarn.version" property if it is different from "hadoop.version". Spark only supports YARN versions 2.2.0 and later. Examples: From 08b18c7eb790c65670778eab8a6e32486c5f76e9 Mon Sep 17 00:00:00 2001 From: Denny Lee Date: Thu, 25 Dec 2014 14:05:55 -0800 Subject: [PATCH 100/320] Fix "Building Spark With Maven" link in README.md Corrected link to the Building Spark with Maven page from its original (http://spark.apache.org/docs/latest/building-with-maven.html) to the current page (http://spark.apache.org/docs/latest/building-spark.html) Author: Denny Lee Closes #3802 from dennyglee/patch-1 and squashes the following commits: 15f601a [Denny Lee] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 8d57d50da96c9..16628bd406775 100644 --- a/README.md +++ b/README.md @@ -26,7 +26,7 @@ To build Spark and its example programs, run: (You do not need to do this if you downloaded a pre-built package.) More detailed documentation is available from the project site, at -["Building Spark with Maven"](http://spark.apache.org/docs/latest/building-with-maven.html). +["Building Spark with Maven"](http://spark.apache.org/docs/latest/building-spark.html). ## Interactive Scala Shell From b6b6393b477baa7246e2c7c4942b30c14cb05fa4 Mon Sep 17 00:00:00 2001 From: Nicholas Chammas Date: Thu, 25 Dec 2014 14:13:12 -0800 Subject: [PATCH 101/320] [EC2] Update default Spark version to 1.2.0 Now that 1.2.0 is out, let's update the default Spark version. Author: Nicholas Chammas Closes #3793 from nchammas/patch-1 and squashes the following commits: 3255832 [Nicholas Chammas] add 1.2.0 version to Spark-Shark map ec0e904 [Nicholas Chammas] [EC2] Update default Spark version to 1.2.0 --- ec2/spark_ec2.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/ec2/spark_ec2.py b/ec2/spark_ec2.py index 556d99d1027b8..c6679f7a0b7e9 100755 --- a/ec2/spark_ec2.py +++ b/ec2/spark_ec2.py @@ -39,7 +39,7 @@ from optparse import OptionParser from sys import stderr -DEFAULT_SPARK_VERSION = "1.1.0" +DEFAULT_SPARK_VERSION = "1.2.0" SPARK_EC2_DIR = os.path.dirname(os.path.realpath(__file__)) MESOS_SPARK_EC2_BRANCH = "v4" @@ -251,10 +251,13 @@ def get_spark_shark_version(opts): "0.8.1": "0.8.1", "0.9.0": "0.9.0", "0.9.1": "0.9.1", + # These are dummy versions (no Shark versions after this) "1.0.0": "1.0.0", "1.0.1": "1.0.1", "1.0.2": "1.0.2", "1.1.0": "1.1.0", + "1.1.1": "1.1.1", + "1.2.0": "1.2.0", } version = opts.spark_version.replace("v", "") if version not in spark_shark_map: From ac8278593ea68dd3be8cddf8cd5ce739f163ab84 Mon Sep 17 00:00:00 2001 From: Nicholas Chammas Date: Thu, 25 Dec 2014 14:16:50 -0800 Subject: [PATCH 102/320] [EC2] Update mesos/spark-ec2 branch to branch-1.3 Going forward, we'll use matching branch names across the mesos/spark-ec2 and apache/spark repositories, per [the discussion here](https://github.com/mesos/spark-ec2/pull/85#issuecomment-68069589). Author: Nicholas Chammas Closes #3804 from nchammas/patch-2 and squashes the following commits: cd2c0d4 [Nicholas Chammas] [EC2] Update mesos/spark-ec2 branch to branch-1.3 --- ec2/spark_ec2.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ec2/spark_ec2.py b/ec2/spark_ec2.py index c6679f7a0b7e9..485eea4f5e683 100755 --- a/ec2/spark_ec2.py +++ b/ec2/spark_ec2.py @@ -42,7 +42,7 @@ DEFAULT_SPARK_VERSION = "1.2.0" SPARK_EC2_DIR = os.path.dirname(os.path.realpath(__file__)) -MESOS_SPARK_EC2_BRANCH = "v4" +MESOS_SPARK_EC2_BRANCH = "branch-1.3" # A URL prefix from which to fetch AMI information AMI_PREFIX = "https://raw.github.com/mesos/spark-ec2/{b}/ami-list".format(b=MESOS_SPARK_EC2_BRANCH) From f205fe477c33a541053c198cd43a5811d6cf9fe2 Mon Sep 17 00:00:00 2001 From: jerryshao Date: Thu, 25 Dec 2014 19:39:49 -0800 Subject: [PATCH 103/320] [SPARK-4537][Streaming] Expand StreamingSource to add more metrics Add `processingDelay`, `schedulingDelay` and `totalDelay` for the last completed batch. Add `lastReceivedBatchRecords` and `totalReceivedBatchRecords` to the received records counting. Author: jerryshao Closes #3466 from jerryshao/SPARK-4537 and squashes the following commits: 00f5f7f [jerryshao] Change the code style and add totalProcessedRecords 44721a6 [jerryshao] Further address the comments c097ddc [jerryshao] Address the comments 02dd44f [jerryshao] Fix the addressed comments c7a9376 [jerryshao] Expand StreamingSource to add more metrics --- .../spark/streaming/StreamingSource.scala | 53 ++++++++++++++----- .../ui/StreamingJobProgressListener.scala | 19 ++++++- 2 files changed, 57 insertions(+), 15 deletions(-) diff --git a/streaming/src/main/scala/org/apache/spark/streaming/StreamingSource.scala b/streaming/src/main/scala/org/apache/spark/streaming/StreamingSource.scala index e35a568ddf115..9697437dd2fe5 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/StreamingSource.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/StreamingSource.scala @@ -29,9 +29,17 @@ private[streaming] class StreamingSource(ssc: StreamingContext) extends Source { private val streamingListener = ssc.progressListener private def registerGauge[T](name: String, f: StreamingJobProgressListener => T, - defaultValue: T) { + defaultValue: T): Unit = { + registerGaugeWithOption[T](name, + (l: StreamingJobProgressListener) => Option(f(streamingListener)), defaultValue) + } + + private def registerGaugeWithOption[T]( + name: String, + f: StreamingJobProgressListener => Option[T], + defaultValue: T): Unit = { metricRegistry.register(MetricRegistry.name("streaming", name), new Gauge[T] { - override def getValue: T = Option(f(streamingListener)).getOrElse(defaultValue) + override def getValue: T = f(streamingListener).getOrElse(defaultValue) }) } @@ -41,6 +49,12 @@ private[streaming] class StreamingSource(ssc: StreamingContext) extends Source { // Gauge for number of total completed batches registerGauge("totalCompletedBatches", _.numTotalCompletedBatches, 0L) + // Gauge for number of total received records + registerGauge("totalReceivedRecords", _.numTotalReceivedRecords, 0L) + + // Gauge for number of total processed records + registerGauge("totalProcessedRecords", _.numTotalProcessedRecords, 0L) + // Gauge for number of unprocessed batches registerGauge("unprocessedBatches", _.numUnprocessedBatches, 0L) @@ -55,19 +69,30 @@ private[streaming] class StreamingSource(ssc: StreamingContext) extends Source { // Gauge for last completed batch, useful for monitoring the streaming job's running status, // displayed data -1 for any abnormal condition. - registerGauge("lastCompletedBatch_submissionTime", - _.lastCompletedBatch.map(_.submissionTime).getOrElse(-1L), -1L) - registerGauge("lastCompletedBatch_processStartTime", - _.lastCompletedBatch.flatMap(_.processingStartTime).getOrElse(-1L), -1L) - registerGauge("lastCompletedBatch_processEndTime", - _.lastCompletedBatch.flatMap(_.processingEndTime).getOrElse(-1L), -1L) + registerGaugeWithOption("lastCompletedBatch_submissionTime", + _.lastCompletedBatch.map(_.submissionTime), -1L) + registerGaugeWithOption("lastCompletedBatch_processingStartTime", + _.lastCompletedBatch.flatMap(_.processingStartTime), -1L) + registerGaugeWithOption("lastCompletedBatch_processingEndTime", + _.lastCompletedBatch.flatMap(_.processingEndTime), -1L) + + // Gauge for last completed batch's delay information. + registerGaugeWithOption("lastCompletedBatch_processingDelay", + _.lastCompletedBatch.flatMap(_.processingDelay), -1L) + registerGaugeWithOption("lastCompletedBatch_schedulingDelay", + _.lastCompletedBatch.flatMap(_.schedulingDelay), -1L) + registerGaugeWithOption("lastCompletedBatch_totalDelay", + _.lastCompletedBatch.flatMap(_.totalDelay), -1L) // Gauge for last received batch, useful for monitoring the streaming job's running status, // displayed data -1 for any abnormal condition. - registerGauge("lastReceivedBatch_submissionTime", - _.lastCompletedBatch.map(_.submissionTime).getOrElse(-1L), -1L) - registerGauge("lastReceivedBatch_processStartTime", - _.lastCompletedBatch.flatMap(_.processingStartTime).getOrElse(-1L), -1L) - registerGauge("lastReceivedBatch_processEndTime", - _.lastCompletedBatch.flatMap(_.processingEndTime).getOrElse(-1L), -1L) + registerGaugeWithOption("lastReceivedBatch_submissionTime", + _.lastCompletedBatch.map(_.submissionTime), -1L) + registerGaugeWithOption("lastReceivedBatch_processingStartTime", + _.lastCompletedBatch.flatMap(_.processingStartTime), -1L) + registerGaugeWithOption("lastReceivedBatch_processingEndTime", + _.lastCompletedBatch.flatMap(_.processingEndTime), -1L) + + // Gauge for last received batch records. + registerGauge("lastReceivedBatch_records", _.lastReceivedBatchRecords.values.sum, 0L) } diff --git a/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingJobProgressListener.scala b/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingJobProgressListener.scala index f61069b56db5e..5ee53a5c5f561 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingJobProgressListener.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingJobProgressListener.scala @@ -25,7 +25,6 @@ import org.apache.spark.streaming.scheduler.StreamingListenerBatchStarted import org.apache.spark.streaming.scheduler.BatchInfo import org.apache.spark.streaming.scheduler.StreamingListenerBatchSubmitted import org.apache.spark.util.Distribution -import org.apache.spark.Logging private[streaming] class StreamingJobProgressListener(ssc: StreamingContext) @@ -36,6 +35,8 @@ private[streaming] class StreamingJobProgressListener(ssc: StreamingContext) private val completedaBatchInfos = new Queue[BatchInfo] private val batchInfoLimit = ssc.conf.getInt("spark.streaming.ui.retainedBatches", 100) private var totalCompletedBatches = 0L + private var totalReceivedRecords = 0L + private var totalProcessedRecords = 0L private val receiverInfos = new HashMap[Int, ReceiverInfo] val batchDuration = ssc.graph.batchDuration.milliseconds @@ -65,6 +66,10 @@ private[streaming] class StreamingJobProgressListener(ssc: StreamingContext) override def onBatchStarted(batchStarted: StreamingListenerBatchStarted) = synchronized { runningBatchInfos(batchStarted.batchInfo.batchTime) = batchStarted.batchInfo waitingBatchInfos.remove(batchStarted.batchInfo.batchTime) + + batchStarted.batchInfo.receivedBlockInfo.foreach { case (_, infos) => + totalReceivedRecords += infos.map(_.numRecords).sum + } } override def onBatchCompleted(batchCompleted: StreamingListenerBatchCompleted) = synchronized { @@ -73,6 +78,10 @@ private[streaming] class StreamingJobProgressListener(ssc: StreamingContext) completedaBatchInfos.enqueue(batchCompleted.batchInfo) if (completedaBatchInfos.size > batchInfoLimit) completedaBatchInfos.dequeue() totalCompletedBatches += 1L + + batchCompleted.batchInfo.receivedBlockInfo.foreach { case (_, infos) => + totalProcessedRecords += infos.map(_.numRecords).sum + } } def numReceivers = synchronized { @@ -83,6 +92,14 @@ private[streaming] class StreamingJobProgressListener(ssc: StreamingContext) totalCompletedBatches } + def numTotalReceivedRecords: Long = synchronized { + totalReceivedRecords + } + + def numTotalProcessedRecords: Long = synchronized { + totalProcessedRecords + } + def numUnprocessedBatches: Long = synchronized { waitingBatchInfos.size + runningBatchInfos.size } From f9ed2b6641b9df39cee4b98a33cd5a3ddda2d146 Mon Sep 17 00:00:00 2001 From: zsxwing Date: Thu, 25 Dec 2014 19:46:05 -0800 Subject: [PATCH 104/320] [SPARK-4608][Streaming] Reorganize StreamingContext implicit to improve API convenience There is only one implicit function `toPairDStreamFunctions` in `StreamingContext`. This PR did similar reorganization like [SPARK-4397](https://issues.apache.org/jira/browse/SPARK-4397). Compiled the following codes with Spark Streaming 1.1.0 and ran it with this PR. Everything is fine. ```Scala import org.apache.spark._ import org.apache.spark.streaming._ import org.apache.spark.streaming.StreamingContext._ object StreamingApp { def main(args: Array[String]) { val conf = new SparkConf().setMaster("local[2]").setAppName("FileWordCount") val ssc = new StreamingContext(conf, Seconds(10)) val lines = ssc.textFileStream("/some/path") val words = lines.flatMap(_.split(" ")) val pairs = words.map(word => (word, 1)) val wordCounts = pairs.reduceByKey(_ + _) wordCounts.print() ssc.start() ssc.awaitTermination() } } ``` Author: zsxwing Closes #3464 from zsxwing/SPARK-4608 and squashes the following commits: aa6d44a [zsxwing] Fix a copy-paste error f74c190 [zsxwing] Merge branch 'master' into SPARK-4608 e6f9cc9 [zsxwing] Update the docs 27833bb [zsxwing] Remove `import StreamingContext._` c15162c [zsxwing] Reorganize StreamingContext implicit to improve API convenience --- docs/streaming-programming-guide.md | 4 +-- .../examples/streaming/KafkaWordCount.scala | 1 - .../examples/streaming/CustomReceiver.scala | 1 - .../examples/streaming/HdfsWordCount.scala | 1 - .../examples/streaming/MQTTWordCount.scala | 1 - .../examples/streaming/NetworkWordCount.scala | 1 - .../examples/streaming/QueueStream.scala | 1 - .../RecoverableNetworkWordCount.scala | 1 - .../streaming/StatefulNetworkWordCount.scala | 1 - .../streaming/TwitterAlgebirdCMS.scala | 1 - .../streaming/TwitterPopularTags.scala | 1 - .../examples/streaming/ZeroMQWordCount.scala | 1 - .../clickstream/PageViewStream.scala | 1 - .../mllib/clustering/StreamingKMeans.scala | 1 - .../regression/StreamingLinearAlgorithm.scala | 1 - .../spark/streaming/StreamingContext.scala | 7 ++-- .../streaming/api/java/JavaPairDStream.scala | 3 +- .../spark/streaming/dstream/DStream.scala | 22 ++++++++---- .../dstream/PairDStreamFunctions.scala | 4 +-- .../dstream/ReducedWindowedDStream.scala | 2 -- .../org/apache/spark/streaming/package.scala | 2 +- .../streaming/BasicOperationsSuite.scala | 1 - .../spark/streaming/CheckpointSuite.scala | 1 - .../spark/streaming/MasterFailureTest.scala | 1 - .../streaming/WindowOperationsSuite.scala | 1 - .../spark/streamingtest/ImplicitSuite.scala | 35 +++++++++++++++++++ 26 files changed, 60 insertions(+), 37 deletions(-) create mode 100644 streaming/src/test/scala/org/apache/spark/streamingtest/ImplicitSuite.scala diff --git a/docs/streaming-programming-guide.md b/docs/streaming-programming-guide.md index 1ac5b9e863ad4..01450efe35e55 100644 --- a/docs/streaming-programming-guide.md +++ b/docs/streaming-programming-guide.md @@ -75,7 +75,7 @@ main entry point for all streaming functionality. We create a local StreamingCon {% highlight scala %} import org.apache.spark._ import org.apache.spark.streaming._ -import org.apache.spark.streaming.StreamingContext._ +import org.apache.spark.streaming.StreamingContext._ // not necessary in Spark 1.3+ // Create a local StreamingContext with two working thread and batch interval of 1 second. // The master requires 2 cores to prevent from a starvation scenario. @@ -107,7 +107,7 @@ each line will be split into multiple words and the stream of words is represent `words` DStream. Next, we want to count these words. {% highlight scala %} -import org.apache.spark.streaming.StreamingContext._ +import org.apache.spark.streaming.StreamingContext._ // not necessary in Spark 1.3+ // Count each word in each batch val pairs = words.map(word => (word, 1)) val wordCounts = pairs.reduceByKey(_ + _) diff --git a/examples/scala-2.10/src/main/scala/org/apache/spark/examples/streaming/KafkaWordCount.scala b/examples/scala-2.10/src/main/scala/org/apache/spark/examples/streaming/KafkaWordCount.scala index c9e1511278ede..2adc63f7ff30e 100644 --- a/examples/scala-2.10/src/main/scala/org/apache/spark/examples/streaming/KafkaWordCount.scala +++ b/examples/scala-2.10/src/main/scala/org/apache/spark/examples/streaming/KafkaWordCount.scala @@ -22,7 +22,6 @@ import java.util.Properties import kafka.producer._ import org.apache.spark.streaming._ -import org.apache.spark.streaming.StreamingContext._ import org.apache.spark.streaming.kafka._ import org.apache.spark.SparkConf diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/CustomReceiver.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/CustomReceiver.scala index 6bb659fbd8be8..30269a7ccae97 100644 --- a/examples/src/main/scala/org/apache/spark/examples/streaming/CustomReceiver.scala +++ b/examples/src/main/scala/org/apache/spark/examples/streaming/CustomReceiver.scala @@ -23,7 +23,6 @@ import java.net.Socket import org.apache.spark.{SparkConf, Logging} import org.apache.spark.storage.StorageLevel import org.apache.spark.streaming.{Seconds, StreamingContext} -import org.apache.spark.streaming.StreamingContext._ import org.apache.spark.streaming.receiver.Receiver /** diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/HdfsWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/HdfsWordCount.scala index 6c24bc3ad09e0..4b4667fec44e6 100644 --- a/examples/src/main/scala/org/apache/spark/examples/streaming/HdfsWordCount.scala +++ b/examples/src/main/scala/org/apache/spark/examples/streaming/HdfsWordCount.scala @@ -19,7 +19,6 @@ package org.apache.spark.examples.streaming import org.apache.spark.SparkConf import org.apache.spark.streaming.{Seconds, StreamingContext} -import org.apache.spark.streaming.StreamingContext._ /** * Counts words in new text files created in the given directory diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/MQTTWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/MQTTWordCount.scala index e4283e04a1b11..6ff0c47793a25 100644 --- a/examples/src/main/scala/org/apache/spark/examples/streaming/MQTTWordCount.scala +++ b/examples/src/main/scala/org/apache/spark/examples/streaming/MQTTWordCount.scala @@ -22,7 +22,6 @@ import org.eclipse.paho.client.mqttv3.persist.MqttDefaultFilePersistence import org.apache.spark.storage.StorageLevel import org.apache.spark.streaming.{Seconds, StreamingContext} -import org.apache.spark.streaming.StreamingContext._ import org.apache.spark.streaming.mqtt._ import org.apache.spark.SparkConf diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/NetworkWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/NetworkWordCount.scala index ae0a08c6cdb1a..2cd8073dada14 100644 --- a/examples/src/main/scala/org/apache/spark/examples/streaming/NetworkWordCount.scala +++ b/examples/src/main/scala/org/apache/spark/examples/streaming/NetworkWordCount.scala @@ -19,7 +19,6 @@ package org.apache.spark.examples.streaming import org.apache.spark.SparkConf import org.apache.spark.streaming.{Seconds, StreamingContext} -import org.apache.spark.streaming.StreamingContext._ import org.apache.spark.storage.StorageLevel /** diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/QueueStream.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/QueueStream.scala index 4caa90659111a..13ba9a43ec3c9 100644 --- a/examples/src/main/scala/org/apache/spark/examples/streaming/QueueStream.scala +++ b/examples/src/main/scala/org/apache/spark/examples/streaming/QueueStream.scala @@ -22,7 +22,6 @@ import scala.collection.mutable.SynchronizedQueue import org.apache.spark.SparkConf import org.apache.spark.rdd.RDD import org.apache.spark.streaming.{Seconds, StreamingContext} -import org.apache.spark.streaming.StreamingContext._ object QueueStream { diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/RecoverableNetworkWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/RecoverableNetworkWordCount.scala index 19427e629f76d..c3a05c89d817e 100644 --- a/examples/src/main/scala/org/apache/spark/examples/streaming/RecoverableNetworkWordCount.scala +++ b/examples/src/main/scala/org/apache/spark/examples/streaming/RecoverableNetworkWordCount.scala @@ -25,7 +25,6 @@ import com.google.common.io.Files import org.apache.spark.SparkConf import org.apache.spark.rdd.RDD import org.apache.spark.streaming.{Time, Seconds, StreamingContext} -import org.apache.spark.streaming.StreamingContext._ import org.apache.spark.util.IntParam /** diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/StatefulNetworkWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/StatefulNetworkWordCount.scala index ed186ea5650c4..345d0bc441351 100644 --- a/examples/src/main/scala/org/apache/spark/examples/streaming/StatefulNetworkWordCount.scala +++ b/examples/src/main/scala/org/apache/spark/examples/streaming/StatefulNetworkWordCount.scala @@ -20,7 +20,6 @@ package org.apache.spark.examples.streaming import org.apache.spark.SparkConf import org.apache.spark.HashPartitioner import org.apache.spark.streaming._ -import org.apache.spark.streaming.StreamingContext._ /** * Counts words cumulatively in UTF8 encoded, '\n' delimited text received from the network every diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/TwitterAlgebirdCMS.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/TwitterAlgebirdCMS.scala index 683752ac96241..62f49530edb12 100644 --- a/examples/src/main/scala/org/apache/spark/examples/streaming/TwitterAlgebirdCMS.scala +++ b/examples/src/main/scala/org/apache/spark/examples/streaming/TwitterAlgebirdCMS.scala @@ -23,7 +23,6 @@ import org.apache.spark.SparkConf import org.apache.spark.SparkContext._ import org.apache.spark.storage.StorageLevel import org.apache.spark.streaming.{Seconds, StreamingContext} -import org.apache.spark.streaming.StreamingContext._ import org.apache.spark.streaming.twitter._ // scalastyle:off diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/TwitterPopularTags.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/TwitterPopularTags.scala index f55d23ab3924b..f253d75b279f7 100644 --- a/examples/src/main/scala/org/apache/spark/examples/streaming/TwitterPopularTags.scala +++ b/examples/src/main/scala/org/apache/spark/examples/streaming/TwitterPopularTags.scala @@ -18,7 +18,6 @@ package org.apache.spark.examples.streaming import org.apache.spark.streaming.{Seconds, StreamingContext} -import StreamingContext._ import org.apache.spark.SparkContext._ import org.apache.spark.streaming.twitter._ import org.apache.spark.SparkConf diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/ZeroMQWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/ZeroMQWordCount.scala index 79905af381a12..6510c70bd1866 100644 --- a/examples/src/main/scala/org/apache/spark/examples/streaming/ZeroMQWordCount.scala +++ b/examples/src/main/scala/org/apache/spark/examples/streaming/ZeroMQWordCount.scala @@ -24,7 +24,6 @@ import akka.zeromq.Subscribe import akka.util.ByteString import org.apache.spark.streaming.{Seconds, StreamingContext} -import org.apache.spark.streaming.StreamingContext._ import org.apache.spark.streaming.zeromq._ import scala.language.implicitConversions diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/clickstream/PageViewStream.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/clickstream/PageViewStream.scala index 55226c0a6df60..fbacaee98690f 100644 --- a/examples/src/main/scala/org/apache/spark/examples/streaming/clickstream/PageViewStream.scala +++ b/examples/src/main/scala/org/apache/spark/examples/streaming/clickstream/PageViewStream.scala @@ -19,7 +19,6 @@ package org.apache.spark.examples.streaming.clickstream import org.apache.spark.SparkContext._ import org.apache.spark.streaming.{Seconds, StreamingContext} -import org.apache.spark.streaming.StreamingContext._ import org.apache.spark.examples.streaming.StreamingExamples // scalastyle:off /** Analyses a streaming dataset of web page views. This class demonstrates several types of diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/StreamingKMeans.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/StreamingKMeans.scala index 6189dce9b27da..7752c1988fdd1 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/StreamingKMeans.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/StreamingKMeans.scala @@ -24,7 +24,6 @@ import org.apache.spark.SparkContext._ import org.apache.spark.annotation.DeveloperApi import org.apache.spark.mllib.linalg.{BLAS, Vector, Vectors} import org.apache.spark.rdd.RDD -import org.apache.spark.streaming.StreamingContext._ import org.apache.spark.streaming.dstream.DStream import org.apache.spark.util.Utils import org.apache.spark.util.random.XORShiftRandom diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/StreamingLinearAlgorithm.scala b/mllib/src/main/scala/org/apache/spark/mllib/regression/StreamingLinearAlgorithm.scala index 8db0442a7a569..b549b7c475fc3 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/regression/StreamingLinearAlgorithm.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/regression/StreamingLinearAlgorithm.scala @@ -22,7 +22,6 @@ import scala.reflect.ClassTag import org.apache.spark.Logging import org.apache.spark.annotation.DeveloperApi import org.apache.spark.mllib.linalg.Vector -import org.apache.spark.streaming.StreamingContext._ import org.apache.spark.streaming.dstream.DStream /** diff --git a/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala b/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala index ecab5510a8e7b..8ef0787137845 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala @@ -22,7 +22,6 @@ import java.util.concurrent.atomic.AtomicInteger import scala.collection.Map import scala.collection.mutable.Queue -import scala.language.implicitConversions import scala.reflect.ClassTag import akka.actor.{Props, SupervisorStrategy} @@ -523,9 +522,11 @@ object StreamingContext extends Logging { private[streaming] val DEFAULT_CLEANER_TTL = 3600 - implicit def toPairDStreamFunctions[K, V](stream: DStream[(K, V)]) + @deprecated("Replaced by implicit functions in the DStream companion object. This is " + + "kept here only for backward compatibility.", "1.3.0") + def toPairDStreamFunctions[K, V](stream: DStream[(K, V)]) (implicit kt: ClassTag[K], vt: ClassTag[V], ord: Ordering[K] = null) = { - new PairDStreamFunctions[K, V](stream) + DStream.toPairDStreamFunctions(stream)(kt, vt, ord) } /** diff --git a/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaPairDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaPairDStream.scala index bb44b906d7386..de124cf40eff1 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaPairDStream.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaPairDStream.scala @@ -36,7 +36,6 @@ import org.apache.spark.api.java.function.{Function => JFunction, Function2 => J import org.apache.spark.rdd.RDD import org.apache.spark.storage.StorageLevel import org.apache.spark.streaming._ -import org.apache.spark.streaming.StreamingContext._ import org.apache.spark.streaming.dstream.DStream /** @@ -815,6 +814,6 @@ object JavaPairDStream { def scalaToJavaLong[K: ClassTag](dstream: JavaPairDStream[K, Long]) : JavaPairDStream[K, JLong] = { - StreamingContext.toPairDStreamFunctions(dstream.dstream).mapValues(new JLong(_)) + DStream.toPairDStreamFunctions(dstream.dstream).mapValues(new JLong(_)) } } diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala index dbf1ebbaf653a..7f8651e719d84 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala @@ -20,8 +20,8 @@ package org.apache.spark.streaming.dstream import java.io.{IOException, ObjectInputStream, ObjectOutputStream} -import scala.deprecated import scala.collection.mutable.HashMap +import scala.language.implicitConversions import scala.reflect.ClassTag import scala.util.matching.Regex @@ -29,7 +29,7 @@ import org.apache.spark.{Logging, SparkException} import org.apache.spark.rdd.{BlockRDD, RDD} import org.apache.spark.storage.StorageLevel import org.apache.spark.streaming._ -import org.apache.spark.streaming.StreamingContext._ +import org.apache.spark.streaming.StreamingContext.rddToFileName import org.apache.spark.streaming.scheduler.Job import org.apache.spark.util.{CallSite, MetadataCleaner, Utils} @@ -48,8 +48,7 @@ import org.apache.spark.util.{CallSite, MetadataCleaner, Utils} * `window`. In addition, [[org.apache.spark.streaming.dstream.PairDStreamFunctions]] contains * operations available only on DStreams of key-value pairs, such as `groupByKeyAndWindow` and * `join`. These operations are automatically available on any DStream of pairs - * (e.g., DStream[(Int, Int)] through implicit conversions when - * `org.apache.spark.streaming.StreamingContext._` is imported. + * (e.g., DStream[(Int, Int)] through implicit conversions. * * DStreams internally is characterized by a few basic properties: * - A list of other DStreams that the DStream depends on @@ -802,10 +801,21 @@ abstract class DStream[T: ClassTag] ( } } -private[streaming] object DStream { +object DStream { + + // `toPairDStreamFunctions` was in SparkContext before 1.3 and users had to + // `import StreamingContext._` to enable it. Now we move it here to make the compiler find + // it automatically. However, we still keep the old function in StreamingContext for backward + // compatibility and forward to the following function directly. + + implicit def toPairDStreamFunctions[K, V](stream: DStream[(K, V)]) + (implicit kt: ClassTag[K], vt: ClassTag[V], ord: Ordering[K] = null): + PairDStreamFunctions[K, V] = { + new PairDStreamFunctions[K, V](stream) + } /** Get the creation site of a DStream from the stack trace of when the DStream is created. */ - def getCreationSite(): CallSite = { + private[streaming] def getCreationSite(): CallSite = { val SPARK_CLASS_REGEX = """^org\.apache\.spark""".r val SPARK_STREAMING_TESTCLASS_REGEX = """^org\.apache\.spark\.streaming\.test""".r val SPARK_EXAMPLES_CLASS_REGEX = """^org\.apache\.spark\.examples""".r diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/PairDStreamFunctions.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/PairDStreamFunctions.scala index 98539e06b4e29..8a58571632447 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/PairDStreamFunctions.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/PairDStreamFunctions.scala @@ -27,12 +27,10 @@ import org.apache.hadoop.mapreduce.{OutputFormat => NewOutputFormat} import org.apache.spark.{HashPartitioner, Partitioner, SerializableWritable} import org.apache.spark.rdd.RDD import org.apache.spark.streaming.{Duration, Time} -import org.apache.spark.streaming.StreamingContext._ +import org.apache.spark.streaming.StreamingContext.rddToFileName /** * Extra functions available on DStream of (key, value) pairs through an implicit conversion. - * Import `org.apache.spark.streaming.StreamingContext._` at the top of your program to use - * these functions. */ class PairDStreamFunctions[K, V](self: DStream[(K,V)]) (implicit kt: ClassTag[K], vt: ClassTag[V], ord: Ordering[K]) diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/ReducedWindowedDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/ReducedWindowedDStream.scala index 1a47089e513c4..c0a5af0b65cc3 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/ReducedWindowedDStream.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/ReducedWindowedDStream.scala @@ -17,8 +17,6 @@ package org.apache.spark.streaming.dstream -import org.apache.spark.streaming.StreamingContext._ - import org.apache.spark.rdd.RDD import org.apache.spark.rdd.{CoGroupedRDD, MapPartitionsRDD} import org.apache.spark.Partitioner diff --git a/streaming/src/main/scala/org/apache/spark/streaming/package.scala b/streaming/src/main/scala/org/apache/spark/streaming/package.scala index 4dd985cf5a178..2153ae0d34184 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/package.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/package.scala @@ -26,7 +26,7 @@ package org.apache.spark * available only on DStreams * of key-value pairs, such as `groupByKey` and `reduceByKey`. These operations are automatically * available on any DStream of the right type (e.g. DStream[(Int, Int)] through implicit - * conversions when you `import org.apache.spark.streaming.StreamingContext._`. + * conversions. * * For the Java API of Spark Streaming, take a look at the * [[org.apache.spark.streaming.api.java.JavaStreamingContext]] which serves as the entry point, and diff --git a/streaming/src/test/scala/org/apache/spark/streaming/BasicOperationsSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/BasicOperationsSuite.scala index 86b96785d7b87..199f5e7161124 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/BasicOperationsSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/BasicOperationsSuite.scala @@ -28,7 +28,6 @@ import org.apache.spark.{SparkConf, SparkException} import org.apache.spark.SparkContext._ import org.apache.spark.rdd.{BlockRDD, RDD} import org.apache.spark.storage.StorageLevel -import org.apache.spark.streaming.StreamingContext._ import org.apache.spark.streaming.dstream.{DStream, WindowedDStream} import org.apache.spark.HashPartitioner diff --git a/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala index c97998add8ffa..72d055eb2ea31 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala @@ -30,7 +30,6 @@ import org.apache.hadoop.io.{IntWritable, Text} import org.apache.hadoop.mapred.TextOutputFormat import org.apache.hadoop.mapreduce.lib.output.{TextOutputFormat => NewTextOutputFormat} -import org.apache.spark.streaming.StreamingContext._ import org.apache.spark.streaming.dstream.{DStream, FileInputDStream} import org.apache.spark.streaming.util.ManualClock import org.apache.spark.util.Utils diff --git a/streaming/src/test/scala/org/apache/spark/streaming/MasterFailureTest.scala b/streaming/src/test/scala/org/apache/spark/streaming/MasterFailureTest.scala index 5dbb7232009eb..e0f14fd954280 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/MasterFailureTest.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/MasterFailureTest.scala @@ -20,7 +20,6 @@ package org.apache.spark.streaming import org.apache.spark.Logging import org.apache.spark.streaming.dstream.DStream import org.apache.spark.util.Utils -import org.apache.spark.streaming.StreamingContext._ import scala.util.Random import scala.collection.mutable.ArrayBuffer diff --git a/streaming/src/test/scala/org/apache/spark/streaming/WindowOperationsSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/WindowOperationsSuite.scala index 471c99fab4682..a5d2bb2fde16c 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/WindowOperationsSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/WindowOperationsSuite.scala @@ -17,7 +17,6 @@ package org.apache.spark.streaming -import org.apache.spark.streaming.StreamingContext._ import org.apache.spark.streaming.dstream.DStream import org.apache.spark.storage.StorageLevel diff --git a/streaming/src/test/scala/org/apache/spark/streamingtest/ImplicitSuite.scala b/streaming/src/test/scala/org/apache/spark/streamingtest/ImplicitSuite.scala new file mode 100644 index 0000000000000..d0bf328f2b74d --- /dev/null +++ b/streaming/src/test/scala/org/apache/spark/streamingtest/ImplicitSuite.scala @@ -0,0 +1,35 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.streamingtest + +/** + * A test suite to make sure all `implicit` functions work correctly. + * + * As `implicit` is a compiler feature, we don't need to run this class. + * What we need to do is making the compiler happy. + */ +class ImplicitSuite { + + // We only want to test if `implict` works well with the compiler, so we don't need a real DStream. + def mockDStream[T]: org.apache.spark.streaming.dstream.DStream[T] = null + + def testToPairDStreamFunctions(): Unit = { + val dstream: org.apache.spark.streaming.dstream.DStream[(Int, Int)] = mockDStream + dstream.groupByKey() + } +} From fda4331d58aae454a2b0f4c757d105f8bc228a3d Mon Sep 17 00:00:00 2001 From: CodingCat Date: Fri, 26 Dec 2014 12:03:22 -0800 Subject: [PATCH 105/320] SPARK-4971: Fix typo in BlockGenerator comment Author: CodingCat Closes #3807 from CodingCat/new_branch and squashes the following commits: 5167f01 [CodingCat] fix typo in the comment --- .../org/apache/spark/streaming/receiver/BlockGenerator.scala | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/streaming/src/main/scala/org/apache/spark/streaming/receiver/BlockGenerator.scala b/streaming/src/main/scala/org/apache/spark/streaming/receiver/BlockGenerator.scala index 55765dc90698b..79263a7183977 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/receiver/BlockGenerator.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/receiver/BlockGenerator.scala @@ -116,7 +116,7 @@ private[streaming] class BlockGenerator( /** * Push a single data item into the buffer. After buffering the data, the - * `BlockGeneratorListnere.onAddData` callback will be called. All received data items + * `BlockGeneratorListener.onAddData` callback will be called. All received data items * will be periodically pushed into BlockManager. */ def addDataWithCallback(data: Any, metadata: Any) = synchronized { From 534f24b2d094eaac8554f3e4c8c8addd40c62441 Mon Sep 17 00:00:00 2001 From: Patrick Wendell Date: Fri, 26 Dec 2014 22:39:56 -0800 Subject: [PATCH 106/320] MAINTENANCE: Automated closing of pull requests. This commit exists to close the following pull requests on Github: Closes #3456 (close requested by 'pwendell') Closes #1602 (close requested by 'tdas') Closes #2633 (close requested by 'tdas') Closes #2059 (close requested by 'JoshRosen') Closes #2348 (close requested by 'tdas') Closes #3662 (close requested by 'tdas') Closes #2031 (close requested by 'andrewor14') Closes #265 (close requested by 'JoshRosen') From de95c57ac6fcb2a62cf5083feb3cc79ab18a836f Mon Sep 17 00:00:00 2001 From: Kousuke Saruta Date: Fri, 26 Dec 2014 22:52:04 -0800 Subject: [PATCH 107/320] [SPARK-3787][BUILD] Assembly jar name is wrong when we build with sbt omitting -Dhadoop.version This PR is another solution for When we build with sbt with profile for hadoop and without property for hadoop version like: sbt/sbt -Phadoop-2.2 assembly jar name is always used default version (1.0.4). When we build with maven with same condition for sbt, default version for each profile is used. For instance, if we build like: mvn -Phadoop-2.2 package jar name is used hadoop2.2.0 as a default version of hadoop-2.2. Author: Kousuke Saruta Closes #3046 from sarutak/fix-assembly-jarname-2 and squashes the following commits: 41ef90e [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into fix-assembly-jarname-2 50c8676 [Kousuke Saruta] Merge branch 'fix-assembly-jarname-2' of github.com:sarutak/spark into fix-assembly-jarname-2 52a1cd2 [Kousuke Saruta] Fixed comflicts dd30768 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into fix-assembly-jarname2 f1c90bb [Kousuke Saruta] Fixed SparkBuild.scala in order to read `hadoop.version` property from pom.xml af6b100 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into fix-assembly-jarname c81806b [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into fix-assembly-jarname ad1f96e [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into fix-assembly-jarname b2318eb [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into fix-assembly-jarname 5fc1259 [Kousuke Saruta] Fixed typo. eebbb7d [Kousuke Saruta] Fixed wrong jar name --- project/SparkBuild.scala | 16 +++++++++++++--- 1 file changed, 13 insertions(+), 3 deletions(-) diff --git a/project/SparkBuild.scala b/project/SparkBuild.scala index f52074282e1f7..4d103f9dc0e2c 100644 --- a/project/SparkBuild.scala +++ b/project/SparkBuild.scala @@ -15,6 +15,8 @@ * limitations under the License. */ +import java.io.File + import scala.util.Properties import scala.collection.JavaConversions._ @@ -23,7 +25,7 @@ import sbt.Classpaths.publishTask import sbt.Keys._ import sbtunidoc.Plugin.genjavadocSettings import sbtunidoc.Plugin.UnidocKeys.unidocGenjavadocVersion -import com.typesafe.sbt.pom.{PomBuild, SbtPomKeys} +import com.typesafe.sbt.pom.{loadEffectivePom, PomBuild, SbtPomKeys} import net.virtualvoid.sbt.graph.Plugin.graphSettings object BuildCommons { @@ -112,6 +114,15 @@ object SparkBuild extends PomBuild { override val userPropertiesMap = System.getProperties.toMap + val pom = loadEffectivePom(new File("pom.xml"), + profiles = profiles, + userProps = userPropertiesMap) + + if (System.getProperty("hadoop.version") == null) { + System.setProperty("hadoop.version", + pom.getProperties.get("hadoop.version").asInstanceOf[String]) + } + lazy val MavenCompile = config("m2r") extend(Compile) lazy val publishLocalBoth = TaskKey[Unit]("publish-local", "publish local for m2 and ivy") @@ -297,8 +308,7 @@ object Assembly { // This must match the same name used in maven (see network/yarn/pom.xml) "spark-" + v + "-yarn-shuffle.jar" } else { - mName + "-" + v + "-hadoop" + - Option(System.getProperty("hadoop.version")).getOrElse("1.0.4") + ".jar" + mName + "-" + v + "-hadoop" + System.getProperty("hadoop.version") + ".jar" } }, mergeStrategy in assembly := { From 82bf4bee15bb449a418290c0c07652e9a8ec8fdd Mon Sep 17 00:00:00 2001 From: Patrick Wendell Date: Fri, 26 Dec 2014 22:55:04 -0800 Subject: [PATCH 108/320] HOTFIX: Slight tweak on previous commit. Meant to merge this in when committing SPARK-3787. --- project/SparkBuild.scala | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/project/SparkBuild.scala b/project/SparkBuild.scala index 4d103f9dc0e2c..c512b62f6137e 100644 --- a/project/SparkBuild.scala +++ b/project/SparkBuild.scala @@ -114,10 +114,12 @@ object SparkBuild extends PomBuild { override val userPropertiesMap = System.getProperties.toMap + // Handle case where hadoop.version is set via profile. + // Needed only because we read back this property in sbt + // when we create the assembly jar. val pom = loadEffectivePom(new File("pom.xml"), profiles = profiles, userProps = userPropertiesMap) - if (System.getProperty("hadoop.version") == null) { System.setProperty("hadoop.version", pom.getProperties.get("hadoop.version").asInstanceOf[String]) From 2483c1efb6429a7d8a20c96d18ce2fec93a1aff9 Mon Sep 17 00:00:00 2001 From: Jongyoul Lee Date: Fri, 26 Dec 2014 22:59:34 -0800 Subject: [PATCH 109/320] [SPARK-3955] Different versions between jackson-mapper-asl and jackson-c... ...ore-asl - set the same version to jackson-mapper-asl and jackson-core-asl - It's related with #2818 - coded a same patch from a latest master Author: Jongyoul Lee Closes #3716 from jongyoul/SPARK-3955 and squashes the following commits: efa29aa [Jongyoul Lee] [SPARK-3955] Different versions between jackson-mapper-asl and jackson-core-asl - set the same version to jackson-mapper-asl and jackson-core-asl --- pom.xml | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/pom.xml b/pom.xml index e4db1393ba9cf..a843af2b22d6c 100644 --- a/pom.xml +++ b/pom.xml @@ -149,6 +149,7 @@ 2.10 ${scala.version} org.scala-lang + 1.8.8 @@ -819,10 +820,15 @@ - + org.codehaus.jackson jackson-mapper-asl - 1.8.8 + ${jackson.version} + + + org.codehaus.jackson + jackson-mapper-asl + ${jackson.version} From 786808abfd6ca8c8d3a2331d1be49c1466006a46 Mon Sep 17 00:00:00 2001 From: "Zhang, Liye" Date: Fri, 26 Dec 2014 23:23:13 -0800 Subject: [PATCH 110/320] [SPARK-4954][Core] add spark version infomation in log for standalone mode The master and worker spark version may be not the same with Driver spark version. That is because spark Jar file might be replaced for new application without restarting the spark cluster. So there shall log out the spark-version in both Mater and Worker log. Author: Zhang, Liye Closes #3790 from liyezhang556520/version4Standalone and squashes the following commits: e05e1e3 [Zhang, Liye] add spark version infomation in log for standalone mode --- core/src/main/scala/org/apache/spark/deploy/master/Master.scala | 1 + core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala | 1 + 2 files changed, 2 insertions(+) diff --git a/core/src/main/scala/org/apache/spark/deploy/master/Master.scala b/core/src/main/scala/org/apache/spark/deploy/master/Master.scala index 81fa0770bbaf9..e8a5cfc746fed 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/Master.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/Master.scala @@ -123,6 +123,7 @@ private[spark] class Master( override def preStart() { logInfo("Starting Spark master at " + masterUrl) + logInfo(s"Running Spark version ${org.apache.spark.SPARK_VERSION}") // Listen for remote client disconnection events, since they don't go through Akka's watch() context.system.eventStream.subscribe(self, classOf[RemotingLifecycleEvent]) webUi.bind() diff --git a/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala b/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala index 86a87ec22235e..f0f3da5eec4df 100755 --- a/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala +++ b/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala @@ -155,6 +155,7 @@ private[spark] class Worker( assert(!registered) logInfo("Starting Spark worker %s:%d with %d cores, %s RAM".format( host, port, cores, Utils.megabytesToString(memory))) + logInfo(s"Running Spark version ${org.apache.spark.SPARK_VERSION}") logInfo("Spark home: " + sparkHome) createWorkDir() context.system.eventStream.subscribe(self, classOf[RemotingLifecycleEvent]) From 080ceb771a1e6b9f844cfd4f1baa01133c106888 Mon Sep 17 00:00:00 2001 From: GuoQiang Li Date: Fri, 26 Dec 2014 23:31:29 -0800 Subject: [PATCH 111/320] [SPARK-4952][Core]Handle ConcurrentModificationExceptions in SparkEnv.environmentDetails Author: GuoQiang Li Closes #3788 from witgo/SPARK-4952 and squashes the following commits: d903529 [GuoQiang Li] Handle ConcurrentModificationExceptions in SparkEnv.environmentDetails --- core/src/main/scala/org/apache/spark/SparkEnv.scala | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/core/src/main/scala/org/apache/spark/SparkEnv.scala b/core/src/main/scala/org/apache/spark/SparkEnv.scala index 6656df44d3599..43436a1697000 100644 --- a/core/src/main/scala/org/apache/spark/SparkEnv.scala +++ b/core/src/main/scala/org/apache/spark/SparkEnv.scala @@ -395,7 +395,7 @@ object SparkEnv extends Logging { val sparkProperties = (conf.getAll ++ schedulerMode).sorted // System properties that are not java classpaths - val systemProperties = System.getProperties.iterator.toSeq + val systemProperties = Utils.getSystemProperties.toSeq val otherProperties = systemProperties.filter { case (k, _) => k != "java.class.path" && !k.startsWith("spark.") }.sorted From a3e51cc990812c8099dcaf1f3bd6d5bae45cf8e6 Mon Sep 17 00:00:00 2001 From: Brennon York Date: Sat, 27 Dec 2014 13:25:18 -0800 Subject: [PATCH 112/320] [SPARK-4501][Core] - Create build/mvn to automatically download maven/zinc/scalac Creates a top level directory script (as `build/mvn`) to automatically download zinc and the specific version of scala used to easily build spark. This will also download and install maven if the user doesn't already have it and all packages are hosted under the `build/` directory. Tested on both Linux and OSX OS's and both work. All commands pass through to the maven binary so it acts exactly as a traditional maven call would. Author: Brennon York Closes #3707 from brennonyork/SPARK-4501 and squashes the following commits: 0e5a0e4 [Brennon York] minor incorrect doc verbage (with -> this) 9b79e38 [Brennon York] fixed merge conflicts with dev/run-tests, properly quoted args in sbt/sbt, fixed bug where relative paths would fail if passed in from build/mvn d2d41b6 [Brennon York] added blurb about leverging zinc with build/mvn b979c58 [Brennon York] updated the merge conflict c5634de [Brennon York] updated documentation to overview build/mvn, updated all points where sbt/sbt was referenced with build/sbt b8437ba [Brennon York] set progress bars for curl and wget when not run on jenkins, no progress bar when run on jenkins, moved sbt script to build/sbt, wrote stub and warning under sbt/sbt which calls build/sbt, modified build/sbt to use the correct directory, fixed bug in build/sbt-launch-lib.bash to correctly pull the sbt version be11317 [Brennon York] added switch to silence download progress only if AMPLAB_JENKINS is set 28d0a99 [Brennon York] updated to remove the python dependency, uses grep instead 7e785a6 [Brennon York] added silent and quiet flags to curl and wget respectively, added single echo output to denote start of a download if download is needed 14a5da0 [Brennon York] removed unnecessary zinc output on startup 1af4a94 [Brennon York] fixed bug with uppercase vs lowercase variable 3e8b9b3 [Brennon York] updated to properly only restart zinc if it was freshly installed a680d12 [Brennon York] Added comments to functions and tested various mvn calls bb8cc9d [Brennon York] removed package files ef017e6 [Brennon York] removed OS complexities, setup generic install_app call, removed extra file complexities, removed help, removed forced install (defaults now), removed double-dash from cli 07bf018 [Brennon York] Updated to specifically handle pulling down the correct scala version f914dea [Brennon York] Beginning final portions of localized scala home 69c4e44 [Brennon York] working linux and osx installers for purely local mvn build 4a1609c [Brennon York] finalizing working linux install for maven to local ./build/apache-maven folder cbfcc68 [Brennon York] Changed the default sbt/sbt to build/sbt and added a build/mvn which will automatically download, install, and execute maven with zinc for easier build capability --- .gitignore | 7 +- build/mvn | 132 +++++++++++++++++++++++ build/sbt | 111 +++++++++++++++++++ {sbt => build}/sbt-launch-lib.bash | 6 +- dev/create-release/create-release.sh | 10 +- dev/mima | 8 +- dev/run-tests | 24 ++--- dev/scalastyle | 4 +- docs/README.md | 6 +- docs/_plugins/copy_api_dirs.rb | 4 +- docs/building-spark.md | 45 +++++--- docs/hadoop-third-party-distributions.md | 10 +- extras/java8-tests/README.md | 6 +- python/pyspark/sql.py | 2 +- sbt/sbt | 117 ++------------------ sql/README.md | 4 +- 16 files changed, 330 insertions(+), 166 deletions(-) create mode 100755 build/mvn create mode 100755 build/sbt rename {sbt => build}/sbt-launch-lib.bash (96%) diff --git a/.gitignore b/.gitignore index 20095dd97343e..9757054a50f9e 100644 --- a/.gitignore +++ b/.gitignore @@ -8,16 +8,19 @@ *.pyc .idea/ .idea_modules/ -sbt/*.jar +build/*.jar .settings .cache +cache .generated-mima* -/build/ work/ out/ .DS_Store third_party/libmesos.so third_party/libmesos.dylib +build/apache-maven* +build/zinc* +build/scala* conf/java-opts conf/*.sh conf/*.cmd diff --git a/build/mvn b/build/mvn new file mode 100755 index 0000000000000..dde486a8ac605 --- /dev/null +++ b/build/mvn @@ -0,0 +1,132 @@ +#!/usr/bin/env bash + +# Determine the current working directory +_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )" +# Preserve the calling directory +_CALLING_DIR="$(pwd)" + +# Installs any application tarball given a URL, the expected tarball name, +# and, optionally, a checkable binary path to determine if the binary has +# already been installed +## Arg1 - URL +## Arg2 - Tarball Name +## Arg3 - Checkable Binary +install_app() { + local remote_tarball="$1/$2" + local local_tarball="${_DIR}/$2" + local binary="${_DIR}/$3" + + # setup `curl` and `wget` silent options if we're running on Jenkins + local curl_opts="" + local wget_opts="" + if [ -n "$AMPLAB_JENKINS" ]; then + curl_opts="-s" + wget_opts="--quiet" + else + curl_opts="--progress-bar" + wget_opts="--progress=bar:force" + fi + + if [ -z "$3" -o ! -f "$binary" ]; then + # check if we already have the tarball + # check if we have curl installed + # download application + [ ! -f "${local_tarball}" ] && [ -n "`which curl 2>/dev/null`" ] && \ + echo "exec: curl ${curl_opts} ${remote_tarball}" && \ + curl ${curl_opts} "${remote_tarball}" > "${local_tarball}" + # if the file still doesn't exist, lets try `wget` and cross our fingers + [ ! -f "${local_tarball}" ] && [ -n "`which wget 2>/dev/null`" ] && \ + echo "exec: wget ${wget_opts} ${remote_tarball}" && \ + wget ${wget_opts} -O "${local_tarball}" "${remote_tarball}" + # if both were unsuccessful, exit + [ ! -f "${local_tarball}" ] && \ + echo -n "ERROR: Cannot download $2 with cURL or wget; " && \ + echo "please install manually and try again." && \ + exit 2 + cd "${_DIR}" && tar -xzf "$2" + rm -rf "$local_tarball" + fi +} + +# Install maven under the build/ folder +install_mvn() { + install_app \ + "http://apache.claz.org/maven/maven-3/3.2.3/binaries" \ + "apache-maven-3.2.3-bin.tar.gz" \ + "apache-maven-3.2.3/bin/mvn" + MVN_BIN="${_DIR}/apache-maven-3.2.3/bin/mvn" +} + +# Install zinc under the build/ folder +install_zinc() { + local zinc_path="zinc-0.3.5.3/bin/zinc" + [ ! -f "${zinc_path}" ] && ZINC_INSTALL_FLAG=1 + install_app \ + "http://downloads.typesafe.com/zinc/0.3.5.3" \ + "zinc-0.3.5.3.tgz" \ + "${zinc_path}" + ZINC_BIN="${_DIR}/${zinc_path}" +} + +# Determine the Scala version from the root pom.xml file, set the Scala URL, +# and, with that, download the specific version of Scala necessary under +# the build/ folder +install_scala() { + # determine the Scala version used in Spark + local scala_version=`grep "scala.version" "${_DIR}/../pom.xml" | \ + head -1 | cut -f2 -d'>' | cut -f1 -d'<'` + local scala_bin="${_DIR}/scala-${scala_version}/bin/scala" + + install_app \ + "http://downloads.typesafe.com/scala/${scala_version}" \ + "scala-${scala_version}.tgz" \ + "scala-${scala_version}/bin/scala" + + SCALA_COMPILER="$(cd "$(dirname ${scala_bin})/../lib" && pwd)/scala-compiler.jar" + SCALA_LIBRARY="$(cd "$(dirname ${scala_bin})/../lib" && pwd)/scala-library.jar" +} + +# Determines if a given application is already installed. If not, will attempt +# to install +## Arg1 - application name +## Arg2 - Alternate path to local install under build/ dir +check_and_install_app() { + # create the local environment variable in uppercase + local app_bin="`echo $1 | awk '{print toupper(\$0)}'`_BIN" + # some black magic to set the generated app variable (i.e. MVN_BIN) into the + # environment + eval "${app_bin}=`which $1 2>/dev/null`" + + if [ -z "`which $1 2>/dev/null`" ]; then + install_$1 + fi +} + +# Setup healthy defaults for the Zinc port if none were provided from +# the environment +ZINC_PORT=${ZINC_PORT:-"3030"} + +# Check and install all applications necessary to build Spark +check_and_install_app "mvn" + +# Install the proper version of Scala and Zinc for the build +install_zinc +install_scala + +# Reset the current working directory +cd "${_CALLING_DIR}" + +# Now that zinc is ensured to be installed, check its status and, if its +# not running or just installed, start it +if [ -n "${ZINC_INSTALL_FLAG}" -o -z "`${ZINC_BIN} -status`" ]; then + ${ZINC_BIN} -shutdown + ${ZINC_BIN} -start -port ${ZINC_PORT} \ + -scala-compiler "${SCALA_COMPILER}" \ + -scala-library "${SCALA_LIBRARY}" &>/dev/null +fi + +# Set any `mvn` options if not already present +export MAVEN_OPTS=${MAVEN_OPTS:-"-Xmx2g -XX:MaxPermSize=512M -XX:ReservedCodeCacheSize=512m"} + +# Last, call the `mvn` command as usual +${MVN_BIN} "$@" diff --git a/build/sbt b/build/sbt new file mode 100755 index 0000000000000..0a251d97db95c --- /dev/null +++ b/build/sbt @@ -0,0 +1,111 @@ +#!/usr/bin/env bash + +# When creating new tests for Spark SQL Hive, the HADOOP_CLASSPATH must contain the hive jars so +# that we can run Hive to generate the golden answer. This is not required for normal development +# or testing. +for i in "$HIVE_HOME"/lib/* +do HADOOP_CLASSPATH="$HADOOP_CLASSPATH:$i" +done +export HADOOP_CLASSPATH + +realpath () { +( + TARGET_FILE="$1" + + cd "$(dirname "$TARGET_FILE")" + TARGET_FILE="$(basename "$TARGET_FILE")" + + COUNT=0 + while [ -L "$TARGET_FILE" -a $COUNT -lt 100 ] + do + TARGET_FILE="$(readlink "$TARGET_FILE")" + cd $(dirname "$TARGET_FILE") + TARGET_FILE="$(basename $TARGET_FILE)" + COUNT=$(($COUNT + 1)) + done + + echo "$(pwd -P)/"$TARGET_FILE"" +) +} + +. "$(dirname "$(realpath "$0")")"/sbt-launch-lib.bash + + +declare -r noshare_opts="-Dsbt.global.base=project/.sbtboot -Dsbt.boot.directory=project/.boot -Dsbt.ivy.home=project/.ivy" +declare -r sbt_opts_file=".sbtopts" +declare -r etc_sbt_opts_file="/etc/sbt/sbtopts" + +usage() { + cat < path to global settings/plugins directory (default: ~/.sbt) + -sbt-boot path to shared boot directory (default: ~/.sbt/boot in 0.11 series) + -ivy path to local Ivy repository (default: ~/.ivy2) + -mem set memory options (default: $sbt_mem, which is $(get_mem_opts $sbt_mem)) + -no-share use all local caches; no sharing + -no-global uses global caches, but does not use global ~/.sbt directory. + -jvm-debug Turn on JVM debugging, open at the given port. + -batch Disable interactive mode + + # sbt version (default: from project/build.properties if present, else latest release) + -sbt-version use the specified version of sbt + -sbt-jar use the specified jar as the sbt launcher + -sbt-rc use an RC version of sbt + -sbt-snapshot use a snapshot version of sbt + + # java version (default: java from PATH, currently $(java -version 2>&1 | grep version)) + -java-home alternate JAVA_HOME + + # jvm options and output control + JAVA_OPTS environment variable, if unset uses "$java_opts" + SBT_OPTS environment variable, if unset uses "$default_sbt_opts" + .sbtopts if this file exists in the current directory, it is + prepended to the runner args + /etc/sbt/sbtopts if this file exists, it is prepended to the runner args + -Dkey=val pass -Dkey=val directly to the java runtime + -J-X pass option -X directly to the java runtime + (-J is stripped) + -S-X add -X to sbt's scalacOptions (-S is stripped) + -PmavenProfiles Enable a maven profile for the build. + +In the case of duplicated or conflicting options, the order above +shows precedence: JAVA_OPTS lowest, command line options highest. +EOM +} + +process_my_args () { + while [[ $# -gt 0 ]]; do + case "$1" in + -no-colors) addJava "-Dsbt.log.noformat=true" && shift ;; + -no-share) addJava "$noshare_opts" && shift ;; + -no-global) addJava "-Dsbt.global.base=$(pwd)/project/.sbtboot" && shift ;; + -sbt-boot) require_arg path "$1" "$2" && addJava "-Dsbt.boot.directory=$2" && shift 2 ;; + -sbt-dir) require_arg path "$1" "$2" && addJava "-Dsbt.global.base=$2" && shift 2 ;; + -debug-inc) addJava "-Dxsbt.inc.debug=true" && shift ;; + -batch) exec &1 \ | grep -e "^java version" --max-count=1 \ | sed "s/java version \"\(.*\)\.\(.*\)\.\(.*\)\"/\1\2/" ) - + if [ "$JAVA_VERSION" -lt 18 ]; then echo "[warn] Java 8 tests will not run because JDK version is < 1.8." fi @@ -79,7 +79,7 @@ export SBT_MAVEN_PROFILES_ARGS="$SBT_MAVEN_PROFILES_ARGS -Pkinesis-asl" # Partial solution for SPARK-1455. if [ -n "$AMPLAB_JENKINS" ]; then git fetch origin master:master - + sql_diffs=$( git diff --name-only master \ | grep -e "^sql/" -e "^bin/spark-sql" -e "^sbin/start-thriftserver.sh" @@ -93,7 +93,7 @@ if [ -n "$AMPLAB_JENKINS" ]; then if [ -n "$sql_diffs" ]; then echo "[info] Detected changes in SQL. Will run Hive test suite." _RUN_SQL_TESTS=true - + if [ -z "$non_sql_diffs" ]; then echo "[info] Detected no changes except in SQL. Will only run SQL tests." _SQL_TESTS_ONLY=true @@ -151,7 +151,7 @@ CURRENT_BLOCK=$BLOCK_BUILD HIVE_12_BUILD_ARGS="$SBT_MAVEN_PROFILES_ARGS -Phive -Phive-thriftserver -Phive-0.12.0" echo "[info] Compile with Hive 0.12.0" echo -e "q\n" \ - | sbt/sbt $HIVE_12_BUILD_ARGS clean hive/compile hive-thriftserver/compile \ + | build/sbt $HIVE_12_BUILD_ARGS clean hive/compile hive-thriftserver/compile \ | grep -v -e "info.*Resolving" -e "warn.*Merging" -e "info.*Including" # Then build with default Hive version (0.13.1) because tests are based on this version @@ -160,7 +160,7 @@ CURRENT_BLOCK=$BLOCK_BUILD echo "[info] Building Spark with these arguments: $SBT_MAVEN_PROFILES_ARGS"\ " -Phive -Phive-thriftserver" echo -e "q\n" \ - | sbt/sbt $SBT_MAVEN_PROFILES_ARGS -Phive -Phive-thriftserver package assembly/assembly \ + | build/sbt $SBT_MAVEN_PROFILES_ARGS -Phive -Phive-thriftserver package assembly/assembly \ | grep -v -e "info.*Resolving" -e "warn.*Merging" -e "info.*Including" } @@ -177,7 +177,7 @@ CURRENT_BLOCK=$BLOCK_SPARK_UNIT_TESTS if [ -n "$_RUN_SQL_TESTS" ]; then SBT_MAVEN_PROFILES_ARGS="$SBT_MAVEN_PROFILES_ARGS -Phive -Phive-thriftserver" fi - + if [ -n "$_SQL_TESTS_ONLY" ]; then # This must be an array of individual arguments. Otherwise, having one long string # will be interpreted as a single test, which doesn't work. @@ -185,19 +185,19 @@ CURRENT_BLOCK=$BLOCK_SPARK_UNIT_TESTS else SBT_MAVEN_TEST_ARGS=("test") fi - + echo "[info] Running Spark tests with these arguments: $SBT_MAVEN_PROFILES_ARGS ${SBT_MAVEN_TEST_ARGS[@]}" - + # NOTE: echo "q" is needed because sbt on encountering a build file with failure # (either resolution or compilation) prompts the user for input either q, r, etc # to quit or retry. This echo is there to make it not block. - # NOTE: Do not quote $SBT_MAVEN_PROFILES_ARGS or else it will be interpreted as a + # NOTE: Do not quote $SBT_MAVEN_PROFILES_ARGS or else it will be interpreted as a # single argument! # "${SBT_MAVEN_TEST_ARGS[@]}" is cool because it's an array. # QUESTION: Why doesn't 'yes "q"' work? # QUESTION: Why doesn't 'grep -v -e "^\[info\] Resolving"' work? echo -e "q\n" \ - | sbt/sbt $SBT_MAVEN_PROFILES_ARGS "${SBT_MAVEN_TEST_ARGS[@]}" \ + | build/sbt $SBT_MAVEN_PROFILES_ARGS "${SBT_MAVEN_TEST_ARGS[@]}" \ | grep -v -e "info.*Resolving" -e "warn.*Merging" -e "info.*Including" } diff --git a/dev/scalastyle b/dev/scalastyle index 3a4df6e4bf1bc..86919227ed1ab 100755 --- a/dev/scalastyle +++ b/dev/scalastyle @@ -17,9 +17,9 @@ # limitations under the License. # -echo -e "q\n" | sbt/sbt -Phive -Phive-thriftserver scalastyle > scalastyle.txt +echo -e "q\n" | build/sbt -Phive -Phive-thriftserver scalastyle > scalastyle.txt # Check style with YARN built too -echo -e "q\n" | sbt/sbt -Pyarn -Phadoop-2.2 -Dhadoop.version=2.2.0 scalastyle \ +echo -e "q\n" | build/sbt -Pyarn -Phadoop-2.2 -Dhadoop.version=2.2.0 scalastyle \ >> scalastyle.txt ERRORS=$(cat scalastyle.txt | awk '{if($1~/error/)print}') diff --git a/docs/README.md b/docs/README.md index 119484038083f..8a54724c4beae 100644 --- a/docs/README.md +++ b/docs/README.md @@ -21,7 +21,7 @@ read those text files directly if you want. Start with index.md. The markdown code can be compiled to HTML using the [Jekyll tool](http://jekyllrb.com). `Jekyll` and a few dependencies must be installed for this to work. We recommend -installing via the Ruby Gem dependency manager. Since the exact HTML output +installing via the Ruby Gem dependency manager. Since the exact HTML output varies between versions of Jekyll and its dependencies, we list specific versions here in some cases: @@ -60,7 +60,7 @@ We use Sphinx to generate Python API docs, so you will need to install it by run ## API Docs (Scaladoc and Sphinx) -You can build just the Spark scaladoc by running `sbt/sbt doc` from the SPARK_PROJECT_ROOT directory. +You can build just the Spark scaladoc by running `build/sbt doc` from the SPARK_PROJECT_ROOT directory. Similarly, you can build just the PySpark docs by running `make html` from the SPARK_PROJECT_ROOT/python/docs directory. Documentation is only generated for classes that are listed as @@ -68,7 +68,7 @@ public in `__init__.py`. When you run `jekyll` in the `docs` directory, it will also copy over the scaladoc for the various Spark subprojects into the `docs` directory (and then also into the `_site` directory). We use a -jekyll plugin to run `sbt/sbt doc` before building the site so if you haven't run it (recently) it +jekyll plugin to run `build/sbt doc` before building the site so if you haven't run it (recently) it may take some time as it generates all of the scaladoc. The jekyll plugin also generates the PySpark docs [Sphinx](http://sphinx-doc.org/). diff --git a/docs/_plugins/copy_api_dirs.rb b/docs/_plugins/copy_api_dirs.rb index 4566a2fff562b..3c626a0b7f54b 100644 --- a/docs/_plugins/copy_api_dirs.rb +++ b/docs/_plugins/copy_api_dirs.rb @@ -25,8 +25,8 @@ curr_dir = pwd cd("..") - puts "Running 'sbt/sbt -Pkinesis-asl compile unidoc' from " + pwd + "; this may take a few minutes..." - puts `sbt/sbt -Pkinesis-asl compile unidoc` + puts "Running 'build/sbt -Pkinesis-asl compile unidoc' from " + pwd + "; this may take a few minutes..." + puts `build/sbt -Pkinesis-asl compile unidoc` puts "Moving back into docs dir." cd("docs") diff --git a/docs/building-spark.md b/docs/building-spark.md index dab3d2aef497e..c1bcd91b5b853 100644 --- a/docs/building-spark.md +++ b/docs/building-spark.md @@ -9,6 +9,15 @@ redirect_from: "building-with-maven.html" Building Spark using Maven requires Maven 3.0.4 or newer and Java 6+. +# Building with `build/mvn` + +Spark now comes packaged with a self-contained Maven installation to ease building and deployment of Spark from source located under the `build/` directory. This script will automatically download and setup all necessary build requirements ([Maven](https://maven.apache.org/), [Scala](http://www.scala-lang.org/), and [Zinc](https://github.com/typesafehub/zinc)) locally within the `build/` directory itself. It honors any `mvn` binary if present already, however, will pull down its own copy of Scala and Zinc regardless to ensure proper version requirements are met. `build/mvn` execution acts as a pass through to the `mvn` call allowing easy transition from previous build methods. As an example, one can build a version of Spark as follows: + +{% highlight bash %} +build/mvn -Pyarn -Phadoop-2.4 -Dhadoop.version=2.4.0 -DskipTests clean package +{% endhighlight %} + +Other build examples can be found below. # Setting up Maven's Memory Usage @@ -28,7 +37,9 @@ If you don't run this, you may see errors like the following: You can fix this by setting the `MAVEN_OPTS` variable as discussed before. -**Note:** *For Java 8 and above this step is not required.* +**Note:** +* *For Java 8 and above this step is not required.* +* *If using `build/mvn` and `MAVEN_OPTS` were not already set, the script will automate this for you.* # Specifying the Hadoop Version @@ -84,7 +95,7 @@ mvn -Pyarn -Phadoop-2.3 -Dhadoop.version=2.3.0 -Dyarn.version=2.2.0 -DskipTests # Building With Hive and JDBC Support To enable Hive integration for Spark SQL along with its JDBC server and CLI, add the `-Phive` and `Phive-thriftserver` profiles to your existing build options. -By default Spark will build with Hive 0.13.1 bindings. You can also build for +By default Spark will build with Hive 0.13.1 bindings. You can also build for Hive 0.12.0 using the `-Phive-0.12.0` profile. {% highlight bash %} # Apache Hadoop 2.4.X with Hive 13 support @@ -106,7 +117,7 @@ supported in Scala 2.11 builds. # Spark Tests in Maven -Tests are run by default via the [ScalaTest Maven plugin](http://www.scalatest.org/user_guide/using_the_scalatest_maven_plugin). +Tests are run by default via the [ScalaTest Maven plugin](http://www.scalatest.org/user_guide/using_the_scalatest_maven_plugin). Some of the tests require Spark to be packaged first, so always run `mvn package` with `-DskipTests` the first time. The following is an example of a correct (build, test) sequence: @@ -124,7 +135,7 @@ We use the scala-maven-plugin which supports incremental and continuous compilat mvn scala:cc -should run continuous compilation (i.e. wait for changes). However, this has not been tested +should run continuous compilation (i.e. wait for changes). However, this has not been tested extensively. A couple of gotchas to note: * it only scans the paths `src/main` and `src/test` (see [docs](http://scala-tools.org/mvnsites/maven-scala-plugin/usage_cc.html)), so it will only work @@ -157,9 +168,9 @@ The debian package can then be found under assembly/target. We added the short c Running only Java 8 tests and nothing else. mvn install -DskipTests -Pjava8-tests - -Java 8 tests are run when `-Pjava8-tests` profile is enabled, they will run in spite of `-DskipTests`. -For these tests to run your system must have a JDK 8 installation. + +Java 8 tests are run when `-Pjava8-tests` profile is enabled, they will run in spite of `-DskipTests`. +For these tests to run your system must have a JDK 8 installation. If you have JDK 8 installed but it is not the system default, you can set JAVA_HOME to point to JDK 8 before running the tests. # Building for PySpark on YARN @@ -171,7 +182,7 @@ then ship it over to the cluster. We are investigating the exact cause for this. # Packaging without Hadoop Dependencies for YARN -The assembly jar produced by `mvn package` will, by default, include all of Spark's dependencies, including Hadoop and some of its ecosystem projects. On YARN deployments, this causes multiple versions of these to appear on executor classpaths: the version packaged in the Spark assembly and the version on each node, included with yarn.application.classpath. The `hadoop-provided` profile builds the assembly without including Hadoop-ecosystem projects, like ZooKeeper and Hadoop itself. +The assembly jar produced by `mvn package` will, by default, include all of Spark's dependencies, including Hadoop and some of its ecosystem projects. On YARN deployments, this causes multiple versions of these to appear on executor classpaths: the version packaged in the Spark assembly and the version on each node, included with yarn.application.classpath. The `hadoop-provided` profile builds the assembly without including Hadoop-ecosystem projects, like ZooKeeper and Hadoop itself. # Building with SBT @@ -182,22 +193,22 @@ compilation. More advanced developers may wish to use SBT. The SBT build is derived from the Maven POM files, and so the same Maven profiles and variables can be set to control the SBT build. For example: - sbt/sbt -Pyarn -Phadoop-2.3 assembly + build/sbt -Pyarn -Phadoop-2.3 assembly # Testing with SBT -Some of the tests require Spark to be packaged first, so always run `sbt/sbt assembly` the first time. The following is an example of a correct (build, test) sequence: +Some of the tests require Spark to be packaged first, so always run `build/sbt assembly` the first time. The following is an example of a correct (build, test) sequence: - sbt/sbt -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver assembly - sbt/sbt -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver test + build/sbt -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver assembly + build/sbt -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver test To run only a specific test suite as follows: - sbt/sbt -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver "test-only org.apache.spark.repl.ReplSuite" + build/sbt -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver "test-only org.apache.spark.repl.ReplSuite" To run test suites of a specific sub project as follows: - sbt/sbt -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver core/test + build/sbt -Pyarn -Phadoop-2.3 -Phive -Phive-thriftserver core/test # Speeding up Compilation with Zinc @@ -206,3 +217,9 @@ compiler. When run locally as a background process, it speeds up builds of Scala like Spark. Developers who regularly recompile Spark with Maven will be the most interested in Zinc. The project site gives instructions for building and running `zinc`; OS X users can install it using `brew install zinc`. + +If using the `build/mvn` package `zinc` will automatically be downloaded and leveraged for all +builds. This process will auto-start after the first time `build/mvn` is called and bind to port +3030 unless the `ZINC_PORT` environment variable is set. The `zinc` process can subsequently be +shut down at any time by running `build/zinc-/bin/zinc -shutdown` and will automatically +restart whenever `build/mvn` is called. diff --git a/docs/hadoop-third-party-distributions.md b/docs/hadoop-third-party-distributions.md index dd73e9dc54440..87dcc58feb494 100644 --- a/docs/hadoop-third-party-distributions.md +++ b/docs/hadoop-third-party-distributions.md @@ -18,7 +18,7 @@ see the guide on [building with maven](building-spark.html#specifying-the-hadoop The table below lists the corresponding `hadoop.version` code for each CDH/HDP release. Note that some Hadoop releases are binary compatible across client versions. This means the pre-built Spark -distribution may "just work" without you needing to compile. That said, we recommend compiling with +distribution may "just work" without you needing to compile. That said, we recommend compiling with the _exact_ Hadoop version you are running to avoid any compatibility errors. @@ -50,7 +50,7 @@ the _exact_ Hadoop version you are running to avoid any compatibility errors. In SBT, the equivalent can be achieved by setting the the `hadoop.version` property: - sbt/sbt -Dhadoop.version=1.0.4 assembly + build/sbt -Dhadoop.version=1.0.4 assembly # Linking Applications to the Hadoop Version @@ -98,11 +98,11 @@ Spark can run in a variety of deployment modes: * Using dedicated set of Spark nodes in your cluster. These nodes should be co-located with your Hadoop installation. -* Running on the same nodes as an existing Hadoop installation, with a fixed amount memory and +* Running on the same nodes as an existing Hadoop installation, with a fixed amount memory and cores dedicated to Spark on each node. * Run Spark alongside Hadoop using a cluster resource manager, such as YARN or Mesos. -These options are identical for those using CDH and HDP. +These options are identical for those using CDH and HDP. # Inheriting Cluster Configuration @@ -116,5 +116,5 @@ The location of these configuration files varies across CDH and HDP versions, bu a common location is inside of `/etc/hadoop/conf`. Some tools, such as Cloudera Manager, create configurations on-the-fly, but offer a mechanisms to download copies of them. -To make these files visible to Spark, set `HADOOP_CONF_DIR` in `$SPARK_HOME/spark-env.sh` +To make these files visible to Spark, set `HADOOP_CONF_DIR` in `$SPARK_HOME/spark-env.sh` to a location containing the configuration files. diff --git a/extras/java8-tests/README.md b/extras/java8-tests/README.md index e95b73ac7702a..dc9e87f2eeb92 100644 --- a/extras/java8-tests/README.md +++ b/extras/java8-tests/README.md @@ -8,7 +8,7 @@ to your Java location. The set-up depends a bit on the build system: `-java-home` to the sbt launch script. If a Java 8 JDK is detected sbt will automatically include the Java 8 test project. - `$ JAVA_HOME=/opt/jdk1.8.0/ sbt/sbt clean "test-only org.apache.spark.Java8APISuite"` + `$ JAVA_HOME=/opt/jdk1.8.0/ build/sbt clean "test-only org.apache.spark.Java8APISuite"` * For Maven users, @@ -19,6 +19,6 @@ to your Java location. The set-up depends a bit on the build system: `$ JAVA_HOME=/opt/jdk1.8.0/ mvn clean install -DskipTests` `$ JAVA_HOME=/opt/jdk1.8.0/ mvn test -Pjava8-tests -DwildcardSuites=org.apache.spark.Java8APISuite` - Note that the above command can only be run from project root directory since this module - depends on core and the test-jars of core and streaming. This means an install step is + Note that the above command can only be run from project root directory since this module + depends on core and the test-jars of core and streaming. This means an install step is required to make the test dependencies visible to the Java 8 sub-project. diff --git a/python/pyspark/sql.py b/python/pyspark/sql.py index 9807a84a66f11..0e8b398fc6b97 100644 --- a/python/pyspark/sql.py +++ b/python/pyspark/sql.py @@ -1671,7 +1671,7 @@ def _ssql_ctx(self): except Py4JError as e: raise Exception("You must build Spark with Hive. " "Export 'SPARK_HIVE=true' and run " - "sbt/sbt assembly", e) + "build/sbt assembly", e) def _get_hive_ctx(self): return self._jvm.HiveContext(self._jsc.sc()) diff --git a/sbt/sbt b/sbt/sbt index 0a251d97db95c..6f3e5e08ed27a 100755 --- a/sbt/sbt +++ b/sbt/sbt @@ -1,111 +1,12 @@ -#!/usr/bin/env bash +#!/bin/bash -# When creating new tests for Spark SQL Hive, the HADOOP_CLASSPATH must contain the hive jars so -# that we can run Hive to generate the golden answer. This is not required for normal development -# or testing. -for i in "$HIVE_HOME"/lib/* -do HADOOP_CLASSPATH="$HADOOP_CLASSPATH:$i" -done -export HADOOP_CLASSPATH +# Determine the current working directory +_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )" -realpath () { -( - TARGET_FILE="$1" +echo "NOTE: The sbt/sbt script has been relocated to build/sbt." >&2 +echo " Please update references to point to the new location." >&2 +echo "" >&2 +echo " Invoking 'build/sbt $@' now ..." >&2 +echo "" >&2 - cd "$(dirname "$TARGET_FILE")" - TARGET_FILE="$(basename "$TARGET_FILE")" - - COUNT=0 - while [ -L "$TARGET_FILE" -a $COUNT -lt 100 ] - do - TARGET_FILE="$(readlink "$TARGET_FILE")" - cd $(dirname "$TARGET_FILE") - TARGET_FILE="$(basename $TARGET_FILE)" - COUNT=$(($COUNT + 1)) - done - - echo "$(pwd -P)/"$TARGET_FILE"" -) -} - -. "$(dirname "$(realpath "$0")")"/sbt-launch-lib.bash - - -declare -r noshare_opts="-Dsbt.global.base=project/.sbtboot -Dsbt.boot.directory=project/.boot -Dsbt.ivy.home=project/.ivy" -declare -r sbt_opts_file=".sbtopts" -declare -r etc_sbt_opts_file="/etc/sbt/sbtopts" - -usage() { - cat < path to global settings/plugins directory (default: ~/.sbt) - -sbt-boot path to shared boot directory (default: ~/.sbt/boot in 0.11 series) - -ivy path to local Ivy repository (default: ~/.ivy2) - -mem set memory options (default: $sbt_mem, which is $(get_mem_opts $sbt_mem)) - -no-share use all local caches; no sharing - -no-global uses global caches, but does not use global ~/.sbt directory. - -jvm-debug Turn on JVM debugging, open at the given port. - -batch Disable interactive mode - - # sbt version (default: from project/build.properties if present, else latest release) - -sbt-version use the specified version of sbt - -sbt-jar use the specified jar as the sbt launcher - -sbt-rc use an RC version of sbt - -sbt-snapshot use a snapshot version of sbt - - # java version (default: java from PATH, currently $(java -version 2>&1 | grep version)) - -java-home alternate JAVA_HOME - - # jvm options and output control - JAVA_OPTS environment variable, if unset uses "$java_opts" - SBT_OPTS environment variable, if unset uses "$default_sbt_opts" - .sbtopts if this file exists in the current directory, it is - prepended to the runner args - /etc/sbt/sbtopts if this file exists, it is prepended to the runner args - -Dkey=val pass -Dkey=val directly to the java runtime - -J-X pass option -X directly to the java runtime - (-J is stripped) - -S-X add -X to sbt's scalacOptions (-S is stripped) - -PmavenProfiles Enable a maven profile for the build. - -In the case of duplicated or conflicting options, the order above -shows precedence: JAVA_OPTS lowest, command line options highest. -EOM -} - -process_my_args () { - while [[ $# -gt 0 ]]; do - case "$1" in - -no-colors) addJava "-Dsbt.log.noformat=true" && shift ;; - -no-share) addJava "$noshare_opts" && shift ;; - -no-global) addJava "-Dsbt.global.base=$(pwd)/project/.sbtboot" && shift ;; - -sbt-boot) require_arg path "$1" "$2" && addJava "-Dsbt.boot.directory=$2" && shift 2 ;; - -sbt-dir) require_arg path "$1" "$2" && addJava "-Dsbt.global.base=$2" && shift 2 ;; - -debug-inc) addJava "-Dxsbt.inc.debug=true" && shift ;; - -batch) exec Date: Mon, 29 Dec 2014 08:20:30 -0600 Subject: [PATCH 113/320] [SPARK-4966][YARN]The MemoryOverhead value is setted not correctly Author: meiyoula <1039320815@qq.com> Closes #3797 from XuTingjun/MemoryOverhead and squashes the following commits: 5a780fc [meiyoula] Update ClientArguments.scala --- .../scala/org/apache/spark/deploy/yarn/ClientArguments.scala | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala index 7305249f80e83..39f1021c9d942 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala @@ -39,6 +39,8 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf) var appName: String = "Spark" var priority = 0 + parseArgs(args.toList) + // Additional memory to allocate to containers // For now, use driver's memory overhead as our AM container's memory overhead val amMemoryOverhead = sparkConf.getInt("spark.yarn.driver.memoryOverhead", @@ -50,7 +52,6 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf) private val isDynamicAllocationEnabled = sparkConf.getBoolean("spark.dynamicAllocation.enabled", false) - parseArgs(args.toList) loadEnvironmentArgs() validateArgs() From 6645e52580747990321e22340ae742f26d2f2504 Mon Sep 17 00:00:00 2001 From: wangxiaojing Date: Mon, 29 Dec 2014 10:45:14 -0800 Subject: [PATCH 114/320] [SPARK-4982][DOC] `spark.ui.retainedJobs` description is wrong in Spark UI configuration guide Author: wangxiaojing Closes #3818 from wangxiaojing/SPARK-4982 and squashes the following commits: fe2ad5f [wangxiaojing] change stages to jobs --- docs/configuration.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/configuration.md b/docs/configuration.md index 2cc013c47fdbb..fa9d311f85068 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -452,7 +452,7 @@ Apart from these, the following properties are also available, and may be useful From 4cef05e1c1d420af89164d6f4fabbad090542f1b Mon Sep 17 00:00:00 2001 From: Kousuke Saruta Date: Mon, 29 Dec 2014 10:48:53 -0800 Subject: [PATCH 115/320] Adde LICENSE Header to build/mvn, build/sbt and sbt/sbt Recently, build/mvn and build/sbt are added, and sbt/sbt is changed but there are no license headers. Should we add license headers to the scripts right? If it's not right, please let me correct. This PR doesn't affect behavior of Spark, I don't file in JIRA. Author: Kousuke Saruta Closes #3817 from sarutak/add-license-header and squashes the following commits: 1abc972 [Kousuke Saruta] Added LICENSE Header --- build/mvn | 17 +++++++++++++++++ build/sbt | 17 +++++++++++++++++ sbt/sbt | 19 ++++++++++++++++++- 3 files changed, 52 insertions(+), 1 deletion(-) diff --git a/build/mvn b/build/mvn index dde486a8ac605..43471f83e904c 100755 --- a/build/mvn +++ b/build/mvn @@ -1,5 +1,22 @@ #!/usr/bin/env bash +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + # Determine the current working directory _DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )" # Preserve the calling directory diff --git a/build/sbt b/build/sbt index 0a251d97db95c..28ebb64f7197c 100755 --- a/build/sbt +++ b/build/sbt @@ -1,5 +1,22 @@ #!/usr/bin/env bash +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + # When creating new tests for Spark SQL Hive, the HADOOP_CLASSPATH must contain the hive jars so # that we can run Hive to generate the golden answer. This is not required for normal development # or testing. diff --git a/sbt/sbt b/sbt/sbt index 6f3e5e08ed27a..41438251f681e 100755 --- a/sbt/sbt +++ b/sbt/sbt @@ -1,4 +1,21 @@ -#!/bin/bash +#!/usr/bin/env bash + +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# # Determine the current working directory _DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )" From 815de54002f9c1cfedc398e95896fa207b4a5305 Mon Sep 17 00:00:00 2001 From: YanTangZhai Date: Mon, 29 Dec 2014 11:30:54 -0800 Subject: [PATCH 116/320] [SPARK-4946] [CORE] Using AkkaUtils.askWithReply in MapOutputTracker.askTracker to reduce the chance of the communicating problem Using AkkaUtils.askWithReply in MapOutputTracker.askTracker to reduce the chance of the communicating problem Author: YanTangZhai Author: yantangzhai Closes #3785 from YanTangZhai/SPARK-4946 and squashes the following commits: 9ca6541 [yantangzhai] [SPARK-4946] [CORE] Using AkkaUtils.askWithReply in MapOutputTracker.askTracker to reduce the chance of the communicating problem e4c2c0a [YanTangZhai] Merge pull request #15 from apache/master 718afeb [YanTangZhai] Merge pull request #12 from apache/master 6e643f8 [YanTangZhai] Merge pull request #11 from apache/master e249846 [YanTangZhai] Merge pull request #10 from apache/master d26d982 [YanTangZhai] Merge pull request #9 from apache/master 76d4027 [YanTangZhai] Merge pull request #8 from apache/master 03b62b0 [YanTangZhai] Merge pull request #7 from apache/master 8a00106 [YanTangZhai] Merge pull request #6 from apache/master cbcba66 [YanTangZhai] Merge pull request #3 from apache/master cdef539 [YanTangZhai] Merge pull request #1 from apache/master --- core/src/main/scala/org/apache/spark/MapOutputTracker.scala | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/MapOutputTracker.scala b/core/src/main/scala/org/apache/spark/MapOutputTracker.scala index a074ab8ece1b7..6e4edc7c80d7a 100644 --- a/core/src/main/scala/org/apache/spark/MapOutputTracker.scala +++ b/core/src/main/scala/org/apache/spark/MapOutputTracker.scala @@ -76,6 +76,8 @@ private[spark] class MapOutputTrackerMasterActor(tracker: MapOutputTrackerMaster */ private[spark] abstract class MapOutputTracker(conf: SparkConf) extends Logging { private val timeout = AkkaUtils.askTimeout(conf) + private val retryAttempts = AkkaUtils.numRetries(conf) + private val retryIntervalMs = AkkaUtils.retryWaitMs(conf) /** Set to the MapOutputTrackerActor living on the driver. */ var trackerActor: ActorRef = _ @@ -108,8 +110,7 @@ private[spark] abstract class MapOutputTracker(conf: SparkConf) extends Logging */ protected def askTracker(message: Any): Any = { try { - val future = trackerActor.ask(message)(timeout) - Await.result(future, timeout) + AkkaUtils.askWithReply(message, trackerActor, retryAttempts, retryIntervalMs, timeout) } catch { case e: Exception => logError("Error communicating with MapOutputTracker", e) From 8d72341ab75a7fb138b056cfb4e21db42aca55fb Mon Sep 17 00:00:00 2001 From: Kousuke Saruta Date: Mon, 29 Dec 2014 12:05:08 -0800 Subject: [PATCH 117/320] [Minor] Fix a typo of type parameter in JavaUtils.scala In JavaUtils.scala, thare is a typo of type parameter. In addition, the type information is removed at the time of compile by erasure. This issue is really minor so I don't file in JIRA. Author: Kousuke Saruta Closes #3789 from sarutak/fix-typo-in-javautils and squashes the following commits: e20193d [Kousuke Saruta] Fixed a typo of type parameter 82bc5d9 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into fix-typo-in-javautils 99f6f63 [Kousuke Saruta] Fixed a typo of type parameter in JavaUtils.scala --- core/src/main/scala/org/apache/spark/api/java/JavaUtils.scala | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/core/src/main/scala/org/apache/spark/api/java/JavaUtils.scala b/core/src/main/scala/org/apache/spark/api/java/JavaUtils.scala index 86e94931300f8..71b26737b8c02 100644 --- a/core/src/main/scala/org/apache/spark/api/java/JavaUtils.scala +++ b/core/src/main/scala/org/apache/spark/api/java/JavaUtils.scala @@ -80,7 +80,7 @@ private[spark] object JavaUtils { prev match { case Some(k) => underlying match { - case mm: mutable.Map[a, _] => + case mm: mutable.Map[A, _] => mm remove k prev = None case _ => From 02b55de3dce9a1fef806be13e5cefa0f39ea2fcc Mon Sep 17 00:00:00 2001 From: Burak Yavuz Date: Mon, 29 Dec 2014 13:24:26 -0800 Subject: [PATCH 118/320] [SPARK-4409][MLlib] Additional Linear Algebra Utils Addition of a very limited number of local matrix manipulation and generation methods that would be helpful in the further development for algorithms on top of BlockMatrix (SPARK-3974), such as Randomized SVD, and Multi Model Training (SPARK-1486). The proposed methods for addition are: For `Matrix` - map: maps the values in the matrix with a given function. Produces a new matrix. - update: the values in the matrix are updated with a given function. Occurs in place. Factory methods for `DenseMatrix`: - *zeros: Generate a matrix consisting of zeros - *ones: Generate a matrix consisting of ones - *eye: Generate an identity matrix - *rand: Generate a matrix consisting of i.i.d. uniform random numbers - *randn: Generate a matrix consisting of i.i.d. gaussian random numbers - *diag: Generate a diagonal matrix from a supplied vector *These methods already exist in the factory methods for `Matrices`, however for cases where we require a `DenseMatrix`, you constantly have to add `.asInstanceOf[DenseMatrix]` everywhere, which makes the code "dirtier". I propose moving these functions to factory methods for `DenseMatrix` where the putput will be a `DenseMatrix` and the factory methods for `Matrices` will call these functions directly and output a generic `Matrix`. Factory methods for `SparseMatrix`: - speye: Identity matrix in sparse format. Saves a ton of memory when dimensions are large, especially in Multi Model Training, where each row requires being multiplied by a scalar. - sprand: Generate a sparse matrix with a given density consisting of i.i.d. uniform random numbers. - sprandn: Generate a sparse matrix with a given density consisting of i.i.d. gaussian random numbers. - diag: Generate a diagonal matrix from a supplied vector, but is memory efficient, because it just stores the diagonal. Again, very helpful in Multi Model Training. Factory methods for `Matrices`: - Include all the factory methods given above, but return a generic `Matrix` rather than `SparseMatrix` or `DenseMatrix`. - horzCat: Horizontally concatenate matrices to form one larger matrix. Very useful in both Multi Model Training, and for the repartitioning of BlockMatrix. - vertCat: Vertically concatenate matrices to form one larger matrix. Very useful for the repartitioning of BlockMatrix. The names for these methods were selected from MATLAB Author: Burak Yavuz Author: Xiangrui Meng Closes #3319 from brkyvz/SPARK-4409 and squashes the following commits: b0354f6 [Burak Yavuz] [SPARK-4409] Incorporated mengxr's code 04c4829 [Burak Yavuz] Merge pull request #1 from mengxr/SPARK-4409 80cfa29 [Xiangrui Meng] minor changes ecc937a [Xiangrui Meng] update sprand 4e95e24 [Xiangrui Meng] simplify fromCOO implementation 10a63a6 [Burak Yavuz] [SPARK-4409] Fourth pass of code review f62d6c7 [Burak Yavuz] [SPARK-4409] Modified genRandMatrix 3971c93 [Burak Yavuz] [SPARK-4409] Third pass of code review 75239f8 [Burak Yavuz] [SPARK-4409] Second pass of code review e4bd0c0 [Burak Yavuz] [SPARK-4409] Modified horzcat and vertcat 65c562e [Burak Yavuz] [SPARK-4409] Hopefully fixed Java Test d8be7bc [Burak Yavuz] [SPARK-4409] Organized imports 065b531 [Burak Yavuz] [SPARK-4409] First pass after code review a8120d2 [Burak Yavuz] [SPARK-4409] Finished updates to API according to SPARK-4614 f798c82 [Burak Yavuz] [SPARK-4409] Updated API according to SPARK-4614 c75f3cd [Burak Yavuz] [SPARK-4409] Added JavaAPI Tests, and fixed a couple of bugs d662f9d [Burak Yavuz] [SPARK-4409] Modified according to remote repo 83dfe37 [Burak Yavuz] [SPARK-4409] Scalastyle error fixed a14c0da [Burak Yavuz] [SPARK-4409] Initial commit to add methods --- .../apache/spark/mllib/linalg/Matrices.scala | 570 ++++++++++++++++-- .../spark/mllib/linalg/JavaMatricesSuite.java | 163 +++++ .../spark/mllib/linalg/MatricesSuite.scala | 172 +++++- .../spark/mllib/util/TestingUtils.scala | 6 +- 4 files changed, 868 insertions(+), 43 deletions(-) create mode 100644 mllib/src/test/java/org/apache/spark/mllib/linalg/JavaMatricesSuite.java diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala index 327366a1a3a82..5a7281ec6dc3c 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala @@ -17,9 +17,11 @@ package org.apache.spark.mllib.linalg -import java.util.{Random, Arrays} +import java.util.{Arrays, Random} -import breeze.linalg.{Matrix => BM, DenseMatrix => BDM, CSCMatrix => BSM} +import scala.collection.mutable.{ArrayBuilder => MArrayBuilder, HashSet => MHashSet, ArrayBuffer} + +import breeze.linalg.{CSCMatrix => BSM, DenseMatrix => BDM, Matrix => BM} /** * Trait for a local matrix. @@ -80,6 +82,16 @@ sealed trait Matrix extends Serializable { /** A human readable representation of the matrix */ override def toString: String = toBreeze.toString() + + /** Map the values of this matrix using a function. Generates a new matrix. Performs the + * function on only the backing array. For example, an operation such as addition or + * subtraction will only be performed on the non-zero values in a `SparseMatrix`. */ + private[mllib] def map(f: Double => Double): Matrix + + /** Update all the values of this matrix using the function f. Performed in-place on the + * backing array. For example, an operation such as addition or subtraction will only be + * performed on the non-zero values in a `SparseMatrix`. */ + private[mllib] def update(f: Double => Double): Matrix } /** @@ -123,6 +135,122 @@ class DenseMatrix(val numRows: Int, val numCols: Int, val values: Array[Double]) } override def copy = new DenseMatrix(numRows, numCols, values.clone()) + + private[mllib] def map(f: Double => Double) = new DenseMatrix(numRows, numCols, values.map(f)) + + private[mllib] def update(f: Double => Double): DenseMatrix = { + val len = values.length + var i = 0 + while (i < len) { + values(i) = f(values(i)) + i += 1 + } + this + } + + /** Generate a `SparseMatrix` from the given `DenseMatrix`. */ + def toSparse(): SparseMatrix = { + val spVals: MArrayBuilder[Double] = new MArrayBuilder.ofDouble + val colPtrs: Array[Int] = new Array[Int](numCols + 1) + val rowIndices: MArrayBuilder[Int] = new MArrayBuilder.ofInt + var nnz = 0 + var j = 0 + while (j < numCols) { + var i = 0 + val indStart = j * numRows + while (i < numRows) { + val v = values(indStart + i) + if (v != 0.0) { + rowIndices += i + spVals += v + nnz += 1 + } + i += 1 + } + j += 1 + colPtrs(j) = nnz + } + new SparseMatrix(numRows, numCols, colPtrs, rowIndices.result(), spVals.result()) + } +} + +/** + * Factory methods for [[org.apache.spark.mllib.linalg.DenseMatrix]]. + */ +object DenseMatrix { + + /** + * Generate a `DenseMatrix` consisting of zeros. + * @param numRows number of rows of the matrix + * @param numCols number of columns of the matrix + * @return `DenseMatrix` with size `numRows` x `numCols` and values of zeros + */ + def zeros(numRows: Int, numCols: Int): DenseMatrix = + new DenseMatrix(numRows, numCols, new Array[Double](numRows * numCols)) + + /** + * Generate a `DenseMatrix` consisting of ones. + * @param numRows number of rows of the matrix + * @param numCols number of columns of the matrix + * @return `DenseMatrix` with size `numRows` x `numCols` and values of ones + */ + def ones(numRows: Int, numCols: Int): DenseMatrix = + new DenseMatrix(numRows, numCols, Array.fill(numRows * numCols)(1.0)) + + /** + * Generate an Identity Matrix in `DenseMatrix` format. + * @param n number of rows and columns of the matrix + * @return `DenseMatrix` with size `n` x `n` and values of ones on the diagonal + */ + def eye(n: Int): DenseMatrix = { + val identity = DenseMatrix.zeros(n, n) + var i = 0 + while (i < n) { + identity.update(i, i, 1.0) + i += 1 + } + identity + } + + /** + * Generate a `DenseMatrix` consisting of i.i.d. uniform random numbers. + * @param numRows number of rows of the matrix + * @param numCols number of columns of the matrix + * @param rng a random number generator + * @return `DenseMatrix` with size `numRows` x `numCols` and values in U(0, 1) + */ + def rand(numRows: Int, numCols: Int, rng: Random): DenseMatrix = { + new DenseMatrix(numRows, numCols, Array.fill(numRows * numCols)(rng.nextDouble())) + } + + /** + * Generate a `DenseMatrix` consisting of i.i.d. gaussian random numbers. + * @param numRows number of rows of the matrix + * @param numCols number of columns of the matrix + * @param rng a random number generator + * @return `DenseMatrix` with size `numRows` x `numCols` and values in N(0, 1) + */ + def randn(numRows: Int, numCols: Int, rng: Random): DenseMatrix = { + new DenseMatrix(numRows, numCols, Array.fill(numRows * numCols)(rng.nextGaussian())) + } + + /** + * Generate a diagonal matrix in `DenseMatrix` format from the supplied values. + * @param vector a `Vector` that will form the values on the diagonal of the matrix + * @return Square `DenseMatrix` with size `values.length` x `values.length` and `values` + * on the diagonal + */ + def diag(vector: Vector): DenseMatrix = { + val n = vector.size + val matrix = DenseMatrix.zeros(n, n) + val values = vector.toArray + var i = 0 + while (i < n) { + matrix.update(i, i, values(i)) + i += 1 + } + matrix + } } /** @@ -156,6 +284,8 @@ class SparseMatrix( require(colPtrs.length == numCols + 1, "The length of the column indices should be the " + s"number of columns + 1. Currently, colPointers.length: ${colPtrs.length}, " + s"numCols: $numCols") + require(values.length == colPtrs.last, "The last value of colPtrs must equal the number of " + + s"elements. values.length: ${values.length}, colPtrs.last: ${colPtrs.last}") override def toArray: Array[Double] = { val arr = new Array[Double](numRows * numCols) @@ -188,7 +318,7 @@ class SparseMatrix( private[mllib] def update(i: Int, j: Int, v: Double): Unit = { val ind = index(i, j) - if (ind == -1){ + if (ind == -1) { throw new NoSuchElementException("The given row and column indices correspond to a zero " + "value. Only non-zero elements in Sparse Matrices can be updated.") } else { @@ -197,6 +327,192 @@ class SparseMatrix( } override def copy = new SparseMatrix(numRows, numCols, colPtrs, rowIndices, values.clone()) + + private[mllib] def map(f: Double => Double) = + new SparseMatrix(numRows, numCols, colPtrs, rowIndices, values.map(f)) + + private[mllib] def update(f: Double => Double): SparseMatrix = { + val len = values.length + var i = 0 + while (i < len) { + values(i) = f(values(i)) + i += 1 + } + this + } + + /** Generate a `DenseMatrix` from the given `SparseMatrix`. */ + def toDense(): DenseMatrix = { + new DenseMatrix(numRows, numCols, toArray) + } +} + +/** + * Factory methods for [[org.apache.spark.mllib.linalg.SparseMatrix]]. + */ +object SparseMatrix { + + /** + * Generate a `SparseMatrix` from Coordinate List (COO) format. Input must be an array of + * (i, j, value) tuples. Entries that have duplicate values of i and j are + * added together. Tuples where value is equal to zero will be omitted. + * @param numRows number of rows of the matrix + * @param numCols number of columns of the matrix + * @param entries Array of (i, j, value) tuples + * @return The corresponding `SparseMatrix` + */ + def fromCOO(numRows: Int, numCols: Int, entries: Iterable[(Int, Int, Double)]): SparseMatrix = { + val sortedEntries = entries.toSeq.sortBy(v => (v._2, v._1)) + val numEntries = sortedEntries.size + if (sortedEntries.nonEmpty) { + // Since the entries are sorted by column index, we only need to check the first and the last. + for (col <- Seq(sortedEntries.head._2, sortedEntries.last._2)) { + require(col >= 0 && col < numCols, s"Column index out of range [0, $numCols): $col.") + } + } + val colPtrs = new Array[Int](numCols + 1) + val rowIndices = MArrayBuilder.make[Int] + rowIndices.sizeHint(numEntries) + val values = MArrayBuilder.make[Double] + values.sizeHint(numEntries) + var nnz = 0 + var prevCol = 0 + var prevRow = -1 + var prevVal = 0.0 + // Append a dummy entry to include the last one at the end of the loop. + (sortedEntries.view :+ (numRows, numCols, 1.0)).foreach { case (i, j, v) => + if (v != 0) { + if (i == prevRow && j == prevCol) { + prevVal += v + } else { + if (prevVal != 0) { + require(prevRow >= 0 && prevRow < numRows, + s"Row index out of range [0, $numRows): $prevRow.") + nnz += 1 + rowIndices += prevRow + values += prevVal + } + prevRow = i + prevVal = v + while (prevCol < j) { + colPtrs(prevCol + 1) = nnz + prevCol += 1 + } + } + } + } + new SparseMatrix(numRows, numCols, colPtrs, rowIndices.result(), values.result()) + } + + /** + * Generate an Identity Matrix in `SparseMatrix` format. + * @param n number of rows and columns of the matrix + * @return `SparseMatrix` with size `n` x `n` and values of ones on the diagonal + */ + def speye(n: Int): SparseMatrix = { + new SparseMatrix(n, n, (0 to n).toArray, (0 until n).toArray, Array.fill(n)(1.0)) + } + + /** + * Generates the skeleton of a random `SparseMatrix` with a given random number generator. + * The values of the matrix returned are undefined. + */ + private def genRandMatrix( + numRows: Int, + numCols: Int, + density: Double, + rng: Random): SparseMatrix = { + require(numRows > 0, s"numRows must be greater than 0 but got $numRows") + require(numCols > 0, s"numCols must be greater than 0 but got $numCols") + require(density >= 0.0 && density <= 1.0, + s"density must be a double in the range 0.0 <= d <= 1.0. Currently, density: $density") + val size = numRows.toLong * numCols + val expected = size * density + assert(expected < Int.MaxValue, + "The expected number of nonzeros cannot be greater than Int.MaxValue.") + val nnz = math.ceil(expected).toInt + if (density == 0.0) { + new SparseMatrix(numRows, numCols, new Array[Int](numCols + 1), Array[Int](), Array[Double]()) + } else if (density == 1.0) { + val colPtrs = Array.tabulate(numCols + 1)(j => j * numRows) + val rowIndices = Array.tabulate(size.toInt)(idx => idx % numRows) + new SparseMatrix(numRows, numCols, colPtrs, rowIndices, new Array[Double](numRows * numCols)) + } else if (density < 0.34) { + // draw-by-draw, expected number of iterations is less than 1.5 * nnz + val entries = MHashSet[(Int, Int)]() + while (entries.size < nnz) { + entries += ((rng.nextInt(numRows), rng.nextInt(numCols))) + } + SparseMatrix.fromCOO(numRows, numCols, entries.map(v => (v._1, v._2, 1.0))) + } else { + // selection-rejection method + var idx = 0L + var numSelected = 0 + var j = 0 + val colPtrs = new Array[Int](numCols + 1) + val rowIndices = new Array[Int](nnz) + while (j < numCols && numSelected < nnz) { + var i = 0 + while (i < numRows && numSelected < nnz) { + if (rng.nextDouble() < 1.0 * (nnz - numSelected) / (size - idx)) { + rowIndices(numSelected) = i + numSelected += 1 + } + i += 1 + idx += 1 + } + colPtrs(j + 1) = numSelected + j += 1 + } + new SparseMatrix(numRows, numCols, colPtrs, rowIndices, new Array[Double](nnz)) + } + } + + /** + * Generate a `SparseMatrix` consisting of i.i.d. uniform random numbers. The number of non-zero + * elements equal the ceiling of `numRows` x `numCols` x `density` + * + * @param numRows number of rows of the matrix + * @param numCols number of columns of the matrix + * @param density the desired density for the matrix + * @param rng a random number generator + * @return `SparseMatrix` with size `numRows` x `numCols` and values in U(0, 1) + */ + def sprand(numRows: Int, numCols: Int, density: Double, rng: Random): SparseMatrix = { + val mat = genRandMatrix(numRows, numCols, density, rng) + mat.update(i => rng.nextDouble()) + } + + /** + * Generate a `SparseMatrix` consisting of i.i.d. gaussian random numbers. + * @param numRows number of rows of the matrix + * @param numCols number of columns of the matrix + * @param density the desired density for the matrix + * @param rng a random number generator + * @return `SparseMatrix` with size `numRows` x `numCols` and values in N(0, 1) + */ + def sprandn(numRows: Int, numCols: Int, density: Double, rng: Random): SparseMatrix = { + val mat = genRandMatrix(numRows, numCols, density, rng) + mat.update(i => rng.nextGaussian()) + } + + /** + * Generate a diagonal matrix in `SparseMatrix` format from the supplied values. + * @param vector a `Vector` that will form the values on the diagonal of the matrix + * @return Square `SparseMatrix` with size `values.length` x `values.length` and non-zero + * `values` on the diagonal + */ + def diag(vector: Vector): SparseMatrix = { + val n = vector.size + vector match { + case sVec: SparseVector => + SparseMatrix.fromCOO(n, n, sVec.indices.zip(sVec.values).map(v => (v._1, v._1, v._2))) + case dVec: DenseVector => + val entries = dVec.values.zipWithIndex + val nnzVals = entries.filter(v => v._1 != 0.0) + SparseMatrix.fromCOO(n, n, nnzVals.map(v => (v._2, v._2, v._1))) + } + } } /** @@ -256,72 +572,250 @@ object Matrices { * Generate a `DenseMatrix` consisting of zeros. * @param numRows number of rows of the matrix * @param numCols number of columns of the matrix - * @return `DenseMatrix` with size `numRows` x `numCols` and values of zeros + * @return `Matrix` with size `numRows` x `numCols` and values of zeros */ - def zeros(numRows: Int, numCols: Int): Matrix = - new DenseMatrix(numRows, numCols, new Array[Double](numRows * numCols)) + def zeros(numRows: Int, numCols: Int): Matrix = DenseMatrix.zeros(numRows, numCols) /** * Generate a `DenseMatrix` consisting of ones. * @param numRows number of rows of the matrix * @param numCols number of columns of the matrix - * @return `DenseMatrix` with size `numRows` x `numCols` and values of ones + * @return `Matrix` with size `numRows` x `numCols` and values of ones */ - def ones(numRows: Int, numCols: Int): Matrix = - new DenseMatrix(numRows, numCols, Array.fill(numRows * numCols)(1.0)) + def ones(numRows: Int, numCols: Int): Matrix = DenseMatrix.ones(numRows, numCols) /** - * Generate an Identity Matrix in `DenseMatrix` format. + * Generate a dense Identity Matrix in `Matrix` format. * @param n number of rows and columns of the matrix - * @return `DenseMatrix` with size `n` x `n` and values of ones on the diagonal + * @return `Matrix` with size `n` x `n` and values of ones on the diagonal */ - def eye(n: Int): Matrix = { - val identity = Matrices.zeros(n, n) - var i = 0 - while (i < n){ - identity.update(i, i, 1.0) - i += 1 - } - identity - } + def eye(n: Int): Matrix = DenseMatrix.eye(n) + + /** + * Generate a sparse Identity Matrix in `Matrix` format. + * @param n number of rows and columns of the matrix + * @return `Matrix` with size `n` x `n` and values of ones on the diagonal + */ + def speye(n: Int): Matrix = SparseMatrix.speye(n) /** * Generate a `DenseMatrix` consisting of i.i.d. uniform random numbers. * @param numRows number of rows of the matrix * @param numCols number of columns of the matrix * @param rng a random number generator - * @return `DenseMatrix` with size `numRows` x `numCols` and values in U(0, 1) + * @return `Matrix` with size `numRows` x `numCols` and values in U(0, 1) */ - def rand(numRows: Int, numCols: Int, rng: Random): Matrix = { - new DenseMatrix(numRows, numCols, Array.fill(numRows * numCols)(rng.nextDouble())) - } + def rand(numRows: Int, numCols: Int, rng: Random): Matrix = + DenseMatrix.rand(numRows, numCols, rng) + + /** + * Generate a `SparseMatrix` consisting of i.i.d. gaussian random numbers. + * @param numRows number of rows of the matrix + * @param numCols number of columns of the matrix + * @param density the desired density for the matrix + * @param rng a random number generator + * @return `Matrix` with size `numRows` x `numCols` and values in U(0, 1) + */ + def sprand(numRows: Int, numCols: Int, density: Double, rng: Random): Matrix = + SparseMatrix.sprand(numRows, numCols, density, rng) /** * Generate a `DenseMatrix` consisting of i.i.d. gaussian random numbers. * @param numRows number of rows of the matrix * @param numCols number of columns of the matrix * @param rng a random number generator - * @return `DenseMatrix` with size `numRows` x `numCols` and values in N(0, 1) + * @return `Matrix` with size `numRows` x `numCols` and values in N(0, 1) */ - def randn(numRows: Int, numCols: Int, rng: Random): Matrix = { - new DenseMatrix(numRows, numCols, Array.fill(numRows * numCols)(rng.nextGaussian())) - } + def randn(numRows: Int, numCols: Int, rng: Random): Matrix = + DenseMatrix.randn(numRows, numCols, rng) + + /** + * Generate a `SparseMatrix` consisting of i.i.d. gaussian random numbers. + * @param numRows number of rows of the matrix + * @param numCols number of columns of the matrix + * @param density the desired density for the matrix + * @param rng a random number generator + * @return `Matrix` with size `numRows` x `numCols` and values in N(0, 1) + */ + def sprandn(numRows: Int, numCols: Int, density: Double, rng: Random): Matrix = + SparseMatrix.sprandn(numRows, numCols, density, rng) /** * Generate a diagonal matrix in `DenseMatrix` format from the supplied values. * @param vector a `Vector` tat will form the values on the diagonal of the matrix - * @return Square `DenseMatrix` with size `values.length` x `values.length` and `values` + * @return Square `Matrix` with size `values.length` x `values.length` and `values` * on the diagonal */ - def diag(vector: Vector): Matrix = { - val n = vector.size - val matrix = Matrices.eye(n) - val values = vector.toArray - var i = 0 - while (i < n) { - matrix.update(i, i, values(i)) - i += 1 + def diag(vector: Vector): Matrix = DenseMatrix.diag(vector) + + /** + * Horizontally concatenate a sequence of matrices. The returned matrix will be in the format + * the matrices are supplied in. Supplying a mix of dense and sparse matrices will result in + * a sparse matrix. If the Array is empty, an empty `DenseMatrix` will be returned. + * @param matrices array of matrices + * @return a single `Matrix` composed of the matrices that were horizontally concatenated + */ + def horzcat(matrices: Array[Matrix]): Matrix = { + if (matrices.isEmpty) { + return new DenseMatrix(0, 0, Array[Double]()) + } else if (matrices.size == 1) { + return matrices(0) + } + val numRows = matrices(0).numRows + var hasSparse = false + var numCols = 0 + matrices.foreach { mat => + require(numRows == mat.numRows, "The number of rows of the matrices in this sequence, " + + "don't match!") + mat match { + case sparse: SparseMatrix => hasSparse = true + case dense: DenseMatrix => // empty on purpose + case _ => throw new IllegalArgumentException("Unsupported matrix format. Expected " + + s"SparseMatrix or DenseMatrix. Instead got: ${mat.getClass}") + } + numCols += mat.numCols + } + if (!hasSparse) { + new DenseMatrix(numRows, numCols, matrices.flatMap(_.toArray)) + } else { + var startCol = 0 + val entries: Array[(Int, Int, Double)] = matrices.flatMap { + case spMat: SparseMatrix => + var j = 0 + val colPtrs = spMat.colPtrs + val rowIndices = spMat.rowIndices + val values = spMat.values + val data = new Array[(Int, Int, Double)](values.length) + val nCols = spMat.numCols + while (j < nCols) { + var idx = colPtrs(j) + while (idx < colPtrs(j + 1)) { + val i = rowIndices(idx) + val v = values(idx) + data(idx) = (i, j + startCol, v) + idx += 1 + } + j += 1 + } + startCol += nCols + data + case dnMat: DenseMatrix => + val data = new ArrayBuffer[(Int, Int, Double)]() + var j = 0 + val nCols = dnMat.numCols + val nRows = dnMat.numRows + val values = dnMat.values + while (j < nCols) { + var i = 0 + val indStart = j * nRows + while (i < nRows) { + val v = values(indStart + i) + if (v != 0.0) { + data.append((i, j + startCol, v)) + } + i += 1 + } + j += 1 + } + startCol += nCols + data + } + SparseMatrix.fromCOO(numRows, numCols, entries) + } + } + + /** + * Vertically concatenate a sequence of matrices. The returned matrix will be in the format + * the matrices are supplied in. Supplying a mix of dense and sparse matrices will result in + * a sparse matrix. If the Array is empty, an empty `DenseMatrix` will be returned. + * @param matrices array of matrices + * @return a single `Matrix` composed of the matrices that were vertically concatenated + */ + def vertcat(matrices: Array[Matrix]): Matrix = { + if (matrices.isEmpty) { + return new DenseMatrix(0, 0, Array[Double]()) + } else if (matrices.size == 1) { + return matrices(0) + } + val numCols = matrices(0).numCols + var hasSparse = false + var numRows = 0 + matrices.foreach { mat => + require(numCols == mat.numCols, "The number of rows of the matrices in this sequence, " + + "don't match!") + mat match { + case sparse: SparseMatrix => + hasSparse = true + case dense: DenseMatrix => + case _ => throw new IllegalArgumentException("Unsupported matrix format. Expected " + + s"SparseMatrix or DenseMatrix. Instead got: ${mat.getClass}") + } + numRows += mat.numRows + + } + if (!hasSparse) { + val allValues = new Array[Double](numRows * numCols) + var startRow = 0 + matrices.foreach { mat => + var j = 0 + val nRows = mat.numRows + val values = mat.toArray + while (j < numCols) { + var i = 0 + val indStart = j * numRows + startRow + val subMatStart = j * nRows + while (i < nRows) { + allValues(indStart + i) = values(subMatStart + i) + i += 1 + } + j += 1 + } + startRow += nRows + } + new DenseMatrix(numRows, numCols, allValues) + } else { + var startRow = 0 + val entries: Array[(Int, Int, Double)] = matrices.flatMap { + case spMat: SparseMatrix => + var j = 0 + val colPtrs = spMat.colPtrs + val rowIndices = spMat.rowIndices + val values = spMat.values + val data = new Array[(Int, Int, Double)](values.length) + while (j < numCols) { + var idx = colPtrs(j) + while (idx < colPtrs(j + 1)) { + val i = rowIndices(idx) + val v = values(idx) + data(idx) = (i + startRow, j, v) + idx += 1 + } + j += 1 + } + startRow += spMat.numRows + data + case dnMat: DenseMatrix => + val data = new ArrayBuffer[(Int, Int, Double)]() + var j = 0 + val nCols = dnMat.numCols + val nRows = dnMat.numRows + val values = dnMat.values + while (j < nCols) { + var i = 0 + val indStart = j * nRows + while (i < nRows) { + val v = values(indStart + i) + if (v != 0.0) { + data.append((i + startRow, j, v)) + } + i += 1 + } + j += 1 + } + startRow += nRows + data + } + SparseMatrix.fromCOO(numRows, numCols, entries) } - matrix } } diff --git a/mllib/src/test/java/org/apache/spark/mllib/linalg/JavaMatricesSuite.java b/mllib/src/test/java/org/apache/spark/mllib/linalg/JavaMatricesSuite.java new file mode 100644 index 0000000000000..704d484d0b585 --- /dev/null +++ b/mllib/src/test/java/org/apache/spark/mllib/linalg/JavaMatricesSuite.java @@ -0,0 +1,163 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.mllib.linalg; + +import static org.junit.Assert.*; +import org.junit.Test; + +import java.io.Serializable; +import java.util.Random; + +public class JavaMatricesSuite implements Serializable { + + @Test + public void randMatrixConstruction() { + Random rng = new Random(24); + Matrix r = Matrices.rand(3, 4, rng); + rng.setSeed(24); + DenseMatrix dr = DenseMatrix.rand(3, 4, rng); + assertArrayEquals(r.toArray(), dr.toArray(), 0.0); + + rng.setSeed(24); + Matrix rn = Matrices.randn(3, 4, rng); + rng.setSeed(24); + DenseMatrix drn = DenseMatrix.randn(3, 4, rng); + assertArrayEquals(rn.toArray(), drn.toArray(), 0.0); + + rng.setSeed(24); + Matrix s = Matrices.sprand(3, 4, 0.5, rng); + rng.setSeed(24); + SparseMatrix sr = SparseMatrix.sprand(3, 4, 0.5, rng); + assertArrayEquals(s.toArray(), sr.toArray(), 0.0); + + rng.setSeed(24); + Matrix sn = Matrices.sprandn(3, 4, 0.5, rng); + rng.setSeed(24); + SparseMatrix srn = SparseMatrix.sprandn(3, 4, 0.5, rng); + assertArrayEquals(sn.toArray(), srn.toArray(), 0.0); + } + + @Test + public void identityMatrixConstruction() { + Matrix r = Matrices.eye(2); + DenseMatrix dr = DenseMatrix.eye(2); + SparseMatrix sr = SparseMatrix.speye(2); + assertArrayEquals(r.toArray(), dr.toArray(), 0.0); + assertArrayEquals(sr.toArray(), dr.toArray(), 0.0); + assertArrayEquals(r.toArray(), new double[]{1.0, 0.0, 0.0, 1.0}, 0.0); + } + + @Test + public void diagonalMatrixConstruction() { + Vector v = Vectors.dense(1.0, 0.0, 2.0); + Vector sv = Vectors.sparse(3, new int[]{0, 2}, new double[]{1.0, 2.0}); + + Matrix m = Matrices.diag(v); + Matrix sm = Matrices.diag(sv); + DenseMatrix d = DenseMatrix.diag(v); + DenseMatrix sd = DenseMatrix.diag(sv); + SparseMatrix s = SparseMatrix.diag(v); + SparseMatrix ss = SparseMatrix.diag(sv); + + assertArrayEquals(m.toArray(), sm.toArray(), 0.0); + assertArrayEquals(d.toArray(), sm.toArray(), 0.0); + assertArrayEquals(d.toArray(), sd.toArray(), 0.0); + assertArrayEquals(sd.toArray(), s.toArray(), 0.0); + assertArrayEquals(s.toArray(), ss.toArray(), 0.0); + assertArrayEquals(s.values(), ss.values(), 0.0); + assert(s.values().length == 2); + assert(ss.values().length == 2); + assert(s.colPtrs().length == 4); + assert(ss.colPtrs().length == 4); + } + + @Test + public void zerosMatrixConstruction() { + Matrix z = Matrices.zeros(2, 2); + Matrix one = Matrices.ones(2, 2); + DenseMatrix dz = DenseMatrix.zeros(2, 2); + DenseMatrix done = DenseMatrix.ones(2, 2); + + assertArrayEquals(z.toArray(), new double[]{0.0, 0.0, 0.0, 0.0}, 0.0); + assertArrayEquals(dz.toArray(), new double[]{0.0, 0.0, 0.0, 0.0}, 0.0); + assertArrayEquals(one.toArray(), new double[]{1.0, 1.0, 1.0, 1.0}, 0.0); + assertArrayEquals(done.toArray(), new double[]{1.0, 1.0, 1.0, 1.0}, 0.0); + } + + @Test + public void sparseDenseConversion() { + int m = 3; + int n = 2; + double[] values = new double[]{1.0, 2.0, 4.0, 5.0}; + double[] allValues = new double[]{1.0, 2.0, 0.0, 0.0, 4.0, 5.0}; + int[] colPtrs = new int[]{0, 2, 4}; + int[] rowIndices = new int[]{0, 1, 1, 2}; + + SparseMatrix spMat1 = new SparseMatrix(m, n, colPtrs, rowIndices, values); + DenseMatrix deMat1 = new DenseMatrix(m, n, allValues); + + SparseMatrix spMat2 = deMat1.toSparse(); + DenseMatrix deMat2 = spMat1.toDense(); + + assertArrayEquals(spMat1.toArray(), spMat2.toArray(), 0.0); + assertArrayEquals(deMat1.toArray(), deMat2.toArray(), 0.0); + } + + @Test + public void concatenateMatrices() { + int m = 3; + int n = 2; + + Random rng = new Random(42); + SparseMatrix spMat1 = SparseMatrix.sprand(m, n, 0.5, rng); + rng.setSeed(42); + DenseMatrix deMat1 = DenseMatrix.rand(m, n, rng); + Matrix deMat2 = Matrices.eye(3); + Matrix spMat2 = Matrices.speye(3); + Matrix deMat3 = Matrices.eye(2); + Matrix spMat3 = Matrices.speye(2); + + Matrix spHorz = Matrices.horzcat(new Matrix[]{spMat1, spMat2}); + Matrix deHorz1 = Matrices.horzcat(new Matrix[]{deMat1, deMat2}); + Matrix deHorz2 = Matrices.horzcat(new Matrix[]{spMat1, deMat2}); + Matrix deHorz3 = Matrices.horzcat(new Matrix[]{deMat1, spMat2}); + + assert(deHorz1.numRows() == 3); + assert(deHorz2.numRows() == 3); + assert(deHorz3.numRows() == 3); + assert(spHorz.numRows() == 3); + assert(deHorz1.numCols() == 5); + assert(deHorz2.numCols() == 5); + assert(deHorz3.numCols() == 5); + assert(spHorz.numCols() == 5); + + Matrix spVert = Matrices.vertcat(new Matrix[]{spMat1, spMat3}); + Matrix deVert1 = Matrices.vertcat(new Matrix[]{deMat1, deMat3}); + Matrix deVert2 = Matrices.vertcat(new Matrix[]{spMat1, deMat3}); + Matrix deVert3 = Matrices.vertcat(new Matrix[]{deMat1, spMat3}); + + assert(deVert1.numRows() == 5); + assert(deVert2.numRows() == 5); + assert(deVert3.numRows() == 5); + assert(spVert.numRows() == 5); + assert(deVert1.numCols() == 2); + assert(deVert2.numCols() == 2); + assert(deVert3.numCols() == 2); + assert(spVert.numCols() == 2); + } +} diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala index 322a0e9242918..a35d0fe389fdd 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala @@ -43,9 +43,9 @@ class MatricesSuite extends FunSuite { test("sparse matrix construction") { val m = 3 - val n = 2 + val n = 4 val values = Array(1.0, 2.0, 4.0, 5.0) - val colPtrs = Array(0, 2, 4) + val colPtrs = Array(0, 2, 2, 4, 4) val rowIndices = Array(1, 2, 1, 2) val mat = Matrices.sparse(m, n, colPtrs, rowIndices, values).asInstanceOf[SparseMatrix] assert(mat.numRows === m) @@ -53,6 +53,13 @@ class MatricesSuite extends FunSuite { assert(mat.values.eq(values), "should not copy data") assert(mat.colPtrs.eq(colPtrs), "should not copy data") assert(mat.rowIndices.eq(rowIndices), "should not copy data") + + val entries: Array[(Int, Int, Double)] = Array((2, 2, 3.0), (1, 0, 1.0), (2, 0, 2.0), + (1, 2, 2.0), (2, 2, 2.0), (1, 2, 2.0), (0, 0, 0.0)) + + val mat2 = SparseMatrix.fromCOO(m, n, entries) + assert(mat.toBreeze === mat2.toBreeze) + assert(mat2.values.length == 4) } test("sparse matrix construction with wrong number of elements") { @@ -117,6 +124,142 @@ class MatricesSuite extends FunSuite { assert(sparseMat.values(2) === 10.0) } + test("toSparse, toDense") { + val m = 3 + val n = 2 + val values = Array(1.0, 2.0, 4.0, 5.0) + val allValues = Array(1.0, 2.0, 0.0, 0.0, 4.0, 5.0) + val colPtrs = Array(0, 2, 4) + val rowIndices = Array(0, 1, 1, 2) + + val spMat1 = new SparseMatrix(m, n, colPtrs, rowIndices, values) + val deMat1 = new DenseMatrix(m, n, allValues) + + val spMat2 = deMat1.toSparse() + val deMat2 = spMat1.toDense() + + assert(spMat1.toBreeze === spMat2.toBreeze) + assert(deMat1.toBreeze === deMat2.toBreeze) + } + + test("map, update") { + val m = 3 + val n = 2 + val values = Array(1.0, 2.0, 4.0, 5.0) + val allValues = Array(1.0, 2.0, 0.0, 0.0, 4.0, 5.0) + val colPtrs = Array(0, 2, 4) + val rowIndices = Array(0, 1, 1, 2) + + val spMat1 = new SparseMatrix(m, n, colPtrs, rowIndices, values) + val deMat1 = new DenseMatrix(m, n, allValues) + val deMat2 = deMat1.map(_ * 2) + val spMat2 = spMat1.map(_ * 2) + deMat1.update(_ * 2) + spMat1.update(_ * 2) + + assert(spMat1.toArray === spMat2.toArray) + assert(deMat1.toArray === deMat2.toArray) + } + + test("horzcat, vertcat, eye, speye") { + val m = 3 + val n = 2 + val values = Array(1.0, 2.0, 4.0, 5.0) + val allValues = Array(1.0, 2.0, 0.0, 0.0, 4.0, 5.0) + val colPtrs = Array(0, 2, 4) + val rowIndices = Array(0, 1, 1, 2) + + val spMat1 = new SparseMatrix(m, n, colPtrs, rowIndices, values) + val deMat1 = new DenseMatrix(m, n, allValues) + val deMat2 = Matrices.eye(3) + val spMat2 = Matrices.speye(3) + val deMat3 = Matrices.eye(2) + val spMat3 = Matrices.speye(2) + + val spHorz = Matrices.horzcat(Array(spMat1, spMat2)) + val spHorz2 = Matrices.horzcat(Array(spMat1, deMat2)) + val spHorz3 = Matrices.horzcat(Array(deMat1, spMat2)) + val deHorz1 = Matrices.horzcat(Array(deMat1, deMat2)) + + val deHorz2 = Matrices.horzcat(Array[Matrix]()) + + assert(deHorz1.numRows === 3) + assert(spHorz2.numRows === 3) + assert(spHorz3.numRows === 3) + assert(spHorz.numRows === 3) + assert(deHorz1.numCols === 5) + assert(spHorz2.numCols === 5) + assert(spHorz3.numCols === 5) + assert(spHorz.numCols === 5) + assert(deHorz2.numRows === 0) + assert(deHorz2.numCols === 0) + assert(deHorz2.toArray.length === 0) + + assert(deHorz1.toBreeze.toDenseMatrix === spHorz2.toBreeze.toDenseMatrix) + assert(spHorz2.toBreeze === spHorz3.toBreeze) + assert(spHorz(0, 0) === 1.0) + assert(spHorz(2, 1) === 5.0) + assert(spHorz(0, 2) === 1.0) + assert(spHorz(1, 2) === 0.0) + assert(spHorz(1, 3) === 1.0) + assert(spHorz(2, 4) === 1.0) + assert(spHorz(1, 4) === 0.0) + assert(deHorz1(0, 0) === 1.0) + assert(deHorz1(2, 1) === 5.0) + assert(deHorz1(0, 2) === 1.0) + assert(deHorz1(1, 2) == 0.0) + assert(deHorz1(1, 3) === 1.0) + assert(deHorz1(2, 4) === 1.0) + assert(deHorz1(1, 4) === 0.0) + + intercept[IllegalArgumentException] { + Matrices.horzcat(Array(spMat1, spMat3)) + } + + intercept[IllegalArgumentException] { + Matrices.horzcat(Array(deMat1, spMat3)) + } + + val spVert = Matrices.vertcat(Array(spMat1, spMat3)) + val deVert1 = Matrices.vertcat(Array(deMat1, deMat3)) + val spVert2 = Matrices.vertcat(Array(spMat1, deMat3)) + val spVert3 = Matrices.vertcat(Array(deMat1, spMat3)) + val deVert2 = Matrices.vertcat(Array[Matrix]()) + + assert(deVert1.numRows === 5) + assert(spVert2.numRows === 5) + assert(spVert3.numRows === 5) + assert(spVert.numRows === 5) + assert(deVert1.numCols === 2) + assert(spVert2.numCols === 2) + assert(spVert3.numCols === 2) + assert(spVert.numCols === 2) + assert(deVert2.numRows === 0) + assert(deVert2.numCols === 0) + assert(deVert2.toArray.length === 0) + + assert(deVert1.toBreeze.toDenseMatrix === spVert2.toBreeze.toDenseMatrix) + assert(spVert2.toBreeze === spVert3.toBreeze) + assert(spVert(0, 0) === 1.0) + assert(spVert(2, 1) === 5.0) + assert(spVert(3, 0) === 1.0) + assert(spVert(3, 1) === 0.0) + assert(spVert(4, 1) === 1.0) + assert(deVert1(0, 0) === 1.0) + assert(deVert1(2, 1) === 5.0) + assert(deVert1(3, 0) === 1.0) + assert(deVert1(3, 1) === 0.0) + assert(deVert1(4, 1) === 1.0) + + intercept[IllegalArgumentException] { + Matrices.vertcat(Array(spMat1, spMat2)) + } + + intercept[IllegalArgumentException] { + Matrices.vertcat(Array(deMat1, spMat2)) + } + } + test("zeros") { val mat = Matrices.zeros(2, 3).asInstanceOf[DenseMatrix] assert(mat.numRows === 2) @@ -162,4 +305,29 @@ class MatricesSuite extends FunSuite { assert(mat.numCols === 2) assert(mat.values.toSeq === Seq(1.0, 0.0, 0.0, 2.0)) } + + test("sprand") { + val rng = mock[Random] + when(rng.nextInt(4)).thenReturn(0, 1, 1, 3, 2, 2, 0, 1, 3, 0) + when(rng.nextDouble()).thenReturn(1.0, 2.0, 3.0, 4.0, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0) + val mat = SparseMatrix.sprand(4, 4, 0.25, rng) + assert(mat.numRows === 4) + assert(mat.numCols === 4) + assert(mat.rowIndices.toSeq === Seq(3, 0, 2, 1)) + assert(mat.values.toSeq === Seq(1.0, 2.0, 3.0, 4.0)) + val mat2 = SparseMatrix.sprand(2, 3, 1.0, rng) + assert(mat2.rowIndices.toSeq === Seq(0, 1, 0, 1, 0, 1)) + assert(mat2.colPtrs.toSeq === Seq(0, 2, 4, 6)) + } + + test("sprandn") { + val rng = mock[Random] + when(rng.nextInt(4)).thenReturn(0, 1, 1, 3, 2, 2, 0, 1, 3, 0) + when(rng.nextGaussian()).thenReturn(1.0, 2.0, 3.0, 4.0) + val mat = SparseMatrix.sprandn(4, 4, 0.25, rng) + assert(mat.numRows === 4) + assert(mat.numCols === 4) + assert(mat.rowIndices.toSeq === Seq(3, 0, 2, 1)) + assert(mat.values.toSeq === Seq(1.0, 2.0, 3.0, 4.0)) + } } diff --git a/mllib/src/test/scala/org/apache/spark/mllib/util/TestingUtils.scala b/mllib/src/test/scala/org/apache/spark/mllib/util/TestingUtils.scala index 30b906aaa3ba4..e957fa5d25f4c 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/util/TestingUtils.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/util/TestingUtils.scala @@ -178,17 +178,17 @@ object TestingUtils { implicit class MatrixWithAlmostEquals(val x: Matrix) { /** - * When the difference of two vectors are within eps, returns true; otherwise, returns false. + * When the difference of two matrices are within eps, returns true; otherwise, returns false. */ def ~=(r: CompareMatrixRightSide): Boolean = r.fun(x, r.y, r.eps) /** - * When the difference of two vectors are within eps, returns false; otherwise, returns true. + * When the difference of two matrices are within eps, returns false; otherwise, returns true. */ def !~=(r: CompareMatrixRightSide): Boolean = !r.fun(x, r.y, r.eps) /** - * Throws exception when the difference of two vectors are NOT within eps; + * Throws exception when the difference of two matrices are NOT within eps; * otherwise, returns true. */ def ~==(r: CompareMatrixRightSide): Boolean = { From 9bc0df6804f241aff24520d9c6ec54d9b11f5785 Mon Sep 17 00:00:00 2001 From: Yash Datta Date: Mon, 29 Dec 2014 13:49:45 -0800 Subject: [PATCH 119/320] SPARK-4968: takeOrdered to skip reduce step in case mappers return no partitions takeOrdered should skip reduce step in case mapped RDDs have no partitions. This prevents the mentioned exception : 4. run query SELECT * FROM testTable WHERE market = 'market2' ORDER BY End_Time DESC LIMIT 100; Error trace java.lang.UnsupportedOperationException: empty collection at org.apache.spark.rdd.RDD$$anonfun$reduce$1.apply(RDD.scala:863) at org.apache.spark.rdd.RDD$$anonfun$reduce$1.apply(RDD.scala:863) at scala.Option.getOrElse(Option.scala:120) at org.apache.spark.rdd.RDD.reduce(RDD.scala:863) at org.apache.spark.rdd.RDD.takeOrdered(RDD.scala:1136) Author: Yash Datta Closes #3830 from saucam/fix_takeorder and squashes the following commits: 5974d10 [Yash Datta] SPARK-4968: takeOrdered to skip reduce step in case mappers return no partitions --- .../src/main/scala/org/apache/spark/rdd/RDD.scala | 15 ++++++++++----- 1 file changed, 10 insertions(+), 5 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/rdd/RDD.scala b/core/src/main/scala/org/apache/spark/rdd/RDD.scala index f47c2d1fcdcc7..5118e2b911120 100644 --- a/core/src/main/scala/org/apache/spark/rdd/RDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/RDD.scala @@ -1146,15 +1146,20 @@ abstract class RDD[T: ClassTag]( if (num == 0) { Array.empty } else { - mapPartitions { items => + val mapRDDs = mapPartitions { items => // Priority keeps the largest elements, so let's reverse the ordering. val queue = new BoundedPriorityQueue[T](num)(ord.reverse) queue ++= util.collection.Utils.takeOrdered(items, num)(ord) Iterator.single(queue) - }.reduce { (queue1, queue2) => - queue1 ++= queue2 - queue1 - }.toArray.sorted(ord) + } + if (mapRDDs.partitions.size == 0) { + Array.empty + } else { + mapRDDs.reduce { (queue1, queue2) => + queue1 ++= queue2 + queue1 + }.toArray.sorted(ord) + } } } From 6cf6fdf3ff5d1cf33c2dc28f039adc4d7c0f0464 Mon Sep 17 00:00:00 2001 From: Travis Galoppo Date: Mon, 29 Dec 2014 15:29:15 -0800 Subject: [PATCH 120/320] SPARK-4156 [MLLIB] EM algorithm for GMMs Implementation of Expectation-Maximization for Gaussian Mixture Models. This is my maiden contribution to Apache Spark, so I apologize now if I have done anything incorrectly; having said that, this work is my own, and I offer it to the project under the project's open source license. Author: Travis Galoppo Author: Travis Galoppo Author: tgaloppo Author: FlytxtRnD Closes #3022 from tgaloppo/master and squashes the following commits: aaa8f25 [Travis Galoppo] MLUtils: changed privacy of EPSILON from [util] to [mllib] 709e4bf [Travis Galoppo] fixed usage line to include optional maxIterations parameter acf1fba [Travis Galoppo] Fixed parameter comment in GaussianMixtureModel Made maximum iterations an optional parameter to DenseGmmEM 9b2fc2a [Travis Galoppo] Style improvements Changed ExpectationSum to a private class b97fe00 [Travis Galoppo] Minor fixes and tweaks. 1de73f3 [Travis Galoppo] Removed redundant array from array creation 578c2d1 [Travis Galoppo] Removed unused import 227ad66 [Travis Galoppo] Moved prediction methods into model class. 308c8ad [Travis Galoppo] Numerous changes to improve code cff73e0 [Travis Galoppo] Replaced accumulators with RDD.aggregate 20ebca1 [Travis Galoppo] Removed unusued code 42b2142 [Travis Galoppo] Added functionality to allow setting of GMM starting point. Added two cluster test to testing suite. 8b633f3 [Travis Galoppo] Style issue 9be2534 [Travis Galoppo] Style issue d695034 [Travis Galoppo] Fixed style issues c3b8ce0 [Travis Galoppo] Merge branch 'master' of https://github.com/tgaloppo/spark Adds predict() method 2df336b [Travis Galoppo] Fixed style issue b99ecc4 [tgaloppo] Merge pull request #1 from FlytxtRnD/predictBranch f407b4c [FlytxtRnD] Added predict() to return the cluster labels and membership values 97044cf [Travis Galoppo] Fixed style issues dc9c742 [Travis Galoppo] Moved MultivariateGaussian utility class e7d413b [Travis Galoppo] Moved multivariate Gaussian utility class to mllib/stat/impl Improved comments 9770261 [Travis Galoppo] Corrected a variety of style and naming issues. 8aaa17d [Travis Galoppo] Added additional train() method to companion object for cluster count and tolerance parameters. 676e523 [Travis Galoppo] Fixed to no longer ignore delta value provided on command line e6ea805 [Travis Galoppo] Merged with master branch; update test suite with latest context changes. Improved cluster initialization strategy. 86fb382 [Travis Galoppo] Merge remote-tracking branch 'upstream/master' 719d8cc [Travis Galoppo] Added scala test suite with basic test c1a8e16 [Travis Galoppo] Made GaussianMixtureModel class serializable Modified sum function for better performance 5c96c57 [Travis Galoppo] Merge remote-tracking branch 'upstream/master' c15405c [Travis Galoppo] SPARK-4156 --- .../spark/examples/mllib/DenseGmmEM.scala | 67 +++++ .../mllib/clustering/GaussianMixtureEM.scala | 241 ++++++++++++++++++ .../clustering/GaussianMixtureModel.scala | 91 +++++++ .../stat/impl/MultivariateGaussian.scala | 39 +++ .../org/apache/spark/mllib/util/MLUtils.scala | 2 +- .../GMMExpectationMaximizationSuite.scala | 78 ++++++ 6 files changed, 517 insertions(+), 1 deletion(-) create mode 100644 examples/src/main/scala/org/apache/spark/examples/mllib/DenseGmmEM.scala create mode 100644 mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureEM.scala create mode 100644 mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala create mode 100644 mllib/src/main/scala/org/apache/spark/mllib/stat/impl/MultivariateGaussian.scala create mode 100644 mllib/src/test/scala/org/apache/spark/mllib/clustering/GMMExpectationMaximizationSuite.scala diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/DenseGmmEM.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/DenseGmmEM.scala new file mode 100644 index 0000000000000..948c350953e27 --- /dev/null +++ b/examples/src/main/scala/org/apache/spark/examples/mllib/DenseGmmEM.scala @@ -0,0 +1,67 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.examples.mllib + +import org.apache.spark.{SparkConf, SparkContext} +import org.apache.spark.mllib.clustering.GaussianMixtureEM +import org.apache.spark.mllib.linalg.Vectors + +/** + * An example Gaussian Mixture Model EM app. Run with + * {{{ + * ./bin/run-example org.apache.spark.examples.mllib.DenseGmmEM + * }}} + * If you use it as a template to create your own app, please use `spark-submit` to submit your app. + */ +object DenseGmmEM { + def main(args: Array[String]): Unit = { + if (args.length < 3) { + println("usage: DenseGmmEM [maxIterations]") + } else { + val maxIterations = if (args.length > 3) args(3).toInt else 100 + run(args(0), args(1).toInt, args(2).toDouble, maxIterations) + } + } + + private def run(inputFile: String, k: Int, convergenceTol: Double, maxIterations: Int) { + val conf = new SparkConf().setAppName("Gaussian Mixture Model EM example") + val ctx = new SparkContext(conf) + + val data = ctx.textFile(inputFile).map { line => + Vectors.dense(line.trim.split(' ').map(_.toDouble)) + }.cache() + + val clusters = new GaussianMixtureEM() + .setK(k) + .setConvergenceTol(convergenceTol) + .setMaxIterations(maxIterations) + .run(data) + + for (i <- 0 until clusters.k) { + println("weight=%f\nmu=%s\nsigma=\n%s\n" format + (clusters.weight(i), clusters.mu(i), clusters.sigma(i))) + } + + println("Cluster labels (first <= 100):") + val clusterLabels = clusters.predict(data) + clusterLabels.take(100).foreach { x => + print(" " + x) + } + println() + } +} diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureEM.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureEM.scala new file mode 100644 index 0000000000000..bdf984aee4dae --- /dev/null +++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureEM.scala @@ -0,0 +1,241 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.mllib.clustering + +import scala.collection.mutable.IndexedSeq + +import breeze.linalg.{DenseVector => BreezeVector, DenseMatrix => BreezeMatrix, diag, Transpose} +import org.apache.spark.rdd.RDD +import org.apache.spark.mllib.linalg.{Matrices, Vector, Vectors} +import org.apache.spark.mllib.stat.impl.MultivariateGaussian +import org.apache.spark.mllib.util.MLUtils + +/** + * This class performs expectation maximization for multivariate Gaussian + * Mixture Models (GMMs). A GMM represents a composite distribution of + * independent Gaussian distributions with associated "mixing" weights + * specifying each's contribution to the composite. + * + * Given a set of sample points, this class will maximize the log-likelihood + * for a mixture of k Gaussians, iterating until the log-likelihood changes by + * less than convergenceTol, or until it has reached the max number of iterations. + * While this process is generally guaranteed to converge, it is not guaranteed + * to find a global optimum. + * + * @param k The number of independent Gaussians in the mixture model + * @param convergenceTol The maximum change in log-likelihood at which convergence + * is considered to have occurred. + * @param maxIterations The maximum number of iterations to perform + */ +class GaussianMixtureEM private ( + private var k: Int, + private var convergenceTol: Double, + private var maxIterations: Int) extends Serializable { + + /** A default instance, 2 Gaussians, 100 iterations, 0.01 log-likelihood threshold */ + def this() = this(2, 0.01, 100) + + // number of samples per cluster to use when initializing Gaussians + private val nSamples = 5 + + // an initializing GMM can be provided rather than using the + // default random starting point + private var initialModel: Option[GaussianMixtureModel] = None + + /** Set the initial GMM starting point, bypassing the random initialization. + * You must call setK() prior to calling this method, and the condition + * (model.k == this.k) must be met; failure will result in an IllegalArgumentException + */ + def setInitialModel(model: GaussianMixtureModel): this.type = { + if (model.k == k) { + initialModel = Some(model) + } else { + throw new IllegalArgumentException("mismatched cluster count (model.k != k)") + } + this + } + + /** Return the user supplied initial GMM, if supplied */ + def getInitialModel: Option[GaussianMixtureModel] = initialModel + + /** Set the number of Gaussians in the mixture model. Default: 2 */ + def setK(k: Int): this.type = { + this.k = k + this + } + + /** Return the number of Gaussians in the mixture model */ + def getK: Int = k + + /** Set the maximum number of iterations to run. Default: 100 */ + def setMaxIterations(maxIterations: Int): this.type = { + this.maxIterations = maxIterations + this + } + + /** Return the maximum number of iterations to run */ + def getMaxIterations: Int = maxIterations + + /** + * Set the largest change in log-likelihood at which convergence is + * considered to have occurred. + */ + def setConvergenceTol(convergenceTol: Double): this.type = { + this.convergenceTol = convergenceTol + this + } + + /** Return the largest change in log-likelihood at which convergence is + * considered to have occurred. + */ + def getConvergenceTol: Double = convergenceTol + + /** Perform expectation maximization */ + def run(data: RDD[Vector]): GaussianMixtureModel = { + val sc = data.sparkContext + + // we will operate on the data as breeze data + val breezeData = data.map(u => u.toBreeze.toDenseVector).cache() + + // Get length of the input vectors + val d = breezeData.first.length + + // Determine initial weights and corresponding Gaussians. + // If the user supplied an initial GMM, we use those values, otherwise + // we start with uniform weights, a random mean from the data, and + // diagonal covariance matrices using component variances + // derived from the samples + val (weights, gaussians) = initialModel match { + case Some(gmm) => (gmm.weight, gmm.mu.zip(gmm.sigma).map { case(mu, sigma) => + new MultivariateGaussian(mu.toBreeze.toDenseVector, sigma.toBreeze.toDenseMatrix) + }) + + case None => { + val samples = breezeData.takeSample(true, k * nSamples, scala.util.Random.nextInt) + (Array.fill(k)(1.0 / k), Array.tabulate(k) { i => + val slice = samples.view(i * nSamples, (i + 1) * nSamples) + new MultivariateGaussian(vectorMean(slice), initCovariance(slice)) + }) + } + } + + var llh = Double.MinValue // current log-likelihood + var llhp = 0.0 // previous log-likelihood + + var iter = 0 + while(iter < maxIterations && Math.abs(llh-llhp) > convergenceTol) { + // create and broadcast curried cluster contribution function + val compute = sc.broadcast(ExpectationSum.add(weights, gaussians)_) + + // aggregate the cluster contribution for all sample points + val sums = breezeData.aggregate(ExpectationSum.zero(k, d))(compute.value, _ += _) + + // Create new distributions based on the partial assignments + // (often referred to as the "M" step in literature) + val sumWeights = sums.weights.sum + var i = 0 + while (i < k) { + val mu = sums.means(i) / sums.weights(i) + val sigma = sums.sigmas(i) / sums.weights(i) - mu * new Transpose(mu) // TODO: Use BLAS.dsyr + weights(i) = sums.weights(i) / sumWeights + gaussians(i) = new MultivariateGaussian(mu, sigma) + i = i + 1 + } + + llhp = llh // current becomes previous + llh = sums.logLikelihood // this is the freshly computed log-likelihood + iter += 1 + } + + // Need to convert the breeze matrices to MLlib matrices + val means = Array.tabulate(k) { i => Vectors.fromBreeze(gaussians(i).mu) } + val sigmas = Array.tabulate(k) { i => Matrices.fromBreeze(gaussians(i).sigma) } + new GaussianMixtureModel(weights, means, sigmas) + } + + /** Average of dense breeze vectors */ + private def vectorMean(x: IndexedSeq[BreezeVector[Double]]): BreezeVector[Double] = { + val v = BreezeVector.zeros[Double](x(0).length) + x.foreach(xi => v += xi) + v / x.length.toDouble + } + + /** + * Construct matrix where diagonal entries are element-wise + * variance of input vectors (computes biased variance) + */ + private def initCovariance(x: IndexedSeq[BreezeVector[Double]]): BreezeMatrix[Double] = { + val mu = vectorMean(x) + val ss = BreezeVector.zeros[Double](x(0).length) + x.map(xi => (xi - mu) :^ 2.0).foreach(u => ss += u) + diag(ss / x.length.toDouble) + } +} + +// companion class to provide zero constructor for ExpectationSum +private object ExpectationSum { + def zero(k: Int, d: Int): ExpectationSum = { + new ExpectationSum(0.0, Array.fill(k)(0.0), + Array.fill(k)(BreezeVector.zeros(d)), Array.fill(k)(BreezeMatrix.zeros(d,d))) + } + + // compute cluster contributions for each input point + // (U, T) => U for aggregation + def add( + weights: Array[Double], + dists: Array[MultivariateGaussian]) + (sums: ExpectationSum, x: BreezeVector[Double]): ExpectationSum = { + val p = weights.zip(dists).map { + case (weight, dist) => MLUtils.EPSILON + weight * dist.pdf(x) + } + val pSum = p.sum + sums.logLikelihood += math.log(pSum) + val xxt = x * new Transpose(x) + var i = 0 + while (i < sums.k) { + p(i) /= pSum + sums.weights(i) += p(i) + sums.means(i) += x * p(i) + sums.sigmas(i) += xxt * p(i) // TODO: use BLAS.dsyr + i = i + 1 + } + sums + } +} + +// Aggregation class for partial expectation results +private class ExpectationSum( + var logLikelihood: Double, + val weights: Array[Double], + val means: Array[BreezeVector[Double]], + val sigmas: Array[BreezeMatrix[Double]]) extends Serializable { + + val k = weights.length + + def +=(x: ExpectationSum): ExpectationSum = { + var i = 0 + while (i < k) { + weights(i) += x.weights(i) + means(i) += x.means(i) + sigmas(i) += x.sigmas(i) + i = i + 1 + } + logLikelihood += x.logLikelihood + this + } +} diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala new file mode 100644 index 0000000000000..11a110db1f7ca --- /dev/null +++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala @@ -0,0 +1,91 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.mllib.clustering + +import breeze.linalg.{DenseVector => BreezeVector} + +import org.apache.spark.rdd.RDD +import org.apache.spark.mllib.linalg.{Matrix, Vector} +import org.apache.spark.mllib.stat.impl.MultivariateGaussian +import org.apache.spark.mllib.util.MLUtils + +/** + * Multivariate Gaussian Mixture Model (GMM) consisting of k Gaussians, where points + * are drawn from each Gaussian i=1..k with probability w(i); mu(i) and sigma(i) are + * the respective mean and covariance for each Gaussian distribution i=1..k. + * + * @param weight Weights for each Gaussian distribution in the mixture, where weight(i) is + * the weight for Gaussian i, and weight.sum == 1 + * @param mu Means for each Gaussian in the mixture, where mu(i) is the mean for Gaussian i + * @param sigma Covariance maxtrix for each Gaussian in the mixture, where sigma(i) is the + * covariance matrix for Gaussian i + */ +class GaussianMixtureModel( + val weight: Array[Double], + val mu: Array[Vector], + val sigma: Array[Matrix]) extends Serializable { + + /** Number of gaussians in mixture */ + def k: Int = weight.length + + /** Maps given points to their cluster indices. */ + def predict(points: RDD[Vector]): RDD[Int] = { + val responsibilityMatrix = predictMembership(points, mu, sigma, weight, k) + responsibilityMatrix.map(r => r.indexOf(r.max)) + } + + /** + * Given the input vectors, return the membership value of each vector + * to all mixture components. + */ + def predictMembership( + points: RDD[Vector], + mu: Array[Vector], + sigma: Array[Matrix], + weight: Array[Double], + k: Int): RDD[Array[Double]] = { + val sc = points.sparkContext + val dists = sc.broadcast { + (0 until k).map { i => + new MultivariateGaussian(mu(i).toBreeze.toDenseVector, sigma(i).toBreeze.toDenseMatrix) + }.toArray + } + val weights = sc.broadcast(weight) + points.map { x => + computeSoftAssignments(x.toBreeze.toDenseVector, dists.value, weights.value, k) + } + } + + /** + * Compute the partial assignments for each vector + */ + private def computeSoftAssignments( + pt: BreezeVector[Double], + dists: Array[MultivariateGaussian], + weights: Array[Double], + k: Int): Array[Double] = { + val p = weights.zip(dists).map { + case (weight, dist) => MLUtils.EPSILON + weight * dist.pdf(pt) + } + val pSum = p.sum + for (i <- 0 until k) { + p(i) /= pSum + } + p + } +} diff --git a/mllib/src/main/scala/org/apache/spark/mllib/stat/impl/MultivariateGaussian.scala b/mllib/src/main/scala/org/apache/spark/mllib/stat/impl/MultivariateGaussian.scala new file mode 100644 index 0000000000000..2eab5d277827d --- /dev/null +++ b/mllib/src/main/scala/org/apache/spark/mllib/stat/impl/MultivariateGaussian.scala @@ -0,0 +1,39 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.mllib.stat.impl + +import breeze.linalg.{DenseVector => DBV, DenseMatrix => DBM, Transpose, det, pinv} + +/** + * Utility class to implement the density function for multivariate Gaussian distribution. + * Breeze provides this functionality, but it requires the Apache Commons Math library, + * so this class is here so-as to not introduce a new dependency in Spark. + */ +private[mllib] class MultivariateGaussian( + val mu: DBV[Double], + val sigma: DBM[Double]) extends Serializable { + private val sigmaInv2 = pinv(sigma) * -0.5 + private val U = math.pow(2.0 * math.Pi, -mu.length / 2.0) * math.pow(det(sigma), -0.5) + + /** Returns density of this multivariate Gaussian at given point, x */ + def pdf(x: DBV[Double]): Double = { + val delta = x - mu + val deltaTranspose = new Transpose(delta) + U * math.exp(deltaTranspose * sigmaInv2 * delta) + } +} diff --git a/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala b/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala index b0d05ae33e1b5..1d07b5dab8268 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala @@ -39,7 +39,7 @@ import org.apache.spark.streaming.dstream.DStream */ object MLUtils { - private[util] lazy val EPSILON = { + private[mllib] lazy val EPSILON = { var eps = 1.0 while ((1.0 + (eps / 2.0)) != 1.0) { eps /= 2.0 diff --git a/mllib/src/test/scala/org/apache/spark/mllib/clustering/GMMExpectationMaximizationSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/clustering/GMMExpectationMaximizationSuite.scala new file mode 100644 index 0000000000000..23feb82874b70 --- /dev/null +++ b/mllib/src/test/scala/org/apache/spark/mllib/clustering/GMMExpectationMaximizationSuite.scala @@ -0,0 +1,78 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.mllib.clustering + +import org.scalatest.FunSuite + +import org.apache.spark.mllib.linalg.{Vectors, Matrices} +import org.apache.spark.mllib.util.MLlibTestSparkContext +import org.apache.spark.mllib.util.TestingUtils._ + +class GMMExpectationMaximizationSuite extends FunSuite with MLlibTestSparkContext { + test("single cluster") { + val data = sc.parallelize(Array( + Vectors.dense(6.0, 9.0), + Vectors.dense(5.0, 10.0), + Vectors.dense(4.0, 11.0) + )) + + // expectations + val Ew = 1.0 + val Emu = Vectors.dense(5.0, 10.0) + val Esigma = Matrices.dense(2, 2, Array(2.0 / 3.0, -2.0 / 3.0, -2.0 / 3.0, 2.0 / 3.0)) + + val gmm = new GaussianMixtureEM().setK(1).run(data) + + assert(gmm.weight(0) ~== Ew absTol 1E-5) + assert(gmm.mu(0) ~== Emu absTol 1E-5) + assert(gmm.sigma(0) ~== Esigma absTol 1E-5) + } + + test("two clusters") { + val data = sc.parallelize(Array( + Vectors.dense(-5.1971), Vectors.dense(-2.5359), Vectors.dense(-3.8220), + Vectors.dense(-5.2211), Vectors.dense(-5.0602), Vectors.dense( 4.7118), + Vectors.dense( 6.8989), Vectors.dense( 3.4592), Vectors.dense( 4.6322), + Vectors.dense( 5.7048), Vectors.dense( 4.6567), Vectors.dense( 5.5026), + Vectors.dense( 4.5605), Vectors.dense( 5.2043), Vectors.dense( 6.2734) + )) + + // we set an initial gaussian to induce expected results + val initialGmm = new GaussianMixtureModel( + Array(0.5, 0.5), + Array(Vectors.dense(-1.0), Vectors.dense(1.0)), + Array(Matrices.dense(1, 1, Array(1.0)), Matrices.dense(1, 1, Array(1.0))) + ) + + val Ew = Array(1.0 / 3.0, 2.0 / 3.0) + val Emu = Array(Vectors.dense(-4.3673), Vectors.dense(5.1604)) + val Esigma = Array(Matrices.dense(1, 1, Array(1.1098)), Matrices.dense(1, 1, Array(0.86644))) + + val gmm = new GaussianMixtureEM() + .setK(2) + .setInitialModel(initialGmm) + .run(data) + + assert(gmm.weight(0) ~== Ew(0) absTol 1E-3) + assert(gmm.weight(1) ~== Ew(1) absTol 1E-3) + assert(gmm.mu(0) ~== Emu(0) absTol 1E-3) + assert(gmm.mu(1) ~== Emu(1) absTol 1E-3) + assert(gmm.sigma(0) ~== Esigma(0) absTol 1E-3) + assert(gmm.sigma(1) ~== Esigma(1) absTol 1E-3) + } +} From 343db392b58fb33a3e4bc6fda1da69aaf686b5a9 Mon Sep 17 00:00:00 2001 From: ganonp Date: Mon, 29 Dec 2014 15:31:19 -0800 Subject: [PATCH 121/320] Added setMinCount to Word2Vec.scala Wanted to customize the private minCount variable in the Word2Vec class. Added a method to do so. Author: ganonp Closes #3693 from ganonp/my-custom-spark and squashes the following commits: ad534f2 [ganonp] made norm method public 5110a6f [ganonp] Reorganized 854958b [ganonp] Fixed Indentation for setMinCount 12ed8f9 [ganonp] Update Word2Vec.scala 76bdf5a [ganonp] Update Word2Vec.scala ffb88bb [ganonp] Update Word2Vec.scala 5eb9100 [ganonp] Added setMinCount to Word2Vec.scala --- .../org/apache/spark/mllib/feature/Word2Vec.scala | 15 +++++++++++---- .../org/apache/spark/mllib/linalg/Vectors.scala | 2 +- 2 files changed, 12 insertions(+), 5 deletions(-) diff --git a/mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala b/mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala index 7960f3cab576f..d25a7cd5b439d 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/feature/Word2Vec.scala @@ -71,7 +71,8 @@ class Word2Vec extends Serializable with Logging { private var numPartitions = 1 private var numIterations = 1 private var seed = Utils.random.nextLong() - + private var minCount = 5 + /** * Sets vector size (default: 100). */ @@ -114,6 +115,15 @@ class Word2Vec extends Serializable with Logging { this } + /** + * Sets minCount, the minimum number of times a token must appear to be included in the word2vec + * model's vocabulary (default: 5). + */ + def setMinCount(minCount: Int): this.type = { + this.minCount = minCount + this + } + private val EXP_TABLE_SIZE = 1000 private val MAX_EXP = 6 private val MAX_CODE_LENGTH = 40 @@ -122,9 +132,6 @@ class Word2Vec extends Serializable with Logging { /** context words from [-window, window] */ private val window = 5 - /** minimum frequency to consider a vocabulary word */ - private val minCount = 5 - private var trainWordsCount = 0 private var vocabSize = 0 private var vocab: Array[VocabWord] = null diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala index 47d1a76fa361d..01f3f90577142 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala @@ -268,7 +268,7 @@ object Vectors { * @param p norm. * @return norm in L^p^ space. */ - private[spark] def norm(vector: Vector, p: Double): Double = { + def norm(vector: Vector, p: Double): Double = { require(p >= 1.0) val values = vector match { case dv: DenseVector => dv.values From 040d6f2d13b132b3ef2a1e4f12f9f0e781c5a0b8 Mon Sep 17 00:00:00 2001 From: DB Tsai Date: Mon, 29 Dec 2014 17:17:12 -0800 Subject: [PATCH 122/320] [SPARK-4972][MLlib] Updated the scala doc for lasso and ridge regression for the change of LeastSquaresGradient In #SPARK-4907, we added factor of 2 into the LeastSquaresGradient. We updated the scala doc for lasso and ridge regression here. Author: DB Tsai Closes #3808 from dbtsai/doc and squashes the following commits: ec3c989 [DB Tsai] first commit --- .../main/scala/org/apache/spark/mllib/regression/Lasso.scala | 2 +- .../org/apache/spark/mllib/regression/RidgeRegression.scala | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala b/mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala index f9791c6571782..8ecd5c6ad93c0 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala @@ -45,7 +45,7 @@ class LassoModel ( /** * Train a regression model with L1-regularization using Stochastic Gradient Descent. * This solves the l1-regularized least squares regression formulation - * f(weights) = 1/n ||A weights-y||^2 + regParam ||weights||_1 + * f(weights) = 1/2n ||A weights-y||^2 + regParam ||weights||_1 * Here the data matrix has n rows, and the input RDD holds the set of rows of A, each with * its corresponding right hand side label y. * See also the documentation for the precise formulation. diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala b/mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala index c8cad773f5efb..076ba35051c9d 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala @@ -45,7 +45,7 @@ class RidgeRegressionModel ( /** * Train a regression model with L2-regularization using Stochastic Gradient Descent. * This solves the l1-regularized least squares regression formulation - * f(weights) = 1/n ||A weights-y||^2 + regParam/2 ||weights||^2 + * f(weights) = 1/2n ||A weights-y||^2 + regParam/2 ||weights||^2 * Here the data matrix has n rows, and the input RDD holds the set of rows of A, each with * its corresponding right hand side label y. * See also the documentation for the precise formulation. From 9077e721cd36adfecd50cbd1fd7735d28e5be8b5 Mon Sep 17 00:00:00 2001 From: "Zhang, Liye" Date: Tue, 30 Dec 2014 09:19:47 -0800 Subject: [PATCH 123/320] [SPARK-4920][UI] add version on master and worker page for standalone mode Author: Zhang, Liye Closes #3769 from liyezhang556520/spark-4920_WebVersion and squashes the following commits: 3bb7e0d [Zhang, Liye] add version on master and worker page --- core/src/main/scala/org/apache/spark/ui/UIUtils.scala | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/ui/UIUtils.scala b/core/src/main/scala/org/apache/spark/ui/UIUtils.scala index 7486cb6b1bbc0..b5022fe853c49 100644 --- a/core/src/main/scala/org/apache/spark/ui/UIUtils.scala +++ b/core/src/main/scala/org/apache/spark/ui/UIUtils.scala @@ -234,8 +234,9 @@ private[spark] object UIUtils extends Logging {

- + + {org.apache.spark.SPARK_VERSION} {title}

From efa80a531ecd485f6cf0cdc24ffa42ba17eea46d Mon Sep 17 00:00:00 2001 From: Josh Rosen Date: Tue, 30 Dec 2014 09:29:52 -0800 Subject: [PATCH 124/320] [SPARK-4882] Register PythonBroadcast with Kryo so that PySpark works with KryoSerializer This PR fixes an issue where PySpark broadcast variables caused NullPointerExceptions if KryoSerializer was used. The fix is to register PythonBroadcast with Kryo so that it's deserialized with a KryoJavaSerializer. Author: Josh Rosen Closes #3831 from JoshRosen/SPARK-4882 and squashes the following commits: 0466c7a [Josh Rosen] Register PythonBroadcast with Kryo. d5b409f [Josh Rosen] Enable registrationRequired, which would have caught this bug. 069d8a7 [Josh Rosen] Add failing test for SPARK-4882 --- .../spark/serializer/KryoSerializer.scala | 2 + .../api/python/PythonBroadcastSuite.scala | 60 +++++++++++++++++++ 2 files changed, 62 insertions(+) create mode 100644 core/src/test/scala/org/apache/spark/api/python/PythonBroadcastSuite.scala diff --git a/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala b/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala index 621a951c27d07..d2947dcea4f7c 100644 --- a/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala +++ b/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala @@ -26,6 +26,7 @@ import com.esotericsoftware.kryo.serializers.{JavaSerializer => KryoJavaSerializ import com.twitter.chill.{AllScalaRegistrar, EmptyScalaKryoInstantiator} import org.apache.spark._ +import org.apache.spark.api.python.PythonBroadcast import org.apache.spark.broadcast.HttpBroadcast import org.apache.spark.network.nio.{PutBlock, GotBlock, GetBlock} import org.apache.spark.scheduler.MapStatus @@ -90,6 +91,7 @@ class KryoSerializer(conf: SparkConf) // Allow sending SerializableWritable kryo.register(classOf[SerializableWritable[_]], new KryoJavaSerializer()) kryo.register(classOf[HttpBroadcast[_]], new KryoJavaSerializer()) + kryo.register(classOf[PythonBroadcast], new KryoJavaSerializer()) try { // Use the default classloader when calling the user registrator. diff --git a/core/src/test/scala/org/apache/spark/api/python/PythonBroadcastSuite.scala b/core/src/test/scala/org/apache/spark/api/python/PythonBroadcastSuite.scala new file mode 100644 index 0000000000000..8959a843dbd7d --- /dev/null +++ b/core/src/test/scala/org/apache/spark/api/python/PythonBroadcastSuite.scala @@ -0,0 +1,60 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.api.python + +import scala.io.Source + +import java.io.{PrintWriter, File} + +import org.scalatest.{Matchers, FunSuite} + +import org.apache.spark.{SharedSparkContext, SparkConf} +import org.apache.spark.serializer.KryoSerializer +import org.apache.spark.util.Utils + +// This test suite uses SharedSparkContext because we need a SparkEnv in order to deserialize +// a PythonBroadcast: +class PythonBroadcastSuite extends FunSuite with Matchers with SharedSparkContext { + test("PythonBroadcast can be serialized with Kryo (SPARK-4882)") { + val tempDir = Utils.createTempDir() + val broadcastedString = "Hello, world!" + def assertBroadcastIsValid(broadcast: PythonBroadcast): Unit = { + val source = Source.fromFile(broadcast.path) + val contents = source.mkString + source.close() + contents should be (broadcastedString) + } + try { + val broadcastDataFile: File = { + val file = new File(tempDir, "broadcastData") + val printWriter = new PrintWriter(file) + printWriter.write(broadcastedString) + printWriter.close() + file + } + val broadcast = new PythonBroadcast(broadcastDataFile.getAbsolutePath) + assertBroadcastIsValid(broadcast) + val conf = new SparkConf().set("spark.kryo.registrationRequired", "true") + val deserializedBroadcast = + Utils.clone[PythonBroadcast](broadcast, new KryoSerializer(conf).newInstance()) + assertBroadcastIsValid(deserializedBroadcast) + } finally { + Utils.deleteRecursively(tempDir) + } + } +} From 480bd1d2edd1de06af607b0cf3ff3c0b16089add Mon Sep 17 00:00:00 2001 From: Michael Armbrust Date: Tue, 30 Dec 2014 11:24:46 -0800 Subject: [PATCH 125/320] [SPARK-4908][SQL] Prevent multiple concurrent hive native commands This is just a quick fix that locks when calling `runHive`. If we can find a way to avoid the error without a global lock that would be better. Author: Michael Armbrust Closes #3834 from marmbrus/hiveConcurrency and squashes the following commits: bf25300 [Michael Armbrust] prevent multiple concurrent hive native commands --- .../main/scala/org/apache/spark/sql/hive/HiveContext.scala | 2 +- .../apache/spark/sql/hive/execution/HiveQuerySuite.scala | 7 +++++++ 2 files changed, 8 insertions(+), 1 deletion(-) diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala index 56fe27a77b838..982e0593fcfd1 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala @@ -284,7 +284,7 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { * Execute the command using Hive and return the results as a sequence. Each element * in the sequence is one row. */ - protected def runHive(cmd: String, maxRows: Int = 1000): Seq[String] = { + protected def runHive(cmd: String, maxRows: Int = 1000): Seq[String] = synchronized { try { val cmd_trimmed: String = cmd.trim() val tokens: Array[String] = cmd_trimmed.split("\\s+") diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala index 4d81acc753a27..fb6da33e88ef6 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala @@ -56,6 +56,13 @@ class HiveQuerySuite extends HiveComparisonTest with BeforeAndAfter { Locale.setDefault(originalLocale) } + test("SPARK-4908: concurent hive native commands") { + (1 to 100).par.map { _ => + sql("USE default") + sql("SHOW TABLES") + } + } + createQueryTest("constant object inspector for generic udf", """SELECT named_struct( lower("AA"), "10", From 94d60b7021960dc10d98039dbc6ad7193e8557f5 Mon Sep 17 00:00:00 2001 From: Daoyuan Wang Date: Tue, 30 Dec 2014 11:29:13 -0800 Subject: [PATCH 126/320] [SQL] enable view test This is a follow up of #3396 , just add a test to white list. Author: Daoyuan Wang Closes #3826 from adrian-wang/viewtest and squashes the following commits: f105f68 [Daoyuan Wang] enable view test --- .../execution/HiveCompatibilitySuite.scala | 3 +- ...anslate-0-dc7fc9ce5109ef459ee84ccfbb12d2c0 | 0 ...anslate-1-3896ae0e680a5fdc01833533b11c07bb | 0 ...nslate-10-7016e1e3a4248564f3d08cddad7ae116 | 0 ...nslate-11-e27c6a59a833dcbc2e5cdb7ff7972828 | 0 ...anslate-2-6b4caec6d7e3a91e61720bbd6b7697f0 | 0 ...anslate-3-30dc3e80e3873af5115e4f5e39078a13 | 27 ++++++++++++++++ ...anslate-4-cefb7530126f9e60cb4a29441d578f23 | 0 ...anslate-5-856ea995681b18a543dc0e53b8b43a8e | 32 +++++++++++++++++++ ...anslate-6-a14cfe3eff322066e61023ec06c7735d | 0 ...anslate-7-e947bf2dacc907825df154a4131a3fcc | 0 ...anslate-8-b1a99b0beffb0b298aec9233ecc0707f | 0 ...anslate-9-fc0dc39c4796d917685e0797bc4a9786 | 0 13 files changed, 61 insertions(+), 1 deletion(-) create mode 100644 sql/hive/src/test/resources/golden/create_view_translate-0-dc7fc9ce5109ef459ee84ccfbb12d2c0 create mode 100644 sql/hive/src/test/resources/golden/create_view_translate-1-3896ae0e680a5fdc01833533b11c07bb create mode 100644 sql/hive/src/test/resources/golden/create_view_translate-10-7016e1e3a4248564f3d08cddad7ae116 create mode 100644 sql/hive/src/test/resources/golden/create_view_translate-11-e27c6a59a833dcbc2e5cdb7ff7972828 create mode 100644 sql/hive/src/test/resources/golden/create_view_translate-2-6b4caec6d7e3a91e61720bbd6b7697f0 create mode 100644 sql/hive/src/test/resources/golden/create_view_translate-3-30dc3e80e3873af5115e4f5e39078a13 create mode 100644 sql/hive/src/test/resources/golden/create_view_translate-4-cefb7530126f9e60cb4a29441d578f23 create mode 100644 sql/hive/src/test/resources/golden/create_view_translate-5-856ea995681b18a543dc0e53b8b43a8e create mode 100644 sql/hive/src/test/resources/golden/create_view_translate-6-a14cfe3eff322066e61023ec06c7735d create mode 100644 sql/hive/src/test/resources/golden/create_view_translate-7-e947bf2dacc907825df154a4131a3fcc create mode 100644 sql/hive/src/test/resources/golden/create_view_translate-8-b1a99b0beffb0b298aec9233ecc0707f create mode 100644 sql/hive/src/test/resources/golden/create_view_translate-9-fc0dc39c4796d917685e0797bc4a9786 diff --git a/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala b/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala index 1e44dd239458a..23283fd3fe6b1 100644 --- a/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala +++ b/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala @@ -101,6 +101,7 @@ class HiveCompatibilitySuite extends HiveQueryFileTest with BeforeAndAfter { "describe_comment_nonascii", "create_merge_compressed", + "create_view", "create_view_partitioned", "database_location", "database_properties", @@ -110,7 +111,6 @@ class HiveCompatibilitySuite extends HiveQueryFileTest with BeforeAndAfter { // Weird DDL differences result in failures on jenkins. "create_like2", - "create_view_translate", "partitions_json", // This test is totally fine except that it includes wrong queries and expects errors, but error @@ -349,6 +349,7 @@ class HiveCompatibilitySuite extends HiveQueryFileTest with BeforeAndAfter { "create_nested_type", "create_skewed_table1", "create_struct_table", + "create_view_translate", "cross_join", "cross_product_check_1", "cross_product_check_2", diff --git a/sql/hive/src/test/resources/golden/create_view_translate-0-dc7fc9ce5109ef459ee84ccfbb12d2c0 b/sql/hive/src/test/resources/golden/create_view_translate-0-dc7fc9ce5109ef459ee84ccfbb12d2c0 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/create_view_translate-1-3896ae0e680a5fdc01833533b11c07bb b/sql/hive/src/test/resources/golden/create_view_translate-1-3896ae0e680a5fdc01833533b11c07bb new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/create_view_translate-10-7016e1e3a4248564f3d08cddad7ae116 b/sql/hive/src/test/resources/golden/create_view_translate-10-7016e1e3a4248564f3d08cddad7ae116 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/create_view_translate-11-e27c6a59a833dcbc2e5cdb7ff7972828 b/sql/hive/src/test/resources/golden/create_view_translate-11-e27c6a59a833dcbc2e5cdb7ff7972828 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/create_view_translate-2-6b4caec6d7e3a91e61720bbd6b7697f0 b/sql/hive/src/test/resources/golden/create_view_translate-2-6b4caec6d7e3a91e61720bbd6b7697f0 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/create_view_translate-3-30dc3e80e3873af5115e4f5e39078a13 b/sql/hive/src/test/resources/golden/create_view_translate-3-30dc3e80e3873af5115e4f5e39078a13 new file mode 100644 index 0000000000000..cec5f77033aa4 --- /dev/null +++ b/sql/hive/src/test/resources/golden/create_view_translate-3-30dc3e80e3873af5115e4f5e39078a13 @@ -0,0 +1,27 @@ +# col_name data_type comment + +key string + +# Detailed Table Information +Database: default +Owner: animal +CreateTime: Mon Dec 29 00:57:55 PST 2014 +LastAccessTime: UNKNOWN +Protect Mode: None +Retention: 0 +Table Type: VIRTUAL_VIEW +Table Parameters: + transient_lastDdlTime 1419843475 + +# Storage Information +SerDe Library: null +InputFormat: org.apache.hadoop.mapred.SequenceFileInputFormat +OutputFormat: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat +Compressed: No +Num Buckets: -1 +Bucket Columns: [] +Sort Columns: [] + +# View Information +View Original Text: select cast(key as string) from src +View Expanded Text: select cast(`src`.`key` as string) from `default`.`src` diff --git a/sql/hive/src/test/resources/golden/create_view_translate-4-cefb7530126f9e60cb4a29441d578f23 b/sql/hive/src/test/resources/golden/create_view_translate-4-cefb7530126f9e60cb4a29441d578f23 new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/create_view_translate-5-856ea995681b18a543dc0e53b8b43a8e b/sql/hive/src/test/resources/golden/create_view_translate-5-856ea995681b18a543dc0e53b8b43a8e new file mode 100644 index 0000000000000..bf582fc0964a3 --- /dev/null +++ b/sql/hive/src/test/resources/golden/create_view_translate-5-856ea995681b18a543dc0e53b8b43a8e @@ -0,0 +1,32 @@ +# col_name data_type comment + +key int +value string + +# Detailed Table Information +Database: default +Owner: animal +CreateTime: Mon Dec 29 00:57:55 PST 2014 +LastAccessTime: UNKNOWN +Protect Mode: None +Retention: 0 +Table Type: VIRTUAL_VIEW +Table Parameters: + transient_lastDdlTime 1419843475 + +# Storage Information +SerDe Library: null +InputFormat: org.apache.hadoop.mapred.SequenceFileInputFormat +OutputFormat: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat +Compressed: No +Num Buckets: -1 +Bucket Columns: [] +Sort Columns: [] + +# View Information +View Original Text: select key, value from ( + select key, value from src +) a +View Expanded Text: select key, value from ( + select `src`.`key`, `src`.`value` from `default`.`src` +) `a` diff --git a/sql/hive/src/test/resources/golden/create_view_translate-6-a14cfe3eff322066e61023ec06c7735d b/sql/hive/src/test/resources/golden/create_view_translate-6-a14cfe3eff322066e61023ec06c7735d new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/create_view_translate-7-e947bf2dacc907825df154a4131a3fcc b/sql/hive/src/test/resources/golden/create_view_translate-7-e947bf2dacc907825df154a4131a3fcc new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/create_view_translate-8-b1a99b0beffb0b298aec9233ecc0707f b/sql/hive/src/test/resources/golden/create_view_translate-8-b1a99b0beffb0b298aec9233ecc0707f new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/sql/hive/src/test/resources/golden/create_view_translate-9-fc0dc39c4796d917685e0797bc4a9786 b/sql/hive/src/test/resources/golden/create_view_translate-9-fc0dc39c4796d917685e0797bc4a9786 new file mode 100644 index 0000000000000..e69de29bb2d1d From 65357f11c25a7c91577df5da31ebf349d7845eef Mon Sep 17 00:00:00 2001 From: scwf Date: Tue, 30 Dec 2014 11:30:47 -0800 Subject: [PATCH 127/320] [SPARK-4975][SQL] Fix HiveInspectorSuite test failure MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit HiveInspectorSuite test failure： [info] - wrap / unwrap null, constant null and writables *** FAILED *** (21 milliseconds) [info] 1 did not equal 0 (HiveInspectorSuite.scala:136) this is because the origin date(is 3914-10-23) not equals the date returned by ```unwrap```(is 3914-10-22). Setting TimeZone and Locale fix this. Another minor change here is rename ```def checkValues(v1: Any, v2: Any): Unit``` to ```def checkValue(v1: Any, v2: Any): Unit ``` to make the code more clear Author: scwf Author: Fei Wang Closes #3814 from scwf/fix-inspectorsuite and squashes the following commits: d8531ef [Fei Wang] Delete test.log 72b19a9 [scwf] fix HiveInspectorSuite test error --- .../spark/sql/hive/HiveInspectorSuite.scala | 28 +++++++++++-------- 1 file changed, 17 insertions(+), 11 deletions(-) diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala index bfe608a51a30b..f90d3607915ae 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala @@ -19,6 +19,7 @@ package org.apache.spark.sql.hive import java.sql.Date import java.util +import java.util.{Locale, TimeZone} import org.apache.hadoop.hive.serde2.io.DoubleWritable import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory @@ -63,6 +64,11 @@ class HiveInspectorSuite extends FunSuite with HiveInspectors { .get()) } + // Timezone is fixed to America/Los_Angeles for those timezone sensitive tests (timestamp_*) + TimeZone.setDefault(TimeZone.getTimeZone("America/Los_Angeles")) + // Add Locale setting + Locale.setDefault(Locale.US) + val data = Literal(true) :: Literal(0.asInstanceOf[Byte]) :: @@ -121,11 +127,11 @@ class HiveInspectorSuite extends FunSuite with HiveInspectors { def checkValues(row1: Seq[Any], row2: Seq[Any]): Unit = { row1.zip(row2).map { - case (r1, r2) => checkValues(r1, r2) + case (r1, r2) => checkValue(r1, r2) } } - def checkValues(v1: Any, v2: Any): Unit = { + def checkValue(v1: Any, v2: Any): Unit = { (v1, v2) match { case (r1: Decimal, r2: Decimal) => // Ignore the Decimal precision @@ -195,26 +201,26 @@ class HiveInspectorSuite extends FunSuite with HiveInspectors { }) checkValues(row, unwrap(wrap(row, toInspector(dt)), toInspector(dt)).asInstanceOf[Row]) - checkValues(null, unwrap(wrap(null, toInspector(dt)), toInspector(dt))) + checkValue(null, unwrap(wrap(null, toInspector(dt)), toInspector(dt))) } test("wrap / unwrap Array Type") { val dt = ArrayType(dataTypes(0)) val d = row(0) :: row(0) :: Nil - checkValues(d, unwrap(wrap(d, toInspector(dt)), toInspector(dt))) - checkValues(null, unwrap(wrap(null, toInspector(dt)), toInspector(dt))) - checkValues(d, unwrap(wrap(d, toInspector(Literal(d, dt))), toInspector(Literal(d, dt)))) - checkValues(d, unwrap(wrap(null, toInspector(Literal(d, dt))), toInspector(Literal(d, dt)))) + checkValue(d, unwrap(wrap(d, toInspector(dt)), toInspector(dt))) + checkValue(null, unwrap(wrap(null, toInspector(dt)), toInspector(dt))) + checkValue(d, unwrap(wrap(d, toInspector(Literal(d, dt))), toInspector(Literal(d, dt)))) + checkValue(d, unwrap(wrap(null, toInspector(Literal(d, dt))), toInspector(Literal(d, dt)))) } test("wrap / unwrap Map Type") { val dt = MapType(dataTypes(0), dataTypes(1)) val d = Map(row(0) -> row(1)) - checkValues(d, unwrap(wrap(d, toInspector(dt)), toInspector(dt))) - checkValues(null, unwrap(wrap(null, toInspector(dt)), toInspector(dt))) - checkValues(d, unwrap(wrap(d, toInspector(Literal(d, dt))), toInspector(Literal(d, dt)))) - checkValues(d, unwrap(wrap(null, toInspector(Literal(d, dt))), toInspector(Literal(d, dt)))) + checkValue(d, unwrap(wrap(d, toInspector(dt)), toInspector(dt))) + checkValue(null, unwrap(wrap(null, toInspector(dt)), toInspector(dt))) + checkValue(d, unwrap(wrap(d, toInspector(Literal(d, dt))), toInspector(Literal(d, dt)))) + checkValue(d, unwrap(wrap(null, toInspector(Literal(d, dt))), toInspector(Literal(d, dt)))) } } From 5595eaa74f139fdb6fd8a7bb0ca6ed421ef00ac8 Mon Sep 17 00:00:00 2001 From: Cheng Hao Date: Tue, 30 Dec 2014 11:33:47 -0800 Subject: [PATCH 128/320] [SPARK-4959] [SQL] Attributes are case sensitive when using a select query from a projection Author: Cheng Hao Closes #3796 from chenghao-intel/spark_4959 and squashes the following commits: 3ec08f8 [Cheng Hao] Replace the attribute in comparing its exprId other than itself --- .../spark/sql/catalyst/optimizer/Optimizer.scala | 8 ++++---- .../sql/hive/execution/HiveTableScanSuite.scala | 14 +++++++++++++- 2 files changed, 17 insertions(+), 5 deletions(-) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala index 806c1394eb151..0f2eae6400d21 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala @@ -142,16 +142,16 @@ object ColumnPruning extends Rule[LogicalPlan] { case Project(projectList1, Project(projectList2, child)) => // Create a map of Aliases to their values from the child projection. // e.g., 'SELECT ... FROM (SELECT a + b AS c, d ...)' produces Map(c -> Alias(a + b, c)). - val aliasMap = projectList2.collect { - case a @ Alias(e, _) => (a.toAttribute: Expression, a) - }.toMap + val aliasMap = AttributeMap(projectList2.collect { + case a @ Alias(e, _) => (a.toAttribute, a) + }) // Substitute any attributes that are produced by the child projection, so that we safely // eliminate it. // e.g., 'SELECT c + 1 FROM (SELECT a + b AS C ...' produces 'SELECT a + b + 1 ...' // TODO: Fix TransformBase to avoid the cast below. val substitutedProjection = projectList1.map(_.transform { - case a if aliasMap.contains(a) => aliasMap(a) + case a: Attribute if aliasMap.contains(a) => aliasMap(a) }).asInstanceOf[Seq[NamedExpression]] Project(substitutedProjection, child) diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveTableScanSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveTableScanSuite.scala index a0ace91060a28..16f77a438e1ae 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveTableScanSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveTableScanSuite.scala @@ -18,7 +18,8 @@ package org.apache.spark.sql.hive.execution import org.apache.spark.sql.hive.test.TestHive -import org.apache.spark.sql.{Row, SchemaRDD} +import org.apache.spark.sql.hive.test.TestHive._ +import org.apache.spark.sql.Row import org.apache.spark.util.Utils @@ -76,4 +77,15 @@ class HiveTableScanSuite extends HiveComparisonTest { === Array(Row(java.sql.Timestamp.valueOf("2014-12-11 00:00:00")),Row(null))) TestHive.sql("DROP TABLE timestamp_query_null") } + + test("Spark-4959 Attributes are case sensitive when using a select query from a projection") { + sql("create table spark_4959 (col1 string)") + sql("""insert into table spark_4959 select "hi" from src limit 1""") + table("spark_4959").select( + 'col1.as('CaseSensitiveColName), + 'col1.as('CaseSensitiveColName2)).registerTempTable("spark_4959_2") + + assert(sql("select CaseSensitiveColName from spark_4959_2").first() === Row("hi")) + assert(sql("select casesensitivecolname from spark_4959_2").first() === Row("hi")) + } } From 63b84b7d6785a687dd7f4c0e2bb1e348800d30d8 Mon Sep 17 00:00:00 2001 From: Cheng Hao Date: Tue, 30 Dec 2014 11:47:08 -0800 Subject: [PATCH 129/320] [SPARK-4904] [SQL] Remove the unnecessary code change in Generic UDF Since #3429 has been merged, the bug of wrapping to Writable for HiveGenericUDF is resolved, we can safely remove the foldable checking in `HiveGenericUdf.eval`, which discussed in #2802. Author: Cheng Hao Closes #3745 from chenghao-intel/generic_udf and squashes the following commits: 622ad03 [Cheng Hao] Remove the unnecessary code change in Generic UDF --- .../src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala | 6 ------ 1 file changed, 6 deletions(-) diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala index 93b6ef9fbc59b..7d863f9d89dae 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala @@ -158,11 +158,6 @@ private[hive] case class HiveGenericUdf(funcWrapper: HiveFunctionWrapper, childr override def foldable = isUDFDeterministic && returnInspector.isInstanceOf[ConstantObjectInspector] - @transient - protected def constantReturnValue = unwrap( - returnInspector.asInstanceOf[ConstantObjectInspector].getWritableConstantValue(), - returnInspector) - @transient protected lazy val deferedObjects = argumentInspectors.map(new DeferredObjectAdapter(_)).toArray[DeferredObject] @@ -171,7 +166,6 @@ private[hive] case class HiveGenericUdf(funcWrapper: HiveFunctionWrapper, childr override def eval(input: Row): Any = { returnInspector // Make sure initialized. - if(foldable) return constantReturnValue var i = 0 while (i < children.length) { From daac221302e0cf71a7b7bda31625134cf7b9dce1 Mon Sep 17 00:00:00 2001 From: wangfei Date: Tue, 30 Dec 2014 12:07:24 -0800 Subject: [PATCH 130/320] [SPARK-5002][SQL] Using ascending by default when not specify order in order by spark sql does not support ```SELECT a, b FROM testData2 ORDER BY a desc, b```. Author: wangfei Closes #3838 from scwf/orderby and squashes the following commits: 114b64a [wangfei] remove nouse methods 48145d3 [wangfei] fix order, using asc by default --- .../scala/org/apache/spark/sql/catalyst/SqlParser.scala | 8 ++------ .../test/scala/org/apache/spark/sql/SQLQuerySuite.scala | 7 +++++++ 2 files changed, 9 insertions(+), 6 deletions(-) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala index d4fc9bbfd3118..66860a4c0923a 100755 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala @@ -209,15 +209,11 @@ class SqlParser extends AbstractSparkSQLParser { ) protected lazy val ordering: Parser[Seq[SortOrder]] = - ( rep1sep(singleOrder, ",") - | rep1sep(expression, ",") ~ direction.? ^^ { - case exps ~ d => exps.map(SortOrder(_, d.getOrElse(Ascending))) + ( rep1sep(expression ~ direction.? , ",") ^^ { + case exps => exps.map(pair => SortOrder(pair._1, pair._2.getOrElse(Ascending))) } ) - protected lazy val singleOrder: Parser[SortOrder] = - expression ~ direction ^^ { case e ~ o => SortOrder(e, o) } - protected lazy val direction: Parser[SortDirection] = ( ASC ^^^ Ascending | DESC ^^^ Descending diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala index ddf4776ecf7ae..add4e218a22ee 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala @@ -987,6 +987,13 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll { ) } + test("oder by asc by default when not specify ascending and descending") { + checkAnswer( + sql("SELECT a, b FROM testData2 ORDER BY a desc, b"), + Seq((3, 1), (3, 2), (2, 1), (2,2), (1, 1), (1, 2)) + ) + } + test("Supporting relational operator '<=>' in Spark SQL") { val nullCheckData1 = TestData(1,"1") :: TestData(2,null) :: Nil val rdd1 = sparkContext.parallelize((0 to 1).map(i => nullCheckData1(i))) From 53f0a00b6051fb6cb52a90f91ae01bcd77e332c5 Mon Sep 17 00:00:00 2001 From: Cheng Hao Date: Tue, 30 Dec 2014 12:11:44 -0800 Subject: [PATCH 131/320] [Spark-4512] [SQL] Unresolved Attribute Exception in Sort By It will cause exception while do query like: SELECT key+key FROM src sort by value; Author: Cheng Hao Closes #3386 from chenghao-intel/sort and squashes the following commits: 38c78cc [Cheng Hao] revert the SortPartition in SparkStrategies 7e9dd15 [Cheng Hao] update the typo fcd1d64 [Cheng Hao] rebase the latest master and update the SortBy unit test --- .../apache/spark/sql/catalyst/SqlParser.scala | 4 ++-- .../sql/catalyst/analysis/Analyzer.scala | 13 +++++++------ .../spark/sql/catalyst/dsl/package.scala | 4 ++-- .../plans/logical/basicOperators.scala | 11 ++++++++++- .../org/apache/spark/sql/SchemaRDD.scala | 5 ++--- .../spark/sql/execution/SparkStrategies.scala | 11 +++++------ .../org/apache/spark/sql/DslQuerySuite.scala | 19 ++++++++++++++----- .../scala/org/apache/spark/sql/TestData.scala | 2 +- .../org/apache/spark/sql/hive/HiveQl.scala | 8 ++++---- .../hive/execution/HiveComparisonTest.scala | 2 +- .../sql/hive/execution/SQLQuerySuite.scala | 7 +++++++ 11 files changed, 55 insertions(+), 31 deletions(-) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala index 66860a4c0923a..f79d4ff444dc0 100755 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala @@ -204,8 +204,8 @@ class SqlParser extends AbstractSparkSQLParser { ) protected lazy val sortType: Parser[LogicalPlan => LogicalPlan] = - ( ORDER ~ BY ~> ordering ^^ { case o => l: LogicalPlan => Sort(o, l) } - | SORT ~ BY ~> ordering ^^ { case o => l: LogicalPlan => SortPartitions(o, l) } + ( ORDER ~ BY ~> ordering ^^ { case o => l: LogicalPlan => Sort(o, true, l) } + | SORT ~ BY ~> ordering ^^ { case o => l: LogicalPlan => Sort(o, false, l) } ) protected lazy val ordering: Parser[Seq[SortOrder]] = diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala index 1c4088b8438e1..72680f37a0b4d 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala @@ -246,7 +246,7 @@ class Analyzer(catalog: Catalog, case p: LogicalPlan if !p.childrenResolved => p // If the projection list contains Stars, expand it. - case p@Project(projectList, child) if containsStar(projectList) => + case p @ Project(projectList, child) if containsStar(projectList) => Project( projectList.flatMap { case s: Star => s.expand(child.output, resolver) @@ -310,7 +310,8 @@ class Analyzer(catalog: Catalog, */ object ResolveSortReferences extends Rule[LogicalPlan] { def apply(plan: LogicalPlan): LogicalPlan = plan transformUp { - case s @ Sort(ordering, p @ Project(projectList, child)) if !s.resolved && p.resolved => + case s @ Sort(ordering, global, p @ Project(projectList, child)) + if !s.resolved && p.resolved => val unresolved = ordering.flatMap(_.collect { case UnresolvedAttribute(name) => name }) val resolved = unresolved.flatMap(child.resolve(_, resolver)) val requiredAttributes = AttributeSet(resolved.collect { case a: Attribute => a }) @@ -319,13 +320,14 @@ class Analyzer(catalog: Catalog, if (missingInProject.nonEmpty) { // Add missing attributes and then project them away after the sort. Project(projectList.map(_.toAttribute), - Sort(ordering, + Sort(ordering, global, Project(projectList ++ missingInProject, child))) } else { logDebug(s"Failed to find $missingInProject in ${p.output.mkString(", ")}") s // Nothing we can do here. Return original plan. } - case s @ Sort(ordering, a @ Aggregate(grouping, aggs, child)) if !s.resolved && a.resolved => + case s @ Sort(ordering, global, a @ Aggregate(grouping, aggs, child)) + if !s.resolved && a.resolved => val unresolved = ordering.flatMap(_.collect { case UnresolvedAttribute(name) => name }) // A small hack to create an object that will allow us to resolve any references that // refer to named expressions that are present in the grouping expressions. @@ -340,8 +342,7 @@ class Analyzer(catalog: Catalog, if (missingInAggs.nonEmpty) { // Add missing grouping exprs and then project them away after the sort. Project(a.output, - Sort(ordering, - Aggregate(grouping, aggs ++ missingInAggs, child))) + Sort(ordering, global, Aggregate(grouping, aggs ++ missingInAggs, child))) } else { s // Nothing we can do here. Return original plan. } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala index fb252cdf51534..a14e5b9ef14d0 100755 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala @@ -244,9 +244,9 @@ package object dsl { condition: Option[Expression] = None) = Join(logicalPlan, otherPlan, joinType, condition) - def orderBy(sortExprs: SortOrder*) = Sort(sortExprs, logicalPlan) + def orderBy(sortExprs: SortOrder*) = Sort(sortExprs, true, logicalPlan) - def sortBy(sortExprs: SortOrder*) = SortPartitions(sortExprs, logicalPlan) + def sortBy(sortExprs: SortOrder*) = Sort(sortExprs, false, logicalPlan) def groupBy(groupingExprs: Expression*)(aggregateExprs: Expression*) = { val aliasedExprs = aggregateExprs.map { diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala index a9282b98adfab..0b9f01cbae9ea 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala @@ -130,7 +130,16 @@ case class WriteToFile( override def output = child.output } -case class Sort(order: Seq[SortOrder], child: LogicalPlan) extends UnaryNode { +/** + * @param order The ordering expressions + * @param global True means global sorting apply for entire data set, + * False means sorting only apply within the partition. + * @param child Child logical plan + */ +case class Sort( + order: Seq[SortOrder], + global: Boolean, + child: LogicalPlan) extends UnaryNode { override def output = child.output } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala index 856b10f1a8fd8..80787b61ce1bf 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala @@ -214,7 +214,7 @@ class SchemaRDD( * @group Query */ def orderBy(sortExprs: SortOrder*): SchemaRDD = - new SchemaRDD(sqlContext, Sort(sortExprs, logicalPlan)) + new SchemaRDD(sqlContext, Sort(sortExprs, true, logicalPlan)) /** * Sorts the results by the given expressions within partition. @@ -227,7 +227,7 @@ class SchemaRDD( * @group Query */ def sortBy(sortExprs: SortOrder*): SchemaRDD = - new SchemaRDD(sqlContext, SortPartitions(sortExprs, logicalPlan)) + new SchemaRDD(sqlContext, Sort(sortExprs, false, logicalPlan)) @deprecated("use limit with integer argument", "1.1.0") def limit(limitExpr: Expression): SchemaRDD = @@ -238,7 +238,6 @@ class SchemaRDD( * {{{ * schemaRDD.limit(10) * }}} - * * @group Query */ def limit(limitNum: Int): SchemaRDD = diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala index 2954d4ce7d2d8..9151da69ed44c 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala @@ -190,7 +190,7 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { object TakeOrdered extends Strategy { def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match { - case logical.Limit(IntegerLiteral(limit), logical.Sort(order, child)) => + case logical.Limit(IntegerLiteral(limit), logical.Sort(order, true, child)) => execution.TakeOrdered(limit, order, planLater(child)) :: Nil case _ => Nil } @@ -257,15 +257,14 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { execution.Distinct(partial = false, execution.Distinct(partial = true, planLater(child))) :: Nil - case logical.Sort(sortExprs, child) if sqlContext.externalSortEnabled => - execution.ExternalSort(sortExprs, global = true, planLater(child)):: Nil - case logical.Sort(sortExprs, child) => - execution.Sort(sortExprs, global = true, planLater(child)):: Nil - case logical.SortPartitions(sortExprs, child) => // This sort only sorts tuples within a partition. Its requiredDistribution will be // an UnspecifiedDistribution. execution.Sort(sortExprs, global = false, planLater(child)) :: Nil + case logical.Sort(sortExprs, global, child) if sqlContext.externalSortEnabled => + execution.ExternalSort(sortExprs, global, planLater(child)):: Nil + case logical.Sort(sortExprs, global, child) => + execution.Sort(sortExprs, global, planLater(child)):: Nil case logical.Project(projectList, child) => execution.Project(projectList, planLater(child)) :: Nil case logical.Filter(condition, child) => diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala index 691c4b38287bf..c0b9cf5163120 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala @@ -88,7 +88,7 @@ class DslQuerySuite extends QueryTest { Seq(Seq(6))) } - test("sorting") { + test("global sorting") { checkAnswer( testData2.orderBy('a.asc, 'b.asc), Seq((1,1), (1,2), (2,1), (2,2), (3,1), (3,2))) @@ -122,22 +122,31 @@ class DslQuerySuite extends QueryTest { mapData.collect().sortBy(_.data(1)).reverse.toSeq) } - test("sorting #2") { + test("partition wide sorting") { + // 2 partitions totally, and + // Partition #1 with values: + // (1, 1) + // (1, 2) + // (2, 1) + // Partition #2 with values: + // (2, 2) + // (3, 1) + // (3, 2) checkAnswer( testData2.sortBy('a.asc, 'b.asc), Seq((1,1), (1,2), (2,1), (2,2), (3,1), (3,2))) checkAnswer( testData2.sortBy('a.asc, 'b.desc), - Seq((1,2), (1,1), (2,2), (2,1), (3,2), (3,1))) + Seq((1,2), (1,1), (2,1), (2,2), (3,2), (3,1))) checkAnswer( testData2.sortBy('a.desc, 'b.desc), - Seq((3,2), (3,1), (2,2), (2,1), (1,2), (1,1))) + Seq((2,1), (1,2), (1,1), (3,2), (3,1), (2,2))) checkAnswer( testData2.sortBy('a.desc, 'b.asc), - Seq((3,1), (3,2), (2,1), (2,2), (1,1), (1,2))) + Seq((2,1), (1,1), (1,2), (3,1), (3,2), (2,2))) } test("limit") { diff --git a/sql/core/src/test/scala/org/apache/spark/sql/TestData.scala b/sql/core/src/test/scala/org/apache/spark/sql/TestData.scala index bb553a0a1e50c..497897c3c0d4d 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/TestData.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/TestData.scala @@ -55,7 +55,7 @@ object TestData { TestData2(2, 1) :: TestData2(2, 2) :: TestData2(3, 1) :: - TestData2(3, 2) :: Nil).toSchemaRDD + TestData2(3, 2) :: Nil, 2).toSchemaRDD testData2.registerTempTable("testData2") case class DecimalData(a: BigDecimal, b: BigDecimal) diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala index 3f3d9e7cd4fbe..8a9613cf96e54 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala @@ -680,16 +680,16 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C val withSort = (orderByClause, sortByClause, distributeByClause, clusterByClause) match { case (Some(totalOrdering), None, None, None) => - Sort(totalOrdering.getChildren.map(nodeToSortOrder), withHaving) + Sort(totalOrdering.getChildren.map(nodeToSortOrder), true, withHaving) case (None, Some(perPartitionOrdering), None, None) => - SortPartitions(perPartitionOrdering.getChildren.map(nodeToSortOrder), withHaving) + Sort(perPartitionOrdering.getChildren.map(nodeToSortOrder), false, withHaving) case (None, None, Some(partitionExprs), None) => Repartition(partitionExprs.getChildren.map(nodeToExpr), withHaving) case (None, Some(perPartitionOrdering), Some(partitionExprs), None) => - SortPartitions(perPartitionOrdering.getChildren.map(nodeToSortOrder), + Sort(perPartitionOrdering.getChildren.map(nodeToSortOrder), false, Repartition(partitionExprs.getChildren.map(nodeToExpr), withHaving)) case (None, None, None, Some(clusterExprs)) => - SortPartitions(clusterExprs.getChildren.map(nodeToExpr).map(SortOrder(_, Ascending)), + Sort(clusterExprs.getChildren.map(nodeToExpr).map(SortOrder(_, Ascending)), false, Repartition(clusterExprs.getChildren.map(nodeToExpr), withHaving)) case (None, None, None, None) => withHaving case _ => sys.error("Unsupported set of ordering / distribution clauses.") diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala index 8011f9b8773b3..4104df8f8e022 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala @@ -132,7 +132,7 @@ abstract class HiveComparisonTest def isSorted(plan: LogicalPlan): Boolean = plan match { case _: Join | _: Aggregate | _: Generate | _: Sample | _: Distinct => false - case PhysicalOperation(_, _, Sort(_, _)) => true + case PhysicalOperation(_, _, Sort(_, true, _)) => true case _ => plan.children.iterator.exists(isSorted) } diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala index f57f31af15566..5d0fb7237011f 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala @@ -32,6 +32,13 @@ case class Nested3(f3: Int) * valid, but Hive currently cannot execute it. */ class SQLQuerySuite extends QueryTest { + test("SPARK-4512 Fix attribute reference resolution error when using SORT BY") { + checkAnswer( + sql("SELECT * FROM (SELECT key + key AS a FROM src SORT BY value) t ORDER BY t.a"), + sql("SELECT key + key as a FROM src ORDER BY a").collect().toSeq + ) + } + test("CTAS with serde") { sql("CREATE TABLE ctas1 AS SELECT key k, value FROM src ORDER BY k, value").collect sql( From 19a8802e703e6b075a148ba73dc9dd80748d6322 Mon Sep 17 00:00:00 2001 From: Cheng Lian Date: Tue, 30 Dec 2014 12:16:45 -0800 Subject: [PATCH 132/320] [SPARK-4493][SQL] Tests for IsNull / IsNotNull in the ParquetFilterSuite This is a follow-up of #3367 and #3644. At the time #3644 was written, #3367 hadn't been merged yet, thus `IsNull` and `IsNotNull` filters are not covered in the first version of `ParquetFilterSuite`. This PR adds corresponding test cases. [Review on Reviewable](https://reviewable.io/reviews/apache/spark/3748) Author: Cheng Lian Closes #3748 from liancheng/test-null-filters and squashes the following commits: 1ab943f [Cheng Lian] IsNull and IsNotNull Parquet filter test case for boolean type bcd616b [Cheng Lian] Adds Parquet filter pushedown tests for IsNull and IsNotNull --- .../sql/parquet/ParquetFilterSuite.scala | 60 +++++++++++++++---- 1 file changed, 50 insertions(+), 10 deletions(-) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala index b17300475b6f6..4c3a04506ce42 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetFilterSuite.scala @@ -28,11 +28,14 @@ import org.apache.spark.sql.{QueryTest, SQLConf, SchemaRDD} /** * A test suite that tests Parquet filter2 API based filter pushdown optimization. * - * Notice that `!(a cmp b)` are always transformed to its negated form `a cmp' b` by the - * `BooleanSimplification` optimization rule whenever possible. As a result, predicate `!(a < 1)` - * results a `GtEq` filter predicate rather than a `Not`. + * NOTE: * - * @todo Add test cases for `IsNull` and `IsNotNull` after merging PR #3367 + * 1. `!(a cmp b)` is always transformed to its negated form `a cmp' b` by the + * `BooleanSimplification` optimization rule whenever possible. As a result, predicate `!(a < 1)` + * results in a `GtEq` filter predicate rather than a `Not`. + * + * 2. `Tuple1(Option(x))` is used together with `AnyVal` types like `Int` to ensure the inferred + * data type is nullable. */ class ParquetFilterSuite extends QueryTest with ParquetTest { val sqlContext = TestSQLContext @@ -85,14 +88,26 @@ class ParquetFilterSuite extends QueryTest with ParquetTest { } test("filter pushdown - boolean") { - withParquetRDD((true :: false :: Nil).map(Tuple1.apply)) { rdd => + withParquetRDD((true :: false :: Nil).map(b => Tuple1.apply(Option(b)))) { rdd => + checkFilterPushdown(rdd, '_1)('_1.isNull, classOf[Eq[java.lang.Boolean]])(Seq.empty[Row]) + checkFilterPushdown(rdd, '_1)('_1.isNotNull, classOf[NotEq[java.lang.Boolean]]) { + Seq(Row(true), Row(false)) + } + checkFilterPushdown(rdd, '_1)('_1 === true, classOf[Eq[java.lang.Boolean]])(true) - checkFilterPushdown(rdd, '_1)('_1 !== true, classOf[Operators.NotEq[java.lang.Boolean]])(false) + checkFilterPushdown(rdd, '_1)('_1 !== true, classOf[Operators.NotEq[java.lang.Boolean]]) { + false + } } } test("filter pushdown - integer") { - withParquetRDD((1 to 4).map(Tuple1.apply)) { rdd => + withParquetRDD((1 to 4).map(i => Tuple1(Option(i)))) { rdd => + checkFilterPushdown(rdd, '_1)('_1.isNull, classOf[Eq[Integer]])(Seq.empty[Row]) + checkFilterPushdown(rdd, '_1)('_1.isNotNull, classOf[NotEq[Integer]]) { + (1 to 4).map(Row.apply(_)) + } + checkFilterPushdown(rdd, '_1)('_1 === 1, classOf[Eq[Integer]])(1) checkFilterPushdown(rdd, '_1)('_1 !== 1, classOf[Operators.NotEq[Integer]]) { (2 to 4).map(Row.apply(_)) @@ -118,7 +133,12 @@ class ParquetFilterSuite extends QueryTest with ParquetTest { } test("filter pushdown - long") { - withParquetRDD((1 to 4).map(i => Tuple1(i.toLong))) { rdd => + withParquetRDD((1 to 4).map(i => Tuple1(Option(i.toLong)))) { rdd => + checkFilterPushdown(rdd, '_1)('_1.isNull, classOf[Eq[java.lang.Long]])(Seq.empty[Row]) + checkFilterPushdown(rdd, '_1)('_1.isNotNull, classOf[NotEq[java.lang.Long]]) { + (1 to 4).map(Row.apply(_)) + } + checkFilterPushdown(rdd, '_1)('_1 === 1, classOf[Eq[java.lang.Long]])(1) checkFilterPushdown(rdd, '_1)('_1 !== 1, classOf[Operators.NotEq[java.lang.Long]]) { (2 to 4).map(Row.apply(_)) @@ -144,7 +164,12 @@ class ParquetFilterSuite extends QueryTest with ParquetTest { } test("filter pushdown - float") { - withParquetRDD((1 to 4).map(i => Tuple1(i.toFloat))) { rdd => + withParquetRDD((1 to 4).map(i => Tuple1(Option(i.toFloat)))) { rdd => + checkFilterPushdown(rdd, '_1)('_1.isNull, classOf[Eq[java.lang.Float]])(Seq.empty[Row]) + checkFilterPushdown(rdd, '_1)('_1.isNotNull, classOf[NotEq[java.lang.Float]]) { + (1 to 4).map(Row.apply(_)) + } + checkFilterPushdown(rdd, '_1)('_1 === 1, classOf[Eq[java.lang.Float]])(1) checkFilterPushdown(rdd, '_1)('_1 !== 1, classOf[Operators.NotEq[java.lang.Float]]) { (2 to 4).map(Row.apply(_)) @@ -170,7 +195,12 @@ class ParquetFilterSuite extends QueryTest with ParquetTest { } test("filter pushdown - double") { - withParquetRDD((1 to 4).map(i => Tuple1(i.toDouble))) { rdd => + withParquetRDD((1 to 4).map(i => Tuple1(Option(i.toDouble)))) { rdd => + checkFilterPushdown(rdd, '_1)('_1.isNull, classOf[Eq[java.lang.Double]])(Seq.empty[Row]) + checkFilterPushdown(rdd, '_1)('_1.isNotNull, classOf[NotEq[java.lang.Double]]) { + (1 to 4).map(Row.apply(_)) + } + checkFilterPushdown(rdd, '_1)('_1 === 1, classOf[Eq[java.lang.Double]])(1) checkFilterPushdown(rdd, '_1)('_1 !== 1, classOf[Operators.NotEq[java.lang.Double]]) { (2 to 4).map(Row.apply(_)) @@ -197,6 +227,11 @@ class ParquetFilterSuite extends QueryTest with ParquetTest { test("filter pushdown - string") { withParquetRDD((1 to 4).map(i => Tuple1(i.toString))) { rdd => + checkFilterPushdown(rdd, '_1)('_1.isNull, classOf[Eq[java.lang.String]])(Seq.empty[Row]) + checkFilterPushdown(rdd, '_1)('_1.isNotNull, classOf[NotEq[java.lang.String]]) { + (1 to 4).map(i => Row.apply(i.toString)) + } + checkFilterPushdown(rdd, '_1)('_1 === "1", classOf[Eq[String]])("1") checkFilterPushdown(rdd, '_1)('_1 !== "1", classOf[Operators.NotEq[String]]) { (2 to 4).map(i => Row.apply(i.toString)) @@ -227,6 +262,11 @@ class ParquetFilterSuite extends QueryTest with ParquetTest { } withParquetRDD((1 to 4).map(i => Tuple1(i.b))) { rdd => + checkBinaryFilterPushdown(rdd, '_1)('_1.isNull, classOf[Eq[java.lang.String]])(Seq.empty[Row]) + checkBinaryFilterPushdown(rdd, '_1)('_1.isNotNull, classOf[NotEq[java.lang.String]]) { + (1 to 4).map(i => Row.apply(i.b)).toSeq + } + checkBinaryFilterPushdown(rdd, '_1)('_1 === 1.b, classOf[Eq[Array[Byte]]])(1.b) checkBinaryFilterPushdown(rdd, '_1)('_1 !== 1.b, classOf[Operators.NotEq[Array[Byte]]]) { (2 to 4).map(i => Row.apply(i.b)).toSeq From f7a41a0e79561a722e41800257dca886732ccaad Mon Sep 17 00:00:00 2001 From: luogankun Date: Tue, 30 Dec 2014 12:17:49 -0800 Subject: [PATCH 133/320] [SPARK-4916][SQL][DOCS]Update SQL programming guide about cache section `SchemeRDD.cache()` now uses in-memory columnar storage. Author: luogankun Closes #3759 from luogankun/SPARK-4916 and squashes the following commits: 7b39864 [luogankun] [SPARK-4916]Update SQL programming guide 6018122 [luogankun] Merge branch 'master' of https://github.com/apache/spark into SPARK-4916 0b93785 [luogankun] [SPARK-4916]Update SQL programming guide 99b2336 [luogankun] [SPARK-4916]Update SQL programming guide --- docs/sql-programming-guide.md | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/docs/sql-programming-guide.md b/docs/sql-programming-guide.md index 2aea8a8aedafc..1b5fde991e405 100644 --- a/docs/sql-programming-guide.md +++ b/docs/sql-programming-guide.md @@ -831,13 +831,10 @@ turning on some experimental options. ## Caching Data In Memory -Spark SQL can cache tables using an in-memory columnar format by calling `sqlContext.cacheTable("tableName")`. +Spark SQL can cache tables using an in-memory columnar format by calling `sqlContext.cacheTable("tableName")` or `schemaRDD.cache()`. Then Spark SQL will scan only required columns and will automatically tune compression to minimize memory usage and GC pressure. You can call `sqlContext.uncacheTable("tableName")` to remove the table from memory. -Note that if you call `schemaRDD.cache()` rather than `sqlContext.cacheTable(...)`, tables will _not_ be cached using -the in-memory columnar format, and therefore `sqlContext.cacheTable(...)` is strongly recommended for this use case. - Configuration of in-memory caching can be done using the `setConf` method on SQLContext or by running `SET key=value` commands using SQL. From 2deac748b4e1245c2cb9bd43ad87c80d6d130a83 Mon Sep 17 00:00:00 2001 From: luogankun Date: Tue, 30 Dec 2014 12:18:55 -0800 Subject: [PATCH 134/320] [SPARK-4930][SQL][DOCS]Update SQL programming guide, CACHE TABLE is eager `CACHE TABLE tbl` is now __eager__ by default not __lazy__ Author: luogankun Closes #3773 from luogankun/SPARK-4930 and squashes the following commits: cc17b7d [luogankun] [SPARK-4930][SQL][DOCS]Update SQL programming guide, add CACHE [LAZY] TABLE [AS SELECT] ... bffe0e8 [luogankun] [SPARK-4930][SQL][DOCS]Update SQL programming guide, CACHE TABLE tbl is eager --- docs/sql-programming-guide.md | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) diff --git a/docs/sql-programming-guide.md b/docs/sql-programming-guide.md index 1b5fde991e405..729045b81a8c0 100644 --- a/docs/sql-programming-guide.md +++ b/docs/sql-programming-guide.md @@ -1007,12 +1007,11 @@ let user control table caching explicitly: CACHE TABLE logs_last_month; UNCACHE TABLE logs_last_month; -**NOTE:** `CACHE TABLE tbl` is lazy, similar to `.cache` on an RDD. This command only marks `tbl` to ensure that -partitions are cached when calculated but doesn't actually cache it until a query that touches `tbl` is executed. -To force the table to be cached, you may simply count the table immediately after executing `CACHE TABLE`: +**NOTE:** `CACHE TABLE tbl` is now __eager__ by default not __lazy__. Don’t need to trigger cache materialization manually anymore. - CACHE TABLE logs_last_month; - SELECT COUNT(1) FROM logs_last_month; +Spark SQL newly introduced a statement to let user control table caching whether or not lazy since Spark 1.2.0: + + CACHE [LAZY] TABLE [AS SELECT] ... Several caching related features are not supported yet: From a75dd83b72586695768c89ed32b240aa8f48f32c Mon Sep 17 00:00:00 2001 From: guowei2 Date: Tue, 30 Dec 2014 12:21:00 -0800 Subject: [PATCH 135/320] [SPARK-4928][SQL] Fix: Operator '>,<,>=,<=' with decimal between different precision report error case operator with decimal between different precision, we need change them to unlimited Author: guowei2 Closes #3767 from guowei2/SPARK-4928 and squashes the following commits: c6a6e3e [guowei2] fix code style 3214e0a [guowei2] add test case b4985a2 [guowei2] fix code style 27adf42 [guowei2] Fix: Operation '>,<,>=,<=' with Decimal report error --- .../catalyst/analysis/HiveTypeCoercion.scala | 16 ++++++++++++++++ .../analysis/DecimalPrecisionSuite.scala | 17 +++++++++++++++++ 2 files changed, 33 insertions(+) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala index e38114ab3cf25..242f28f670298 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala @@ -361,6 +361,22 @@ trait HiveTypeCoercion { DecimalType(min(p1 - s1, p2 - s2) + max(s1, s2), max(s1, s2)) ) + case LessThan(e1 @ DecimalType.Expression(p1, s1), + e2 @ DecimalType.Expression(p2, s2)) if p1 != p2 || s1 != s2 => + LessThan(Cast(e1, DecimalType.Unlimited), Cast(e2, DecimalType.Unlimited)) + + case LessThanOrEqual(e1 @ DecimalType.Expression(p1, s1), + e2 @ DecimalType.Expression(p2, s2)) if p1 != p2 || s1 != s2 => + LessThanOrEqual(Cast(e1, DecimalType.Unlimited), Cast(e2, DecimalType.Unlimited)) + + case GreaterThan(e1 @ DecimalType.Expression(p1, s1), + e2 @ DecimalType.Expression(p2, s2)) if p1 != p2 || s1 != s2 => + GreaterThan(Cast(e1, DecimalType.Unlimited), Cast(e2, DecimalType.Unlimited)) + + case GreaterThanOrEqual(e1 @ DecimalType.Expression(p1, s1), + e2 @ DecimalType.Expression(p2, s2)) if p1 != p2 || s1 != s2 => + GreaterThanOrEqual(Cast(e1, DecimalType.Unlimited), Cast(e2, DecimalType.Unlimited)) + // Promote integers inside a binary expression with fixed-precision decimals to decimals, // and fixed-precision decimals in an expression with floats / doubles to doubles case b: BinaryExpression if b.left.dataType != b.right.dataType => diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/DecimalPrecisionSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/DecimalPrecisionSuite.scala index d5b7d2789a103..3677a6e72e23a 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/DecimalPrecisionSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/DecimalPrecisionSuite.scala @@ -49,6 +49,15 @@ class DecimalPrecisionSuite extends FunSuite with BeforeAndAfter { assert(analyzer(plan).schema.fields(0).dataType === expectedType) } + private def checkComparison(expression: Expression, expectedType: DataType): Unit = { + val plan = Project(Alias(expression, "c")() :: Nil, relation) + val comparison = analyzer(plan).collect { + case Project(Alias(e: BinaryComparison, _) :: Nil, _) => e + }.head + assert(comparison.left.dataType === expectedType) + assert(comparison.right.dataType === expectedType) + } + test("basic operations") { checkType(Add(d1, d2), DecimalType(6, 2)) checkType(Subtract(d1, d2), DecimalType(6, 2)) @@ -65,6 +74,14 @@ class DecimalPrecisionSuite extends FunSuite with BeforeAndAfter { checkType(Add(Add(d1, d2), Add(d1, d2)), DecimalType(7, 2)) } + test("Comparison operations") { + checkComparison(LessThan(i, d1), DecimalType.Unlimited) + checkComparison(LessThanOrEqual(d1, d2), DecimalType.Unlimited) + checkComparison(GreaterThan(d2, u), DecimalType.Unlimited) + checkComparison(GreaterThanOrEqual(d1, f), DoubleType) + checkComparison(GreaterThan(d2, d2), DecimalType(5, 2)) + } + test("bringing in primitive types") { checkType(Add(d1, i), DecimalType(12, 1)) checkType(Add(d1, f), DoubleType) From 61a99f6a11d85e931e7d60f9ab4370b3b40a52ef Mon Sep 17 00:00:00 2001 From: Cheng Lian Date: Tue, 30 Dec 2014 13:38:27 -0800 Subject: [PATCH 136/320] [SPARK-4937][SQL] Normalizes conjunctions and disjunctions to eliminate common predicates This PR is a simplified version of several filter optimization rules introduced in #3778 authored by scwf. Newly introduced optimizations include: 1. `a && a` => `a` 2. `a || a` => `a` 3. `(a || b || c || ...) && (a || b || d || ...)` => `a && b && (c || d || ...)` The 3rd rule is particularly useful for optimizing the following query, which is planned into a cartesian product ```sql SELECT * FROM t1, t2 WHERE (t1.key = t2.key AND t1.value > 10) OR (t1.key = t2.key AND t2.value < 20) ``` to the following one, which is planned into an equi-join: ```sql SELECT * FROM t1, t2 WHERE t1.key = t2.key AND (t1.value > 10 OR t2.value < 20) ``` The example above is quite artificial, but common predicates are likely to appear in real life complex queries (like the one mentioned in #3778). A difference between this PR and #3778 is that these optimizations are not limited to `Filter`, but are generalized to all logical plan nodes. Thanks to scwf for bringing up these optimizations, and chenghao-intel for the generalization suggestion. [Review on Reviewable](https://reviewable.io/reviews/apache/spark/3784) Author: Cheng Lian Closes #3784 from liancheng/normalize-filters and squashes the following commits: caca560 [Cheng Lian] Moves filter normalization into BooleanSimplification rule 4ab3a58 [Cheng Lian] Fixes test failure, adds more tests 5d54349 [Cheng Lian] Fixes typo in comment 2abbf8e [Cheng Lian] Forgot our sacred Apache licence header... cf95639 [Cheng Lian] Adds an optimization rule for filter normalization --- .../sql/catalyst/expressions/predicates.scala | 9 ++- .../sql/catalyst/optimizer/Optimizer.scala | 27 +++++-- .../optimizer/NormalizeFiltersSuite.scala | 72 +++++++++++++++++++ .../columnar/PartitionBatchPruningSuite.scala | 10 ++- 4 files changed, 110 insertions(+), 8 deletions(-) create mode 100644 sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/NormalizeFiltersSuite.scala diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala index 94b6fb084d38a..cb5ff67959868 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala @@ -17,7 +17,6 @@ package org.apache.spark.sql.catalyst.expressions -import scala.collection.immutable.HashSet import org.apache.spark.sql.catalyst.analysis.UnresolvedException import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan import org.apache.spark.sql.catalyst.types.BooleanType @@ -48,6 +47,14 @@ trait PredicateHelper { } } + protected def splitDisjunctivePredicates(condition: Expression): Seq[Expression] = { + condition match { + case Or(cond1, cond2) => + splitDisjunctivePredicates(cond1) ++ splitDisjunctivePredicates(cond2) + case other => other :: Nil + } + } + /** * Returns true if `expr` can be evaluated using only the output of `plan`. This method * can be used to determine when is is acceptable to move expression evaluation within a query diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala index 0f2eae6400d21..cd3137980ca43 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala @@ -294,11 +294,16 @@ object OptimizeIn extends Rule[LogicalPlan] { } /** - * Simplifies boolean expressions where the answer can be determined without evaluating both sides. + * Simplifies boolean expressions: + * + * 1. Simplifies expressions whose answer can be determined without evaluating both sides. + * 2. Eliminates / extracts common factors. + * 3. Removes `Not` operator. + * * Note that this rule can eliminate expressions that might otherwise have been evaluated and thus * is only safe when evaluations of expressions does not result in side effects. */ -object BooleanSimplification extends Rule[LogicalPlan] { +object BooleanSimplification extends Rule[LogicalPlan] with PredicateHelper { def apply(plan: LogicalPlan): LogicalPlan = plan transform { case q: LogicalPlan => q transformExpressionsUp { case and @ And(left, right) => @@ -307,7 +312,9 @@ object BooleanSimplification extends Rule[LogicalPlan] { case (l, Literal(true, BooleanType)) => l case (Literal(false, BooleanType), _) => Literal(false) case (_, Literal(false, BooleanType)) => Literal(false) - case (_, _) => and + // a && a && a ... => a + case _ if splitConjunctivePredicates(and).distinct.size == 1 => left + case _ => and } case or @ Or(left, right) => @@ -316,7 +323,19 @@ object BooleanSimplification extends Rule[LogicalPlan] { case (_, Literal(true, BooleanType)) => Literal(true) case (Literal(false, BooleanType), r) => r case (l, Literal(false, BooleanType)) => l - case (_, _) => or + // a || a || a ... => a + case _ if splitDisjunctivePredicates(or).distinct.size == 1 => left + // (a && b && c && ...) || (a && b && d && ...) => a && b && (c || d || ...) + case _ => + val lhsSet = splitConjunctivePredicates(left).toSet + val rhsSet = splitConjunctivePredicates(right).toSet + val common = lhsSet.intersect(rhsSet) + + (lhsSet.diff(common).reduceOption(And) ++ rhsSet.diff(common).reduceOption(And)) + .reduceOption(Or) + .map(_ :: common.toList) + .getOrElse(common.toList) + .reduce(And) } case not @ Not(exp) => diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/NormalizeFiltersSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/NormalizeFiltersSuite.scala new file mode 100644 index 0000000000000..906300d8336cb --- /dev/null +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/NormalizeFiltersSuite.scala @@ -0,0 +1,72 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.catalyst.optimizer + +import org.apache.spark.sql.catalyst.analysis.EliminateAnalysisOperators +import org.apache.spark.sql.catalyst.expressions.{And, Expression, Or} +import org.apache.spark.sql.catalyst.plans.PlanTest +import org.apache.spark.sql.catalyst.plans.logical.{Filter, LocalRelation, LogicalPlan} +import org.apache.spark.sql.catalyst.rules.RuleExecutor + +// For implicit conversions +import org.apache.spark.sql.catalyst.dsl.expressions._ +import org.apache.spark.sql.catalyst.dsl.plans._ + +class NormalizeFiltersSuite extends PlanTest { + object Optimize extends RuleExecutor[LogicalPlan] { + val batches = Seq( + Batch("AnalysisNodes", Once, + EliminateAnalysisOperators), + Batch("NormalizeFilters", FixedPoint(100), + BooleanSimplification, + SimplifyFilters)) + } + + val relation = LocalRelation('a.int, 'b.int, 'c.string) + + def checkExpression(original: Expression, expected: Expression): Unit = { + val actual = Optimize(relation.where(original)).collect { case f: Filter => f.condition }.head + val result = (actual, expected) match { + case (And(l1, r1), And(l2, r2)) => (l1 == l2 && r1 == r2) || (l1 == r2 && l2 == r1) + case (Or (l1, r1), Or (l2, r2)) => (l1 == l2 && r1 == r2) || (l1 == r2 && l2 == r1) + case (lhs, rhs) => lhs fastEquals rhs + } + + assert(result, s"$actual isn't equivalent to $expected") + } + + test("a && a => a") { + checkExpression('a === 1 && 'a === 1, 'a === 1) + checkExpression('a === 1 && 'a === 1 && 'a === 1, 'a === 1) + } + + test("a || a => a") { + checkExpression('a === 1 || 'a === 1, 'a === 1) + checkExpression('a === 1 || 'a === 1 || 'a === 1, 'a === 1) + } + + test("(a && b) || (a && c) => a && (b || c)") { + checkExpression( + ('a === 1 && 'a < 10) || ('a > 2 && 'a === 1), + ('a === 1) && ('a < 10 || 'a > 2)) + + checkExpression( + ('a < 1 && 'b > 2 && 'c.isNull) || ('a < 1 && 'c === "hello" && 'b > 2), + ('c.isNull || 'c === "hello") && 'a < 1 && 'b > 2) + } +} diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/PartitionBatchPruningSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/PartitionBatchPruningSuite.scala index 82afa31a99a7e..1915c25392f1e 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/PartitionBatchPruningSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/PartitionBatchPruningSuite.scala @@ -105,7 +105,9 @@ class PartitionBatchPruningSuite extends FunSuite with BeforeAndAfterAll with Be test(query) { val schemaRdd = sql(query) - assertResult(expectedQueryResult.toArray, "Wrong query result") { + val queryExecution = schemaRdd.queryExecution + + assertResult(expectedQueryResult.toArray, s"Wrong query result: $queryExecution") { schemaRdd.collect().map(_.head).toArray } @@ -113,8 +115,10 @@ class PartitionBatchPruningSuite extends FunSuite with BeforeAndAfterAll with Be case in: InMemoryColumnarTableScan => (in.readPartitions.value, in.readBatches.value) }.head - assert(readBatches === expectedReadBatches, "Wrong number of read batches") - assert(readPartitions === expectedReadPartitions, "Wrong number of read partitions") + assert(readBatches === expectedReadBatches, s"Wrong number of read batches: $queryExecution") + assert( + readPartitions === expectedReadPartitions, + s"Wrong number of read partitions: $queryExecution") } } } From 7425bec320227bf8818dc2844c12d5373d166364 Mon Sep 17 00:00:00 2001 From: Michael Davies Date: Tue, 30 Dec 2014 13:40:51 -0800 Subject: [PATCH 137/320] [SPARK-4386] Improve performance when writing Parquet files Convert type of RowWriteSupport.attributes to Array. Analysis of performance for writing very wide tables shows that time is spent predominantly in apply method on attributes var. Type of attributes previously was LinearSeqOptimized and apply is O(N) which made write O(N squared). Measurements on 575 column table showed this change made a 6x improvement in write times. Author: Michael Davies Closes #3843 from MickDavies/SPARK-4386 and squashes the following commits: 892519d [Michael Davies] [SPARK-4386] Improve performance when writing Parquet files --- .../org/apache/spark/sql/parquet/ParquetTableSupport.scala | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableSupport.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableSupport.scala index ef3687e692964..9049eb5932b79 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableSupport.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableSupport.scala @@ -130,7 +130,7 @@ private[parquet] object RowReadSupport { private[parquet] class RowWriteSupport extends WriteSupport[Row] with Logging { private[parquet] var writer: RecordConsumer = null - private[parquet] var attributes: Seq[Attribute] = null + private[parquet] var attributes: Array[Attribute] = null override def init(configuration: Configuration): WriteSupport.WriteContext = { val origAttributesStr: String = configuration.get(RowWriteSupport.SPARK_ROW_SCHEMA) @@ -138,7 +138,7 @@ private[parquet] class RowWriteSupport extends WriteSupport[Row] with Logging { metadata.put(RowReadSupport.SPARK_METADATA_KEY, origAttributesStr) if (attributes == null) { - attributes = ParquetTypesConverter.convertFromString(origAttributesStr) + attributes = ParquetTypesConverter.convertFromString(origAttributesStr).toArray } log.debug(s"write support initialized for requested schema $attributes") From 8f29b7cafc2b6e802e4eb21f681d6369da2f30fa Mon Sep 17 00:00:00 2001 From: wangfei Date: Tue, 30 Dec 2014 13:44:30 -0800 Subject: [PATCH 138/320] [SPARK-4935][SQL] When hive.cli.print.header configured, spark-sql aborted if passed in a invalid sql If we passed in a wrong sql like ```abdcdfsfs```, the spark-sql script aborted. Author: wangfei Author: Fei Wang Closes #3761 from scwf/patch-10 and squashes the following commits: 46dc344 [Fei Wang] revert console.printError(rc.getErrorMessage()) 0330e07 [wangfei] avoid to print error message repeatedly 1614a11 [wangfei] spark-sql abort when passed in a wrong sql --- .../spark/sql/hive/thriftserver/AbstractSparkSQLDriver.scala | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/AbstractSparkSQLDriver.scala b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/AbstractSparkSQLDriver.scala index 6ed8fd2768f95..7a3d76c61c3a1 100644 --- a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/AbstractSparkSQLDriver.scala +++ b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/AbstractSparkSQLDriver.scala @@ -60,7 +60,7 @@ private[hive] abstract class AbstractSparkSQLDriver( } catch { case cause: Throwable => logError(s"Failed in [$command]", cause) - new CommandProcessorResponse(0, ExceptionUtils.getFullStackTrace(cause), null) + new CommandProcessorResponse(1, ExceptionUtils.getFullStackTrace(cause), null) } } From 07fa1910d9c4092d670381c447403105f01c584e Mon Sep 17 00:00:00 2001 From: wangxiaojing Date: Tue, 30 Dec 2014 13:54:12 -0800 Subject: [PATCH 139/320] [SPARK-4570][SQL]add BroadcastLeftSemiJoinHash JIRA issue: [SPARK-4570](https://issues.apache.org/jira/browse/SPARK-4570) We are planning to create a `BroadcastLeftSemiJoinHash` to implement the broadcast join for `left semijoin` In left semijoin : If the size of data from right side is smaller than the user-settable threshold `AUTO_BROADCASTJOIN_THRESHOLD`, the planner would mark it as the `broadcast` relation and mark the other relation as the stream side. The broadcast table will be broadcasted to all of the executors involved in the join, as a `org.apache.spark.broadcast.Broadcast` object. It will use `joins.BroadcastLeftSemiJoinHash`.,else it will use `joins.LeftSemiJoinHash`. The benchmark suggests these made the optimized version 4x faster when `left semijoin` 

Original:
left semi join : 9288 ms
Optimized:
left semi join : 1963 ms
The micro benchmark load `data1/kv3.txt` into a normal Hive table. Benchmark code: 

 def benchmark(f: => Unit) = {
    val begin = System.currentTimeMillis()
    f
    val end = System.currentTimeMillis()
    end - begin
  }
  val sc = new SparkContext(
    new SparkConf()
      .setMaster("local")
      .setAppName(getClass.getSimpleName.stripSuffix("$")))
  val hiveContext = new HiveContext(sc)
  import hiveContext._
  sql("drop table if exists left_table")
  sql("drop table if exists right_table")
  sql( """create table left_table (key int, value string)
       """.stripMargin)
  sql( s"""load data local inpath "/data1/kv3.txt" into table left_table""")
  sql( """create table right_table (key int, value string)
       """.stripMargin)
  sql(
    """
      |from left_table
      |insert overwrite table right_table
      |select left_table.key, left_table.value
    """.stripMargin)

  val leftSimeJoin = sql(
    """select a.key from left_table a
      |left semi join right_table b on a.key = b.key""".stripMargin)
  val leftSemiJoinDuration = benchmark(leftSimeJoin.count())
  println(s"left semi join : $leftSemiJoinDuration ms ")
Author: wangxiaojing Closes #3442 from wangxiaojing/SPARK-4570 and squashes the following commits: a4a43c9 [wangxiaojing] rebase f103983 [wangxiaojing] change style fbe4887 [wangxiaojing] change style ff2e618 [wangxiaojing] add testsuite 1a8da2a [wangxiaojing] add BroadcastLeftSemiJoinHash --- .../spark/sql/execution/SparkStrategies.scala | 6 ++ .../joins/BroadcastLeftSemiJoinHash.scala | 67 +++++++++++++++++++ .../org/apache/spark/sql/JoinSuite.scala | 38 +++++++++++ .../spark/sql/hive/StatisticsSuite.scala | 50 +++++++++++++- 4 files changed, 160 insertions(+), 1 deletion(-) create mode 100644 sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastLeftSemiJoinHash.scala diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala index 9151da69ed44c..ce878c137e627 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala @@ -33,6 +33,12 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { object LeftSemiJoin extends Strategy with PredicateHelper { def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match { + case ExtractEquiJoinKeys(LeftSemi, leftKeys, rightKeys, condition, left, right) + if sqlContext.autoBroadcastJoinThreshold > 0 && + right.statistics.sizeInBytes <= sqlContext.autoBroadcastJoinThreshold => + val semiJoin = joins.BroadcastLeftSemiJoinHash( + leftKeys, rightKeys, planLater(left), planLater(right)) + condition.map(Filter(_, semiJoin)).getOrElse(semiJoin) :: Nil // Find left semi joins where at least some predicates can be evaluated by matching join keys case ExtractEquiJoinKeys(LeftSemi, leftKeys, rightKeys, condition, left, right) => val semiJoin = joins.LeftSemiJoinHash( diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastLeftSemiJoinHash.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastLeftSemiJoinHash.scala new file mode 100644 index 0000000000000..2ab064fd0151e --- /dev/null +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastLeftSemiJoinHash.scala @@ -0,0 +1,67 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.execution.joins + +import org.apache.spark.annotation.DeveloperApi +import org.apache.spark.sql.catalyst.expressions.{Expression, Row} +import org.apache.spark.sql.catalyst.plans.physical.ClusteredDistribution +import org.apache.spark.sql.execution.{BinaryNode, SparkPlan} + +/** + * :: DeveloperApi :: + * Build the right table's join keys into a HashSet, and iteratively go through the left + * table, to find the if join keys are in the Hash set. + */ +@DeveloperApi +case class BroadcastLeftSemiJoinHash( + leftKeys: Seq[Expression], + rightKeys: Seq[Expression], + left: SparkPlan, + right: SparkPlan) extends BinaryNode with HashJoin { + + override val buildSide = BuildRight + + override def output = left.output + + override def execute() = { + val buildIter= buildPlan.execute().map(_.copy()).collect().toIterator + val hashSet = new java.util.HashSet[Row]() + var currentRow: Row = null + + // Create a Hash set of buildKeys + while (buildIter.hasNext) { + currentRow = buildIter.next() + val rowKey = buildSideKeyGenerator(currentRow) + if (!rowKey.anyNull) { + val keyExists = hashSet.contains(rowKey) + if (!keyExists) { + hashSet.add(rowKey) + } + } + } + + val broadcastedRelation = sparkContext.broadcast(hashSet) + + streamedPlan.execute().mapPartitions { streamIter => + val joinKeys = streamSideKeyGenerator() + streamIter.filter(current => { + !joinKeys(current).anyNull && broadcastedRelation.value.contains(joinKeys.currentValue) + }) + } + } +} diff --git a/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala index 0378fd7e367f0..1a4232dab86e7 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala @@ -48,6 +48,7 @@ class JoinSuite extends QueryTest with BeforeAndAfterEach { case j: LeftSemiJoinBNL => j case j: CartesianProduct => j case j: BroadcastNestedLoopJoin => j + case j: BroadcastLeftSemiJoinHash => j } assert(operators.size === 1) @@ -382,4 +383,41 @@ class JoinSuite extends QueryTest with BeforeAndAfterEach { """.stripMargin), (null, 10) :: Nil) } + + test("broadcasted left semi join operator selection") { + clearCache() + sql("CACHE TABLE testData") + val tmp = autoBroadcastJoinThreshold + + sql(s"SET ${SQLConf.AUTO_BROADCASTJOIN_THRESHOLD}=1000000000") + Seq( + ("SELECT * FROM testData LEFT SEMI JOIN testData2 ON key = a", + classOf[BroadcastLeftSemiJoinHash]) + ).foreach { + case (query, joinClass) => assertJoin(query, joinClass) + } + + sql(s"SET ${SQLConf.AUTO_BROADCASTJOIN_THRESHOLD}=-1") + + Seq( + ("SELECT * FROM testData LEFT SEMI JOIN testData2 ON key = a", classOf[LeftSemiJoinHash]) + ).foreach { + case (query, joinClass) => assertJoin(query, joinClass) + } + + setConf(SQLConf.AUTO_BROADCASTJOIN_THRESHOLD, tmp.toString) + sql("UNCACHE TABLE testData") + } + + test("left semi join") { + val rdd = sql("SELECT * FROM testData2 LEFT SEMI JOIN testData ON key = a") + checkAnswer(rdd, + (1, 1) :: + (1, 2) :: + (2, 1) :: + (2, 2) :: + (3, 1) :: + (3, 2) :: Nil) + + } } diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala index ff4071d8e2f10..4b6a9308b9811 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala @@ -22,7 +22,7 @@ import org.scalatest.BeforeAndAfterAll import scala.reflect.ClassTag import org.apache.spark.sql.{SQLConf, QueryTest} -import org.apache.spark.sql.execution.joins.{BroadcastHashJoin, ShuffledHashJoin} +import org.apache.spark.sql.execution.joins._ import org.apache.spark.sql.hive.test.TestHive import org.apache.spark.sql.hive.test.TestHive._ import org.apache.spark.sql.hive.execution._ @@ -193,4 +193,52 @@ class StatisticsSuite extends QueryTest with BeforeAndAfterAll { ) } + test("auto converts to broadcast left semi join, by size estimate of a relation") { + val leftSemiJoinQuery = + """SELECT * FROM src a + |left semi JOIN src b ON a.key=86 and a.key = b.key""".stripMargin + val answer = (86, "val_86") :: Nil + + var rdd = sql(leftSemiJoinQuery) + + // Assert src has a size smaller than the threshold. + val sizes = rdd.queryExecution.analyzed.collect { + case r if implicitly[ClassTag[MetastoreRelation]].runtimeClass + .isAssignableFrom(r.getClass) => + r.statistics.sizeInBytes + } + assert(sizes.size === 2 && sizes(1) <= autoBroadcastJoinThreshold + && sizes(0) <= autoBroadcastJoinThreshold, + s"query should contain two relations, each of which has size smaller than autoConvertSize") + + // Using `sparkPlan` because for relevant patterns in HashJoin to be + // matched, other strategies need to be applied. + var bhj = rdd.queryExecution.sparkPlan.collect { + case j: BroadcastLeftSemiJoinHash => j + } + assert(bhj.size === 1, + s"actual query plans do not contain broadcast join: ${rdd.queryExecution}") + + checkAnswer(rdd, answer) // check correctness of output + + TestHive.settings.synchronized { + val tmp = autoBroadcastJoinThreshold + + sql(s"SET ${SQLConf.AUTO_BROADCASTJOIN_THRESHOLD}=-1") + rdd = sql(leftSemiJoinQuery) + bhj = rdd.queryExecution.sparkPlan.collect { + case j: BroadcastLeftSemiJoinHash => j + } + assert(bhj.isEmpty, "BroadcastHashJoin still planned even though it is switched off") + + val shj = rdd.queryExecution.sparkPlan.collect { + case j: LeftSemiJoinHash => j + } + assert(shj.size === 1, + "LeftSemiJoinHash should be planned when BroadcastHashJoin is turned off") + + sql(s"SET ${SQLConf.AUTO_BROADCASTJOIN_THRESHOLD}=$tmp") + } + + } } From b239ea1c31aeaa752d5dc8f45423df1f8c0924ca Mon Sep 17 00:00:00 2001 From: Sean Owen Date: Tue, 30 Dec 2014 14:00:57 -0800 Subject: [PATCH 140/320] SPARK-3955 part 2 [CORE] [HOTFIX] Different versions between jackson-mapper-asl and jackson-core-asl pwendell https://github.com/apache/spark/commit/2483c1efb6429a7d8a20c96d18ce2fec93a1aff9 didn't actually add a reference to `jackson-core-asl` as intended, but a second redundant reference to `jackson-mapper-asl`, as markhamstra picked up on (https://github.com/apache/spark/pull/3716#issuecomment-68180192) This just rectifies the typo. I missed it as well; the original PR https://github.com/apache/spark/pull/2818 had it correct and I also didn't see the problem. Author: Sean Owen Closes #3829 from srowen/SPARK-3955 and squashes the following commits: 6cfdc4e [Sean Owen] Actually refer to jackson-core-asl --- pom.xml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pom.xml b/pom.xml index a843af2b22d6c..05f59a9b4140b 100644 --- a/pom.xml +++ b/pom.xml @@ -827,7 +827,7 @@ org.codehaus.jackson - jackson-mapper-asl + jackson-core-asl ${jackson.version} From 0f31992c61f6662e5347745f6a1ac272a5fd63c9 Mon Sep 17 00:00:00 2001 From: Jakub Dubovsky Date: Tue, 30 Dec 2014 14:19:07 -0800 Subject: [PATCH 141/320] [Spark-4995] Replace Vector.toBreeze.activeIterator with foreachActive New foreachActive method of vector was introduced by SPARK-4431 as more efficient alternative to vector.toBreeze.activeIterator. There are some parts of codebase where it was not yet replaced. dbtsai Author: Jakub Dubovsky Closes #3846 from james64/SPARK-4995-foreachActive and squashes the following commits: 3eb7e37 [Jakub Dubovsky] Scalastyle fix 32fe6c6 [Jakub Dubovsky] activeIterator removed - IndexedRowMatrix.toBreeze 47a4777 [Jakub Dubovsky] activeIterator removed in RowMatrix.toBreeze 90a7d98 [Jakub Dubovsky] activeIterator removed in MLUtils.saveAsLibSVMFile --- .../spark/mllib/linalg/distributed/IndexedRowMatrix.scala | 2 +- .../apache/spark/mllib/linalg/distributed/RowMatrix.scala | 4 ++-- .../main/scala/org/apache/spark/mllib/util/MLUtils.scala | 8 +++++--- 3 files changed, 8 insertions(+), 6 deletions(-) diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrix.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrix.scala index 5c1acca0ec532..36d8cadd2bdd7 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrix.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrix.scala @@ -142,7 +142,7 @@ class IndexedRowMatrix( val mat = BDM.zeros[Double](m, n) rows.collect().foreach { case IndexedRow(rowIndex, vector) => val i = rowIndex.toInt - vector.toBreeze.activeIterator.foreach { case (j, v) => + vector.foreachActive { case (j, v) => mat(i, j) = v } } diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala index 10a515af88802..a3fca53929ab7 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala @@ -588,8 +588,8 @@ class RowMatrix( val n = numCols().toInt val mat = BDM.zeros[Double](m, n) var i = 0 - rows.collect().foreach { v => - v.toBreeze.activeIterator.foreach { case (j, v) => + rows.collect().foreach { vector => + vector.foreachActive { case (j, v) => mat(i, j) = v } i += 1 diff --git a/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala b/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala index 1d07b5dab8268..da0da0a168c1d 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala @@ -154,10 +154,12 @@ object MLUtils { def saveAsLibSVMFile(data: RDD[LabeledPoint], dir: String) { // TODO: allow to specify label precision and feature precision. val dataStr = data.map { case LabeledPoint(label, features) => - val featureStrings = features.toBreeze.activeIterator.map { case (i, v) => - s"${i + 1}:$v" + val sb = new StringBuilder(label.toString) + features.foreachActive { case (i, v) => + sb += ' ' + sb ++= s"${i + 1}:$v" } - (Iterator(label) ++ featureStrings).mkString(" ") + sb.mkString } dataStr.saveAsTextFile(dir) } From 6a897829444e2ef273586511f93a40d36e64fb0b Mon Sep 17 00:00:00 2001 From: zsxwing Date: Tue, 30 Dec 2014 14:39:13 -0800 Subject: [PATCH 142/320] [SPARK-4813][Streaming] Fix the issue that ContextWaiter didn't handle 'spurious wakeup' Used `Condition` to rewrite `ContextWaiter` because it provides a convenient API `awaitNanos` for timeout. Author: zsxwing Closes #3661 from zsxwing/SPARK-4813 and squashes the following commits: 52247f5 [zsxwing] Add explicit unit type be42bcf [zsxwing] Update as per review suggestion e06bd4f [zsxwing] Fix the issue that ContextWaiter didn't handle 'spurious wakeup' --- .../spark/streaming/ContextWaiter.scala | 63 ++++++++++++++----- 1 file changed, 48 insertions(+), 15 deletions(-) diff --git a/streaming/src/main/scala/org/apache/spark/streaming/ContextWaiter.scala b/streaming/src/main/scala/org/apache/spark/streaming/ContextWaiter.scala index a0aeacbc733bd..fdbbe2aa6ef08 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/ContextWaiter.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/ContextWaiter.scala @@ -17,30 +17,63 @@ package org.apache.spark.streaming +import java.util.concurrent.TimeUnit +import java.util.concurrent.locks.ReentrantLock + private[streaming] class ContextWaiter { + + private val lock = new ReentrantLock() + private val condition = lock.newCondition() + + // Guarded by "lock" private var error: Throwable = null - private var stopped: Boolean = false - def notifyError(e: Throwable) = synchronized { - error = e - notifyAll() - } + // Guarded by "lock" + private var stopped: Boolean = false - def notifyStop() = synchronized { - stopped = true - notifyAll() + def notifyError(e: Throwable): Unit = { + lock.lock() + try { + error = e + condition.signalAll() + } finally { + lock.unlock() + } } - def waitForStopOrError(timeout: Long = -1) = synchronized { - // If already had error, then throw it - if (error != null) { - throw error + def notifyStop(): Unit = { + lock.lock() + try { + stopped = true + condition.signalAll() + } finally { + lock.unlock() } + } - // If not already stopped, then wait - if (!stopped) { - if (timeout < 0) wait() else wait(timeout) + /** + * Return `true` if it's stopped; or throw the reported error if `notifyError` has been called; or + * `false` if the waiting time detectably elapsed before return from the method. + */ + def waitForStopOrError(timeout: Long = -1): Boolean = { + lock.lock() + try { + if (timeout < 0) { + while (!stopped && error == null) { + condition.await() + } + } else { + var nanos = TimeUnit.MILLISECONDS.toNanos(timeout) + while (!stopped && error == null && nanos > 0) { + nanos = condition.awaitNanos(nanos) + } + } + // If already had error, then throw it if (error != null) throw error + // already stopped or timeout + stopped + } finally { + lock.unlock() } } } From 035bac88c732247c79a1bbad4f9191090cbbdc9a Mon Sep 17 00:00:00 2001 From: Liu Jiongzhou Date: Tue, 30 Dec 2014 15:55:56 -0800 Subject: [PATCH 143/320] [SPARK-4998][MLlib]delete the "train" function To make the functions with the same in "object" effective, specially when using java reflection. As the "train" function defined in "class DecisionTree" will hide the functions with the same name in "object DecisionTree". JIRA[SPARK-4998] Author: Liu Jiongzhou Closes #3836 from ljzzju/master and squashes the following commits: 4e13133 [Liu Jiongzhou] [MLlib]delete the "train" function --- .../scala/org/apache/spark/mllib/tree/DecisionTree.scala | 7 ------- 1 file changed, 7 deletions(-) diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/DecisionTree.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/DecisionTree.scala index 73e7e32c6db31..b3e8ed9af8c51 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/tree/DecisionTree.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/DecisionTree.scala @@ -64,13 +64,6 @@ class DecisionTree (private val strategy: Strategy) extends Serializable with Lo val rfModel = rf.run(input) rfModel.trees(0) } - - /** - * Trains a decision tree model over an RDD. This is deprecated because it hides the static - * methods with the same name in Java. - */ - @deprecated("Please use DecisionTree.run instead.", "1.2.0") - def train(input: RDD[LabeledPoint]): DecisionTreeModel = run(input) } object DecisionTree extends Serializable with Logging { From 352ed6bbe3c3b67e52e298e7c535ae414d96beca Mon Sep 17 00:00:00 2001 From: Josh Rosen Date: Tue, 30 Dec 2014 18:12:20 -0800 Subject: [PATCH 144/320] [SPARK-1010] Clean up uses of System.setProperty in unit tests Several of our tests call System.setProperty (or test code which implicitly sets system properties) and don't always reset/clear the modified properties, which can create ordering dependencies between tests and cause hard-to-diagnose failures. This patch removes most uses of System.setProperty from our tests, since in most cases we can use SparkConf to set these configurations (there are a few exceptions, including the tests of SparkConf itself). For the cases where we continue to use System.setProperty, this patch introduces a `ResetSystemProperties` ScalaTest mixin class which snapshots the system properties before individual tests and to automatically restores them on test completion / failure. See the block comment at the top of the ResetSystemProperties class for more details. Author: Josh Rosen Closes #3739 from JoshRosen/cleanup-system-properties-in-tests and squashes the following commits: 0236d66 [Josh Rosen] Replace setProperty uses in two example programs / tools 3888fe3 [Josh Rosen] Remove setProperty use in LocalJavaStreamingContext 4f4031d [Josh Rosen] Add note on why SparkSubmitSuite needs ResetSystemProperties 4742a5b [Josh Rosen] Clarify ResetSystemProperties trait inheritance ordering. 0eaf0b6 [Josh Rosen] Remove setProperty call in TaskResultGetterSuite. 7a3d224 [Josh Rosen] Fix trait ordering 3fdb554 [Josh Rosen] Remove setProperty call in TaskSchedulerImplSuite bee20df [Josh Rosen] Remove setProperty calls in SparkContextSchedulerCreationSuite 655587c [Josh Rosen] Remove setProperty calls in JobCancellationSuite 3f2f955 [Josh Rosen] Remove System.setProperty calls in DistributedSuite cfe9cce [Josh Rosen] Remove use of system properties in SparkContextSuite 8783ab0 [Josh Rosen] Remove TestUtils.setSystemProperty, since it is subsumed by the ResetSystemProperties trait. 633a84a [Josh Rosen] Remove use of system properties in FileServerSuite 25bfce2 [Josh Rosen] Use ResetSystemProperties in UtilsSuite 1d1aa5a [Josh Rosen] Use ResetSystemProperties in SizeEstimatorSuite dd9492b [Josh Rosen] Use ResetSystemProperties in AkkaUtilsSuite b0daff2 [Josh Rosen] Use ResetSystemProperties in BlockManagerSuite e9ded62 [Josh Rosen] Use ResetSystemProperties in TaskSchedulerImplSuite 5b3cb54 [Josh Rosen] Use ResetSystemProperties in SparkListenerSuite 0995c4b [Josh Rosen] Use ResetSystemProperties in SparkContextSchedulerCreationSuite c83ded8 [Josh Rosen] Use ResetSystemProperties in SparkConfSuite 51aa870 [Josh Rosen] Use withSystemProperty in ShuffleSuite 60a63a1 [Josh Rosen] Use ResetSystemProperties in JobCancellationSuite 14a92e4 [Josh Rosen] Use withSystemProperty in FileServerSuite 628f46c [Josh Rosen] Use ResetSystemProperties in DistributedSuite 9e3e0dd [Josh Rosen] Add ResetSystemProperties test fixture mixin; use it in SparkSubmitSuite. 4dcea38 [Josh Rosen] Move withSystemProperty to TestUtils class. --- .../org/apache/spark/DistributedSuite.scala | 21 ++----- .../org/apache/spark/FileServerSuite.scala | 16 ++--- .../apache/spark/JobCancellationSuite.scala | 21 +++---- .../scala/org/apache/spark/ShuffleSuite.scala | 22 +++---- .../org/apache/spark/SparkConfSuite.scala | 51 ++++++--------- .../SparkContextSchedulerCreationSuite.scala | 31 ++++------ .../org/apache/spark/SparkContextSuite.scala | 62 +++++++------------ .../spark/deploy/SparkSubmitSuite.scala | 6 +- .../spark/scheduler/SparkListenerSuite.scala | 9 +-- .../scheduler/TaskResultGetterSuite.scala | 23 +++---- .../scheduler/TaskSchedulerImplSuite.scala | 6 +- .../spark/storage/BlockManagerSuite.scala | 23 +++---- .../apache/spark/util/AkkaUtilsSuite.scala | 2 +- .../spark/util/ResetSystemProperties.scala | 57 +++++++++++++++++ .../spark/util/SizeEstimatorSuite.scala | 38 +++--------- .../org/apache/spark/util/UtilsSuite.scala | 2 +- .../apache/spark/examples/BroadcastTest.scala | 6 +- .../streaming/LocalJavaStreamingContext.java | 8 ++- .../streaming/LocalJavaStreamingContext.java | 8 ++- .../streaming/LocalJavaStreamingContext.java | 8 ++- .../streaming/LocalJavaStreamingContext.java | 8 ++- .../streaming/LocalJavaStreamingContext.java | 8 ++- .../spark/tools/StoragePerfTester.scala | 12 ++-- 23 files changed, 216 insertions(+), 232 deletions(-) create mode 100644 core/src/test/scala/org/apache/spark/util/ResetSystemProperties.scala diff --git a/core/src/test/scala/org/apache/spark/DistributedSuite.scala b/core/src/test/scala/org/apache/spark/DistributedSuite.scala index 998f3008ec0ea..97ea3578aa8ba 100644 --- a/core/src/test/scala/org/apache/spark/DistributedSuite.scala +++ b/core/src/test/scala/org/apache/spark/DistributedSuite.scala @@ -17,7 +17,6 @@ package org.apache.spark -import org.scalatest.BeforeAndAfter import org.scalatest.FunSuite import org.scalatest.concurrent.Timeouts._ import org.scalatest.Matchers @@ -29,16 +28,10 @@ class NotSerializableClass class NotSerializableExn(val notSer: NotSerializableClass) extends Throwable() {} -class DistributedSuite extends FunSuite with Matchers with BeforeAndAfter - with LocalSparkContext { +class DistributedSuite extends FunSuite with Matchers with LocalSparkContext { val clusterUrl = "local-cluster[2,1,512]" - after { - System.clearProperty("spark.reducer.maxMbInFlight") - System.clearProperty("spark.storage.memoryFraction") - } - test("task throws not serializable exception") { // Ensures that executors do not crash when an exn is not serializable. If executors crash, // this test will hang. Correct behavior is that executors don't crash but fail tasks @@ -84,15 +77,14 @@ class DistributedSuite extends FunSuite with Matchers with BeforeAndAfter } test("groupByKey where map output sizes exceed maxMbInFlight") { - System.setProperty("spark.reducer.maxMbInFlight", "1") - sc = new SparkContext(clusterUrl, "test") + val conf = new SparkConf().set("spark.reducer.maxMbInFlight", "1") + sc = new SparkContext(clusterUrl, "test", conf) // This data should be around 20 MB, so even with 4 mappers and 2 reducers, each map output // file should be about 2.5 MB val pairs = sc.parallelize(1 to 2000, 4).map(x => (x % 16, new Array[Byte](10000))) val groups = pairs.groupByKey(2).map(x => (x._1, x._2.size)).collect() assert(groups.length === 16) assert(groups.map(_._2).sum === 2000) - // Note that spark.reducer.maxMbInFlight will be cleared in the test suite's after{} block } test("accumulators") { @@ -210,7 +202,6 @@ class DistributedSuite extends FunSuite with Matchers with BeforeAndAfter } test("compute without caching when no partitions fit in memory") { - System.setProperty("spark.storage.memoryFraction", "0.0001") sc = new SparkContext(clusterUrl, "test") // data will be 4 million * 4 bytes = 16 MB in size, but our memoryFraction set the cache // to only 50 KB (0.0001 of 512 MB), so no partitions should fit in memory @@ -218,12 +209,11 @@ class DistributedSuite extends FunSuite with Matchers with BeforeAndAfter assert(data.count() === 4000000) assert(data.count() === 4000000) assert(data.count() === 4000000) - System.clearProperty("spark.storage.memoryFraction") } test("compute when only some partitions fit in memory") { - System.setProperty("spark.storage.memoryFraction", "0.01") - sc = new SparkContext(clusterUrl, "test") + val conf = new SparkConf().set("spark.storage.memoryFraction", "0.01") + sc = new SparkContext(clusterUrl, "test", conf) // data will be 4 million * 4 bytes = 16 MB in size, but our memoryFraction set the cache // to only 5 MB (0.01 of 512 MB), so not all of it will fit in memory; we use 20 partitions // to make sure that *some* of them do fit though @@ -231,7 +221,6 @@ class DistributedSuite extends FunSuite with Matchers with BeforeAndAfter assert(data.count() === 4000000) assert(data.count() === 4000000) assert(data.count() === 4000000) - System.clearProperty("spark.storage.memoryFraction") } test("passing environment variables to cluster") { diff --git a/core/src/test/scala/org/apache/spark/FileServerSuite.scala b/core/src/test/scala/org/apache/spark/FileServerSuite.scala index 49426545c767e..0f49ce4754fbb 100644 --- a/core/src/test/scala/org/apache/spark/FileServerSuite.scala +++ b/core/src/test/scala/org/apache/spark/FileServerSuite.scala @@ -31,10 +31,11 @@ class FileServerSuite extends FunSuite with LocalSparkContext { @transient var tmpFile: File = _ @transient var tmpJarUrl: String = _ + def newConf: SparkConf = new SparkConf(loadDefaults = false).set("spark.authenticate", "false") + override def beforeEach() { super.beforeEach() resetSparkContext() - System.setProperty("spark.authenticate", "false") } override def beforeAll() { @@ -52,7 +53,6 @@ class FileServerSuite extends FunSuite with LocalSparkContext { val jarFile = new File(testTempDir, "test.jar") val jarStream = new FileOutputStream(jarFile) val jar = new JarOutputStream(jarStream, new java.util.jar.Manifest()) - System.setProperty("spark.authenticate", "false") val jarEntry = new JarEntry(textFile.getName) jar.putNextEntry(jarEntry) @@ -74,7 +74,7 @@ class FileServerSuite extends FunSuite with LocalSparkContext { } test("Distributing files locally") { - sc = new SparkContext("local[4]", "test") + sc = new SparkContext("local[4]", "test", newConf) sc.addFile(tmpFile.toString) val testData = Array((1,1), (1,1), (2,1), (3,5), (2,2), (3,0)) val result = sc.parallelize(testData).reduceByKey { @@ -108,7 +108,7 @@ class FileServerSuite extends FunSuite with LocalSparkContext { test("Distributing files locally using URL as input") { // addFile("file:///....") - sc = new SparkContext("local[4]", "test") + sc = new SparkContext("local[4]", "test", newConf) sc.addFile(new File(tmpFile.toString).toURI.toString) val testData = Array((1,1), (1,1), (2,1), (3,5), (2,2), (3,0)) val result = sc.parallelize(testData).reduceByKey { @@ -122,7 +122,7 @@ class FileServerSuite extends FunSuite with LocalSparkContext { } test ("Dynamically adding JARS locally") { - sc = new SparkContext("local[4]", "test") + sc = new SparkContext("local[4]", "test", newConf) sc.addJar(tmpJarUrl) val testData = Array((1, 1)) sc.parallelize(testData).foreach { x => @@ -133,7 +133,7 @@ class FileServerSuite extends FunSuite with LocalSparkContext { } test("Distributing files on a standalone cluster") { - sc = new SparkContext("local-cluster[1,1,512]", "test") + sc = new SparkContext("local-cluster[1,1,512]", "test", newConf) sc.addFile(tmpFile.toString) val testData = Array((1,1), (1,1), (2,1), (3,5), (2,2), (3,0)) val result = sc.parallelize(testData).reduceByKey { @@ -147,7 +147,7 @@ class FileServerSuite extends FunSuite with LocalSparkContext { } test ("Dynamically adding JARS on a standalone cluster") { - sc = new SparkContext("local-cluster[1,1,512]", "test") + sc = new SparkContext("local-cluster[1,1,512]", "test", newConf) sc.addJar(tmpJarUrl) val testData = Array((1,1)) sc.parallelize(testData).foreach { x => @@ -158,7 +158,7 @@ class FileServerSuite extends FunSuite with LocalSparkContext { } test ("Dynamically adding JARS on a standalone cluster using local: URL") { - sc = new SparkContext("local-cluster[1,1,512]", "test") + sc = new SparkContext("local-cluster[1,1,512]", "test", newConf) sc.addJar(tmpJarUrl.replace("file", "local")) val testData = Array((1,1)) sc.parallelize(testData).foreach { x => diff --git a/core/src/test/scala/org/apache/spark/JobCancellationSuite.scala b/core/src/test/scala/org/apache/spark/JobCancellationSuite.scala index 41ed2bce55ce1..7584ae79fc920 100644 --- a/core/src/test/scala/org/apache/spark/JobCancellationSuite.scala +++ b/core/src/test/scala/org/apache/spark/JobCancellationSuite.scala @@ -40,12 +40,11 @@ class JobCancellationSuite extends FunSuite with Matchers with BeforeAndAfter override def afterEach() { super.afterEach() resetSparkContext() - System.clearProperty("spark.scheduler.mode") } test("local mode, FIFO scheduler") { - System.setProperty("spark.scheduler.mode", "FIFO") - sc = new SparkContext("local[2]", "test") + val conf = new SparkConf().set("spark.scheduler.mode", "FIFO") + sc = new SparkContext("local[2]", "test", conf) testCount() testTake() // Make sure we can still launch tasks. @@ -53,10 +52,10 @@ class JobCancellationSuite extends FunSuite with Matchers with BeforeAndAfter } test("local mode, fair scheduler") { - System.setProperty("spark.scheduler.mode", "FAIR") + val conf = new SparkConf().set("spark.scheduler.mode", "FAIR") val xmlPath = getClass.getClassLoader.getResource("fairscheduler.xml").getFile() - System.setProperty("spark.scheduler.allocation.file", xmlPath) - sc = new SparkContext("local[2]", "test") + conf.set("spark.scheduler.allocation.file", xmlPath) + sc = new SparkContext("local[2]", "test", conf) testCount() testTake() // Make sure we can still launch tasks. @@ -64,8 +63,8 @@ class JobCancellationSuite extends FunSuite with Matchers with BeforeAndAfter } test("cluster mode, FIFO scheduler") { - System.setProperty("spark.scheduler.mode", "FIFO") - sc = new SparkContext("local-cluster[2,1,512]", "test") + val conf = new SparkConf().set("spark.scheduler.mode", "FIFO") + sc = new SparkContext("local-cluster[2,1,512]", "test", conf) testCount() testTake() // Make sure we can still launch tasks. @@ -73,10 +72,10 @@ class JobCancellationSuite extends FunSuite with Matchers with BeforeAndAfter } test("cluster mode, fair scheduler") { - System.setProperty("spark.scheduler.mode", "FAIR") + val conf = new SparkConf().set("spark.scheduler.mode", "FAIR") val xmlPath = getClass.getClassLoader.getResource("fairscheduler.xml").getFile() - System.setProperty("spark.scheduler.allocation.file", xmlPath) - sc = new SparkContext("local-cluster[2,1,512]", "test") + conf.set("spark.scheduler.allocation.file", xmlPath) + sc = new SparkContext("local-cluster[2,1,512]", "test", conf) testCount() testTake() // Make sure we can still launch tasks. diff --git a/core/src/test/scala/org/apache/spark/ShuffleSuite.scala b/core/src/test/scala/org/apache/spark/ShuffleSuite.scala index 58a96245a9b53..f57921b768310 100644 --- a/core/src/test/scala/org/apache/spark/ShuffleSuite.scala +++ b/core/src/test/scala/org/apache/spark/ShuffleSuite.scala @@ -35,19 +35,15 @@ abstract class ShuffleSuite extends FunSuite with Matchers with LocalSparkContex conf.set("spark.test.noStageRetry", "true") test("groupByKey without compression") { - try { - System.setProperty("spark.shuffle.compress", "false") - sc = new SparkContext("local", "test", conf) - val pairs = sc.parallelize(Array((1, 1), (1, 2), (1, 3), (2, 1)), 4) - val groups = pairs.groupByKey(4).collect() - assert(groups.size === 2) - val valuesFor1 = groups.find(_._1 == 1).get._2 - assert(valuesFor1.toList.sorted === List(1, 2, 3)) - val valuesFor2 = groups.find(_._1 == 2).get._2 - assert(valuesFor2.toList.sorted === List(1)) - } finally { - System.setProperty("spark.shuffle.compress", "true") - } + val myConf = conf.clone().set("spark.shuffle.compress", "false") + sc = new SparkContext("local", "test", myConf) + val pairs = sc.parallelize(Array((1, 1), (1, 2), (1, 3), (2, 1)), 4) + val groups = pairs.groupByKey(4).collect() + assert(groups.size === 2) + val valuesFor1 = groups.find(_._1 == 1).get._2 + assert(valuesFor1.toList.sorted === List(1, 2, 3)) + val valuesFor2 = groups.find(_._1 == 2).get._2 + assert(valuesFor2.toList.sorted === List(1)) } test("shuffle non-zero block size") { diff --git a/core/src/test/scala/org/apache/spark/SparkConfSuite.scala b/core/src/test/scala/org/apache/spark/SparkConfSuite.scala index 5d018ea9868a7..790976a5ac308 100644 --- a/core/src/test/scala/org/apache/spark/SparkConfSuite.scala +++ b/core/src/test/scala/org/apache/spark/SparkConfSuite.scala @@ -19,27 +19,20 @@ package org.apache.spark import org.scalatest.FunSuite import org.apache.spark.serializer.{KryoRegistrator, KryoSerializer} +import org.apache.spark.util.ResetSystemProperties import com.esotericsoftware.kryo.Kryo -class SparkConfSuite extends FunSuite with LocalSparkContext { +class SparkConfSuite extends FunSuite with LocalSparkContext with ResetSystemProperties { test("loading from system properties") { - try { - System.setProperty("spark.test.testProperty", "2") - val conf = new SparkConf() - assert(conf.get("spark.test.testProperty") === "2") - } finally { - System.clearProperty("spark.test.testProperty") - } + System.setProperty("spark.test.testProperty", "2") + val conf = new SparkConf() + assert(conf.get("spark.test.testProperty") === "2") } test("initializing without loading defaults") { - try { - System.setProperty("spark.test.testProperty", "2") - val conf = new SparkConf(false) - assert(!conf.contains("spark.test.testProperty")) - } finally { - System.clearProperty("spark.test.testProperty") - } + System.setProperty("spark.test.testProperty", "2") + val conf = new SparkConf(false) + assert(!conf.contains("spark.test.testProperty")) } test("named set methods") { @@ -117,23 +110,17 @@ class SparkConfSuite extends FunSuite with LocalSparkContext { test("nested property names") { // This wasn't supported by some external conf parsing libraries - try { - System.setProperty("spark.test.a", "a") - System.setProperty("spark.test.a.b", "a.b") - System.setProperty("spark.test.a.b.c", "a.b.c") - val conf = new SparkConf() - assert(conf.get("spark.test.a") === "a") - assert(conf.get("spark.test.a.b") === "a.b") - assert(conf.get("spark.test.a.b.c") === "a.b.c") - conf.set("spark.test.a.b", "A.B") - assert(conf.get("spark.test.a") === "a") - assert(conf.get("spark.test.a.b") === "A.B") - assert(conf.get("spark.test.a.b.c") === "a.b.c") - } finally { - System.clearProperty("spark.test.a") - System.clearProperty("spark.test.a.b") - System.clearProperty("spark.test.a.b.c") - } + System.setProperty("spark.test.a", "a") + System.setProperty("spark.test.a.b", "a.b") + System.setProperty("spark.test.a.b.c", "a.b.c") + val conf = new SparkConf() + assert(conf.get("spark.test.a") === "a") + assert(conf.get("spark.test.a.b") === "a.b") + assert(conf.get("spark.test.a.b.c") === "a.b.c") + conf.set("spark.test.a.b", "A.B") + assert(conf.get("spark.test.a") === "a") + assert(conf.get("spark.test.a.b") === "A.B") + assert(conf.get("spark.test.a.b.c") === "a.b.c") } test("register kryo classes through registerKryoClasses") { diff --git a/core/src/test/scala/org/apache/spark/SparkContextSchedulerCreationSuite.scala b/core/src/test/scala/org/apache/spark/SparkContextSchedulerCreationSuite.scala index 0390a2e4f1dbb..8ae4f243ec1ae 100644 --- a/core/src/test/scala/org/apache/spark/SparkContextSchedulerCreationSuite.scala +++ b/core/src/test/scala/org/apache/spark/SparkContextSchedulerCreationSuite.scala @@ -27,10 +27,13 @@ import org.apache.spark.scheduler.local.LocalBackend class SparkContextSchedulerCreationSuite extends FunSuite with LocalSparkContext with PrivateMethodTester with Logging { - def createTaskScheduler(master: String): TaskSchedulerImpl = { + def createTaskScheduler(master: String): TaskSchedulerImpl = + createTaskScheduler(master, new SparkConf()) + + def createTaskScheduler(master: String, conf: SparkConf): TaskSchedulerImpl = { // Create local SparkContext to setup a SparkEnv. We don't actually want to start() the // real schedulers, so we don't want to create a full SparkContext with the desired scheduler. - sc = new SparkContext("local", "test") + sc = new SparkContext("local", "test", conf) val createTaskSchedulerMethod = PrivateMethod[Tuple2[SchedulerBackend, TaskScheduler]]('createTaskScheduler) val (_, sched) = SparkContext invokePrivate createTaskSchedulerMethod(sc, master) @@ -102,19 +105,13 @@ class SparkContextSchedulerCreationSuite } test("local-default-parallelism") { - val defaultParallelism = System.getProperty("spark.default.parallelism") - System.setProperty("spark.default.parallelism", "16") - val sched = createTaskScheduler("local") + val conf = new SparkConf().set("spark.default.parallelism", "16") + val sched = createTaskScheduler("local", conf) sched.backend match { case s: LocalBackend => assert(s.defaultParallelism() === 16) case _ => fail() } - - Option(defaultParallelism) match { - case Some(v) => System.setProperty("spark.default.parallelism", v) - case _ => System.clearProperty("spark.default.parallelism") - } } test("simr") { @@ -155,9 +152,10 @@ class SparkContextSchedulerCreationSuite testYarn("yarn-client", "org.apache.spark.scheduler.cluster.YarnClientClusterScheduler") } - def testMesos(master: String, expectedClass: Class[_]) { + def testMesos(master: String, expectedClass: Class[_], coarse: Boolean) { + val conf = new SparkConf().set("spark.mesos.coarse", coarse.toString) try { - val sched = createTaskScheduler(master) + val sched = createTaskScheduler(master, conf) assert(sched.backend.getClass === expectedClass) } catch { case e: UnsatisfiedLinkError => @@ -168,17 +166,14 @@ class SparkContextSchedulerCreationSuite } test("mesos fine-grained") { - System.setProperty("spark.mesos.coarse", "false") - testMesos("mesos://localhost:1234", classOf[MesosSchedulerBackend]) + testMesos("mesos://localhost:1234", classOf[MesosSchedulerBackend], coarse = false) } test("mesos coarse-grained") { - System.setProperty("spark.mesos.coarse", "true") - testMesos("mesos://localhost:1234", classOf[CoarseMesosSchedulerBackend]) + testMesos("mesos://localhost:1234", classOf[CoarseMesosSchedulerBackend], coarse = true) } test("mesos with zookeeper") { - System.setProperty("spark.mesos.coarse", "false") - testMesos("zk://localhost:1234,localhost:2345", classOf[MesosSchedulerBackend]) + testMesos("zk://localhost:1234,localhost:2345", classOf[MesosSchedulerBackend], coarse = false) } } diff --git a/core/src/test/scala/org/apache/spark/SparkContextSuite.scala b/core/src/test/scala/org/apache/spark/SparkContextSuite.scala index 1362022104195..8b3c6871a7b39 100644 --- a/core/src/test/scala/org/apache/spark/SparkContextSuite.scala +++ b/core/src/test/scala/org/apache/spark/SparkContextSuite.scala @@ -23,55 +23,37 @@ import org.apache.hadoop.io.BytesWritable class SparkContextSuite extends FunSuite with LocalSparkContext { - /** Allows system properties to be changed in tests */ - private def withSystemProperty[T](property: String, value: String)(block: => T): T = { - val originalValue = System.getProperty(property) - try { - System.setProperty(property, value) - block - } finally { - if (originalValue == null) { - System.clearProperty(property) - } else { - System.setProperty(property, originalValue) - } - } - } - test("Only one SparkContext may be active at a time") { // Regression test for SPARK-4180 - withSystemProperty("spark.driver.allowMultipleContexts", "false") { - val conf = new SparkConf().setAppName("test").setMaster("local") - sc = new SparkContext(conf) - // A SparkContext is already running, so we shouldn't be able to create a second one - intercept[SparkException] { new SparkContext(conf) } - // After stopping the running context, we should be able to create a new one - resetSparkContext() - sc = new SparkContext(conf) - } + val conf = new SparkConf().setAppName("test").setMaster("local") + .set("spark.driver.allowMultipleContexts", "false") + sc = new SparkContext(conf) + // A SparkContext is already running, so we shouldn't be able to create a second one + intercept[SparkException] { new SparkContext(conf) } + // After stopping the running context, we should be able to create a new one + resetSparkContext() + sc = new SparkContext(conf) } test("Can still construct a new SparkContext after failing to construct a previous one") { - withSystemProperty("spark.driver.allowMultipleContexts", "false") { - // This is an invalid configuration (no app name or master URL) - intercept[SparkException] { - new SparkContext(new SparkConf()) - } - // Even though those earlier calls failed, we should still be able to create a new context - sc = new SparkContext(new SparkConf().setMaster("local").setAppName("test")) + val conf = new SparkConf().set("spark.driver.allowMultipleContexts", "false") + // This is an invalid configuration (no app name or master URL) + intercept[SparkException] { + new SparkContext(conf) } + // Even though those earlier calls failed, we should still be able to create a new context + sc = new SparkContext(conf.setMaster("local").setAppName("test")) } test("Check for multiple SparkContexts can be disabled via undocumented debug option") { - withSystemProperty("spark.driver.allowMultipleContexts", "true") { - var secondSparkContext: SparkContext = null - try { - val conf = new SparkConf().setAppName("test").setMaster("local") - sc = new SparkContext(conf) - secondSparkContext = new SparkContext(conf) - } finally { - Option(secondSparkContext).foreach(_.stop()) - } + var secondSparkContext: SparkContext = null + try { + val conf = new SparkConf().setAppName("test").setMaster("local") + .set("spark.driver.allowMultipleContexts", "true") + sc = new SparkContext(conf) + secondSparkContext = new SparkContext(conf) + } finally { + Option(secondSparkContext).foreach(_.stop()) } } diff --git a/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala b/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala index eb7bd7ab3986e..5eda2d41f0e6d 100644 --- a/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala +++ b/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala @@ -23,11 +23,13 @@ import scala.collection.mutable.ArrayBuffer import org.apache.spark._ import org.apache.spark.deploy.SparkSubmit._ -import org.apache.spark.util.Utils +import org.apache.spark.util.{ResetSystemProperties, Utils} import org.scalatest.FunSuite import org.scalatest.Matchers -class SparkSubmitSuite extends FunSuite with Matchers { +// Note: this suite mixes in ResetSystemProperties because SparkSubmit.main() sets a bunch +// of properties that neeed to be cleared after tests. +class SparkSubmitSuite extends FunSuite with Matchers with ResetSystemProperties { def beforeAll() { System.setProperty("spark.testing", "true") } diff --git a/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala index b276343cb412c..24f41bf8cccda 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala @@ -26,9 +26,10 @@ import org.scalatest.Matchers import org.apache.spark.{LocalSparkContext, SparkContext} import org.apache.spark.executor.TaskMetrics +import org.apache.spark.util.ResetSystemProperties -class SparkListenerSuite extends FunSuite with LocalSparkContext with Matchers - with BeforeAndAfter with BeforeAndAfterAll { +class SparkListenerSuite extends FunSuite with LocalSparkContext with Matchers with BeforeAndAfter + with BeforeAndAfterAll with ResetSystemProperties { /** Length of time to wait while draining listener events. */ val WAIT_TIMEOUT_MILLIS = 10000 @@ -37,10 +38,6 @@ class SparkListenerSuite extends FunSuite with LocalSparkContext with Matchers sc = new SparkContext("local", "SparkListenerSuite") } - override def afterAll() { - System.clearProperty("spark.akka.frameSize") - } - test("basic creation and shutdown of LiveListenerBus") { val counter = new BasicJobCounter val bus = new LiveListenerBus diff --git a/core/src/test/scala/org/apache/spark/scheduler/TaskResultGetterSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/TaskResultGetterSuite.scala index 5768a3a733f00..3aab5a156ee77 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/TaskResultGetterSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/TaskResultGetterSuite.scala @@ -21,7 +21,7 @@ import java.nio.ByteBuffer import org.scalatest.{BeforeAndAfter, BeforeAndAfterAll, FunSuite} -import org.apache.spark.{LocalSparkContext, SparkContext, SparkEnv} +import org.apache.spark.{LocalSparkContext, SparkConf, SparkContext, SparkEnv} import org.apache.spark.storage.TaskResultBlockId /** @@ -55,27 +55,20 @@ class ResultDeletingTaskResultGetter(sparkEnv: SparkEnv, scheduler: TaskSchedule /** * Tests related to handling task results (both direct and indirect). */ -class TaskResultGetterSuite extends FunSuite with BeforeAndAfter with BeforeAndAfterAll - with LocalSparkContext { +class TaskResultGetterSuite extends FunSuite with BeforeAndAfter with LocalSparkContext { - override def beforeAll { - // Set the Akka frame size to be as small as possible (it must be an integer, so 1 is as small - // as we can make it) so the tests don't take too long. - System.setProperty("spark.akka.frameSize", "1") - } - - override def afterAll { - System.clearProperty("spark.akka.frameSize") - } + // Set the Akka frame size to be as small as possible (it must be an integer, so 1 is as small + // as we can make it) so the tests don't take too long. + def conf: SparkConf = new SparkConf().set("spark.akka.frameSize", "1") test("handling results smaller than Akka frame size") { - sc = new SparkContext("local", "test") + sc = new SparkContext("local", "test", conf) val result = sc.parallelize(Seq(1), 1).map(x => 2 * x).reduce((x, y) => x) assert(result === 2) } test("handling results larger than Akka frame size") { - sc = new SparkContext("local", "test") + sc = new SparkContext("local", "test", conf) val akkaFrameSize = sc.env.actorSystem.settings.config.getBytes("akka.remote.netty.tcp.maximum-frame-size").toInt val result = sc.parallelize(Seq(1), 1).map(x => 1.to(akkaFrameSize).toArray).reduce((x, y) => x) @@ -89,7 +82,7 @@ class TaskResultGetterSuite extends FunSuite with BeforeAndAfter with BeforeAndA test("task retried if result missing from block manager") { // Set the maximum number of task failures to > 0, so that the task set isn't aborted // after the result is missing. - sc = new SparkContext("local[1,2]", "test") + sc = new SparkContext("local[1,2]", "test", conf) // If this test hangs, it's probably because no resource offers were made after the task // failed. val scheduler: TaskSchedulerImpl = sc.taskScheduler match { diff --git a/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala index 7532da88c6065..40aaf9dd1f1e9 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala @@ -162,12 +162,12 @@ class TaskSchedulerImplSuite extends FunSuite with LocalSparkContext with Loggin } test("Fair Scheduler Test") { - sc = new SparkContext("local", "TaskSchedulerImplSuite") + val xmlPath = getClass.getClassLoader.getResource("fairscheduler.xml").getFile() + val conf = new SparkConf().set("spark.scheduler.allocation.file", xmlPath) + sc = new SparkContext("local", "TaskSchedulerImplSuite", conf) val taskScheduler = new TaskSchedulerImpl(sc) val taskSet = FakeTask.createTaskSet(1) - val xmlPath = getClass.getClassLoader.getResource("fairscheduler.xml").getFile() - System.setProperty("spark.scheduler.allocation.file", xmlPath) val rootPool = new Pool("", SchedulingMode.FAIR, 0, 0) val schedulableBuilder = new FairSchedulableBuilder(rootPool, sc.conf) schedulableBuilder.buildPools() diff --git a/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala b/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala index 5554efbcbadf8..ffe6f039145ea 100644 --- a/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala +++ b/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala @@ -33,7 +33,7 @@ import akka.util.Timeout import org.mockito.Mockito.{mock, when} -import org.scalatest.{BeforeAndAfter, FunSuite, Matchers, PrivateMethodTester} +import org.scalatest._ import org.scalatest.concurrent.Eventually._ import org.scalatest.concurrent.Timeouts._ @@ -44,18 +44,17 @@ import org.apache.spark.scheduler.LiveListenerBus import org.apache.spark.serializer.{JavaSerializer, KryoSerializer} import org.apache.spark.shuffle.hash.HashShuffleManager import org.apache.spark.storage.BlockManagerMessages.BlockManagerHeartbeat -import org.apache.spark.util.{AkkaUtils, ByteBufferInputStream, SizeEstimator, Utils} +import org.apache.spark.util._ -class BlockManagerSuite extends FunSuite with Matchers with BeforeAndAfter - with PrivateMethodTester { +class BlockManagerSuite extends FunSuite with Matchers with BeforeAndAfterEach + with PrivateMethodTester with ResetSystemProperties { private val conf = new SparkConf(false) var store: BlockManager = null var store2: BlockManager = null var actorSystem: ActorSystem = null var master: BlockManagerMaster = null - var oldArch: String = null conf.set("spark.authenticate", "false") val securityMgr = new SecurityManager(conf) val mapOutputTracker = new MapOutputTrackerMaster(conf) @@ -79,13 +78,13 @@ class BlockManagerSuite extends FunSuite with Matchers with BeforeAndAfter manager } - before { + override def beforeEach(): Unit = { val (actorSystem, boundPort) = AkkaUtils.createActorSystem( "test", "localhost", 0, conf = conf, securityManager = securityMgr) this.actorSystem = actorSystem // Set the arch to 64-bit and compressedOops to true to get a deterministic test-case - oldArch = System.setProperty("os.arch", "amd64") + System.setProperty("os.arch", "amd64") conf.set("os.arch", "amd64") conf.set("spark.test.useCompressedOops", "true") conf.set("spark.driver.port", boundPort.toString) @@ -100,7 +99,7 @@ class BlockManagerSuite extends FunSuite with Matchers with BeforeAndAfter SizeEstimator invokePrivate initialize() } - after { + override def afterEach(): Unit = { if (store != null) { store.stop() store = null @@ -113,14 +112,6 @@ class BlockManagerSuite extends FunSuite with Matchers with BeforeAndAfter actorSystem.awaitTermination() actorSystem = null master = null - - if (oldArch != null) { - conf.set("os.arch", oldArch) - } else { - System.clearProperty("os.arch") - } - - System.clearProperty("spark.test.useCompressedOops") } test("StorageLevel object caching") { diff --git a/core/src/test/scala/org/apache/spark/util/AkkaUtilsSuite.scala b/core/src/test/scala/org/apache/spark/util/AkkaUtilsSuite.scala index 7bca1711ae226..6bbf72e929dcb 100644 --- a/core/src/test/scala/org/apache/spark/util/AkkaUtilsSuite.scala +++ b/core/src/test/scala/org/apache/spark/util/AkkaUtilsSuite.scala @@ -31,7 +31,7 @@ import org.apache.spark.storage.BlockManagerId /** * Test the AkkaUtils with various security settings. */ -class AkkaUtilsSuite extends FunSuite with LocalSparkContext { +class AkkaUtilsSuite extends FunSuite with LocalSparkContext with ResetSystemProperties { test("remote fetch security bad password") { val conf = new SparkConf diff --git a/core/src/test/scala/org/apache/spark/util/ResetSystemProperties.scala b/core/src/test/scala/org/apache/spark/util/ResetSystemProperties.scala new file mode 100644 index 0000000000000..d4b92f33dd9e6 --- /dev/null +++ b/core/src/test/scala/org/apache/spark/util/ResetSystemProperties.scala @@ -0,0 +1,57 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util + +import java.util.Properties + +import org.scalatest.{BeforeAndAfterEach, Suite} + +/** + * Mixin for automatically resetting system properties that are modified in ScalaTest tests. + * This resets the properties after each individual test. + * + * The order in which fixtures are mixed in affects the order in which they are invoked by tests. + * If we have a suite `MySuite extends FunSuite with Foo with Bar`, then + * Bar's `super` is Foo, so Bar's beforeEach() will and afterEach() methods will be invoked first + * by the rest runner. + * + * This means that ResetSystemProperties should appear as the last trait in test suites that it's + * mixed into in order to ensure that the system properties snapshot occurs as early as possible. + * ResetSystemProperties calls super.afterEach() before performing its own cleanup, ensuring that + * the old properties are restored as late as possible. + * + * See the "Composing fixtures by stacking traits" section at + * http://www.scalatest.org/user_guide/sharing_fixtures for more details about this pattern. + */ +private[spark] trait ResetSystemProperties extends BeforeAndAfterEach { this: Suite => + var oldProperties: Properties = null + + override def beforeEach(): Unit = { + oldProperties = new Properties(System.getProperties) + super.beforeEach() + } + + override def afterEach(): Unit = { + try { + super.afterEach() + } finally { + System.setProperties(oldProperties) + oldProperties = null + } + } +} diff --git a/core/src/test/scala/org/apache/spark/util/SizeEstimatorSuite.scala b/core/src/test/scala/org/apache/spark/util/SizeEstimatorSuite.scala index 0ea2d13a83505..7424c2e91d4f2 100644 --- a/core/src/test/scala/org/apache/spark/util/SizeEstimatorSuite.scala +++ b/core/src/test/scala/org/apache/spark/util/SizeEstimatorSuite.scala @@ -17,9 +17,7 @@ package org.apache.spark.util -import org.scalatest.BeforeAndAfterAll -import org.scalatest.FunSuite -import org.scalatest.PrivateMethodTester +import org.scalatest.{BeforeAndAfterEach, BeforeAndAfterAll, FunSuite, PrivateMethodTester} class DummyClass1 {} @@ -46,20 +44,12 @@ class DummyString(val arr: Array[Char]) { } class SizeEstimatorSuite - extends FunSuite with BeforeAndAfterAll with PrivateMethodTester { + extends FunSuite with BeforeAndAfterEach with PrivateMethodTester with ResetSystemProperties { - var oldArch: String = _ - var oldOops: String = _ - - override def beforeAll() { + override def beforeEach() { // Set the arch to 64-bit and compressedOops to true to get a deterministic test-case - oldArch = System.setProperty("os.arch", "amd64") - oldOops = System.setProperty("spark.test.useCompressedOops", "true") - } - - override def afterAll() { - resetOrClear("os.arch", oldArch) - resetOrClear("spark.test.useCompressedOops", oldOops) + System.setProperty("os.arch", "amd64") + System.setProperty("spark.test.useCompressedOops", "true") } test("simple classes") { @@ -122,7 +112,7 @@ class SizeEstimatorSuite } test("32-bit arch") { - val arch = System.setProperty("os.arch", "x86") + System.setProperty("os.arch", "x86") val initialize = PrivateMethod[Unit]('initialize) SizeEstimator invokePrivate initialize() @@ -131,14 +121,13 @@ class SizeEstimatorSuite assertResult(48)(SizeEstimator.estimate(DummyString("a"))) assertResult(48)(SizeEstimator.estimate(DummyString("ab"))) assertResult(56)(SizeEstimator.estimate(DummyString("abcdefgh"))) - resetOrClear("os.arch", arch) } // NOTE: The String class definition varies across JDK versions (1.6 vs. 1.7) and vendors // (Sun vs IBM). Use a DummyString class to make tests deterministic. test("64-bit arch with no compressed oops") { - val arch = System.setProperty("os.arch", "amd64") - val oops = System.setProperty("spark.test.useCompressedOops", "false") + System.setProperty("os.arch", "amd64") + System.setProperty("spark.test.useCompressedOops", "false") val initialize = PrivateMethod[Unit]('initialize) SizeEstimator invokePrivate initialize() @@ -146,16 +135,5 @@ class SizeEstimatorSuite assertResult(64)(SizeEstimator.estimate(DummyString("a"))) assertResult(64)(SizeEstimator.estimate(DummyString("ab"))) assertResult(72)(SizeEstimator.estimate(DummyString("abcdefgh"))) - - resetOrClear("os.arch", arch) - resetOrClear("spark.test.useCompressedOops", oops) - } - - def resetOrClear(prop: String, oldValue: String) { - if (oldValue != null) { - System.setProperty(prop, oldValue) - } else { - System.clearProperty(prop) - } } } diff --git a/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala b/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala index f9d4bea823f7c..4544382094f96 100644 --- a/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala +++ b/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala @@ -31,7 +31,7 @@ import org.scalatest.FunSuite import org.apache.spark.SparkConf -class UtilsSuite extends FunSuite { +class UtilsSuite extends FunSuite with ResetSystemProperties { test("bytesToString") { assert(Utils.bytesToString(10) === "10.0 B") diff --git a/examples/src/main/scala/org/apache/spark/examples/BroadcastTest.scala b/examples/src/main/scala/org/apache/spark/examples/BroadcastTest.scala index adecd934358c4..1b53f3edbe92e 100644 --- a/examples/src/main/scala/org/apache/spark/examples/BroadcastTest.scala +++ b/examples/src/main/scala/org/apache/spark/examples/BroadcastTest.scala @@ -28,11 +28,9 @@ object BroadcastTest { val bcName = if (args.length > 2) args(2) else "Http" val blockSize = if (args.length > 3) args(3) else "4096" - System.setProperty("spark.broadcast.factory", "org.apache.spark.broadcast." + bcName + - "BroadcastFactory") - System.setProperty("spark.broadcast.blockSize", blockSize) val sparkConf = new SparkConf().setAppName("Broadcast Test") - + .set("spark.broadcast.factory", s"org.apache.spark.broadcast.${bcName}BroaddcastFactory") + .set("spark.broadcast.blockSize", blockSize) val sc = new SparkContext(sparkConf) val slices = if (args.length > 0) args(0).toInt else 2 diff --git a/external/flume/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java b/external/flume/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java index 6e1f01900071b..1e24da7f5f60c 100644 --- a/external/flume/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java +++ b/external/flume/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java @@ -17,6 +17,7 @@ package org.apache.spark.streaming; +import org.apache.spark.SparkConf; import org.apache.spark.streaming.api.java.JavaStreamingContext; import org.junit.After; import org.junit.Before; @@ -27,8 +28,11 @@ public abstract class LocalJavaStreamingContext { @Before public void setUp() { - System.setProperty("spark.streaming.clock", "org.apache.spark.streaming.util.ManualClock"); - ssc = new JavaStreamingContext("local[2]", "test", new Duration(1000)); + SparkConf conf = new SparkConf() + .setMaster("local[2]") + .setAppName("test") + .set("spark.streaming.clock", "org.apache.spark.streaming.util.ManualClock"); + ssc = new JavaStreamingContext(conf, new Duration(1000)); ssc.checkpoint("checkpoint"); } diff --git a/external/mqtt/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java b/external/mqtt/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java index 6e1f01900071b..1e24da7f5f60c 100644 --- a/external/mqtt/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java +++ b/external/mqtt/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java @@ -17,6 +17,7 @@ package org.apache.spark.streaming; +import org.apache.spark.SparkConf; import org.apache.spark.streaming.api.java.JavaStreamingContext; import org.junit.After; import org.junit.Before; @@ -27,8 +28,11 @@ public abstract class LocalJavaStreamingContext { @Before public void setUp() { - System.setProperty("spark.streaming.clock", "org.apache.spark.streaming.util.ManualClock"); - ssc = new JavaStreamingContext("local[2]", "test", new Duration(1000)); + SparkConf conf = new SparkConf() + .setMaster("local[2]") + .setAppName("test") + .set("spark.streaming.clock", "org.apache.spark.streaming.util.ManualClock"); + ssc = new JavaStreamingContext(conf, new Duration(1000)); ssc.checkpoint("checkpoint"); } diff --git a/external/twitter/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java b/external/twitter/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java index 6e1f01900071b..1e24da7f5f60c 100644 --- a/external/twitter/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java +++ b/external/twitter/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java @@ -17,6 +17,7 @@ package org.apache.spark.streaming; +import org.apache.spark.SparkConf; import org.apache.spark.streaming.api.java.JavaStreamingContext; import org.junit.After; import org.junit.Before; @@ -27,8 +28,11 @@ public abstract class LocalJavaStreamingContext { @Before public void setUp() { - System.setProperty("spark.streaming.clock", "org.apache.spark.streaming.util.ManualClock"); - ssc = new JavaStreamingContext("local[2]", "test", new Duration(1000)); + SparkConf conf = new SparkConf() + .setMaster("local[2]") + .setAppName("test") + .set("spark.streaming.clock", "org.apache.spark.streaming.util.ManualClock"); + ssc = new JavaStreamingContext(conf, new Duration(1000)); ssc.checkpoint("checkpoint"); } diff --git a/external/zeromq/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java b/external/zeromq/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java index 6e1f01900071b..1e24da7f5f60c 100644 --- a/external/zeromq/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java +++ b/external/zeromq/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java @@ -17,6 +17,7 @@ package org.apache.spark.streaming; +import org.apache.spark.SparkConf; import org.apache.spark.streaming.api.java.JavaStreamingContext; import org.junit.After; import org.junit.Before; @@ -27,8 +28,11 @@ public abstract class LocalJavaStreamingContext { @Before public void setUp() { - System.setProperty("spark.streaming.clock", "org.apache.spark.streaming.util.ManualClock"); - ssc = new JavaStreamingContext("local[2]", "test", new Duration(1000)); + SparkConf conf = new SparkConf() + .setMaster("local[2]") + .setAppName("test") + .set("spark.streaming.clock", "org.apache.spark.streaming.util.ManualClock"); + ssc = new JavaStreamingContext(conf, new Duration(1000)); ssc.checkpoint("checkpoint"); } diff --git a/streaming/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java b/streaming/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java index 6e1f01900071b..1e24da7f5f60c 100644 --- a/streaming/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java +++ b/streaming/src/test/java/org/apache/spark/streaming/LocalJavaStreamingContext.java @@ -17,6 +17,7 @@ package org.apache.spark.streaming; +import org.apache.spark.SparkConf; import org.apache.spark.streaming.api.java.JavaStreamingContext; import org.junit.After; import org.junit.Before; @@ -27,8 +28,11 @@ public abstract class LocalJavaStreamingContext { @Before public void setUp() { - System.setProperty("spark.streaming.clock", "org.apache.spark.streaming.util.ManualClock"); - ssc = new JavaStreamingContext("local[2]", "test", new Duration(1000)); + SparkConf conf = new SparkConf() + .setMaster("local[2]") + .setAppName("test") + .set("spark.streaming.clock", "org.apache.spark.streaming.util.ManualClock"); + ssc = new JavaStreamingContext(conf, new Duration(1000)); ssc.checkpoint("checkpoint"); } diff --git a/tools/src/main/scala/org/apache/spark/tools/StoragePerfTester.scala b/tools/src/main/scala/org/apache/spark/tools/StoragePerfTester.scala index db58eb642b56d..15ee95070a3d3 100644 --- a/tools/src/main/scala/org/apache/spark/tools/StoragePerfTester.scala +++ b/tools/src/main/scala/org/apache/spark/tools/StoragePerfTester.scala @@ -21,7 +21,7 @@ import java.util.concurrent.{CountDownLatch, Executors} import java.util.concurrent.atomic.AtomicLong import org.apache.spark.executor.ShuffleWriteMetrics -import org.apache.spark.SparkContext +import org.apache.spark.{SparkConf, SparkContext} import org.apache.spark.serializer.KryoSerializer import org.apache.spark.shuffle.hash.HashShuffleManager import org.apache.spark.util.Utils @@ -49,13 +49,13 @@ object StoragePerfTester { val writeData = "1" * recordLength val executor = Executors.newFixedThreadPool(numMaps) - System.setProperty("spark.shuffle.compress", "false") - System.setProperty("spark.shuffle.sync", "true") - System.setProperty("spark.shuffle.manager", - "org.apache.spark.shuffle.hash.HashShuffleManager") + val conf = new SparkConf() + .set("spark.shuffle.compress", "false") + .set("spark.shuffle.sync", "true") + .set("spark.shuffle.manager", "org.apache.spark.shuffle.hash.HashShuffleManager") // This is only used to instantiate a BlockManager. All thread scheduling is done manually. - val sc = new SparkContext("local[4]", "Write Tester") + val sc = new SparkContext("local[4]", "Write Tester", conf) val hashShuffleManager = sc.env.shuffleManager.asInstanceOf[HashShuffleManager] def writeOutputBytes(mapId: Int, total: AtomicLong) = { From 06a9aa589c518a40a3c7cc201e89d75af77ab93e Mon Sep 17 00:00:00 2001 From: Liang-Chi Hsieh Date: Wed, 31 Dec 2014 11:50:53 -0800 Subject: [PATCH 145/320] [SPARK-4797] Replace breezeSquaredDistance This PR replaces slow breezeSquaredDistance. Author: Liang-Chi Hsieh Closes #3643 from viirya/faster_squareddistance and squashes the following commits: f28b275 [Liang-Chi Hsieh] Move the implementation to linalg.Vectors and rename as sqdist. 0bc48ee [Liang-Chi Hsieh] Merge branch 'master' into faster_squareddistance ba34422 [Liang-Chi Hsieh] Fix bug. 91849d0 [Liang-Chi Hsieh] Modified for comment. 44a65ad [Liang-Chi Hsieh] Modified for comments. 35db395 [Liang-Chi Hsieh] Fix bug and some modifications for comments. f4f5ebb [Liang-Chi Hsieh] Follow BLAS.dot pattern to replace intersect, diff with while-loop. a36e09f [Liang-Chi Hsieh] Use while-loop to replace foreach for better performance. d3e0628 [Liang-Chi Hsieh] Make the methods private. dd415bc [Liang-Chi Hsieh] Consider different cases of SparseVector and DenseVector. 13669db [Liang-Chi Hsieh] Replace breezeSquaredDistance. --- .../apache/spark/mllib/linalg/Vectors.scala | 80 +++++++++++++++++++ .../org/apache/spark/mllib/util/MLUtils.scala | 13 ++- .../spark/mllib/util/MLUtilsSuite.scala | 15 ++++ 3 files changed, 100 insertions(+), 8 deletions(-) diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala index 01f3f90577142..6a782b079aac3 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala @@ -312,6 +312,86 @@ object Vectors { math.pow(sum, 1.0 / p) } } + + /** + * Returns the squared distance between two Vectors. + * @param v1 first Vector. + * @param v2 second Vector. + * @return squared distance between two Vectors. + */ + def sqdist(v1: Vector, v2: Vector): Double = { + var squaredDistance = 0.0 + (v1, v2) match { + case (v1: SparseVector, v2: SparseVector) => + val v1Values = v1.values + val v1Indices = v1.indices + val v2Values = v2.values + val v2Indices = v2.indices + val nnzv1 = v1Indices.size + val nnzv2 = v2Indices.size + + var kv1 = 0 + var kv2 = 0 + while (kv1 < nnzv1 || kv2 < nnzv2) { + var score = 0.0 + + if (kv2 >= nnzv2 || (kv1 < nnzv1 && v1Indices(kv1) < v2Indices(kv2))) { + score = v1Values(kv1) + kv1 += 1 + } else if (kv1 >= nnzv1 || (kv2 < nnzv2 && v2Indices(kv2) < v1Indices(kv1))) { + score = v2Values(kv2) + kv2 += 1 + } else { + score = v1Values(kv1) - v2Values(kv2) + kv1 += 1 + kv2 += 1 + } + squaredDistance += score * score + } + + case (v1: SparseVector, v2: DenseVector) if v1.indices.length / v1.size < 0.5 => + squaredDistance = sqdist(v1, v2) + + case (v1: DenseVector, v2: SparseVector) if v2.indices.length / v2.size < 0.5 => + squaredDistance = sqdist(v2, v1) + + // When a SparseVector is approximately dense, we treat it as a DenseVector + case (v1, v2) => + squaredDistance = v1.toArray.zip(v2.toArray).foldLeft(0.0){ (distance, elems) => + val score = elems._1 - elems._2 + distance + score * score + } + } + squaredDistance + } + + /** + * Returns the squared distance between DenseVector and SparseVector. + */ + private[mllib] def sqdist(v1: SparseVector, v2: DenseVector): Double = { + var kv1 = 0 + var kv2 = 0 + val indices = v1.indices + var squaredDistance = 0.0 + var iv1 = indices(kv1) + val nnzv2 = v2.size + + while (kv2 < nnzv2) { + var score = 0.0 + if (kv2 != iv1) { + score = v2(kv2) + } else { + score = v1.values(kv1) - v2(kv2) + if (kv1 < indices.length - 1) { + kv1 += 1 + iv1 = indices(kv1) + } + } + squaredDistance += score * score + kv2 += 1 + } + squaredDistance + } } /** diff --git a/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala b/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala index da0da0a168c1d..c7843464a7505 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala @@ -19,8 +19,7 @@ package org.apache.spark.mllib.util import scala.reflect.ClassTag -import breeze.linalg.{DenseVector => BDV, SparseVector => BSV, - squaredDistance => breezeSquaredDistance} +import breeze.linalg.{DenseVector => BDV, SparseVector => BSV} import org.apache.spark.annotation.Experimental import org.apache.spark.SparkContext @@ -28,7 +27,7 @@ import org.apache.spark.rdd.RDD import org.apache.spark.rdd.PartitionwiseSampledRDD import org.apache.spark.util.random.BernoulliCellSampler import org.apache.spark.mllib.regression.LabeledPoint -import org.apache.spark.mllib.linalg.{SparseVector, Vector, Vectors} +import org.apache.spark.mllib.linalg.{SparseVector, DenseVector, Vector, Vectors} import org.apache.spark.mllib.linalg.BLAS.dot import org.apache.spark.storage.StorageLevel import org.apache.spark.streaming.StreamingContext @@ -266,7 +265,7 @@ object MLUtils { } Vectors.fromBreeze(vector1) } - + /** * Returns the squared Euclidean distance between two vectors. The following formula will be used * if it does not introduce too much numerical error: @@ -316,12 +315,10 @@ object MLUtils { val precisionBound2 = EPSILON * (sumSquaredNorm + 2.0 * math.abs(dotValue)) / (sqDist + EPSILON) if (precisionBound2 > precision) { - // TODO: breezeSquaredDistance is slow, - // so we should replace it with our own implementation. - sqDist = breezeSquaredDistance(v1.toBreeze, v2.toBreeze) + sqDist = Vectors.sqdist(v1, v2) } } else { - sqDist = breezeSquaredDistance(v1.toBreeze, v2.toBreeze) + sqDist = Vectors.sqdist(v1, v2) } sqDist } diff --git a/mllib/src/test/scala/org/apache/spark/mllib/util/MLUtilsSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/util/MLUtilsSuite.scala index df07987093fbf..7778847f8b72a 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/util/MLUtilsSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/util/MLUtilsSuite.scala @@ -52,12 +52,27 @@ class MLUtilsSuite extends FunSuite with MLlibTestSparkContext { val values = indices.map(i => a(i)) val v2 = Vectors.sparse(n, indices, values) val norm2 = Vectors.norm(v2, 2.0) + val v3 = Vectors.sparse(n, indices, indices.map(i => a(i) + 0.5)) + val norm3 = Vectors.norm(v3, 2.0) val squaredDist = breezeSquaredDistance(v1.toBreeze, v2.toBreeze) val fastSquaredDist1 = fastSquaredDistance(v1, norm1, v2, norm2, precision) assert((fastSquaredDist1 - squaredDist) <= precision * squaredDist, s"failed with m = $m") val fastSquaredDist2 = fastSquaredDistance(v1, norm1, Vectors.dense(v2.toArray), norm2, precision) assert((fastSquaredDist2 - squaredDist) <= precision * squaredDist, s"failed with m = $m") + val squaredDist2 = breezeSquaredDistance(v2.toBreeze, v3.toBreeze) + val fastSquaredDist3 = + fastSquaredDistance(v2, norm2, v3, norm3, precision) + assert((fastSquaredDist3 - squaredDist2) <= precision * squaredDist2, s"failed with m = $m") + if (m > 10) { + val v4 = Vectors.sparse(n, indices.slice(0, m - 10), + indices.map(i => a(i) + 0.5).slice(0, m - 10)) + val norm4 = Vectors.norm(v4, 2.0) + val squaredDist = breezeSquaredDistance(v2.toBreeze, v4.toBreeze) + val fastSquaredDist = + fastSquaredDistance(v2, norm2, v4, norm4, precision) + assert((fastSquaredDist - squaredDist) <= precision * squaredDist, s"failed with m = $m") + } } } From 8e14c5eb551ab06c94859c7f6d8c6b62b4d00d59 Mon Sep 17 00:00:00 2001 From: Brennon York Date: Wed, 31 Dec 2014 11:54:10 -0800 Subject: [PATCH 146/320] [SPARK-4298][Core] - The spark-submit cannot read Main-Class from Manifest. Resolves a bug where the `Main-Class` from a .jar file wasn't being read in properly. This was caused by the fact that the `primaryResource` object was a URI and needed to be normalized through a call to `.getPath` before it could be passed into the `JarFile` object. Author: Brennon York Closes #3561 from brennonyork/SPARK-4298 and squashes the following commits: 5e0fce1 [Brennon York] Use string interpolation for error messages, moved comment line from original code to above its necessary code segment 14daa20 [Brennon York] pushed mainClass assignment into match statement, removed spurious spaces, removed { } from case statements, removed return values c6dad68 [Brennon York] Set case statement to support multiple jar URI's and enabled the 'file' URI to load the main-class 8d20936 [Brennon York] updated to reset the error message back to the default a043039 [Brennon York] updated to split the uri and jar vals 8da7cbf [Brennon York] fixes SPARK-4298 --- .../spark/deploy/SparkSubmitArguments.scala | 26 +++++++++++++------ 1 file changed, 18 insertions(+), 8 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala index f174bc1af59b4..1faabe91f49a8 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala @@ -17,6 +17,7 @@ package org.apache.spark.deploy +import java.net.URI import java.util.jar.JarFile import scala.collection.mutable.{ArrayBuffer, HashMap} @@ -125,14 +126,23 @@ private[spark] class SparkSubmitArguments(args: Seq[String], env: Map[String, St // Try to set main class from JAR if no --class argument is given if (mainClass == null && !isPython && primaryResource != null) { - try { - val jar = new JarFile(primaryResource) - // Note that this might still return null if no main-class is set; we catch that later - mainClass = jar.getManifest.getMainAttributes.getValue("Main-Class") - } catch { - case e: Exception => - SparkSubmit.printErrorAndExit("Cannot load main class from JAR: " + primaryResource) - return + val uri = new URI(primaryResource) + val uriScheme = uri.getScheme() + + uriScheme match { + case "file" => + try { + val jar = new JarFile(uri.getPath) + // Note that this might still return null if no main-class is set; we catch that later + mainClass = jar.getManifest.getMainAttributes.getValue("Main-Class") + } catch { + case e: Exception => + SparkSubmit.printErrorAndExit(s"Cannot load main class from JAR $primaryResource") + } + case _ => + SparkSubmit.printErrorAndExit( + s"Cannot load main class from JAR $primaryResource with URI $uriScheme. " + + "Please specify a class through --class.") } } From 3d194cc75761fceba77b2c91291b36479b8b556c Mon Sep 17 00:00:00 2001 From: Sean Owen Date: Wed, 31 Dec 2014 13:37:04 -0800 Subject: [PATCH 147/320] SPARK-4547 [MLLIB] OOM when making bins in BinaryClassificationMetrics Now that I've implemented the basics here, I'm less convinced there is a need for this change, somehow. Callers can downsample before or after. Really the OOM is not in the ROC curve code, but in code that might `collect()` it for local analysis. Still, might be useful to down-sample since the ROC curve probably never needs millions of points. This is a first pass. Since the `(score,label)` are already grouped and sorted, I think it's sufficient to just take every Nth such pair, in order to downsample by a factor of N? this is just like retaining every Nth point on the curve, which I think is the goal. All of the data is still used to build the curve of course. What do you think about the API, and usefulness? Author: Sean Owen Closes #3702 from srowen/SPARK-4547 and squashes the following commits: 1d34d05 [Sean Owen] Indent and reorganize numBins scaladoc 692d825 [Sean Owen] Change handling of large numBins, make 2nd consturctor instead of optional param, style change a03610e [Sean Owen] Add downsamplingFactor to BinaryClassificationMetrics --- .../BinaryClassificationMetrics.scala | 59 ++++++++++++++++++- .../BinaryClassificationMetricsSuite.scala | 36 +++++++++++ 2 files changed, 92 insertions(+), 3 deletions(-) diff --git a/mllib/src/main/scala/org/apache/spark/mllib/evaluation/BinaryClassificationMetrics.scala b/mllib/src/main/scala/org/apache/spark/mllib/evaluation/BinaryClassificationMetrics.scala index 1af40de2c7fcf..ced042e2f96ca 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/evaluation/BinaryClassificationMetrics.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/evaluation/BinaryClassificationMetrics.scala @@ -28,9 +28,30 @@ import org.apache.spark.rdd.{RDD, UnionRDD} * Evaluator for binary classification. * * @param scoreAndLabels an RDD of (score, label) pairs. + * @param numBins if greater than 0, then the curves (ROC curve, PR curve) computed internally + * will be down-sampled to this many "bins". If 0, no down-sampling will occur. + * This is useful because the curve contains a point for each distinct score + * in the input, and this could be as large as the input itself -- millions of + * points or more, when thousands may be entirely sufficient to summarize + * the curve. After down-sampling, the curves will instead be made of approximately + * `numBins` points instead. Points are made from bins of equal numbers of + * consecutive points. The size of each bin is + * `floor(scoreAndLabels.count() / numBins)`, which means the resulting number + * of bins may not exactly equal numBins. The last bin in each partition may + * be smaller as a result, meaning there may be an extra sample at + * partition boundaries. */ @Experimental -class BinaryClassificationMetrics(scoreAndLabels: RDD[(Double, Double)]) extends Logging { +class BinaryClassificationMetrics( + val scoreAndLabels: RDD[(Double, Double)], + val numBins: Int) extends Logging { + + require(numBins >= 0, "numBins must be nonnegative") + + /** + * Defaults `numBins` to 0. + */ + def this(scoreAndLabels: RDD[(Double, Double)]) = this(scoreAndLabels, 0) /** Unpersist intermediate RDDs used in the computation. */ def unpersist() { @@ -103,7 +124,39 @@ class BinaryClassificationMetrics(scoreAndLabels: RDD[(Double, Double)]) extends mergeValue = (c: BinaryLabelCounter, label: Double) => c += label, mergeCombiners = (c1: BinaryLabelCounter, c2: BinaryLabelCounter) => c1 += c2 ).sortByKey(ascending = false) - val agg = counts.values.mapPartitions { iter => + + val binnedCounts = + // Only down-sample if bins is > 0 + if (numBins == 0) { + // Use original directly + counts + } else { + val countsSize = counts.count() + // Group the iterator into chunks of about countsSize / numBins points, + // so that the resulting number of bins is about numBins + var grouping = countsSize / numBins + if (grouping < 2) { + // numBins was more than half of the size; no real point in down-sampling to bins + logInfo(s"Curve is too small ($countsSize) for $numBins bins to be useful") + counts + } else { + if (grouping >= Int.MaxValue) { + logWarning( + s"Curve too large ($countsSize) for $numBins bins; capping at ${Int.MaxValue}") + grouping = Int.MaxValue + } + counts.mapPartitions(_.grouped(grouping.toInt).map { pairs => + // The score of the combined point will be just the first one's score + val firstScore = pairs.head._1 + // The point will contain all counts in this chunk + val agg = new BinaryLabelCounter() + pairs.foreach(pair => agg += pair._2) + (firstScore, agg) + }) + } + } + + val agg = binnedCounts.values.mapPartitions { iter => val agg = new BinaryLabelCounter() iter.foreach(agg += _) Iterator(agg) @@ -113,7 +166,7 @@ class BinaryClassificationMetrics(scoreAndLabels: RDD[(Double, Double)]) extends (agg: BinaryLabelCounter, c: BinaryLabelCounter) => agg.clone() += c) val totalCount = partitionwiseCumulativeCounts.last logInfo(s"Total counts: $totalCount") - val cumulativeCounts = counts.mapPartitionsWithIndex( + val cumulativeCounts = binnedCounts.mapPartitionsWithIndex( (index: Int, iter: Iterator[(Double, BinaryLabelCounter)]) => { val cumCount = partitionwiseCumulativeCounts(index) iter.map { case (score, c) => diff --git a/mllib/src/test/scala/org/apache/spark/mllib/evaluation/BinaryClassificationMetricsSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/evaluation/BinaryClassificationMetricsSuite.scala index 8a18e2971cab6..e0224f960cc43 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/evaluation/BinaryClassificationMetricsSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/evaluation/BinaryClassificationMetricsSuite.scala @@ -124,4 +124,40 @@ class BinaryClassificationMetricsSuite extends FunSuite with MLlibTestSparkConte validateMetrics(metrics, thresholds, rocCurve, prCurve, f1, f2, precisions, recalls) } + + test("binary evaluation metrics with downsampling") { + val scoreAndLabels = Seq( + (0.1, 0.0), (0.2, 0.0), (0.3, 1.0), (0.4, 0.0), (0.5, 0.0), + (0.6, 1.0), (0.7, 1.0), (0.8, 0.0), (0.9, 1.0)) + + val scoreAndLabelsRDD = sc.parallelize(scoreAndLabels, 1) + + val original = new BinaryClassificationMetrics(scoreAndLabelsRDD) + val originalROC = original.roc().collect().sorted.toList + // Add 2 for (0,0) and (1,1) appended at either end + assert(2 + scoreAndLabels.size == originalROC.size) + assert( + List( + (0.0, 0.0), (0.0, 0.25), (0.2, 0.25), (0.2, 0.5), (0.2, 0.75), + (0.4, 0.75), (0.6, 0.75), (0.6, 1.0), (0.8, 1.0), (1.0, 1.0), + (1.0, 1.0) + ) == + originalROC) + + val numBins = 4 + + val downsampled = new BinaryClassificationMetrics(scoreAndLabelsRDD, numBins) + val downsampledROC = downsampled.roc().collect().sorted.toList + assert( + // May have to add 1 if the sample factor didn't divide evenly + 2 + (numBins + (if (scoreAndLabels.size % numBins == 0) 0 else 1)) == + downsampledROC.size) + assert( + List( + (0.0, 0.0), (0.2, 0.25), (0.2, 0.75), (0.6, 0.75), (0.8, 1.0), + (1.0, 1.0), (1.0, 1.0) + ) == + downsampledROC) + } + } From e24d3a9a29962023cc722896a14c7bfe06e8e601 Mon Sep 17 00:00:00 2001 From: Josh Rosen Date: Fri, 12 Dec 2014 12:38:37 -0800 Subject: [PATCH 148/320] [HOTFIX] Disable Spark UI in SparkSubmitSuite tests This should fix a major cause of build breaks when running many parallel tests. --- .../test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala | 2 ++ 1 file changed, 2 insertions(+) diff --git a/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala b/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala index 5eda2d41f0e6d..065b7534cece6 100644 --- a/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala +++ b/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala @@ -290,6 +290,7 @@ class SparkSubmitSuite extends FunSuite with Matchers with ResetSystemProperties "--class", SimpleApplicationTest.getClass.getName.stripSuffix("$"), "--name", "testApp", "--master", "local", + "--conf", "spark.ui.enabled=false", unusedJar.toString) runSparkSubmit(args) } @@ -304,6 +305,7 @@ class SparkSubmitSuite extends FunSuite with Matchers with ResetSystemProperties "--name", "testApp", "--master", "local-cluster[2,1,512]", "--jars", jarsString, + "--conf", "spark.ui.enabled=false", unusedJar.toString) runSparkSubmit(args) } From c88a3d7fca20d36ee566d48e0cb91fe33a7a6d99 Mon Sep 17 00:00:00 2001 From: Reynold Xin Date: Wed, 31 Dec 2014 14:25:03 -0800 Subject: [PATCH 149/320] [SPARK-5038][SQL] Add explicit return type for implicit functions in Spark SQL As we learned in https://github.com/apache/spark/pull/3580, not explicitly typing implicit functions can lead to compiler bugs and potentially unexpected runtime behavior. Author: Reynold Xin Closes #3859 from rxin/sql-implicits and squashes the following commits: 30c2c24 [Reynold Xin] [SPARK-5038] Add explicit return type for implicit functions in Spark SQL. --- .../spark/sql/catalyst/dsl/package.scala | 80 +++++++++---------- .../org/apache/spark/sql/SQLContext.scala | 2 +- 2 files changed, 41 insertions(+), 41 deletions(-) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala index a14e5b9ef14d0..8e39f79d2ca51 100755 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala @@ -19,8 +19,6 @@ package org.apache.spark.sql.catalyst import java.sql.{Date, Timestamp} -import org.apache.spark.sql.catalyst.types.decimal.Decimal - import scala.language.implicitConversions import scala.reflect.runtime.universe.{TypeTag, typeTag} @@ -29,6 +27,7 @@ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.plans.{Inner, JoinType} import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.catalyst.types.decimal.Decimal /** * A collection of implicit conversions that create a DSL for constructing catalyst data structures. @@ -119,21 +118,22 @@ package object dsl { def expr = e } - implicit def booleanToLiteral(b: Boolean) = Literal(b) - implicit def byteToLiteral(b: Byte) = Literal(b) - implicit def shortToLiteral(s: Short) = Literal(s) - implicit def intToLiteral(i: Int) = Literal(i) - implicit def longToLiteral(l: Long) = Literal(l) - implicit def floatToLiteral(f: Float) = Literal(f) - implicit def doubleToLiteral(d: Double) = Literal(d) - implicit def stringToLiteral(s: String) = Literal(s) - implicit def dateToLiteral(d: Date) = Literal(d) - implicit def bigDecimalToLiteral(d: BigDecimal) = Literal(d) - implicit def decimalToLiteral(d: Decimal) = Literal(d) - implicit def timestampToLiteral(t: Timestamp) = Literal(t) - implicit def binaryToLiteral(a: Array[Byte]) = Literal(a) - - implicit def symbolToUnresolvedAttribute(s: Symbol) = analysis.UnresolvedAttribute(s.name) + implicit def booleanToLiteral(b: Boolean): Literal = Literal(b) + implicit def byteToLiteral(b: Byte): Literal = Literal(b) + implicit def shortToLiteral(s: Short): Literal = Literal(s) + implicit def intToLiteral(i: Int): Literal = Literal(i) + implicit def longToLiteral(l: Long): Literal = Literal(l) + implicit def floatToLiteral(f: Float): Literal = Literal(f) + implicit def doubleToLiteral(d: Double): Literal = Literal(d) + implicit def stringToLiteral(s: String): Literal = Literal(s) + implicit def dateToLiteral(d: Date): Literal = Literal(d) + implicit def bigDecimalToLiteral(d: BigDecimal): Literal = Literal(d) + implicit def decimalToLiteral(d: Decimal): Literal = Literal(d) + implicit def timestampToLiteral(t: Timestamp): Literal = Literal(t) + implicit def binaryToLiteral(a: Array[Byte]): Literal = Literal(a) + + implicit def symbolToUnresolvedAttribute(s: Symbol): analysis.UnresolvedAttribute = + analysis.UnresolvedAttribute(s.name) def sum(e: Expression) = Sum(e) def sumDistinct(e: Expression) = SumDistinct(e) @@ -301,52 +301,52 @@ package object dsl { (1 to 22).map { x => val argTypes = Seq.fill(x)("_").mkString(", ") - s"implicit def functionToUdfBuilder[T: TypeTag](func: Function$x[$argTypes, T]) = ScalaUdfBuilder(func)" + s"implicit def functionToUdfBuilder[T: TypeTag](func: Function$x[$argTypes, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func)" } */ - implicit def functionToUdfBuilder[T: TypeTag](func: Function1[_, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function1[_, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function2[_, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function2[_, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function3[_, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function3[_, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function4[_, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function4[_, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function5[_, _, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function5[_, _, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function6[_, _, _, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function6[_, _, _, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function7[_, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function7[_, _, _, _, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function8[_, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function8[_, _, _, _, _, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function9[_, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function9[_, _, _, _, _, _, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function10[_, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function10[_, _, _, _, _, _, _, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function11[_, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function11[_, _, _, _, _, _, _, _, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function12[_, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function12[_, _, _, _, _, _, _, _, _, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function13[_, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function13[_, _, _, _, _, _, _, _, _, _, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function14[_, _, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function14[_, _, _, _, _, _, _, _, _, _, _, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function15[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function15[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function16[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function16[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function17[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function17[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function18[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function18[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function19[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function19[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function20[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function20[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function21[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function21[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) - implicit def functionToUdfBuilder[T: TypeTag](func: Function22[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func) + implicit def functionToUdfBuilder[T: TypeTag](func: Function22[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]): ScalaUdfBuilder[T] = ScalaUdfBuilder(func) // scalastyle:on } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala index 7a13302229012..6a1a4d995bf61 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala @@ -106,7 +106,7 @@ class SQLContext(@transient val sparkContext: SparkContext) * * @group userf */ - implicit def createSchemaRDD[A <: Product: TypeTag](rdd: RDD[A]) = { + implicit def createSchemaRDD[A <: Product: TypeTag](rdd: RDD[A]): SchemaRDD = { SparkPlan.currentContext.set(self) val attributeSeq = ScalaReflection.attributesFor[A] val schema = StructType.fromAttributes(attributeSeq) From 3610d3c615112faef98d94f04efaea602cc4aa8f Mon Sep 17 00:00:00 2001 From: Hari Shreedharan Date: Wed, 31 Dec 2014 14:35:07 -0800 Subject: [PATCH 150/320] [SPARK-4790][STREAMING] Fix ReceivedBlockTrackerSuite waits for old file... ...s to get deleted before continuing. Since the deletes are happening asynchronously, the getFileStatus call might throw an exception in older HDFS versions, if the delete happens between the time listFiles is called on the directory and getFileStatus is called on the file in the getFileStatus method. This PR addresses this by adding an option to delete the files synchronously and then waiting for the deletion to complete before proceeding. Author: Hari Shreedharan Closes #3726 from harishreedharan/spark-4790 and squashes the following commits: bbbacd1 [Hari Shreedharan] Call cleanUpOldLogs only once in the tests. 3255f17 [Hari Shreedharan] Add test for async deletion. Remove method from ReceiverTracker that does not take waitForCompletion. e4c83ec [Hari Shreedharan] Making waitForCompletion a mandatory param. Remove eventually from WALSuite since the cleanup method returns only after all files are deleted. af00fd1 [Hari Shreedharan] [SPARK-4790][STREAMING] Fix ReceivedBlockTrackerSuite waits for old files to get deleted before continuing. --- .../receiver/ReceivedBlockHandler.scala | 8 ++++---- .../scheduler/ReceivedBlockTracker.scala | 9 ++++++--- .../streaming/scheduler/ReceiverTracker.scala | 2 +- .../streaming/util/WriteAheadLogManager.scala | 17 +++++++++++++---- .../streaming/ReceivedBlockHandlerSuite.scala | 2 +- .../streaming/ReceivedBlockTrackerSuite.scala | 2 +- .../streaming/util/WriteAheadLogSuite.scala | 18 ++++++++++++++++-- 7 files changed, 42 insertions(+), 16 deletions(-) diff --git a/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala b/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala index 8b97db8dd36f1..f7a8ebee8a544 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala @@ -42,7 +42,7 @@ private[streaming] trait ReceivedBlockHandler { def storeBlock(blockId: StreamBlockId, receivedBlock: ReceivedBlock): ReceivedBlockStoreResult /** Cleanup old blocks older than the given threshold time */ - def cleanupOldBlock(threshTime: Long) + def cleanupOldBlocks(threshTime: Long) } @@ -82,7 +82,7 @@ private[streaming] class BlockManagerBasedBlockHandler( BlockManagerBasedStoreResult(blockId) } - def cleanupOldBlock(threshTime: Long) { + def cleanupOldBlocks(threshTime: Long) { // this is not used as blocks inserted into the BlockManager are cleared by DStream's clearing // of BlockRDDs. } @@ -192,8 +192,8 @@ private[streaming] class WriteAheadLogBasedBlockHandler( WriteAheadLogBasedStoreResult(blockId, segment) } - def cleanupOldBlock(threshTime: Long) { - logManager.cleanupOldLogs(threshTime) + def cleanupOldBlocks(threshTime: Long) { + logManager.cleanupOldLogs(threshTime, waitForCompletion = false) } def stop() { diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceivedBlockTracker.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceivedBlockTracker.scala index 02758e0bca6c5..2ce458cddec1a 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceivedBlockTracker.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceivedBlockTracker.scala @@ -139,14 +139,17 @@ private[streaming] class ReceivedBlockTracker( getReceivedBlockQueue(streamId).toSeq } - /** Clean up block information of old batches. */ - def cleanupOldBatches(cleanupThreshTime: Time): Unit = synchronized { + /** + * Clean up block information of old batches. If waitForCompletion is true, this method + * returns only after the files are cleaned up. + */ + def cleanupOldBatches(cleanupThreshTime: Time, waitForCompletion: Boolean): Unit = synchronized { assert(cleanupThreshTime.milliseconds < clock.currentTime()) val timesToCleanup = timeToAllocatedBlocks.keys.filter { _ < cleanupThreshTime }.toSeq logInfo("Deleting batches " + timesToCleanup) writeToLog(BatchCleanupEvent(timesToCleanup)) timeToAllocatedBlocks --= timesToCleanup - logManagerOption.foreach(_.cleanupOldLogs(cleanupThreshTime.milliseconds)) + logManagerOption.foreach(_.cleanupOldLogs(cleanupThreshTime.milliseconds, waitForCompletion)) log } diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceiverTracker.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceiverTracker.scala index 1f0e442a12283..8dbb42a86e3bd 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceiverTracker.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceiverTracker.scala @@ -121,7 +121,7 @@ class ReceiverTracker(ssc: StreamingContext, skipReceiverLaunch: Boolean = false /** Clean up metadata older than the given threshold time */ def cleanupOldMetadata(cleanupThreshTime: Time) { - receivedBlockTracker.cleanupOldBatches(cleanupThreshTime) + receivedBlockTracker.cleanupOldBatches(cleanupThreshTime, waitForCompletion = false) } /** Register a receiver */ diff --git a/streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogManager.scala b/streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogManager.scala index 70d234320be7c..166661b7496df 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogManager.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogManager.scala @@ -19,11 +19,11 @@ package org.apache.spark.streaming.util import java.nio.ByteBuffer import scala.collection.mutable.ArrayBuffer -import scala.concurrent.{ExecutionContext, Future} +import scala.concurrent.duration.Duration +import scala.concurrent.{Await, ExecutionContext, Future} import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.Path -import org.apache.hadoop.fs.permission.FsPermission import org.apache.spark.Logging import org.apache.spark.util.Utils import WriteAheadLogManager._ @@ -124,8 +124,12 @@ private[streaming] class WriteAheadLogManager( * files, which is usually based on the local system time. So if there is coordination necessary * between the node calculating the threshTime (say, driver node), and the local system time * (say, worker node), the caller has to take account of possible time skew. + * + * If waitForCompletion is set to true, this method will return only after old logs have been + * deleted. This should be set to true only for testing. Else the files will be deleted + * asynchronously. */ - def cleanupOldLogs(threshTime: Long): Unit = { + def cleanupOldLogs(threshTime: Long, waitForCompletion: Boolean): Unit = { val oldLogFiles = synchronized { pastLogs.filter { _.endTime < threshTime } } logInfo(s"Attempting to clear ${oldLogFiles.size} old log files in $logDirectory " + s"older than $threshTime: ${oldLogFiles.map { _.path }.mkString("\n")}") @@ -146,10 +150,15 @@ private[streaming] class WriteAheadLogManager( logInfo(s"Cleared log files in $logDirectory older than $threshTime") } if (!executionContext.isShutdown) { - Future { deleteFiles() } + val f = Future { deleteFiles() } + if (waitForCompletion) { + import scala.concurrent.duration._ + Await.ready(f, 1 second) + } } } + /** Stop the manager, close any open log writer */ def stop(): Unit = synchronized { if (currentLogWriter != null) { diff --git a/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockHandlerSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockHandlerSuite.scala index 3661e16a9ef2f..132ff2443fc0f 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockHandlerSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockHandlerSuite.scala @@ -168,7 +168,7 @@ class ReceivedBlockHandlerSuite extends FunSuite with BeforeAndAfter with Matche manualClock.currentTime() shouldEqual 5000L val cleanupThreshTime = 3000L - handler.cleanupOldBlock(cleanupThreshTime) + handler.cleanupOldBlocks(cleanupThreshTime) eventually(timeout(10000 millis), interval(10 millis)) { getWriteAheadLogFiles().size should be < preCleanupLogFiles.size } diff --git a/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockTrackerSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockTrackerSuite.scala index 01a09b67b99dc..de7e9d624bf6b 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockTrackerSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockTrackerSuite.scala @@ -166,7 +166,7 @@ class ReceivedBlockTrackerSuite // Cleanup first batch but not second batch val oldestLogFile = getWriteAheadLogFiles().head incrementTime() - tracker3.cleanupOldBatches(batchTime2) + tracker3.cleanupOldBatches(batchTime2, waitForCompletion = true) // Verify that the batch allocations have been cleaned, and the act has been written to log tracker3.getBlocksOfBatchAndStream(batchTime1, streamId) shouldEqual Seq.empty diff --git a/streaming/src/test/scala/org/apache/spark/streaming/util/WriteAheadLogSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/util/WriteAheadLogSuite.scala index 8f69bcb64279d..7ce9499dc614d 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/util/WriteAheadLogSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/util/WriteAheadLogSuite.scala @@ -182,15 +182,29 @@ class WriteAheadLogSuite extends FunSuite with BeforeAndAfter { } test("WriteAheadLogManager - cleanup old logs") { + logCleanUpTest(waitForCompletion = false) + } + + test("WriteAheadLogManager - cleanup old logs synchronously") { + logCleanUpTest(waitForCompletion = true) + } + + private def logCleanUpTest(waitForCompletion: Boolean): Unit = { // Write data with manager, recover with new manager and verify val manualClock = new ManualClock val dataToWrite = generateRandomData() manager = writeDataUsingManager(testDir, dataToWrite, manualClock, stopManager = false) val logFiles = getLogFilesInDirectory(testDir) assert(logFiles.size > 1) - manager.cleanupOldLogs(manualClock.currentTime() / 2) - eventually(timeout(1 second), interval(10 milliseconds)) { + + manager.cleanupOldLogs(manualClock.currentTime() / 2, waitForCompletion) + + if (waitForCompletion) { assert(getLogFilesInDirectory(testDir).size < logFiles.size) + } else { + eventually(timeout(1 second), interval(10 milliseconds)) { + assert(getLogFilesInDirectory(testDir).size < logFiles.size) + } } } From fdc2aa4918fd4c510f04812b782cc0bfef9a2107 Mon Sep 17 00:00:00 2001 From: jerryshao Date: Wed, 31 Dec 2014 14:45:31 -0800 Subject: [PATCH 151/320] [SPARK-5028][Streaming]Add total received and processed records metrics to Streaming UI This is a follow-up work of [SPARK-4537](https://issues.apache.org/jira/browse/SPARK-4537). Adding total received records and processed records metrics back to UI. ![screenshot](https://dl.dropboxusercontent.com/u/19230832/screenshot.png) Author: jerryshao Closes #3852 from jerryshao/SPARK-5028 and squashes the following commits: c8c4877 [jerryshao] Add total received and processed metrics to Streaming UI --- .../scala/org/apache/spark/streaming/ui/StreamingPage.scala | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingPage.scala b/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingPage.scala index 1353e487c72cf..98e9a2e639e25 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingPage.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingPage.scala @@ -67,6 +67,12 @@ private[ui] class StreamingPage(parent: StreamingTab)
  • Waiting batches: {listener.numUnprocessedBatches}
    • +
  • + Received records: {listener.numTotalReceivedRecords} +
    • +
  • + Processed records: {listener.numTotalProcessedRecords} +
    • } From c4f0b4f334f7f3565375921fcac184ad5b1fb207 Mon Sep 17 00:00:00 2001 From: Travis Galoppo Date: Wed, 31 Dec 2014 15:39:58 -0800 Subject: [PATCH 152/320] SPARK-5020 [MLlib] GaussianMixtureModel.predictMembership() should take an RDD only Removed unnecessary parameters to predictMembership() CC: jkbradley Author: Travis Galoppo Closes #3854 from tgaloppo/spark-5020 and squashes the following commits: 1bf4669 [Travis Galoppo] renamed predictMembership() to predictSoft() 0f1d96e [Travis Galoppo] SPARK-5020 - Removed superfluous parameters from predictMembership() --- .../spark/mllib/clustering/GaussianMixtureModel.scala | 9 ++------- 1 file changed, 2 insertions(+), 7 deletions(-) diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala index 11a110db1f7ca..b461ea4f0f06e 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala @@ -45,7 +45,7 @@ class GaussianMixtureModel( /** Maps given points to their cluster indices. */ def predict(points: RDD[Vector]): RDD[Int] = { - val responsibilityMatrix = predictMembership(points, mu, sigma, weight, k) + val responsibilityMatrix = predictSoft(points) responsibilityMatrix.map(r => r.indexOf(r.max)) } @@ -53,12 +53,7 @@ class GaussianMixtureModel( * Given the input vectors, return the membership value of each vector * to all mixture components. */ - def predictMembership( - points: RDD[Vector], - mu: Array[Vector], - sigma: Array[Matrix], - weight: Array[Double], - k: Int): RDD[Array[Double]] = { + def predictSoft(points: RDD[Vector]): RDD[Array[Double]] = { val sc = points.sparkContext val dists = sc.broadcast { (0 until k).map { i => From fe6efacc0b865e9e827a1565877077000e63976e Mon Sep 17 00:00:00 2001 From: Josh Rosen Date: Wed, 31 Dec 2014 16:02:47 -0800 Subject: [PATCH 153/320] [SPARK-5035] [Streaming] ReceiverMessage trait should extend Serializable Spark Streaming's ReceiverMessage trait should extend Serializable in order to fix a subtle bug that only occurs when running on a real cluster: If you attempt to send a fire-and-forget message to a remote Akka actor and that message cannot be serialized, then this seems to lead to more-or-less silent failures. As an optimization, Akka skips message serialization for messages sent within the same JVM. As a result, Spark's unit tests will never fail due to non-serializable Akka messages, but these will cause mostly-silent failures when running on a real cluster. Before this patch, here was the code for ReceiverMessage: ``` /** Messages sent to the NetworkReceiver. */ private[streaming] sealed trait ReceiverMessage private[streaming] object StopReceiver extends ReceiverMessage ``` Since ReceiverMessage does not extend Serializable and StopReceiver is a regular `object`, not a `case object`, StopReceiver will throw serialization errors. As a result, graceful receiver shutdown is broken on real clusters (and local-cluster mode) but works in local modes. If you want to reproduce this, try running the word count example from the Streaming Programming Guide in the Spark shell: ``` import org.apache.spark._ import org.apache.spark.streaming._ import org.apache.spark.streaming.StreamingContext._ val ssc = new StreamingContext(sc, Seconds(10)) // Create a DStream that will connect to hostname:port, like localhost:9999 val lines = ssc.socketTextStream("localhost", 9999) // Split each line into words val words = lines.flatMap(_.split(" ")) import org.apache.spark.streaming.StreamingContext._ // Count each word in each batch val pairs = words.map(word => (word, 1)) val wordCounts = pairs.reduceByKey(_ + _) // Print the first ten elements of each RDD generated in this DStream to the console wordCounts.print() ssc.start() Thread.sleep(10000) ssc.stop(true, true) ``` Prior to this patch, this would work correctly in local mode but fail when running against a real cluster (it would report that some receivers were not shut down). Author: Josh Rosen Closes #3857 from JoshRosen/SPARK-5035 and squashes the following commits: 71d0eae [Josh Rosen] [SPARK-5035] ReceiverMessage trait should extend Serializable. --- .../org/apache/spark/streaming/receiver/ReceiverMessage.scala | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceiverMessage.scala b/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceiverMessage.scala index bf39d1e891cae..ab9fa192191aa 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceiverMessage.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceiverMessage.scala @@ -18,6 +18,6 @@ package org.apache.spark.streaming.receiver /** Messages sent to the NetworkReceiver. */ -private[streaming] sealed trait ReceiverMessage +private[streaming] sealed trait ReceiverMessage extends Serializable private[streaming] object StopReceiver extends ReceiverMessage From 4bb12488d56ea651c56d9688996b464b99095582 Mon Sep 17 00:00:00 2001 From: Sean Owen Date: Wed, 31 Dec 2014 16:59:17 -0800 Subject: [PATCH 154/320] SPARK-2757 [BUILD] [STREAMING] Add Mima test for Spark Sink after 1.10 is released Re-enable MiMa for Streaming Flume Sink module, now that 1.1.0 is released, per the JIRA TO-DO. That's pretty much all there is to this. Author: Sean Owen Closes #3842 from srowen/SPARK-2757 and squashes the following commits: 50ff80e [Sean Owen] Exclude apparent false positive turned up by re-enabling MiMa checks for Streaming Flume Sink 0e5ba5c [Sean Owen] Re-enable MiMa for Streaming Flume Sink module --- project/MimaExcludes.scala | 5 +++++ project/SparkBuild.scala | 2 +- 2 files changed, 6 insertions(+), 1 deletion(-) diff --git a/project/MimaExcludes.scala b/project/MimaExcludes.scala index 230239aa40500..c377e5cffa7d2 100644 --- a/project/MimaExcludes.scala +++ b/project/MimaExcludes.scala @@ -53,6 +53,11 @@ object MimaExcludes { "org.apache.spark.mllib.linalg.Matrices.randn"), ProblemFilters.exclude[MissingMethodProblem]( "org.apache.spark.mllib.linalg.Matrices.rand") + ) ++ Seq( + // SPARK-2757 + ProblemFilters.exclude[IncompatibleResultTypeProblem]( + "org.apache.spark.streaming.flume.sink.SparkAvroCallbackHandler." + + "removeAndGetProcessor") ) case v if v.startsWith("1.2") => diff --git a/project/SparkBuild.scala b/project/SparkBuild.scala index c512b62f6137e..46a54c6818409 100644 --- a/project/SparkBuild.scala +++ b/project/SparkBuild.scala @@ -166,7 +166,7 @@ object SparkBuild extends PomBuild { // TODO: Add Sql to mima checks allProjects.filterNot(x => Seq(spark, sql, hive, hiveThriftServer, catalyst, repl, - streamingFlumeSink, networkCommon, networkShuffle, networkYarn).contains(x)).foreach { + networkCommon, networkShuffle, networkYarn).contains(x)).foreach { x => enable(MimaBuild.mimaSettings(sparkHome, x))(x) } From 7749dd6c36a182478b20f4636734c8db0b7ddb00 Mon Sep 17 00:00:00 2001 From: Reynold Xin Date: Wed, 31 Dec 2014 17:07:47 -0800 Subject: [PATCH 155/320] [SPARK-5038] Add explicit return type for implicit functions. As we learned in #3580, not explicitly typing implicit functions can lead to compiler bugs and potentially unexpected runtime behavior. This is a follow up PR for rest of Spark (outside Spark SQL). The original PR for Spark SQL can be found at https://github.com/apache/spark/pull/3859 Author: Reynold Xin Closes #3860 from rxin/implicit and squashes the following commits: 73702f9 [Reynold Xin] [SPARK-5038] Add explicit return type for implicit functions. --- .../scala/org/apache/spark/SparkContext.scala | 14 ++--- .../scala/org/apache/spark/util/Vector.scala | 38 +++++------ .../graphx/impl/EdgePartitionBuilder.scala | 63 ++++++++++--------- .../impl/ShippableVertexPartition.scala | 4 +- .../spark/graphx/impl/VertexPartition.scala | 4 +- .../graphx/impl/VertexPartitionBaseOps.scala | 4 +- 6 files changed, 64 insertions(+), 63 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala index 57bc3d4e4ae36..df1cb3cda2dba 100644 --- a/core/src/main/scala/org/apache/spark/SparkContext.scala +++ b/core/src/main/scala/org/apache/spark/SparkContext.scala @@ -1708,19 +1708,19 @@ object SparkContext extends Logging { // Implicit conversions to common Writable types, for saveAsSequenceFile - implicit def intToIntWritable(i: Int) = new IntWritable(i) + implicit def intToIntWritable(i: Int): IntWritable = new IntWritable(i) - implicit def longToLongWritable(l: Long) = new LongWritable(l) + implicit def longToLongWritable(l: Long): LongWritable = new LongWritable(l) - implicit def floatToFloatWritable(f: Float) = new FloatWritable(f) + implicit def floatToFloatWritable(f: Float): FloatWritable = new FloatWritable(f) - implicit def doubleToDoubleWritable(d: Double) = new DoubleWritable(d) + implicit def doubleToDoubleWritable(d: Double): DoubleWritable = new DoubleWritable(d) - implicit def boolToBoolWritable (b: Boolean) = new BooleanWritable(b) + implicit def boolToBoolWritable (b: Boolean): BooleanWritable = new BooleanWritable(b) - implicit def bytesToBytesWritable (aob: Array[Byte]) = new BytesWritable(aob) + implicit def bytesToBytesWritable (aob: Array[Byte]): BytesWritable = new BytesWritable(aob) - implicit def stringToText(s: String) = new Text(s) + implicit def stringToText(s: String): Text = new Text(s) private implicit def arrayToArrayWritable[T <% Writable: ClassTag](arr: Traversable[T]) : ArrayWritable = { diff --git a/core/src/main/scala/org/apache/spark/util/Vector.scala b/core/src/main/scala/org/apache/spark/util/Vector.scala index c6cab82c3e546..2ed827eab46df 100644 --- a/core/src/main/scala/org/apache/spark/util/Vector.scala +++ b/core/src/main/scala/org/apache/spark/util/Vector.scala @@ -24,9 +24,9 @@ import org.apache.spark.util.random.XORShiftRandom @deprecated("Use Vectors.dense from Spark's mllib.linalg package instead.", "1.0.0") class Vector(val elements: Array[Double]) extends Serializable { - def length = elements.length + def length: Int = elements.length - def apply(index: Int) = elements(index) + def apply(index: Int): Double = elements(index) def + (other: Vector): Vector = { if (length != other.length) { @@ -35,7 +35,7 @@ class Vector(val elements: Array[Double]) extends Serializable { Vector(length, i => this(i) + other(i)) } - def add(other: Vector) = this + other + def add(other: Vector): Vector = this + other def - (other: Vector): Vector = { if (length != other.length) { @@ -44,7 +44,7 @@ class Vector(val elements: Array[Double]) extends Serializable { Vector(length, i => this(i) - other(i)) } - def subtract(other: Vector) = this - other + def subtract(other: Vector): Vector = this - other def dot(other: Vector): Double = { if (length != other.length) { @@ -93,19 +93,19 @@ class Vector(val elements: Array[Double]) extends Serializable { this } - def addInPlace(other: Vector) = this +=other + def addInPlace(other: Vector): Vector = this +=other def * (scale: Double): Vector = Vector(length, i => this(i) * scale) - def multiply (d: Double) = this * d + def multiply (d: Double): Vector = this * d def / (d: Double): Vector = this * (1 / d) - def divide (d: Double) = this / d + def divide (d: Double): Vector = this / d - def unary_- = this * -1 + def unary_- : Vector = this * -1 - def sum = elements.reduceLeft(_ + _) + def sum: Double = elements.reduceLeft(_ + _) def squaredDist(other: Vector): Double = { var ans = 0.0 @@ -119,40 +119,40 @@ class Vector(val elements: Array[Double]) extends Serializable { def dist(other: Vector): Double = math.sqrt(squaredDist(other)) - override def toString = elements.mkString("(", ", ", ")") + override def toString: String = elements.mkString("(", ", ", ")") } object Vector { - def apply(elements: Array[Double]) = new Vector(elements) + def apply(elements: Array[Double]): Vector = new Vector(elements) - def apply(elements: Double*) = new Vector(elements.toArray) + def apply(elements: Double*): Vector = new Vector(elements.toArray) def apply(length: Int, initializer: Int => Double): Vector = { val elements: Array[Double] = Array.tabulate(length)(initializer) new Vector(elements) } - def zeros(length: Int) = new Vector(new Array[Double](length)) + def zeros(length: Int): Vector = new Vector(new Array[Double](length)) - def ones(length: Int) = Vector(length, _ => 1) + def ones(length: Int): Vector = Vector(length, _ => 1) /** * Creates this [[org.apache.spark.util.Vector]] of given length containing random numbers * between 0.0 and 1.0. Optional scala.util.Random number generator can be provided. */ - def random(length: Int, random: Random = new XORShiftRandom()) = + def random(length: Int, random: Random = new XORShiftRandom()): Vector = Vector(length, _ => random.nextDouble()) class Multiplier(num: Double) { - def * (vec: Vector) = vec * num + def * (vec: Vector): Vector = vec * num } - implicit def doubleToMultiplier(num: Double) = new Multiplier(num) + implicit def doubleToMultiplier(num: Double): Multiplier = new Multiplier(num) implicit object VectorAccumParam extends org.apache.spark.AccumulatorParam[Vector] { - def addInPlace(t1: Vector, t2: Vector) = t1 + t2 + def addInPlace(t1: Vector, t2: Vector): Vector = t1 + t2 - def zero(initialValue: Vector) = Vector.zeros(initialValue.length) + def zero(initialValue: Vector): Vector = Vector.zeros(initialValue.length) } } diff --git a/graphx/src/main/scala/org/apache/spark/graphx/impl/EdgePartitionBuilder.scala b/graphx/src/main/scala/org/apache/spark/graphx/impl/EdgePartitionBuilder.scala index 409cf60977f6f..906d42328fcb9 100644 --- a/graphx/src/main/scala/org/apache/spark/graphx/impl/EdgePartitionBuilder.scala +++ b/graphx/src/main/scala/org/apache/spark/graphx/impl/EdgePartitionBuilder.scala @@ -129,44 +129,45 @@ private[impl] case class EdgeWithLocalIds[@specialized ED]( srcId: VertexId, dstId: VertexId, localSrcId: Int, localDstId: Int, attr: ED) private[impl] object EdgeWithLocalIds { - implicit def lexicographicOrdering[ED] = new Ordering[EdgeWithLocalIds[ED]] { - override def compare(a: EdgeWithLocalIds[ED], b: EdgeWithLocalIds[ED]): Int = { - if (a.srcId == b.srcId) { - if (a.dstId == b.dstId) 0 - else if (a.dstId < b.dstId) -1 + implicit def lexicographicOrdering[ED]: Ordering[EdgeWithLocalIds[ED]] = + new Ordering[EdgeWithLocalIds[ED]] { + override def compare(a: EdgeWithLocalIds[ED], b: EdgeWithLocalIds[ED]): Int = { + if (a.srcId == b.srcId) { + if (a.dstId == b.dstId) 0 + else if (a.dstId < b.dstId) -1 + else 1 + } else if (a.srcId < b.srcId) -1 else 1 - } else if (a.srcId < b.srcId) -1 - else 1 + } } - } - private[graphx] def edgeArraySortDataFormat[ED] - = new SortDataFormat[EdgeWithLocalIds[ED], Array[EdgeWithLocalIds[ED]]] { - override def getKey( - data: Array[EdgeWithLocalIds[ED]], pos: Int): EdgeWithLocalIds[ED] = { - data(pos) - } + private[graphx] def edgeArraySortDataFormat[ED] = { + new SortDataFormat[EdgeWithLocalIds[ED], Array[EdgeWithLocalIds[ED]]] { + override def getKey(data: Array[EdgeWithLocalIds[ED]], pos: Int): EdgeWithLocalIds[ED] = { + data(pos) + } - override def swap(data: Array[EdgeWithLocalIds[ED]], pos0: Int, pos1: Int): Unit = { - val tmp = data(pos0) - data(pos0) = data(pos1) - data(pos1) = tmp - } + override def swap(data: Array[EdgeWithLocalIds[ED]], pos0: Int, pos1: Int): Unit = { + val tmp = data(pos0) + data(pos0) = data(pos1) + data(pos1) = tmp + } - override def copyElement( - src: Array[EdgeWithLocalIds[ED]], srcPos: Int, - dst: Array[EdgeWithLocalIds[ED]], dstPos: Int) { - dst(dstPos) = src(srcPos) - } + override def copyElement( + src: Array[EdgeWithLocalIds[ED]], srcPos: Int, + dst: Array[EdgeWithLocalIds[ED]], dstPos: Int) { + dst(dstPos) = src(srcPos) + } - override def copyRange( - src: Array[EdgeWithLocalIds[ED]], srcPos: Int, - dst: Array[EdgeWithLocalIds[ED]], dstPos: Int, length: Int) { - System.arraycopy(src, srcPos, dst, dstPos, length) - } + override def copyRange( + src: Array[EdgeWithLocalIds[ED]], srcPos: Int, + dst: Array[EdgeWithLocalIds[ED]], dstPos: Int, length: Int) { + System.arraycopy(src, srcPos, dst, dstPos, length) + } - override def allocate(length: Int): Array[EdgeWithLocalIds[ED]] = { - new Array[EdgeWithLocalIds[ED]](length) + override def allocate(length: Int): Array[EdgeWithLocalIds[ED]] = { + new Array[EdgeWithLocalIds[ED]](length) + } } } } diff --git a/graphx/src/main/scala/org/apache/spark/graphx/impl/ShippableVertexPartition.scala b/graphx/src/main/scala/org/apache/spark/graphx/impl/ShippableVertexPartition.scala index 5412d720475dc..aa320088f2088 100644 --- a/graphx/src/main/scala/org/apache/spark/graphx/impl/ShippableVertexPartition.scala +++ b/graphx/src/main/scala/org/apache/spark/graphx/impl/ShippableVertexPartition.scala @@ -74,8 +74,8 @@ object ShippableVertexPartition { * Implicit conversion to allow invoking `VertexPartitionBase` operations directly on a * `ShippableVertexPartition`. */ - implicit def shippablePartitionToOps[VD: ClassTag](partition: ShippableVertexPartition[VD]) = - new ShippableVertexPartitionOps(partition) + implicit def shippablePartitionToOps[VD: ClassTag](partition: ShippableVertexPartition[VD]) + : ShippableVertexPartitionOps[VD] = new ShippableVertexPartitionOps(partition) /** * Implicit evidence that `ShippableVertexPartition` is a member of the diff --git a/graphx/src/main/scala/org/apache/spark/graphx/impl/VertexPartition.scala b/graphx/src/main/scala/org/apache/spark/graphx/impl/VertexPartition.scala index 55c7a19d1bdab..fbe53acfc32aa 100644 --- a/graphx/src/main/scala/org/apache/spark/graphx/impl/VertexPartition.scala +++ b/graphx/src/main/scala/org/apache/spark/graphx/impl/VertexPartition.scala @@ -38,8 +38,8 @@ private[graphx] object VertexPartition { * Implicit conversion to allow invoking `VertexPartitionBase` operations directly on a * `VertexPartition`. */ - implicit def partitionToOps[VD: ClassTag](partition: VertexPartition[VD]) = - new VertexPartitionOps(partition) + implicit def partitionToOps[VD: ClassTag](partition: VertexPartition[VD]) + : VertexPartitionOps[VD] = new VertexPartitionOps(partition) /** * Implicit evidence that `VertexPartition` is a member of the `VertexPartitionBaseOpsConstructor` diff --git a/graphx/src/main/scala/org/apache/spark/graphx/impl/VertexPartitionBaseOps.scala b/graphx/src/main/scala/org/apache/spark/graphx/impl/VertexPartitionBaseOps.scala index b40aa1b417a0f..4fd2548b7faf6 100644 --- a/graphx/src/main/scala/org/apache/spark/graphx/impl/VertexPartitionBaseOps.scala +++ b/graphx/src/main/scala/org/apache/spark/graphx/impl/VertexPartitionBaseOps.scala @@ -238,8 +238,8 @@ private[graphx] abstract class VertexPartitionBaseOps * because these methods return a `Self` and this implicit conversion re-wraps that in a * `VertexPartitionBaseOps`. This relies on the context bound on `Self`. */ - private implicit def toOps[VD2: ClassTag]( - partition: Self[VD2]): VertexPartitionBaseOps[VD2, Self] = { + private implicit def toOps[VD2: ClassTag](partition: Self[VD2]) + : VertexPartitionBaseOps[VD2, Self] = { implicitly[VertexPartitionBaseOpsConstructor[Self]].toOps(partition) } } From 012839807c3dc6e7c8c41ac6e956d52a550bb031 Mon Sep 17 00:00:00 2001 From: Josh Rosen Date: Thu, 1 Jan 2015 15:03:54 -0800 Subject: [PATCH 156/320] [HOTFIX] Bind web UI to ephemeral port in DriverSuite The job launched by DriverSuite should bind the web UI to an ephemeral port, since it looks like port contention in this test has caused a large number of Jenkins failures when many builds are started simultaneously. Our tests already disable the web UI, but this doesn't affect subprocesses launched by our tests. In this case, I've opted to bind to an ephemeral port instead of disabling the UI because disabling features in this test may mask its ability to catch certain bugs. See also: e24d3a9 Author: Josh Rosen Closes #3873 from JoshRosen/driversuite-webui-port and squashes the following commits: 48cd05c [Josh Rosen] [HOTFIX] Bind web UI to ephemeral port in DriverSuite. --- core/src/test/scala/org/apache/spark/DriverSuite.scala | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/core/src/test/scala/org/apache/spark/DriverSuite.scala b/core/src/test/scala/org/apache/spark/DriverSuite.scala index 5265ba904032f..541d8eac80556 100644 --- a/core/src/test/scala/org/apache/spark/DriverSuite.scala +++ b/core/src/test/scala/org/apache/spark/DriverSuite.scala @@ -50,7 +50,10 @@ class DriverSuite extends FunSuite with Timeouts { object DriverWithoutCleanup { def main(args: Array[String]) { Utils.configTestLog4j("INFO") - val sc = new SparkContext(args(0), "DriverWithoutCleanup") + // Bind the web UI to an ephemeral port in order to avoid conflicts with other tests running on + // the same machine (we shouldn't just disable the UI here, since that might mask bugs): + val conf = new SparkConf().set("spark.ui.port", "0") + val sc = new SparkContext(args(0), "DriverWithoutCleanup", conf) sc.parallelize(1 to 100, 4).count() } } From bd88b7185358ae60efc83dc6cbb3fb1d2bff6074 Mon Sep 17 00:00:00 2001 From: Yadong Qi Date: Fri, 2 Jan 2015 15:09:41 -0800 Subject: [PATCH 157/320] [SPARK-3325][Streaming] Add a parameter to the method print in class DStream This PR is a fixed version of the original PR #3237 by watermen and scwf. This adds the ability to specify how many elements to print in `DStream.print`. Author: Yadong Qi Author: q00251598 Author: Tathagata Das Author: wangfei Closes #3865 from tdas/print-num and squashes the following commits: cd34e9e [Tathagata Das] Fix bug 7c09f16 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into HEAD bb35d1a [Yadong Qi] Update MimaExcludes.scala f8098ca [Yadong Qi] Update MimaExcludes.scala f6ac3cb [Yadong Qi] Update MimaExcludes.scala e4ed897 [Yadong Qi] Update MimaExcludes.scala 3b9d5cf [wangfei] fix conflicts ec8a3af [q00251598] move to Spark 1.3 26a70c0 [q00251598] extend the Python DStream's print b589a4b [q00251598] add another print function --- project/MimaExcludes.scala | 3 +++ python/pyspark/streaming/dstream.py | 12 +++++++----- .../spark/streaming/api/java/JavaDStreamLike.scala | 10 +++++++++- .../apache/spark/streaming/dstream/DStream.scala | 14 +++++++++++--- 4 files changed, 30 insertions(+), 9 deletions(-) diff --git a/project/MimaExcludes.scala b/project/MimaExcludes.scala index c377e5cffa7d2..31d4c317ae569 100644 --- a/project/MimaExcludes.scala +++ b/project/MimaExcludes.scala @@ -54,6 +54,9 @@ object MimaExcludes { ProblemFilters.exclude[MissingMethodProblem]( "org.apache.spark.mllib.linalg.Matrices.rand") ) ++ Seq( + // SPARK-3325 + ProblemFilters.exclude[MissingMethodProblem]( + "org.apache.spark.streaming.api.java.JavaDStreamLike.print"), // SPARK-2757 ProblemFilters.exclude[IncompatibleResultTypeProblem]( "org.apache.spark.streaming.flume.sink.SparkAvroCallbackHandler." + diff --git a/python/pyspark/streaming/dstream.py b/python/pyspark/streaming/dstream.py index 0826ddc56e844..2fe39392ff081 100644 --- a/python/pyspark/streaming/dstream.py +++ b/python/pyspark/streaming/dstream.py @@ -157,18 +157,20 @@ def foreachRDD(self, func): api = self._ssc._jvm.PythonDStream api.callForeachRDD(self._jdstream, jfunc) - def pprint(self): + def pprint(self, num=10): """ - Print the first ten elements of each RDD generated in this DStream. + Print the first num elements of each RDD generated in this DStream. + + @param num: the number of elements from the first will be printed. """ def takeAndPrint(time, rdd): - taken = rdd.take(11) + taken = rdd.take(num + 1) print "-------------------------------------------" print "Time: %s" % time print "-------------------------------------------" - for record in taken[:10]: + for record in taken[:num]: print record - if len(taken) > 10: + if len(taken) > num: print "..." print diff --git a/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaDStreamLike.scala b/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaDStreamLike.scala index 2a7004e56ef53..e0542eda1383f 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaDStreamLike.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaDStreamLike.scala @@ -51,7 +51,15 @@ trait JavaDStreamLike[T, This <: JavaDStreamLike[T, This, R], R <: JavaRDDLike[T * operator, so this DStream will be registered as an output stream and there materialized. */ def print(): Unit = { - dstream.print() + print(10) + } + + /** + * Print the first num elements of each RDD generated in this DStream. This is an output + * operator, so this DStream will be registered as an output stream and there materialized. + */ + def print(num: Int): Unit = { + dstream.print(num) } /** diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala index 7f8651e719d84..28fc00cf3944f 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala @@ -605,13 +605,21 @@ abstract class DStream[T: ClassTag] ( * operator, so this DStream will be registered as an output stream and there materialized. */ def print() { + print(10) + } + + /** + * Print the first num elements of each RDD generated in this DStream. This is an output + * operator, so this DStream will be registered as an output stream and there materialized. + */ + def print(num: Int) { def foreachFunc = (rdd: RDD[T], time: Time) => { - val first11 = rdd.take(11) + val firstNum = rdd.take(num + 1) println ("-------------------------------------------") println ("Time: " + time) println ("-------------------------------------------") - first11.take(10).foreach(println) - if (first11.size > 10) println("...") + firstNum.take(num).foreach(println) + if (firstNum.size > num) println("...") println() } new ForEachDStream(this, context.sparkContext.clean(foreachFunc)).register() From cdccc263b20c1bb27b864411c82cfad7daca1f47 Mon Sep 17 00:00:00 2001 From: Akhil Das Date: Fri, 2 Jan 2015 15:12:27 -0800 Subject: [PATCH 158/320] Fixed typos in streaming-kafka-integration.md Changed projrect to project :) Author: Akhil Das Closes #3876 from akhld/patch-1 and squashes the following commits: e0cf9ef [Akhil Das] Fixed typos in streaming-kafka-integration.md --- docs/streaming-kafka-integration.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/streaming-kafka-integration.md b/docs/streaming-kafka-integration.md index 1c956fcb40da8..4378521dcac70 100644 --- a/docs/streaming-kafka-integration.md +++ b/docs/streaming-kafka-integration.md @@ -4,7 +4,7 @@ title: Spark Streaming + Kafka Integration Guide --- [Apache Kafka](http://kafka.apache.org/) is publish-subscribe messaging rethought as a distributed, partitioned, replicated commit log service. Here we explain how to configure Spark Streaming to receive data from Kafka. -1. **Linking:** In your SBT/Maven projrect definition, link your streaming application against the following artifact (see [Linking section](streaming-programming-guide.html#linking) in the main programming guide for further information). +1. **Linking:** In your SBT/Maven project definition, link your streaming application against the following artifact (see [Linking section](streaming-programming-guide.html#linking) in the main programming guide for further information). groupId = org.apache.spark artifactId = spark-streaming-kafka_{{site.SCALA_BINARY_VERSION}} From 342612b65f3d77c660383a332f0346872f076647 Mon Sep 17 00:00:00 2001 From: sigmoidanalytics Date: Sat, 3 Jan 2015 19:46:08 -0800 Subject: [PATCH 159/320] [SPARK-5058] Updated broken links Updated the broken link pointing to the KafkaWordCount example to the correct one. Author: sigmoidanalytics Closes #3877 from sigmoidanalytics/patch-1 and squashes the following commits: 3e19b31 [sigmoidanalytics] Updated broken links --- docs/streaming-kafka-integration.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/streaming-kafka-integration.md b/docs/streaming-kafka-integration.md index 4378521dcac70..0e38fe2144e9f 100644 --- a/docs/streaming-kafka-integration.md +++ b/docs/streaming-kafka-integration.md @@ -20,7 +20,7 @@ title: Spark Streaming + Kafka Integration Guide streamingContext, [zookeeperQuorum], [group id of the consumer], [per-topic number of Kafka partitions to consume]) See the [API docs](api/scala/index.html#org.apache.spark.streaming.kafka.KafkaUtils$) - and the [example]({{site.SPARK_GITHUB_URL}}/tree/master/examples/src/main/scala/org/apache/spark/examples/streaming/KafkaWordCount.scala). + and the [example]({{site.SPARK_GITHUB_URL}}/blob/master/examples/scala-2.10/src/main/scala/org/apache/spark/examples/streaming/KafkaWordCount.scala).
    import org.apache.spark.streaming.kafka.*; From b96008d5529bac5fd57b76554fd01760139cffff Mon Sep 17 00:00:00 2001 From: Brennon York Date: Sun, 4 Jan 2015 12:40:39 -0800 Subject: [PATCH 160/320] [SPARK-794][Core] Remove sleep() in ClusterScheduler.stop Removed `sleep()` from the `stop()` method of the `TaskSchedulerImpl` class which, from the JIRA ticket, is believed to be a legacy artifact slowing down testing originally introduced in the `ClusterScheduler` class. Author: Brennon York Closes #3851 from brennonyork/SPARK-794 and squashes the following commits: 04c3e64 [Brennon York] Removed sleep() from the stop() method --- .../scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala | 3 --- 1 file changed, 3 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala index cd3c015321e85..a41f3eef195d2 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala @@ -394,9 +394,6 @@ private[spark] class TaskSchedulerImpl( taskResultGetter.stop() } starvationTimer.cancel() - - // sleeping for an arbitrary 1 seconds to ensure that messages are sent out. - Thread.sleep(1000L) } override def defaultParallelism() = backend.defaultParallelism() From 3fddc9468fa50e7683caa973fec6c52e1132268d Mon Sep 17 00:00:00 2001 From: Dale Date: Sun, 4 Jan 2015 13:28:37 -0800 Subject: [PATCH 161/320] [SPARK-4787] Stop SparkContext if a DAGScheduler init error occurs Author: Dale Closes #3809 from tigerquoll/SPARK-4787 and squashes the following commits: 5661e01 [Dale] [SPARK-4787] Ensure that call to stop() doesn't lose the exception by using a finally block. 2172578 [Dale] [SPARK-4787] Stop context properly if an exception occurs during DAGScheduler initialization. --- core/src/main/scala/org/apache/spark/SparkContext.scala | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala index df1cb3cda2dba..4c25d5d6c0ceb 100644 --- a/core/src/main/scala/org/apache/spark/SparkContext.scala +++ b/core/src/main/scala/org/apache/spark/SparkContext.scala @@ -329,8 +329,13 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli try { dagScheduler = new DAGScheduler(this) } catch { - case e: Exception => throw - new SparkException("DAGScheduler cannot be initialized due to %s".format(e.getMessage)) + case e: Exception => { + try { + stop() + } finally { + throw new SparkException("Error while constructing DAGScheduler", e) + } + } } // start TaskScheduler after taskScheduler sets DAGScheduler reference in DAGScheduler's From e767d7ddac5c2330af553f2a74b8575dfc7afb67 Mon Sep 17 00:00:00 2001 From: bilna Date: Sun, 4 Jan 2015 19:37:48 -0800 Subject: [PATCH 162/320] [SPARK-4631] unit test for MQTT Please review the unit test for MQTT Author: bilna Author: Bilna P Closes #3844 from Bilna/master and squashes the following commits: acea3a3 [bilna] Adding dependency with scope test 28681fa [bilna] Merge remote-tracking branch 'upstream/master' fac3904 [bilna] Correction in Indentation and coding style ed9db4c [bilna] Merge remote-tracking branch 'upstream/master' 4b34ee7 [Bilna P] Update MQTTStreamSuite.scala 04503cf [bilna] Added embedded broker service for mqtt test 89d804e [bilna] Merge remote-tracking branch 'upstream/master' fc8eb28 [bilna] Merge remote-tracking branch 'upstream/master' 4b58094 [Bilna P] Update MQTTStreamSuite.scala b1ac4ad [bilna] Added BeforeAndAfter 5f6bfd2 [bilna] Added BeforeAndAfter e8b6623 [Bilna P] Update MQTTStreamSuite.scala 5ca6691 [Bilna P] Update MQTTStreamSuite.scala 8616495 [bilna] [SPARK-4631] unit test for MQTT --- external/mqtt/pom.xml | 6 + .../streaming/mqtt/MQTTStreamSuite.scala | 110 +++++++++++++++--- 2 files changed, 101 insertions(+), 15 deletions(-) diff --git a/external/mqtt/pom.xml b/external/mqtt/pom.xml index 9025915f4447e..d478267b605ba 100644 --- a/external/mqtt/pom.xml +++ b/external/mqtt/pom.xml @@ -66,6 +66,12 @@ junit-interface test + + org.apache.activemq + activemq-core + 5.7.0 + test + target/scala-${scala.binary.version}/classes diff --git a/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala b/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala index 84595acf45ccb..98fe6cb301f52 100644 --- a/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala +++ b/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala @@ -17,31 +17,111 @@ package org.apache.spark.streaming.mqtt -import org.scalatest.FunSuite +import java.net.{URI, ServerSocket} -import org.apache.spark.streaming.{Seconds, StreamingContext} +import org.apache.activemq.broker.{TransportConnector, BrokerService} +import org.apache.spark.util.Utils +import org.scalatest.{BeforeAndAfter, FunSuite} +import org.scalatest.concurrent.Eventually +import scala.concurrent.duration._ +import org.apache.spark.streaming.{Milliseconds, StreamingContext} import org.apache.spark.storage.StorageLevel import org.apache.spark.streaming.dstream.ReceiverInputDStream +import org.eclipse.paho.client.mqttv3._ +import org.eclipse.paho.client.mqttv3.persist.MqttDefaultFilePersistence -class MQTTStreamSuite extends FunSuite { - - val batchDuration = Seconds(1) +class MQTTStreamSuite extends FunSuite with Eventually with BeforeAndAfter { + private val batchDuration = Milliseconds(500) private val master: String = "local[2]" - private val framework: String = this.getClass.getSimpleName + private val freePort = findFreePort() + private val brokerUri = "//localhost:" + freePort + private val topic = "def" + private var ssc: StreamingContext = _ + private val persistenceDir = Utils.createTempDir() + private var broker: BrokerService = _ + private var connector: TransportConnector = _ - test("mqtt input stream") { - val ssc = new StreamingContext(master, framework, batchDuration) - val brokerUrl = "abc" - val topic = "def" + before { + ssc = new StreamingContext(master, framework, batchDuration) + setupMQTT() + } - // tests the API, does not actually test data receiving - val test1: ReceiverInputDStream[String] = MQTTUtils.createStream(ssc, brokerUrl, topic) - val test2: ReceiverInputDStream[String] = - MQTTUtils.createStream(ssc, brokerUrl, topic, StorageLevel.MEMORY_AND_DISK_SER_2) + after { + if (ssc != null) { + ssc.stop() + ssc = null + } + Utils.deleteRecursively(persistenceDir) + tearDownMQTT() + } - // TODO: Actually test receiving data + test("mqtt input stream") { + val sendMessage = "MQTT demo for spark streaming" + val receiveStream: ReceiverInputDStream[String] = + MQTTUtils.createStream(ssc, "tcp:" + brokerUri, topic, StorageLevel.MEMORY_ONLY) + var receiveMessage: List[String] = List() + receiveStream.foreachRDD { rdd => + if (rdd.collect.length > 0) { + receiveMessage = receiveMessage ::: List(rdd.first) + receiveMessage + } + } + ssc.start() + publishData(sendMessage) + eventually(timeout(10000 milliseconds), interval(100 milliseconds)) { + assert(sendMessage.equals(receiveMessage(0))) + } ssc.stop() } + + private def setupMQTT() { + broker = new BrokerService() + connector = new TransportConnector() + connector.setName("mqtt") + connector.setUri(new URI("mqtt:" + brokerUri)) + broker.addConnector(connector) + broker.start() + } + + private def tearDownMQTT() { + if (broker != null) { + broker.stop() + broker = null + } + if (connector != null) { + connector.stop() + connector = null + } + } + + private def findFreePort(): Int = { + Utils.startServiceOnPort(23456, (trialPort: Int) => { + val socket = new ServerSocket(trialPort) + socket.close() + (null, trialPort) + })._2 + } + + def publishData(data: String): Unit = { + var client: MqttClient = null + try { + val persistence: MqttClientPersistence = new MqttDefaultFilePersistence(persistenceDir.getAbsolutePath) + client = new MqttClient("tcp:" + brokerUri, MqttClient.generateClientId(), persistence) + client.connect() + if (client.isConnected) { + val msgTopic: MqttTopic = client.getTopic(topic) + val message: MqttMessage = new MqttMessage(data.getBytes("utf-8")) + message.setQos(1) + message.setRetained(true) + for (i <- 0 to 100) + msgTopic.publish(message) + } + } finally { + client.disconnect() + client.close() + client = null + } + } } From 939ba1f8f6e32fef9026cc43fce55b36e4b9bfd1 Mon Sep 17 00:00:00 2001 From: Josh Rosen Date: Sun, 4 Jan 2015 20:26:18 -0800 Subject: [PATCH 163/320] [SPARK-4835] Disable validateOutputSpecs for Spark Streaming jobs This patch disables output spec. validation for jobs launched through Spark Streaming, since this interferes with checkpoint recovery. Hadoop OutputFormats have a `checkOutputSpecs` method which performs certain checks prior to writing output, such as checking whether the output directory already exists. SPARK-1100 added checks for FileOutputFormat, SPARK-1677 (#947) added a SparkConf configuration to disable these checks, and SPARK-2309 (#1088) extended these checks to run for all OutputFormats, not just FileOutputFormat. In Spark Streaming, we might have to re-process a batch during checkpoint recovery, so `save` actions may be called multiple times. In addition to `DStream`'s own save actions, users might use `transform` or `foreachRDD` and call the `RDD` and `PairRDD` save actions. When output spec. validation is enabled, the second calls to these actions will fail due to existing output. This patch automatically disables output spec. validation for jobs submitted by the Spark Streaming scheduler. This is done by using Scala's `DynamicVariable` to propagate the bypass setting without having to mutate SparkConf or introduce a global variable. Author: Josh Rosen Closes #3832 from JoshRosen/SPARK-4835 and squashes the following commits: 36eaf35 [Josh Rosen] Add comment explaining use of transform() in test. 6485cf8 [Josh Rosen] Add test case in Streaming; fix bug for transform() 7b3e06a [Josh Rosen] Remove Streaming-specific setting to undo this change; update conf. guide bf9094d [Josh Rosen] Revise disableOutputSpecValidation() comment to not refer to Spark Streaming. e581d17 [Josh Rosen] Deduplicate isOutputSpecValidationEnabled logic. 762e473 [Josh Rosen] [SPARK-4835] Disable validateOutputSpecs for Spark Streaming jobs. --- .../apache/spark/rdd/PairRDDFunctions.scala | 19 ++++++++- docs/configuration.md | 4 +- .../spark/streaming/dstream/DStream.scala | 10 ++++- .../dstream/TransformedDStream.scala | 2 +- .../streaming/scheduler/JobScheduler.scala | 8 +++- .../spark/streaming/CheckpointSuite.scala | 39 +++++++++++++++++++ 6 files changed, 75 insertions(+), 7 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala b/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala index 4469c89e6bb1c..f8df5b2a08866 100644 --- a/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala +++ b/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala @@ -25,6 +25,7 @@ import scala.collection.{Map, mutable} import scala.collection.JavaConversions._ import scala.collection.mutable.ArrayBuffer import scala.reflect.ClassTag +import scala.util.DynamicVariable import com.clearspring.analytics.stream.cardinality.HyperLogLogPlus import org.apache.hadoop.conf.{Configurable, Configuration} @@ -964,7 +965,7 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)]) val outfmt = job.getOutputFormatClass val jobFormat = outfmt.newInstance - if (self.conf.getBoolean("spark.hadoop.validateOutputSpecs", true)) { + if (isOutputSpecValidationEnabled) { // FileOutputFormat ignores the filesystem parameter jobFormat.checkOutputSpecs(job) } @@ -1042,7 +1043,7 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)]) logDebug("Saving as hadoop file of type (" + keyClass.getSimpleName + ", " + valueClass.getSimpleName + ")") - if (self.conf.getBoolean("spark.hadoop.validateOutputSpecs", true)) { + if (isOutputSpecValidationEnabled) { // FileOutputFormat ignores the filesystem parameter val ignoredFs = FileSystem.get(hadoopConf) hadoopConf.getOutputFormat.checkOutputSpecs(ignoredFs, hadoopConf) @@ -1117,8 +1118,22 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)]) private[spark] def valueClass: Class[_] = vt.runtimeClass private[spark] def keyOrdering: Option[Ordering[K]] = Option(ord) + + // Note: this needs to be a function instead of a 'val' so that the disableOutputSpecValidation + // setting can take effect: + private def isOutputSpecValidationEnabled: Boolean = { + val validationDisabled = PairRDDFunctions.disableOutputSpecValidation.value + val enabledInConf = self.conf.getBoolean("spark.hadoop.validateOutputSpecs", true) + enabledInConf && !validationDisabled + } } private[spark] object PairRDDFunctions { val RECORDS_BETWEEN_BYTES_WRITTEN_METRIC_UPDATES = 256 + + /** + * Allows for the `spark.hadoop.validateOutputSpecs` checks to be disabled on a case-by-case + * basis; see SPARK-4835 for more details. + */ + val disableOutputSpecValidation: DynamicVariable[Boolean] = new DynamicVariable[Boolean](false) } diff --git a/docs/configuration.md b/docs/configuration.md index fa9d311f85068..9bb6499993735 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -709,7 +709,9 @@ Apart from these, the following properties are also available, and may be useful
    + previous versions of Spark. Simply use Hadoop's FileSystem API to delete output directories by hand. + This setting is ignored for jobs generated through Spark Streaming's StreamingContext, since + data may need to be rewritten to pre-existing output directories during checkpoint recovery. diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala index 28fc00cf3944f..b874f561c12eb 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala @@ -26,7 +26,7 @@ import scala.reflect.ClassTag import scala.util.matching.Regex import org.apache.spark.{Logging, SparkException} -import org.apache.spark.rdd.{BlockRDD, RDD} +import org.apache.spark.rdd.{BlockRDD, PairRDDFunctions, RDD} import org.apache.spark.storage.StorageLevel import org.apache.spark.streaming._ import org.apache.spark.streaming.StreamingContext.rddToFileName @@ -292,7 +292,13 @@ abstract class DStream[T: ClassTag] ( // set this DStream's creation site, generate RDDs and then restore the previous call site. val prevCallSite = ssc.sparkContext.getCallSite() ssc.sparkContext.setCallSite(creationSite) - val rddOption = compute(time) + // Disable checks for existing output directories in jobs launched by the streaming + // scheduler, since we may need to write output to an existing directory during checkpoint + // recovery; see SPARK-4835 for more details. We need to have this call here because + // compute() might cause Spark jobs to be launched. + val rddOption = PairRDDFunctions.disableOutputSpecValidation.withValue(true) { + compute(time) + } ssc.sparkContext.setCallSite(prevCallSite) rddOption.foreach { case newRDD => diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/TransformedDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/TransformedDStream.scala index 7cd4554282ca1..71b61856e23c0 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/TransformedDStream.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/TransformedDStream.scala @@ -17,7 +17,7 @@ package org.apache.spark.streaming.dstream -import org.apache.spark.rdd.RDD +import org.apache.spark.rdd.{PairRDDFunctions, RDD} import org.apache.spark.streaming.{Duration, Time} import scala.reflect.ClassTag diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala index cfa3cd8925c80..0e0f5bd3b9db4 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala @@ -22,6 +22,7 @@ import scala.collection.JavaConversions._ import java.util.concurrent.{TimeUnit, ConcurrentHashMap, Executors} import akka.actor.{ActorRef, Actor, Props} import org.apache.spark.{SparkException, Logging, SparkEnv} +import org.apache.spark.rdd.PairRDDFunctions import org.apache.spark.streaming._ @@ -168,7 +169,12 @@ class JobScheduler(val ssc: StreamingContext) extends Logging { private class JobHandler(job: Job) extends Runnable { def run() { eventActor ! JobStarted(job) - job.run() + // Disable checks for existing output directories in jobs launched by the streaming scheduler, + // since we may need to write output to an existing directory during checkpoint recovery; + // see SPARK-4835 for more details. + PairRDDFunctions.disableOutputSpecValidation.withValue(true) { + job.run() + } eventActor ! JobCompleted(job) } } diff --git a/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala index 72d055eb2ea31..5d232c6ade7a9 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala @@ -255,6 +255,45 @@ class CheckpointSuite extends TestSuiteBase { } } + test("recovery with saveAsHadoopFile inside transform operation") { + // Regression test for SPARK-4835. + // + // In that issue, the problem was that `saveAsHadoopFile(s)` would fail when the last batch + // was restarted from a checkpoint since the output directory would already exist. However, + // the other saveAsHadoopFile* tests couldn't catch this because they only tested whether the + // output matched correctly and not whether the post-restart batch had successfully finished + // without throwing any errors. The following test reproduces the same bug with a test that + // actually fails because the error in saveAsHadoopFile causes transform() to fail, which + // prevents the expected output from being written to the output stream. + // + // This is not actually a valid use of transform, but it's being used here so that we can test + // the fix for SPARK-4835 independently of additional test cleanup. + // + // After SPARK-5079 is addressed, should be able to remove this test since a strengthened + // version of the other saveAsHadoopFile* tests would prevent regressions for this issue. + val tempDir = Files.createTempDir() + try { + testCheckpointedOperation( + Seq(Seq("a", "a", "b"), Seq("", ""), Seq(), Seq("a", "a", "b"), Seq("", ""), Seq()), + (s: DStream[String]) => { + s.transform { (rdd, time) => + val output = rdd.map(x => (x, 1)).reduceByKey(_ + _) + output.saveAsHadoopFile( + new File(tempDir, "result-" + time.milliseconds).getAbsolutePath, + classOf[Text], + classOf[IntWritable], + classOf[TextOutputFormat[Text, IntWritable]]) + output + } + }, + Seq(Seq(("a", 2), ("b", 1)), Seq(("", 2)), Seq(), Seq(("a", 2), ("b", 1)), Seq(("", 2)), Seq()), + 3 + ) + } finally { + Utils.deleteRecursively(tempDir) + } + } + // This tests whether the StateDStream's RDD checkpoints works correctly such // that the system can recover from a master failure. This assumes as reliable, // replayable input source - TestInputDStream. From 72396522bcf5303f761956658510672e4feb2845 Mon Sep 17 00:00:00 2001 From: zsxwing Date: Sun, 4 Jan 2015 21:03:17 -0800 Subject: [PATCH 164/320] [SPARK-5067][Core] Use '===' to compare well-defined case class A simple fix would be adding `assert(e1.appId == e2.appId)` for `SparkListenerApplicationStart`. But actually we can use `===` for well-defined case class directly. Therefore, instead of fixing this issue, I use `===` to compare those well-defined case classes (all fields have implemented a correct `equals` method, such as primitive types) Author: zsxwing Closes #3886 from zsxwing/SPARK-5067 and squashes the following commits: 0a51711 [zsxwing] Use '===' to compare well-defined case class --- .../apache/spark/util/JsonProtocolSuite.scala | 32 +++---------------- 1 file changed, 4 insertions(+), 28 deletions(-) diff --git a/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala b/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala index 593d6dd8c3794..63c2559c5c5f5 100644 --- a/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala +++ b/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala @@ -280,7 +280,7 @@ class JsonProtocolSuite extends FunSuite { private def testBlockManagerId(id: BlockManagerId) { val newId = JsonProtocol.blockManagerIdFromJson(JsonProtocol.blockManagerIdToJson(id)) - assertEquals(id, newId) + assert(id === newId) } private def testTaskInfo(info: TaskInfo) { @@ -335,22 +335,8 @@ class JsonProtocolSuite extends FunSuite { assertEquals(e1.jobResult, e2.jobResult) case (e1: SparkListenerEnvironmentUpdate, e2: SparkListenerEnvironmentUpdate) => assertEquals(e1.environmentDetails, e2.environmentDetails) - case (e1: SparkListenerBlockManagerAdded, e2: SparkListenerBlockManagerAdded) => - assert(e1.maxMem === e2.maxMem) - assert(e1.time === e2.time) - assertEquals(e1.blockManagerId, e2.blockManagerId) - case (e1: SparkListenerBlockManagerRemoved, e2: SparkListenerBlockManagerRemoved) => - assert(e1.time === e2.time) - assertEquals(e1.blockManagerId, e2.blockManagerId) - case (e1: SparkListenerUnpersistRDD, e2: SparkListenerUnpersistRDD) => - assert(e1.rddId == e2.rddId) - case (e1: SparkListenerApplicationStart, e2: SparkListenerApplicationStart) => - assert(e1.appName == e2.appName) - assert(e1.time == e2.time) - assert(e1.sparkUser == e2.sparkUser) - case (e1: SparkListenerApplicationEnd, e2: SparkListenerApplicationEnd) => - assert(e1.time == e2.time) - case (SparkListenerShutdown, SparkListenerShutdown) => + case (e1, e2) => + assert(e1 === e2) case _ => fail("Events don't match in types!") } } @@ -435,16 +421,6 @@ class JsonProtocolSuite extends FunSuite { assert(metrics1.bytesRead === metrics2.bytesRead) } - private def assertEquals(bm1: BlockManagerId, bm2: BlockManagerId) { - if (bm1 == null || bm2 == null) { - assert(bm1 === bm2) - } else { - assert(bm1.executorId === bm2.executorId) - assert(bm1.host === bm2.host) - assert(bm1.port === bm2.port) - } - } - private def assertEquals(result1: JobResult, result2: JobResult) { (result1, result2) match { case (JobSucceeded, JobSucceeded) => @@ -462,7 +438,7 @@ class JsonProtocolSuite extends FunSuite { assert(r1.shuffleId === r2.shuffleId) assert(r1.mapId === r2.mapId) assert(r1.reduceId === r2.reduceId) - assertEquals(r1.bmAddress, r2.bmAddress) + assert(r1.bmAddress === r2.bmAddress) assert(r1.message === r2.message) case (r1: ExceptionFailure, r2: ExceptionFailure) => assert(r1.className === r2.className) From 6c726a3fbd9cd3aa5f3a1992b2132b25eabb76a0 Mon Sep 17 00:00:00 2001 From: zsxwing Date: Sun, 4 Jan 2015 21:06:04 -0800 Subject: [PATCH 165/320] [SPARK-5069][Core] Fix the race condition of TaskSchedulerImpl.dagScheduler It's not necessary to set `TaskSchedulerImpl.dagScheduler` in preStart. It's safe to set it after `initializeEventProcessActor()`. Author: zsxwing Closes #3887 from zsxwing/SPARK-5069 and squashes the following commits: d95894f [zsxwing] Fix the race condition of TaskSchedulerImpl.dagScheduler --- .../scala/org/apache/spark/scheduler/DAGScheduler.scala | 7 +------ .../apache/spark/scheduler/TaskSchedulerImplSuite.scala | 1 - 2 files changed, 1 insertion(+), 7 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala index cb8ccfbdbdcbb..259621d263d7c 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala @@ -138,6 +138,7 @@ class DAGScheduler( } initializeEventProcessActor() + taskScheduler.setDAGScheduler(this) // Called by TaskScheduler to report task's starting. def taskStarted(task: Task[_], taskInfo: TaskInfo) { @@ -1375,12 +1376,6 @@ private[scheduler] class DAGSchedulerActorSupervisor(dagScheduler: DAGScheduler) private[scheduler] class DAGSchedulerEventProcessActor(dagScheduler: DAGScheduler) extends Actor with Logging { - override def preStart() { - // set DAGScheduler for taskScheduler to ensure eventProcessActor is always - // valid when the messages arrive - dagScheduler.taskScheduler.setDAGScheduler(dagScheduler) - } - /** * The main event loop of the DAG scheduler. */ diff --git a/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala index 40aaf9dd1f1e9..00812e6018d1f 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala @@ -305,7 +305,6 @@ class TaskSchedulerImplSuite extends FunSuite with LocalSparkContext with Loggin override def taskStarted(task: Task[_], taskInfo: TaskInfo) {} override def executorAdded(execId: String, host: String) {} } - taskScheduler.setDAGScheduler(dagScheduler) // Give zero core offers. Should not generate any tasks val zeroCoreWorkerOffers = Seq(new WorkerOffer("executor0", "host0", 0), new WorkerOffer("executor1", "host1", 0)) From 27e7f5a7237d9d64a3b2c8a030ba3e3a9a96b26c Mon Sep 17 00:00:00 2001 From: zsxwing Date: Sun, 4 Jan 2015 21:09:21 -0800 Subject: [PATCH 166/320] [SPARK-5083][Core] Fix a flaky test in TaskResultGetterSuite Because `sparkEnv.blockManager.master.removeBlock` is asynchronous, we need to make sure the block has already been removed before calling `super.enqueueSuccessfulTask`. Author: zsxwing Closes #3894 from zsxwing/SPARK-5083 and squashes the following commits: d97c03d [zsxwing] Fix a flaky test in TaskResultGetterSuite --- .../scheduler/TaskResultGetterSuite.scala | 22 +++++++++++++++++-- 1 file changed, 20 insertions(+), 2 deletions(-) diff --git a/core/src/test/scala/org/apache/spark/scheduler/TaskResultGetterSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/TaskResultGetterSuite.scala index 3aab5a156ee77..e3a3803e6483a 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/TaskResultGetterSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/TaskResultGetterSuite.scala @@ -19,7 +19,12 @@ package org.apache.spark.scheduler import java.nio.ByteBuffer -import org.scalatest.{BeforeAndAfter, BeforeAndAfterAll, FunSuite} +import scala.concurrent.duration._ +import scala.language.postfixOps +import scala.util.control.NonFatal + +import org.scalatest.{BeforeAndAfter, FunSuite} +import org.scalatest.concurrent.Eventually._ import org.apache.spark.{LocalSparkContext, SparkConf, SparkContext, SparkEnv} import org.apache.spark.storage.TaskResultBlockId @@ -34,6 +39,8 @@ class ResultDeletingTaskResultGetter(sparkEnv: SparkEnv, scheduler: TaskSchedule extends TaskResultGetter(sparkEnv, scheduler) { var removedResult = false + @volatile var removeBlockSuccessfully = false + override def enqueueSuccessfulTask( taskSetManager: TaskSetManager, tid: Long, serializedData: ByteBuffer) { if (!removedResult) { @@ -42,6 +49,15 @@ class ResultDeletingTaskResultGetter(sparkEnv: SparkEnv, scheduler: TaskSchedule serializer.get().deserialize[TaskResult[_]](serializedData) match { case IndirectTaskResult(blockId, size) => sparkEnv.blockManager.master.removeBlock(blockId) + // removeBlock is asynchronous. Need to wait it's removed successfully + try { + eventually(timeout(3 seconds), interval(200 milliseconds)) { + assert(!sparkEnv.blockManager.master.contains(blockId)) + } + removeBlockSuccessfully = true + } catch { + case NonFatal(e) => removeBlockSuccessfully = false + } case directResult: DirectTaskResult[_] => taskSetManager.abort("Internal error: expect only indirect results") } @@ -92,10 +108,12 @@ class TaskResultGetterSuite extends FunSuite with BeforeAndAfter with LocalSpark assert(false, "Expect local cluster to use TaskSchedulerImpl") throw new ClassCastException } - scheduler.taskResultGetter = new ResultDeletingTaskResultGetter(sc.env, scheduler) + val resultGetter = new ResultDeletingTaskResultGetter(sc.env, scheduler) + scheduler.taskResultGetter = resultGetter val akkaFrameSize = sc.env.actorSystem.settings.config.getBytes("akka.remote.netty.tcp.maximum-frame-size").toInt val result = sc.parallelize(Seq(1), 1).map(x => 1.to(akkaFrameSize).toArray).reduce((x, y) => x) + assert(resultGetter.removeBlockSuccessfully) assert(result === 1.to(akkaFrameSize).toArray) // Make sure two tasks were run (one failed one, and a second retried one). From 5c506cecb933b156b2f06a688ee08c4347bf0d47 Mon Sep 17 00:00:00 2001 From: zsxwing Date: Sun, 4 Jan 2015 21:18:33 -0800 Subject: [PATCH 167/320] [SPARK-5074][Core] Fix a non-deterministic test failure Add `assert(sc.listenerBus.waitUntilEmpty(WAIT_TIMEOUT_MILLIS))` to make sure `sparkListener` receive the message. Author: zsxwing Closes #3889 from zsxwing/SPARK-5074 and squashes the following commits: e61c198 [zsxwing] Fix a non-deterministic test failure --- .../scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala | 1 + 1 file changed, 1 insertion(+) diff --git a/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala index d6ec9e129cceb..d30eb10bbe947 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala @@ -247,6 +247,7 @@ class DAGSchedulerSuite extends TestKit(ActorSystem("DAGSchedulerSuite")) with F test("[SPARK-3353] parent stage should have lower stage id") { sparkListener.stageByOrderOfExecution.clear() sc.parallelize(1 to 10).map(x => (x, x)).reduceByKey(_ + _, 4).count() + assert(sc.listenerBus.waitUntilEmpty(WAIT_TIMEOUT_MILLIS)) assert(sparkListener.stageByOrderOfExecution.length === 2) assert(sparkListener.stageByOrderOfExecution(0) < sparkListener.stageByOrderOfExecution(1)) } From d3f07fd23cc26a70f44c52e24445974d4885d58a Mon Sep 17 00:00:00 2001 From: Varun Saxena Date: Mon, 5 Jan 2015 10:32:37 -0800 Subject: [PATCH 168/320] [SPARK-4688] Have a single shared network timeout in Spark [SPARK-4688] Have a single shared network timeout in Spark Author: Varun Saxena Author: varunsaxena Closes #3562 from varunsaxena/SPARK-4688 and squashes the following commits: 6e97f72 [Varun Saxena] [SPARK-4688] Single shared network timeout cd783a2 [Varun Saxena] SPARK-4688 d6f8c29 [Varun Saxena] SCALA-4688 9562b15 [Varun Saxena] SPARK-4688 a75f014 [varunsaxena] SPARK-4688 594226c [varunsaxena] SPARK-4688 --- .../apache/spark/network/nio/ConnectionManager.scala | 3 ++- .../apache/spark/storage/BlockManagerMasterActor.scala | 7 +++++-- .../main/scala/org/apache/spark/util/AkkaUtils.scala | 2 +- docs/configuration.md | 10 ++++++++++ .../org/apache/spark/network/util/TransportConf.java | 4 +++- 5 files changed, 21 insertions(+), 5 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala b/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala index 243b71c980864..98455c0968263 100644 --- a/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala +++ b/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala @@ -81,7 +81,8 @@ private[nio] class ConnectionManager( private val ackTimeoutMonitor = new HashedWheelTimer(Utils.namedThreadFactory("AckTimeoutMonitor")) - private val ackTimeout = conf.getInt("spark.core.connection.ack.wait.timeout", 60) + private val ackTimeout = + conf.getInt("spark.core.connection.ack.wait.timeout", conf.getInt("spark.network.timeout", 100)) // Get the thread counts from the Spark Configuration. // diff --git a/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterActor.scala b/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterActor.scala index 9cbda41223a8b..9d77cf27882eb 100644 --- a/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterActor.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterActor.scala @@ -52,8 +52,11 @@ class BlockManagerMasterActor(val isLocal: Boolean, conf: SparkConf, listenerBus private val akkaTimeout = AkkaUtils.askTimeout(conf) - val slaveTimeout = conf.getLong("spark.storage.blockManagerSlaveTimeoutMs", - math.max(conf.getInt("spark.executor.heartbeatInterval", 10000) * 3, 45000)) + val slaveTimeout = { + val defaultMs = math.max(conf.getInt("spark.executor.heartbeatInterval", 10000) * 3, 45000) + val networkTimeout = conf.getInt("spark.network.timeout", defaultMs / 1000) + conf.getLong("spark.storage.blockManagerSlaveTimeoutMs", networkTimeout * 1000) + } val checkTimeoutInterval = conf.getLong("spark.storage.blockManagerTimeoutIntervalMs", 60000) diff --git a/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala b/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala index 8c2457f56bffe..64e3a5416c6b5 100644 --- a/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala +++ b/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala @@ -65,7 +65,7 @@ private[spark] object AkkaUtils extends Logging { val akkaThreads = conf.getInt("spark.akka.threads", 4) val akkaBatchSize = conf.getInt("spark.akka.batchSize", 15) - val akkaTimeout = conf.getInt("spark.akka.timeout", 100) + val akkaTimeout = conf.getInt("spark.akka.timeout", conf.getInt("spark.network.timeout", 100)) val akkaFrameSize = maxFrameSizeBytes(conf) val akkaLogLifecycleEvents = conf.getBoolean("spark.akka.logLifecycleEvents", false) val lifecycleEvents = if (akkaLogLifecycleEvents) "on" else "off" diff --git a/docs/configuration.md b/docs/configuration.md index 9bb6499993735..7ada67fc303c6 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -818,6 +818,16 @@ Apart from these, the following properties are also available, and may be useful Communication timeout between Spark nodes, in seconds. + + + + + diff --git a/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java b/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java index 7c9adf52af0f0..e34382da22a50 100644 --- a/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java +++ b/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java @@ -37,7 +37,9 @@ public boolean preferDirectBufs() { /** Connect timeout in milliseconds. Default 120 secs. */ public int connectionTimeoutMs() { - return conf.getInt("spark.shuffle.io.connectionTimeout", 120) * 1000; + int timeout = + conf.getInt("spark.shuffle.io.connectionTimeout", conf.getInt("spark.network.timeout", 100)); + return timeout * 1000; } /** Number of concurrent connections between two nodes for fetching data. */ From ce39b34404868de4ca51be06832169187b1aef7d Mon Sep 17 00:00:00 2001 From: WangTao Date: Mon, 5 Jan 2015 11:59:38 -0800 Subject: [PATCH 169/320] [SPARK-5057] Log message in failed askWithReply attempts https://issues.apache.org/jira/browse/SPARK-5057 Author: WangTao Author: WangTaoTheTonic Closes #3875 from WangTaoTheTonic/SPARK-5057 and squashes the following commits: 1503487 [WangTao] use string interpolation 706c8a7 [WangTaoTheTonic] log more messages --- .../scala/org/apache/spark/util/AkkaUtils.scala | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala b/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala index 64e3a5416c6b5..8d86fd3e11ad7 100644 --- a/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala +++ b/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala @@ -89,7 +89,7 @@ private[spark] object AkkaUtils extends Logging { } val requireCookie = if (isAuthOn) "on" else "off" val secureCookie = if (isAuthOn) secretKey else "" - logDebug("In createActorSystem, requireCookie is: " + requireCookie) + logDebug(s"In createActorSystem, requireCookie is: $requireCookie") val akkaConf = ConfigFactory.parseMap(conf.getAkkaConf.toMap[String, String]).withFallback( ConfigFactory.parseString( @@ -140,8 +140,8 @@ private[spark] object AkkaUtils extends Logging { def maxFrameSizeBytes(conf: SparkConf): Int = { val frameSizeInMB = conf.getInt("spark.akka.frameSize", 10) if (frameSizeInMB > AKKA_MAX_FRAME_SIZE_IN_MB) { - throw new IllegalArgumentException("spark.akka.frameSize should not be greater than " - + AKKA_MAX_FRAME_SIZE_IN_MB + "MB") + throw new IllegalArgumentException( + s"spark.akka.frameSize should not be greater than $AKKA_MAX_FRAME_SIZE_IN_MB MB") } frameSizeInMB * 1024 * 1024 } @@ -182,8 +182,8 @@ private[spark] object AkkaUtils extends Logging { timeout: FiniteDuration): T = { // TODO: Consider removing multiple attempts if (actor == null) { - throw new SparkException("Error sending message as actor is null " + - "[message = " + message + "]") + throw new SparkException(s"Error sending message [message = $message]" + + " as actor is null ") } var attempts = 0 var lastException: Exception = null @@ -200,13 +200,13 @@ private[spark] object AkkaUtils extends Logging { case ie: InterruptedException => throw ie case e: Exception => lastException = e - logWarning("Error sending message in " + attempts + " attempts", e) + logWarning(s"Error sending message [message = $message] in $attempts attempts", e) } Thread.sleep(retryInterval) } throw new SparkException( - "Error sending message [message = " + message + "]", lastException) + s"Error sending message [message = $message]", lastException) } def makeDriverRef(name: String, conf: SparkConf, actorSystem: ActorSystem): ActorRef = { From 1c0e7ce056c79e1db96f85b8c56a479b8b043970 Mon Sep 17 00:00:00 2001 From: Jongyoul Lee Date: Mon, 5 Jan 2015 12:05:09 -0800 Subject: [PATCH 170/320] [SPARK-4465] runAsSparkUser doesn't affect TaskRunner in Mesos environme... ...nt at all. - fixed a scope of runAsSparkUser from MesosExecutorDriver.run to MesosExecutorBackend.launchTask - See the Jira Issue for more details. Author: Jongyoul Lee Closes #3741 from jongyoul/SPARK-4465 and squashes the following commits: 46ad71e [Jongyoul Lee] [SPARK-4465] runAsSparkUser doesn't affect TaskRunner in Mesos environment at all. - Removed unused import 3d6631f [Jongyoul Lee] [SPARK-4465] runAsSparkUser doesn't affect TaskRunner in Mesos environment at all. - Removed comments and adjusted indentations 2343f13 [Jongyoul Lee] [SPARK-4465] runAsSparkUser doesn't affect TaskRunner in Mesos environment at all. - fixed a scope of runAsSparkUser from MesosExecutorDriver.run to MesosExecutorBackend.launchTask --- .../spark/executor/MesosExecutorBackend.scala | 15 +++++++-------- 1 file changed, 7 insertions(+), 8 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/executor/MesosExecutorBackend.scala b/core/src/main/scala/org/apache/spark/executor/MesosExecutorBackend.scala index a098d07bd8659..2e23ae0a4f831 100644 --- a/core/src/main/scala/org/apache/spark/executor/MesosExecutorBackend.scala +++ b/core/src/main/scala/org/apache/spark/executor/MesosExecutorBackend.scala @@ -22,7 +22,7 @@ import java.nio.ByteBuffer import scala.collection.JavaConversions._ import org.apache.mesos.protobuf.ByteString -import org.apache.mesos.{Executor => MesosExecutor, ExecutorDriver, MesosExecutorDriver, MesosNativeLibrary} +import org.apache.mesos.{Executor => MesosExecutor, ExecutorDriver, MesosExecutorDriver} import org.apache.mesos.Protos.{TaskStatus => MesosTaskStatus, _} import org.apache.spark.{Logging, TaskState, SparkConf, SparkEnv} @@ -80,7 +80,9 @@ private[spark] class MesosExecutorBackend if (executor == null) { logError("Received launchTask but executor was null") } else { - executor.launchTask(this, taskId, taskInfo.getName, taskInfo.getData.asReadOnlyByteBuffer) + SparkHadoopUtil.get.runAsSparkUser { () => + executor.launchTask(this, taskId, taskInfo.getName, taskInfo.getData.asReadOnlyByteBuffer) + } } } @@ -112,11 +114,8 @@ private[spark] class MesosExecutorBackend private[spark] object MesosExecutorBackend extends Logging { def main(args: Array[String]) { SignalLogger.register(log) - SparkHadoopUtil.get.runAsSparkUser { () => - MesosNativeLibrary.load() - // Create a new Executor and start it running - val runner = new MesosExecutorBackend() - new MesosExecutorDriver(runner).run() - } + // Create a new Executor and start it running + val runner = new MesosExecutorBackend() + new MesosExecutorDriver(runner).run() } } From 6c6f32574023b8e43a24f2081ff17e6e446de2f3 Mon Sep 17 00:00:00 2001 From: freeman Date: Mon, 5 Jan 2015 13:10:59 -0800 Subject: [PATCH 171/320] [SPARK-5089][PYSPARK][MLLIB] Fix vector convert This is a small change addressing a potentially significant bug in how PySpark + MLlib handles non-float64 numpy arrays. The automatic conversion to `DenseVector` that occurs when passing RDDs to MLlib algorithms in PySpark should automatically upcast to float64s, but currently this wasn't actually happening. As a result, non-float64 would be silently parsed inappropriately during SerDe, yielding erroneous results when running, for example, KMeans. The PR includes the fix, as well as a new test for the correct conversion behavior. davies Author: freeman Closes #3902 from freeman-lab/fix-vector-convert and squashes the following commits: 764db47 [freeman] Add a test for proper conversion behavior 704f97e [freeman] Return array after changing type --- python/pyspark/mllib/linalg.py | 2 +- python/pyspark/mllib/tests.py | 10 ++++++++++ 2 files changed, 11 insertions(+), 1 deletion(-) diff --git a/python/pyspark/mllib/linalg.py b/python/pyspark/mllib/linalg.py index f7aa2b0cb04b3..4f8491f43e457 100644 --- a/python/pyspark/mllib/linalg.py +++ b/python/pyspark/mllib/linalg.py @@ -178,7 +178,7 @@ def __init__(self, ar): elif not isinstance(ar, np.ndarray): ar = np.array(ar, dtype=np.float64) if ar.dtype != np.float64: - ar.astype(np.float64) + ar = ar.astype(np.float64) self.array = ar def __reduce__(self): diff --git a/python/pyspark/mllib/tests.py b/python/pyspark/mllib/tests.py index 5034f229e824a..1f48bc1219dba 100644 --- a/python/pyspark/mllib/tests.py +++ b/python/pyspark/mllib/tests.py @@ -110,6 +110,16 @@ def test_squared_distance(self): self.assertEquals(0.0, _squared_distance(dv, dv)) self.assertEquals(0.0, _squared_distance(lst, lst)) + def test_conversion(self): + # numpy arrays should be automatically upcast to float64 + # tests for fix of [SPARK-5089] + v = array([1, 2, 3, 4], dtype='float64') + dv = DenseVector(v) + self.assertTrue(dv.array.dtype == 'float64') + v = array([1, 2, 3, 4], dtype='float32') + dv = DenseVector(v) + self.assertTrue(dv.array.dtype == 'float64') + class ListTests(PySparkTestCase): From bbcba3a9430365640c0188e7ca6e0677d3227dd8 Mon Sep 17 00:00:00 2001 From: Reynold Xin Date: Mon, 5 Jan 2015 15:19:53 -0800 Subject: [PATCH 172/320] [SPARK-5093] Set spark.network.timeout to 120s consistently. Author: Reynold Xin Closes #3903 from rxin/timeout-120 and squashes the following commits: 7c2138e [Reynold Xin] [SPARK-5093] Set spark.network.timeout to 120s consistently. --- .../org/apache/spark/network/nio/ConnectionManager.scala | 2 +- .../org/apache/spark/storage/BlockManagerMasterActor.scala | 6 +----- core/src/main/scala/org/apache/spark/util/AkkaUtils.scala | 2 +- docs/configuration.md | 6 +++--- .../java/org/apache/spark/network/util/TransportConf.java | 5 ++--- 5 files changed, 8 insertions(+), 13 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala b/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala index 98455c0968263..3340fca08014e 100644 --- a/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala +++ b/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala @@ -82,7 +82,7 @@ private[nio] class ConnectionManager( new HashedWheelTimer(Utils.namedThreadFactory("AckTimeoutMonitor")) private val ackTimeout = - conf.getInt("spark.core.connection.ack.wait.timeout", conf.getInt("spark.network.timeout", 100)) + conf.getInt("spark.core.connection.ack.wait.timeout", conf.getInt("spark.network.timeout", 120)) // Get the thread counts from the Spark Configuration. // diff --git a/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterActor.scala b/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterActor.scala index 9d77cf27882eb..64133464d8daa 100644 --- a/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterActor.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterActor.scala @@ -52,11 +52,7 @@ class BlockManagerMasterActor(val isLocal: Boolean, conf: SparkConf, listenerBus private val akkaTimeout = AkkaUtils.askTimeout(conf) - val slaveTimeout = { - val defaultMs = math.max(conf.getInt("spark.executor.heartbeatInterval", 10000) * 3, 45000) - val networkTimeout = conf.getInt("spark.network.timeout", defaultMs / 1000) - conf.getLong("spark.storage.blockManagerSlaveTimeoutMs", networkTimeout * 1000) - } + val slaveTimeout = conf.getLong("spark.storage.blockManagerSlaveTimeoutMs", 120 * 1000) val checkTimeoutInterval = conf.getLong("spark.storage.blockManagerTimeoutIntervalMs", 60000) diff --git a/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala b/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala index 8d86fd3e11ad7..db2531dc171f8 100644 --- a/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala +++ b/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala @@ -65,7 +65,7 @@ private[spark] object AkkaUtils extends Logging { val akkaThreads = conf.getInt("spark.akka.threads", 4) val akkaBatchSize = conf.getInt("spark.akka.batchSize", 15) - val akkaTimeout = conf.getInt("spark.akka.timeout", conf.getInt("spark.network.timeout", 100)) + val akkaTimeout = conf.getInt("spark.akka.timeout", conf.getInt("spark.network.timeout", 120)) val akkaFrameSize = maxFrameSizeBytes(conf) val akkaLogLifecycleEvents = conf.getBoolean("spark.akka.logLifecycleEvents", false) val lifecycleEvents = if (akkaLogLifecycleEvents) "on" else "off" diff --git a/docs/configuration.md b/docs/configuration.md index 7ada67fc303c6..2add48569bece 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -820,12 +820,12 @@ Apart from these, the following properties are also available, and may be useful - + diff --git a/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java b/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java index e34382da22a50..6c9178688693f 100644 --- a/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java +++ b/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java @@ -37,9 +37,8 @@ public boolean preferDirectBufs() { /** Connect timeout in milliseconds. Default 120 secs. */ public int connectionTimeoutMs() { - int timeout = - conf.getInt("spark.shuffle.io.connectionTimeout", conf.getInt("spark.network.timeout", 100)); - return timeout * 1000; + int defaultTimeout = conf.getInt("spark.network.timeout", 120); + return conf.getInt("spark.shuffle.io.connectionTimeout", defaultTimeout) * 1000; } /** Number of concurrent connections between two nodes for fetching data. */ From 04d55d8e8e4890d110ce5561b5c1ae608c34a7c9 Mon Sep 17 00:00:00 2001 From: Reynold Xin Date: Mon, 5 Jan 2015 15:34:22 -0800 Subject: [PATCH 173/320] [SPARK-5040][SQL] Support expressing unresolved attributes using $"attribute name" notation in SQL DSL. Author: Reynold Xin Closes #3862 from rxin/stringcontext-attr and squashes the following commits: 9b10f57 [Reynold Xin] Rename StrongToAttributeConversionHelper 72121af [Reynold Xin] [SPARK-5040][SQL] Support expressing unresolved attributes using $"attribute name" notation in SQL DSL. --- .../org/apache/spark/sql/catalyst/dsl/package.scala | 9 +++++++++ .../scala/org/apache/spark/sql/DslQuerySuite.scala | 12 ++++++++++++ 2 files changed, 21 insertions(+) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala index 8e39f79d2ca51..9608e15c0f302 100755 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala @@ -135,6 +135,15 @@ package object dsl { implicit def symbolToUnresolvedAttribute(s: Symbol): analysis.UnresolvedAttribute = analysis.UnresolvedAttribute(s.name) + /** Converts $"col name" into an [[analysis.UnresolvedAttribute]]. */ + implicit class StringToAttributeConversionHelper(val sc: StringContext) { + // Note that if we make ExpressionConversions an object rather than a trait, we can + // then make this a value class to avoid the small penalty of runtime instantiation. + def $(args: Any*): analysis.UnresolvedAttribute = { + analysis.UnresolvedAttribute(sc.s(args :_*)) + } + } + def sum(e: Expression) = Sum(e) def sumDistinct(e: Expression) = SumDistinct(e) def count(e: Expression) = Count(e) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala index c0b9cf5163120..ab88f3ad10d66 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala @@ -56,6 +56,18 @@ class DslQuerySuite extends QueryTest { ) } + test("convert $\"attribute name\" into unresolved attribute") { + checkAnswer( + testData.where($"key" === 1).select($"value"), + Seq(Seq("1"))) + } + + test("convert Scala Symbol 'attrname into unresolved attribute") { + checkAnswer( + testData.where('key === 1).select('value), + Seq(Seq("1"))) + } + test("select *") { checkAnswer( testData.select(Star(None)), From 451546aa6d2e61e43b0c0f0669f18cfb7489e584 Mon Sep 17 00:00:00 2001 From: Kostas Sakellis Date: Mon, 5 Jan 2015 23:26:33 -0800 Subject: [PATCH 174/320] SPARK-4843 [YARN] Squash ExecutorRunnableUtil and ExecutorRunnable ExecutorRunnableUtil is a parent of ExecutorRunnable because of the yarn-alpha and yarn-stable split. Now that yarn-alpha is gone, this commit squashes the unnecessary hierarchy. The methods from ExecutorRunnableUtil are added as private. Author: Kostas Sakellis Closes #3696 from ksakellis/kostas-spark-4843 and squashes the following commits: 486716f [Kostas Sakellis] Moved prepareEnvironment call to after yarnConf declaration 470e22e [Kostas Sakellis] Fixed indentation and renamed sparkConf variable 9b1b1c9 [Kostas Sakellis] SPARK-4843 [YARN] Squash ExecutorRunnableUtil and ExecutorRunnable --- .../spark/deploy/yarn/ExecutorRunnable.scala | 182 +++++++++++++++- .../deploy/yarn/ExecutorRunnableUtil.scala | 203 ------------------ 2 files changed, 172 insertions(+), 213 deletions(-) delete mode 100644 yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorRunnableUtil.scala diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorRunnable.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorRunnable.scala index fdd3c2300fa78..6d9198c122e97 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorRunnable.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorRunnable.scala @@ -17,32 +17,33 @@ package org.apache.spark.deploy.yarn +import java.net.URI import java.nio.ByteBuffer -import java.security.PrivilegedExceptionAction + +import org.apache.hadoop.fs.Path +import org.apache.hadoop.yarn.api.ApplicationConstants.Environment +import org.apache.spark.util.Utils import scala.collection.JavaConversions._ +import scala.collection.mutable.{HashMap, ListBuffer} import org.apache.hadoop.conf.Configuration import org.apache.hadoop.io.DataOutputBuffer -import org.apache.hadoop.net.NetUtils import org.apache.hadoop.security.UserGroupInformation import org.apache.hadoop.yarn.api._ import org.apache.hadoop.yarn.api.records._ -import org.apache.hadoop.yarn.api.records.impl.pb.ProtoUtils -import org.apache.hadoop.yarn.api.protocolrecords._ import org.apache.hadoop.yarn.client.api.NMClient import org.apache.hadoop.yarn.conf.YarnConfiguration import org.apache.hadoop.yarn.ipc.YarnRPC -import org.apache.hadoop.yarn.util.{Apps, ConverterUtils, Records} +import org.apache.hadoop.yarn.util.{ConverterUtils, Records} import org.apache.spark.{SecurityManager, SparkConf, Logging} import org.apache.spark.network.util.JavaUtils - class ExecutorRunnable( container: Container, conf: Configuration, - spConf: SparkConf, + sparkConf: SparkConf, masterAddress: String, slaveId: String, hostname: String, @@ -50,13 +51,13 @@ class ExecutorRunnable( executorCores: Int, appId: String, securityMgr: SecurityManager) - extends Runnable with ExecutorRunnableUtil with Logging { + extends Runnable with Logging { var rpc: YarnRPC = YarnRPC.create(conf) var nmClient: NMClient = _ - val sparkConf = spConf val yarnConf: YarnConfiguration = new YarnConfiguration(conf) - + lazy val env = prepareEnvironment + def run = { logInfo("Starting Executor Container") nmClient = NMClient.createNMClient() @@ -110,4 +111,165 @@ class ExecutorRunnable( nmClient.startContainer(container, ctx) } + private def prepareCommand( + masterAddress: String, + slaveId: String, + hostname: String, + executorMemory: Int, + executorCores: Int, + appId: String, + localResources: HashMap[String, LocalResource]): List[String] = { + // Extra options for the JVM + val javaOpts = ListBuffer[String]() + + // Set the environment variable through a command prefix + // to append to the existing value of the variable + var prefixEnv: Option[String] = None + + // Set the JVM memory + val executorMemoryString = executorMemory + "m" + javaOpts += "-Xms" + executorMemoryString + " -Xmx" + executorMemoryString + " " + + // Set extra Java options for the executor, if defined + sys.props.get("spark.executor.extraJavaOptions").foreach { opts => + javaOpts += opts + } + sys.env.get("SPARK_JAVA_OPTS").foreach { opts => + javaOpts += opts + } + sys.props.get("spark.executor.extraLibraryPath").foreach { p => + prefixEnv = Some(Utils.libraryPathEnvPrefix(Seq(p))) + } + + javaOpts += "-Djava.io.tmpdir=" + + new Path(Environment.PWD.$(), YarnConfiguration.DEFAULT_CONTAINER_TEMP_DIR) + + // Certain configs need to be passed here because they are needed before the Executor + // registers with the Scheduler and transfers the spark configs. Since the Executor backend + // uses Akka to connect to the scheduler, the akka settings are needed as well as the + // authentication settings. + sparkConf.getAll. + filter { case (k, v) => k.startsWith("spark.auth") || k.startsWith("spark.akka") }. + foreach { case (k, v) => javaOpts += YarnSparkHadoopUtil.escapeForShell(s"-D$k=$v") } + + sparkConf.getAkkaConf. + foreach { case (k, v) => javaOpts += YarnSparkHadoopUtil.escapeForShell(s"-D$k=$v") } + + // Commenting it out for now - so that people can refer to the properties if required. Remove + // it once cpuset version is pushed out. + // The context is, default gc for server class machines end up using all cores to do gc - hence + // if there are multiple containers in same node, spark gc effects all other containers + // performance (which can also be other spark containers) + // Instead of using this, rely on cpusets by YARN to enforce spark behaves 'properly' in + // multi-tenant environments. Not sure how default java gc behaves if it is limited to subset + // of cores on a node. + /* + else { + // If no java_opts specified, default to using -XX:+CMSIncrementalMode + // It might be possible that other modes/config is being done in + // spark.executor.extraJavaOptions, so we dont want to mess with it. + // In our expts, using (default) throughput collector has severe perf ramnifications in + // multi-tennent machines + // The options are based on + // http://www.oracle.com/technetwork/java/gc-tuning-5-138395.html#0.0.0.%20When%20to%20Use + // %20the%20Concurrent%20Low%20Pause%20Collector|outline + javaOpts += " -XX:+UseConcMarkSweepGC " + javaOpts += " -XX:+CMSIncrementalMode " + javaOpts += " -XX:+CMSIncrementalPacing " + javaOpts += " -XX:CMSIncrementalDutyCycleMin=0 " + javaOpts += " -XX:CMSIncrementalDutyCycle=10 " + } + */ + + // For log4j configuration to reference + javaOpts += ("-Dspark.yarn.app.container.log.dir=" + ApplicationConstants.LOG_DIR_EXPANSION_VAR) + + val commands = prefixEnv ++ Seq(Environment.JAVA_HOME.$() + "/bin/java", + "-server", + // Kill if OOM is raised - leverage yarn's failure handling to cause rescheduling. + // Not killing the task leaves various aspects of the executor and (to some extent) the jvm in + // an inconsistent state. + // TODO: If the OOM is not recoverable by rescheduling it on different node, then do + // 'something' to fail job ... akin to blacklisting trackers in mapred ? + "-XX:OnOutOfMemoryError='kill %p'") ++ + javaOpts ++ + Seq("org.apache.spark.executor.CoarseGrainedExecutorBackend", + masterAddress.toString, + slaveId.toString, + hostname.toString, + executorCores.toString, + appId, + "1>", ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stdout", + "2>", ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stderr") + + // TODO: it would be nicer to just make sure there are no null commands here + commands.map(s => if (s == null) "null" else s).toList + } + + private def setupDistributedCache( + file: String, + rtype: LocalResourceType, + localResources: HashMap[String, LocalResource], + timestamp: String, + size: String, + vis: String): Unit = { + val uri = new URI(file) + val amJarRsrc = Records.newRecord(classOf[LocalResource]) + amJarRsrc.setType(rtype) + amJarRsrc.setVisibility(LocalResourceVisibility.valueOf(vis)) + amJarRsrc.setResource(ConverterUtils.getYarnUrlFromURI(uri)) + amJarRsrc.setTimestamp(timestamp.toLong) + amJarRsrc.setSize(size.toLong) + localResources(uri.getFragment()) = amJarRsrc + } + + private def prepareLocalResources: HashMap[String, LocalResource] = { + logInfo("Preparing Local resources") + val localResources = HashMap[String, LocalResource]() + + if (System.getenv("SPARK_YARN_CACHE_FILES") != null) { + val timeStamps = System.getenv("SPARK_YARN_CACHE_FILES_TIME_STAMPS").split(',') + val fileSizes = System.getenv("SPARK_YARN_CACHE_FILES_FILE_SIZES").split(',') + val distFiles = System.getenv("SPARK_YARN_CACHE_FILES").split(',') + val visibilities = System.getenv("SPARK_YARN_CACHE_FILES_VISIBILITIES").split(',') + for( i <- 0 to distFiles.length - 1) { + setupDistributedCache(distFiles(i), LocalResourceType.FILE, localResources, timeStamps(i), + fileSizes(i), visibilities(i)) + } + } + + if (System.getenv("SPARK_YARN_CACHE_ARCHIVES") != null) { + val timeStamps = System.getenv("SPARK_YARN_CACHE_ARCHIVES_TIME_STAMPS").split(',') + val fileSizes = System.getenv("SPARK_YARN_CACHE_ARCHIVES_FILE_SIZES").split(',') + val distArchives = System.getenv("SPARK_YARN_CACHE_ARCHIVES").split(',') + val visibilities = System.getenv("SPARK_YARN_CACHE_ARCHIVES_VISIBILITIES").split(',') + for( i <- 0 to distArchives.length - 1) { + setupDistributedCache(distArchives(i), LocalResourceType.ARCHIVE, localResources, + timeStamps(i), fileSizes(i), visibilities(i)) + } + } + + logInfo("Prepared Local resources " + localResources) + localResources + } + + private def prepareEnvironment: HashMap[String, String] = { + val env = new HashMap[String, String]() + val extraCp = sparkConf.getOption("spark.executor.extraClassPath") + ClientBase.populateClasspath(null, yarnConf, sparkConf, env, extraCp) + + sparkConf.getExecutorEnv.foreach { case (key, value) => + // This assumes each executor environment variable set here is a path + // This is kept for backward compatibility and consistency with hadoop + YarnSparkHadoopUtil.addPathToEnvironment(env, key, value) + } + + // Keep this for backwards compatibility but users should move to the config + sys.env.get("SPARK_YARN_USER_ENV").foreach { userEnvs => + YarnSparkHadoopUtil.setEnvFromInputString(env, userEnvs) + } + + System.getenv().filterKeys(_.startsWith("SPARK")).foreach { case (k, v) => env(k) = v } + env + } } diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorRunnableUtil.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorRunnableUtil.scala deleted file mode 100644 index 22d73ecf6d010..0000000000000 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorRunnableUtil.scala +++ /dev/null @@ -1,203 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.deploy.yarn - -import java.net.URI - -import scala.collection.JavaConversions._ -import scala.collection.mutable.{HashMap, ListBuffer} - -import org.apache.hadoop.fs.Path -import org.apache.hadoop.yarn.api._ -import org.apache.hadoop.yarn.api.ApplicationConstants.Environment -import org.apache.hadoop.yarn.api.records._ -import org.apache.hadoop.yarn.conf.YarnConfiguration -import org.apache.hadoop.yarn.util.{ConverterUtils, Records} - -import org.apache.spark.{Logging, SparkConf} -import org.apache.spark.util.Utils - -trait ExecutorRunnableUtil extends Logging { - - val yarnConf: YarnConfiguration - val sparkConf: SparkConf - lazy val env = prepareEnvironment - - def prepareCommand( - masterAddress: String, - slaveId: String, - hostname: String, - executorMemory: Int, - executorCores: Int, - appId: String, - localResources: HashMap[String, LocalResource]): List[String] = { - // Extra options for the JVM - val javaOpts = ListBuffer[String]() - - // Set the environment variable through a command prefix - // to append to the existing value of the variable - var prefixEnv: Option[String] = None - - // Set the JVM memory - val executorMemoryString = executorMemory + "m" - javaOpts += "-Xms" + executorMemoryString + " -Xmx" + executorMemoryString + " " - - // Set extra Java options for the executor, if defined - sys.props.get("spark.executor.extraJavaOptions").foreach { opts => - javaOpts += opts - } - sys.env.get("SPARK_JAVA_OPTS").foreach { opts => - javaOpts += opts - } - sys.props.get("spark.executor.extraLibraryPath").foreach { p => - prefixEnv = Some(Utils.libraryPathEnvPrefix(Seq(p))) - } - - javaOpts += "-Djava.io.tmpdir=" + - new Path(Environment.PWD.$(), YarnConfiguration.DEFAULT_CONTAINER_TEMP_DIR) - - // Certain configs need to be passed here because they are needed before the Executor - // registers with the Scheduler and transfers the spark configs. Since the Executor backend - // uses Akka to connect to the scheduler, the akka settings are needed as well as the - // authentication settings. - sparkConf.getAll. - filter { case (k, v) => k.startsWith("spark.auth") || k.startsWith("spark.akka") }. - foreach { case (k, v) => javaOpts += YarnSparkHadoopUtil.escapeForShell(s"-D$k=$v") } - - sparkConf.getAkkaConf. - foreach { case (k, v) => javaOpts += YarnSparkHadoopUtil.escapeForShell(s"-D$k=$v") } - - // Commenting it out for now - so that people can refer to the properties if required. Remove - // it once cpuset version is pushed out. - // The context is, default gc for server class machines end up using all cores to do gc - hence - // if there are multiple containers in same node, spark gc effects all other containers - // performance (which can also be other spark containers) - // Instead of using this, rely on cpusets by YARN to enforce spark behaves 'properly' in - // multi-tenant environments. Not sure how default java gc behaves if it is limited to subset - // of cores on a node. - /* - else { - // If no java_opts specified, default to using -XX:+CMSIncrementalMode - // It might be possible that other modes/config is being done in - // spark.executor.extraJavaOptions, so we dont want to mess with it. - // In our expts, using (default) throughput collector has severe perf ramnifications in - // multi-tennent machines - // The options are based on - // http://www.oracle.com/technetwork/java/gc-tuning-5-138395.html#0.0.0.%20When%20to%20Use - // %20the%20Concurrent%20Low%20Pause%20Collector|outline - javaOpts += " -XX:+UseConcMarkSweepGC " - javaOpts += " -XX:+CMSIncrementalMode " - javaOpts += " -XX:+CMSIncrementalPacing " - javaOpts += " -XX:CMSIncrementalDutyCycleMin=0 " - javaOpts += " -XX:CMSIncrementalDutyCycle=10 " - } - */ - - // For log4j configuration to reference - javaOpts += ("-Dspark.yarn.app.container.log.dir=" + ApplicationConstants.LOG_DIR_EXPANSION_VAR) - - val commands = prefixEnv ++ Seq(Environment.JAVA_HOME.$() + "/bin/java", - "-server", - // Kill if OOM is raised - leverage yarn's failure handling to cause rescheduling. - // Not killing the task leaves various aspects of the executor and (to some extent) the jvm in - // an inconsistent state. - // TODO: If the OOM is not recoverable by rescheduling it on different node, then do - // 'something' to fail job ... akin to blacklisting trackers in mapred ? - "-XX:OnOutOfMemoryError='kill %p'") ++ - javaOpts ++ - Seq("org.apache.spark.executor.CoarseGrainedExecutorBackend", - masterAddress.toString, - slaveId.toString, - hostname.toString, - executorCores.toString, - appId, - "1>", ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stdout", - "2>", ApplicationConstants.LOG_DIR_EXPANSION_VAR + "/stderr") - - // TODO: it would be nicer to just make sure there are no null commands here - commands.map(s => if (s == null) "null" else s).toList - } - - private def setupDistributedCache( - file: String, - rtype: LocalResourceType, - localResources: HashMap[String, LocalResource], - timestamp: String, - size: String, - vis: String): Unit = { - val uri = new URI(file) - val amJarRsrc = Records.newRecord(classOf[LocalResource]) - amJarRsrc.setType(rtype) - amJarRsrc.setVisibility(LocalResourceVisibility.valueOf(vis)) - amJarRsrc.setResource(ConverterUtils.getYarnUrlFromURI(uri)) - amJarRsrc.setTimestamp(timestamp.toLong) - amJarRsrc.setSize(size.toLong) - localResources(uri.getFragment()) = amJarRsrc - } - - def prepareLocalResources: HashMap[String, LocalResource] = { - logInfo("Preparing Local resources") - val localResources = HashMap[String, LocalResource]() - - if (System.getenv("SPARK_YARN_CACHE_FILES") != null) { - val timeStamps = System.getenv("SPARK_YARN_CACHE_FILES_TIME_STAMPS").split(',') - val fileSizes = System.getenv("SPARK_YARN_CACHE_FILES_FILE_SIZES").split(',') - val distFiles = System.getenv("SPARK_YARN_CACHE_FILES").split(',') - val visibilities = System.getenv("SPARK_YARN_CACHE_FILES_VISIBILITIES").split(',') - for( i <- 0 to distFiles.length - 1) { - setupDistributedCache(distFiles(i), LocalResourceType.FILE, localResources, timeStamps(i), - fileSizes(i), visibilities(i)) - } - } - - if (System.getenv("SPARK_YARN_CACHE_ARCHIVES") != null) { - val timeStamps = System.getenv("SPARK_YARN_CACHE_ARCHIVES_TIME_STAMPS").split(',') - val fileSizes = System.getenv("SPARK_YARN_CACHE_ARCHIVES_FILE_SIZES").split(',') - val distArchives = System.getenv("SPARK_YARN_CACHE_ARCHIVES").split(',') - val visibilities = System.getenv("SPARK_YARN_CACHE_ARCHIVES_VISIBILITIES").split(',') - for( i <- 0 to distArchives.length - 1) { - setupDistributedCache(distArchives(i), LocalResourceType.ARCHIVE, localResources, - timeStamps(i), fileSizes(i), visibilities(i)) - } - } - - logInfo("Prepared Local resources " + localResources) - localResources - } - - def prepareEnvironment: HashMap[String, String] = { - val env = new HashMap[String, String]() - val extraCp = sparkConf.getOption("spark.executor.extraClassPath") - ClientBase.populateClasspath(null, yarnConf, sparkConf, env, extraCp) - - sparkConf.getExecutorEnv.foreach { case (key, value) => - // This assumes each executor environment variable set here is a path - // This is kept for backward compatibility and consistency with hadoop - YarnSparkHadoopUtil.addPathToEnvironment(env, key, value) - } - - // Keep this for backwards compatibility but users should move to the config - sys.env.get("SPARK_YARN_USER_ENV").foreach { userEnvs => - YarnSparkHadoopUtil.setEnvFromInputString(env, userEnvs) - } - - System.getenv().filterKeys(_.startsWith("SPARK")).foreach { case (k, v) => env(k) = v } - env - } - -} From a6394bc2c094c6c662237236c2effa2dabe67910 Mon Sep 17 00:00:00 2001 From: Josh Rosen Date: Tue, 6 Jan 2015 00:31:19 -0800 Subject: [PATCH 175/320] [SPARK-1600] Refactor FileInputStream tests to remove Thread.sleep() calls and SystemClock usage This patch refactors Spark Streaming's FileInputStream tests to remove uses of Thread.sleep() and SystemClock, which should hopefully resolve some longstanding flakiness in these tests (see SPARK-1600). Key changes: - Modify FileInputDStream to use the scheduler's Clock instead of System.currentTimeMillis(); this allows it to be tested using ManualClock. - Fix a synchronization issue in ManualClock's `currentTime` method. - Add a StreamingTestWaiter class which allows callers to block until a certain number of batches have finished. - Change the FileInputStream tests so that files' modification times are manually set based off of ManualClock; this eliminates many Thread.sleep calls. - Update these tests to use the withStreamingContext fixture. Author: Josh Rosen Closes #3801 from JoshRosen/SPARK-1600 and squashes the following commits: e4494f4 [Josh Rosen] Address a potential race when setting file modification times 8340bd0 [Josh Rosen] Use set comparisons for output. 0b9c252 [Josh Rosen] Fix some ManualClock usage problems. 1cc689f [Josh Rosen] ConcurrentHashMap -> SynchronizedMap db26c3a [Josh Rosen] Use standard timeout in ScalaTest `eventually` blocks. 3939432 [Josh Rosen] Rename StreamingTestWaiter to BatchCounter 0b9c3a1 [Josh Rosen] Wait for checkpoint to complete 863d71a [Josh Rosen] Remove Thread.sleep that was used to make task run slowly b4442c3 [Josh Rosen] batchTimeToSelectedFiles should be thread-safe 15b48ee [Josh Rosen] Replace several TestWaiter methods w/ ScalaTest eventually. fffc51c [Josh Rosen] Revert "Remove last remaining sleep() call" dbb8247 [Josh Rosen] Remove last remaining sleep() call 566a63f [Josh Rosen] Fix log message and comment typos da32f3f [Josh Rosen] Fix log message and comment typos 3689214 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-1600 c8f06b1 [Josh Rosen] Remove Thread.sleep calls in FileInputStream CheckpointSuite test. d4f2d87 [Josh Rosen] Refactor file input stream tests to not rely on SystemClock. dda1403 [Josh Rosen] Add StreamingTestWaiter class. 3c3efc3 [Josh Rosen] Synchronize `currentTime` in ManualClock a95ddc4 [Josh Rosen] Modify FileInputDStream to use Clock class. --- .../streaming/dstream/FileInputDStream.scala | 16 +- .../apache/spark/streaming/util/Clock.scala | 6 +- .../streaming/BasicOperationsSuite.scala | 2 +- .../spark/streaming/CheckpointSuite.scala | 248 +++++++++++------- .../spark/streaming/InputStreamsSuite.scala | 69 +++-- .../spark/streaming/TestSuiteBase.scala | 46 +++- 6 files changed, 251 insertions(+), 136 deletions(-) diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/FileInputDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/FileInputDStream.scala index 5f13fdc5579ed..e7c5639a63499 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/FileInputDStream.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/FileInputDStream.scala @@ -18,6 +18,7 @@ package org.apache.spark.streaming.dstream import java.io.{IOException, ObjectInputStream} +import java.util.concurrent.ConcurrentHashMap import scala.collection.mutable import scala.reflect.ClassTag @@ -74,12 +75,15 @@ class FileInputDStream[K: ClassTag, V: ClassTag, F <: NewInputFormat[K,V] : Clas newFilesOnly: Boolean = true) extends InputDStream[(K, V)](ssc_) { + // This is a def so that it works during checkpoint recovery: + private def clock = ssc.scheduler.clock + // Data to be saved as part of the streaming checkpoints protected[streaming] override val checkpointData = new FileInputDStreamCheckpointData // Initial ignore threshold based on which old, existing files in the directory (at the time of // starting the streaming application) will be ignored or considered - private val initialModTimeIgnoreThreshold = if (newFilesOnly) System.currentTimeMillis() else 0L + private val initialModTimeIgnoreThreshold = if (newFilesOnly) clock.currentTime() else 0L /* * Make sure that the information of files selected in the last few batches are remembered. @@ -91,8 +95,9 @@ class FileInputDStream[K: ClassTag, V: ClassTag, F <: NewInputFormat[K,V] : Clas remember(durationToRemember) // Map of batch-time to selected file info for the remembered batches + // This is a concurrent map because it's also accessed in unit tests @transient private[streaming] var batchTimeToSelectedFiles = - new mutable.HashMap[Time, Array[String]] + new mutable.HashMap[Time, Array[String]] with mutable.SynchronizedMap[Time, Array[String]] // Set of files that were selected in the remembered batches @transient private var recentlySelectedFiles = new mutable.HashSet[String]() @@ -151,7 +156,7 @@ class FileInputDStream[K: ClassTag, V: ClassTag, F <: NewInputFormat[K,V] : Clas */ private def findNewFiles(currentTime: Long): Array[String] = { try { - lastNewFileFindingTime = System.currentTimeMillis + lastNewFileFindingTime = clock.currentTime() // Calculate ignore threshold val modTimeIgnoreThreshold = math.max( @@ -164,7 +169,7 @@ class FileInputDStream[K: ClassTag, V: ClassTag, F <: NewInputFormat[K,V] : Clas def accept(path: Path): Boolean = isNewFile(path, currentTime, modTimeIgnoreThreshold) } val newFiles = fs.listStatus(directoryPath, filter).map(_.getPath.toString) - val timeTaken = System.currentTimeMillis - lastNewFileFindingTime + val timeTaken = clock.currentTime() - lastNewFileFindingTime logInfo("Finding new files took " + timeTaken + " ms") logDebug("# cached file times = " + fileToModTime.size) if (timeTaken > slideDuration.milliseconds) { @@ -267,7 +272,8 @@ class FileInputDStream[K: ClassTag, V: ClassTag, F <: NewInputFormat[K,V] : Clas logDebug(this.getClass().getSimpleName + ".readObject used") ois.defaultReadObject() generatedRDDs = new mutable.HashMap[Time, RDD[(K,V)]] () - batchTimeToSelectedFiles = new mutable.HashMap[Time, Array[String]]() + batchTimeToSelectedFiles = + new mutable.HashMap[Time, Array[String]] with mutable.SynchronizedMap[Time, Array[String]] recentlySelectedFiles = new mutable.HashSet[String]() fileToModTime = new TimeStampedHashMap[String, Long](true) } diff --git a/streaming/src/main/scala/org/apache/spark/streaming/util/Clock.scala b/streaming/src/main/scala/org/apache/spark/streaming/util/Clock.scala index 7cd867ce34b87..d6d96d7ba00fd 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/util/Clock.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/util/Clock.scala @@ -59,9 +59,11 @@ class SystemClock() extends Clock { private[streaming] class ManualClock() extends Clock { - var time = 0L + private var time = 0L - def currentTime() = time + def currentTime() = this.synchronized { + time + } def setTime(timeToSet: Long) = { this.synchronized { diff --git a/streaming/src/test/scala/org/apache/spark/streaming/BasicOperationsSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/BasicOperationsSuite.scala index 199f5e7161124..e8f4a7779ec21 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/BasicOperationsSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/BasicOperationsSuite.scala @@ -638,7 +638,7 @@ class BasicOperationsSuite extends TestSuiteBase { if (rememberDuration != null) ssc.remember(rememberDuration) val output = runStreams[(Int, Int)](ssc, cleanupTestInput.size, numExpectedOutput) val clock = ssc.scheduler.clock.asInstanceOf[ManualClock] - assert(clock.time === Seconds(10).milliseconds) + assert(clock.currentTime() === Seconds(10).milliseconds) assert(output.size === numExpectedOutput) operatedStream } diff --git a/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala index 5d232c6ade7a9..8f8bc61437ba5 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala @@ -18,17 +18,18 @@ package org.apache.spark.streaming import java.io.File -import java.nio.charset.Charset -import scala.collection.mutable.ArrayBuffer +import scala.collection.mutable.{SynchronizedBuffer, ArrayBuffer} import scala.reflect.ClassTag +import com.google.common.base.Charsets import com.google.common.io.Files import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.{FileSystem, Path} import org.apache.hadoop.io.{IntWritable, Text} import org.apache.hadoop.mapred.TextOutputFormat import org.apache.hadoop.mapreduce.lib.output.{TextOutputFormat => NewTextOutputFormat} +import org.scalatest.concurrent.Eventually._ import org.apache.spark.streaming.dstream.{DStream, FileInputDStream} import org.apache.spark.streaming.util.ManualClock @@ -45,8 +46,6 @@ class CheckpointSuite extends TestSuiteBase { override def batchDuration = Milliseconds(500) - override def actuallyWait = true // to allow checkpoints to be written - override def beforeFunction() { super.beforeFunction() Utils.deleteRecursively(new File(checkpointDir)) @@ -143,7 +142,6 @@ class CheckpointSuite extends TestSuiteBase { ssc.start() advanceTimeWithRealDelay(ssc, 4) ssc.stop() - System.clearProperty("spark.streaming.manualClock.jump") ssc = null } @@ -312,109 +310,161 @@ class CheckpointSuite extends TestSuiteBase { testCheckpointedOperation(input, operation, output, 7) } - // This tests whether file input stream remembers what files were seen before // the master failure and uses them again to process a large window operation. // It also tests whether batches, whose processing was incomplete due to the // failure, are re-processed or not. test("recovery with file input stream") { // Set up the streaming context and input streams + val batchDuration = Seconds(2) // Due to 1-second resolution of setLastModified() on some OS's. val testDir = Utils.createTempDir() - var ssc = new StreamingContext(master, framework, Seconds(1)) - ssc.checkpoint(checkpointDir) - val fileStream = ssc.textFileStream(testDir.toString) - // Making value 3 take large time to process, to ensure that the master - // shuts down in the middle of processing the 3rd batch - val mappedStream = fileStream.map(s => { - val i = s.toInt - if (i == 3) Thread.sleep(2000) - i - }) - - // Reducing over a large window to ensure that recovery from master failure - // requires reprocessing of all the files seen before the failure - val reducedStream = mappedStream.reduceByWindow(_ + _, Seconds(30), Seconds(1)) - val outputBuffer = new ArrayBuffer[Seq[Int]] - var outputStream = new TestOutputStream(reducedStream, outputBuffer) - outputStream.register() - ssc.start() - - // Create files and advance manual clock to process them - // var clock = ssc.scheduler.clock.asInstanceOf[ManualClock] - Thread.sleep(1000) - for (i <- Seq(1, 2, 3)) { - Files.write(i + "\n", new File(testDir, i.toString), Charset.forName("UTF-8")) - // wait to make sure that the file is written such that it gets shown in the file listings - Thread.sleep(1000) + val outputBuffer = new ArrayBuffer[Seq[Int]] with SynchronizedBuffer[Seq[Int]] + + /** + * Writes a file named `i` (which contains the number `i`) to the test directory and sets its + * modification time to `clock`'s current time. + */ + def writeFile(i: Int, clock: ManualClock): Unit = { + val file = new File(testDir, i.toString) + Files.write(i + "\n", file, Charsets.UTF_8) + assert(file.setLastModified(clock.currentTime())) + // Check that the file's modification date is actually the value we wrote, since rounding or + // truncation will break the test: + assert(file.lastModified() === clock.currentTime()) } - logInfo("Output = " + outputStream.output.mkString(",")) - assert(outputStream.output.size > 0, "No files processed before restart") - ssc.stop() - // Verify whether files created have been recorded correctly or not - var fileInputDStream = ssc.graph.getInputStreams().head.asInstanceOf[FileInputDStream[_, _, _]] - def recordedFiles = fileInputDStream.batchTimeToSelectedFiles.values.flatten - assert(!recordedFiles.filter(_.endsWith("1")).isEmpty) - assert(!recordedFiles.filter(_.endsWith("2")).isEmpty) - assert(!recordedFiles.filter(_.endsWith("3")).isEmpty) - - // Create files while the master is down - for (i <- Seq(4, 5, 6)) { - Files.write(i + "\n", new File(testDir, i.toString), Charset.forName("UTF-8")) - Thread.sleep(1000) + /** + * Returns ids that identify which files which have been recorded by the file input stream. + */ + def recordedFiles(ssc: StreamingContext): Seq[Int] = { + val fileInputDStream = + ssc.graph.getInputStreams().head.asInstanceOf[FileInputDStream[_, _, _]] + val filenames = fileInputDStream.batchTimeToSelectedFiles.values.flatten + filenames.map(_.split(File.separator).last.toInt).toSeq.sorted } - // Recover context from checkpoint file and verify whether the files that were - // recorded before failure were saved and successfully recovered - logInfo("*********** RESTARTING ************") - ssc = new StreamingContext(checkpointDir) - fileInputDStream = ssc.graph.getInputStreams().head.asInstanceOf[FileInputDStream[_, _, _]] - assert(!recordedFiles.filter(_.endsWith("1")).isEmpty) - assert(!recordedFiles.filter(_.endsWith("2")).isEmpty) - assert(!recordedFiles.filter(_.endsWith("3")).isEmpty) + try { + // This is a var because it's re-assigned when we restart from a checkpoint + var clock: ManualClock = null + withStreamingContext(new StreamingContext(conf, batchDuration)) { ssc => + ssc.checkpoint(checkpointDir) + clock = ssc.scheduler.clock.asInstanceOf[ManualClock] + val batchCounter = new BatchCounter(ssc) + val fileStream = ssc.textFileStream(testDir.toString) + // Make value 3 take a large time to process, to ensure that the driver + // shuts down in the middle of processing the 3rd batch + CheckpointSuite.batchThreeShouldBlockIndefinitely = true + val mappedStream = fileStream.map(s => { + val i = s.toInt + if (i == 3) { + while (CheckpointSuite.batchThreeShouldBlockIndefinitely) { + Thread.sleep(Long.MaxValue) + } + } + i + }) + + // Reducing over a large window to ensure that recovery from driver failure + // requires reprocessing of all the files seen before the failure + val reducedStream = mappedStream.reduceByWindow(_ + _, batchDuration * 30, batchDuration) + val outputStream = new TestOutputStream(reducedStream, outputBuffer) + outputStream.register() + ssc.start() + + // Advance half a batch so that the first file is created after the StreamingContext starts + clock.addToTime(batchDuration.milliseconds / 2) + // Create files and advance manual clock to process them + for (i <- Seq(1, 2, 3)) { + writeFile(i, clock) + // Advance the clock after creating the file to avoid a race when + // setting its modification time + clock.addToTime(batchDuration.milliseconds) + if (i != 3) { + // Since we want to shut down while the 3rd batch is processing + eventually(eventuallyTimeout) { + assert(batchCounter.getNumCompletedBatches === i) + } + } + } + clock.addToTime(batchDuration.milliseconds) + eventually(eventuallyTimeout) { + // Wait until all files have been recorded and all batches have started + assert(recordedFiles(ssc) === Seq(1, 2, 3) && batchCounter.getNumStartedBatches === 3) + } + // Wait for a checkpoint to be written + val fs = new Path(checkpointDir).getFileSystem(ssc.sc.hadoopConfiguration) + eventually(eventuallyTimeout) { + assert(Checkpoint.getCheckpointFiles(checkpointDir, fs).size === 6) + } + ssc.stop() + // Check that we shut down while the third batch was being processed + assert(batchCounter.getNumCompletedBatches === 2) + assert(outputStream.output.flatten === Seq(1, 3)) + } - // Restart stream computation - ssc.start() - for (i <- Seq(7, 8, 9)) { - Files.write(i + "\n", new File(testDir, i.toString), Charset.forName("UTF-8")) - Thread.sleep(1000) - } - Thread.sleep(1000) - logInfo("Output = " + outputStream.output.mkString("[", ", ", "]")) - assert(outputStream.output.size > 0, "No files processed after restart") - ssc.stop() + // The original StreamingContext has now been stopped. + CheckpointSuite.batchThreeShouldBlockIndefinitely = false - // Verify whether files created while the driver was down have been recorded or not - assert(!recordedFiles.filter(_.endsWith("4")).isEmpty) - assert(!recordedFiles.filter(_.endsWith("5")).isEmpty) - assert(!recordedFiles.filter(_.endsWith("6")).isEmpty) - - // Verify whether new files created after recover have been recorded or not - assert(!recordedFiles.filter(_.endsWith("7")).isEmpty) - assert(!recordedFiles.filter(_.endsWith("8")).isEmpty) - assert(!recordedFiles.filter(_.endsWith("9")).isEmpty) - - // Append the new output to the old buffer - outputStream = ssc.graph.getOutputStreams().head.asInstanceOf[TestOutputStream[Int]] - outputBuffer ++= outputStream.output - - val expectedOutput = Seq(1, 3, 6, 10, 15, 21, 28, 36, 45) - logInfo("--------------------------------") - logInfo("output, size = " + outputBuffer.size) - outputBuffer.foreach(x => logInfo("[" + x.mkString(",") + "]")) - logInfo("expected output, size = " + expectedOutput.size) - expectedOutput.foreach(x => logInfo("[" + x + "]")) - logInfo("--------------------------------") - - // Verify whether all the elements received are as expected - val output = outputBuffer.flatMap(x => x) - assert(output.contains(6)) // To ensure that the 3rd input (i.e., 3) was processed - output.foreach(o => // To ensure all the inputs are correctly added cumulatively - assert(expectedOutput.contains(o), "Expected value " + o + " not found") - ) - // To ensure that all the inputs were received correctly - assert(expectedOutput.last === output.last) - Utils.deleteRecursively(testDir) + // Create files while the streaming driver is down + for (i <- Seq(4, 5, 6)) { + writeFile(i, clock) + // Advance the clock after creating the file to avoid a race when + // setting its modification time + clock.addToTime(batchDuration.milliseconds) + } + + // Recover context from checkpoint file and verify whether the files that were + // recorded before failure were saved and successfully recovered + logInfo("*********** RESTARTING ************") + withStreamingContext(new StreamingContext(checkpointDir)) { ssc => + // So that the restarted StreamingContext's clock has gone forward in time since failure + ssc.conf.set("spark.streaming.manualClock.jump", (batchDuration * 3).milliseconds.toString) + val oldClockTime = clock.currentTime() + clock = ssc.scheduler.clock.asInstanceOf[ManualClock] + val batchCounter = new BatchCounter(ssc) + val outputStream = ssc.graph.getOutputStreams().head.asInstanceOf[TestOutputStream[Int]] + // Check that we remember files that were recorded before the restart + assert(recordedFiles(ssc) === Seq(1, 2, 3)) + + // Restart stream computation + ssc.start() + // Verify that the clock has traveled forward to the expected time + eventually(eventuallyTimeout) { + clock.currentTime() === oldClockTime + } + // Wait for pre-failure batch to be recomputed (3 while SSC was down plus last batch) + val numBatchesAfterRestart = 4 + eventually(eventuallyTimeout) { + assert(batchCounter.getNumCompletedBatches === numBatchesAfterRestart) + } + for ((i, index) <- Seq(7, 8, 9).zipWithIndex) { + writeFile(i, clock) + // Advance the clock after creating the file to avoid a race when + // setting its modification time + clock.addToTime(batchDuration.milliseconds) + eventually(eventuallyTimeout) { + assert(batchCounter.getNumCompletedBatches === index + numBatchesAfterRestart + 1) + } + } + clock.addToTime(batchDuration.milliseconds) + logInfo("Output after restart = " + outputStream.output.mkString("[", ", ", "]")) + assert(outputStream.output.size > 0, "No files processed after restart") + ssc.stop() + + // Verify whether files created while the driver was down (4, 5, 6) and files created after + // recovery (7, 8, 9) have been recorded + assert(recordedFiles(ssc) === (1 to 9)) + + // Append the new output to the old buffer + outputBuffer ++= outputStream.output + + // Verify whether all the elements received are as expected + val expectedOutput = Seq(1, 3, 6, 10, 15, 21, 28, 36, 45) + assert(outputBuffer.flatten.toSet === expectedOutput.toSet) + } + } finally { + Utils.deleteRecursively(testDir) + } } @@ -471,12 +521,12 @@ class CheckpointSuite extends TestSuiteBase { */ def advanceTimeWithRealDelay[V: ClassTag](ssc: StreamingContext, numBatches: Long): Seq[Seq[V]] = { val clock = ssc.scheduler.clock.asInstanceOf[ManualClock] - logInfo("Manual clock before advancing = " + clock.time) + logInfo("Manual clock before advancing = " + clock.currentTime()) for (i <- 1 to numBatches.toInt) { clock.addToTime(batchDuration.milliseconds) Thread.sleep(batchDuration.milliseconds) } - logInfo("Manual clock after advancing = " + clock.time) + logInfo("Manual clock after advancing = " + clock.currentTime()) Thread.sleep(batchDuration.milliseconds) val outputStream = ssc.graph.getOutputStreams.filter { dstream => @@ -485,3 +535,7 @@ class CheckpointSuite extends TestSuiteBase { outputStream.output.map(_.flatten) } } + +private object CheckpointSuite extends Serializable { + var batchThreeShouldBlockIndefinitely: Boolean = true +} \ No newline at end of file diff --git a/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala index 307052a4a9cbb..bddf51e130422 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala @@ -28,7 +28,6 @@ import java.util.concurrent.{Executors, TimeUnit, ArrayBlockingQueue} import java.util.concurrent.atomic.AtomicInteger import scala.collection.mutable.{SynchronizedBuffer, ArrayBuffer, SynchronizedQueue} -import scala.concurrent.duration._ import scala.language.postfixOps import com.google.common.io.Files @@ -234,45 +233,57 @@ class InputStreamsSuite extends TestSuiteBase with BeforeAndAfter { } def testFileStream(newFilesOnly: Boolean) { - var ssc: StreamingContext = null val testDir: File = null try { + val batchDuration = Seconds(2) val testDir = Utils.createTempDir() + // Create a file that exists before the StreamingContext is created: val existingFile = new File(testDir, "0") Files.write("0\n", existingFile, Charset.forName("UTF-8")) + assert(existingFile.setLastModified(10000) && existingFile.lastModified === 10000) - Thread.sleep(1000) // Set up the streaming context and input streams - val newConf = conf.clone.set( - "spark.streaming.clock", "org.apache.spark.streaming.util.SystemClock") - ssc = new StreamingContext(newConf, batchDuration) - val fileStream = ssc.fileStream[LongWritable, Text, TextInputFormat]( - testDir.toString, (x: Path) => true, newFilesOnly = newFilesOnly).map(_._2.toString) - val outputBuffer = new ArrayBuffer[Seq[String]] with SynchronizedBuffer[Seq[String]] - val outputStream = new TestOutputStream(fileStream, outputBuffer) - outputStream.register() - ssc.start() - - // Create files in the directory - val input = Seq(1, 2, 3, 4, 5) - input.foreach { i => - Thread.sleep(batchDuration.milliseconds) - val file = new File(testDir, i.toString) - Files.write(i + "\n", file, Charset.forName("UTF-8")) - logInfo("Created file " + file) - } + withStreamingContext(new StreamingContext(conf, batchDuration)) { ssc => + val clock = ssc.scheduler.clock.asInstanceOf[ManualClock] + // This `setTime` call ensures that the clock is past the creation time of `existingFile` + clock.setTime(existingFile.lastModified + batchDuration.milliseconds) + val batchCounter = new BatchCounter(ssc) + val fileStream = ssc.fileStream[LongWritable, Text, TextInputFormat]( + testDir.toString, (x: Path) => true, newFilesOnly = newFilesOnly).map(_._2.toString) + val outputBuffer = new ArrayBuffer[Seq[String]] with SynchronizedBuffer[Seq[String]] + val outputStream = new TestOutputStream(fileStream, outputBuffer) + outputStream.register() + ssc.start() + + // Advance the clock so that the files are created after StreamingContext starts, but + // not enough to trigger a batch + clock.addToTime(batchDuration.milliseconds / 2) + + // Over time, create files in the directory + val input = Seq(1, 2, 3, 4, 5) + input.foreach { i => + val file = new File(testDir, i.toString) + Files.write(i + "\n", file, Charset.forName("UTF-8")) + assert(file.setLastModified(clock.currentTime())) + assert(file.lastModified === clock.currentTime) + logInfo("Created file " + file) + // Advance the clock after creating the file to avoid a race when + // setting its modification time + clock.addToTime(batchDuration.milliseconds) + eventually(eventuallyTimeout) { + assert(batchCounter.getNumCompletedBatches === i) + } + } - // Verify that all the files have been read - val expectedOutput = if (newFilesOnly) { - input.map(_.toString).toSet - } else { - (Seq(0) ++ input).map(_.toString).toSet - } - eventually(timeout(maxWaitTimeMillis milliseconds), interval(100 milliseconds)) { + // Verify that all the files have been read + val expectedOutput = if (newFilesOnly) { + input.map(_.toString).toSet + } else { + (Seq(0) ++ input).map(_.toString).toSet + } assert(outputBuffer.flatten.toSet === expectedOutput) } } finally { - if (ssc != null) ssc.stop() if (testDir != null) Utils.deleteRecursively(testDir) } } diff --git a/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala b/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala index 52972f63c6c5c..7d82c3e4aadcf 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala @@ -21,11 +21,16 @@ import java.io.{ObjectInputStream, IOException} import scala.collection.mutable.ArrayBuffer import scala.collection.mutable.SynchronizedBuffer +import scala.language.implicitConversions import scala.reflect.ClassTag import org.scalatest.{BeforeAndAfter, FunSuite} +import org.scalatest.time.{Span, Seconds => ScalaTestSeconds} +import org.scalatest.concurrent.Eventually.timeout +import org.scalatest.concurrent.PatienceConfiguration import org.apache.spark.streaming.dstream.{DStream, InputDStream, ForEachDStream} +import org.apache.spark.streaming.scheduler.{StreamingListenerBatchStarted, StreamingListenerBatchCompleted, StreamingListener} import org.apache.spark.streaming.util.ManualClock import org.apache.spark.{SparkConf, Logging} import org.apache.spark.rdd.RDD @@ -103,6 +108,40 @@ class TestOutputStreamWithPartitions[T: ClassTag](parent: DStream[T], def toTestOutputStream = new TestOutputStream[T](this.parent, this.output.map(_.flatten)) } +/** + * An object that counts the number of started / completed batches. This is implemented using a + * StreamingListener. Constructing a new instance automatically registers a StreamingListener on + * the given StreamingContext. + */ +class BatchCounter(ssc: StreamingContext) { + + // All access to this state should be guarded by `BatchCounter.this.synchronized` + private var numCompletedBatches = 0 + private var numStartedBatches = 0 + + private val listener = new StreamingListener { + override def onBatchStarted(batchStarted: StreamingListenerBatchStarted): Unit = + BatchCounter.this.synchronized { + numStartedBatches += 1 + BatchCounter.this.notifyAll() + } + override def onBatchCompleted(batchCompleted: StreamingListenerBatchCompleted): Unit = + BatchCounter.this.synchronized { + numCompletedBatches += 1 + BatchCounter.this.notifyAll() + } + } + ssc.addStreamingListener(listener) + + def getNumCompletedBatches: Int = this.synchronized { + numCompletedBatches + } + + def getNumStartedBatches: Int = this.synchronized { + numStartedBatches + } +} + /** * This is the base trait for Spark Streaming testsuites. This provides basic functionality * to run user-defined set of input on user-defined stream operations, and verify the output. @@ -142,6 +181,9 @@ trait TestSuiteBase extends FunSuite with BeforeAndAfter with Logging { .setMaster(master) .setAppName(framework) + // Timeout for use in ScalaTest `eventually` blocks + val eventuallyTimeout: PatienceConfiguration.Timeout = timeout(Span(10, ScalaTestSeconds)) + // Default before function for any streaming test suite. Override this // if you want to add your stuff to "before" (i.e., don't call before { } ) def beforeFunction() { @@ -291,7 +333,7 @@ trait TestSuiteBase extends FunSuite with BeforeAndAfter with Logging { // Advance manual clock val clock = ssc.scheduler.clock.asInstanceOf[ManualClock] - logInfo("Manual clock before advancing = " + clock.time) + logInfo("Manual clock before advancing = " + clock.currentTime()) if (actuallyWait) { for (i <- 1 to numBatches) { logInfo("Actually waiting for " + batchDuration) @@ -301,7 +343,7 @@ trait TestSuiteBase extends FunSuite with BeforeAndAfter with Logging { } else { clock.addToTime(numBatches * batchDuration.milliseconds) } - logInfo("Manual clock after advancing = " + clock.time) + logInfo("Manual clock after advancing = " + clock.currentTime()) // Wait until expected number of output items have been generated val startTime = System.currentTimeMillis() From 5e3ec1110495899a298313c4aa9c6c151c1f54da Mon Sep 17 00:00:00 2001 From: kj-ki Date: Tue, 6 Jan 2015 09:49:37 -0800 Subject: [PATCH 176/320] [Minor] Fix comments for GraphX 2D partitioning strategy The sum of vertices on matrix (v0 to v11) is 12. And, I think one same block overlaps in this strategy. This is minor PR, so I didn't file in JIRA. Author: kj-ki Closes #3904 from kj-ki/fix-partitionstrategy-comments and squashes the following commits: 79829d9 [kj-ki] Fix comments for 2D partitioning. --- .../scala/org/apache/spark/graphx/PartitionStrategy.scala | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/graphx/src/main/scala/org/apache/spark/graphx/PartitionStrategy.scala b/graphx/src/main/scala/org/apache/spark/graphx/PartitionStrategy.scala index 13033fee0e6b5..7372dfbd9fe98 100644 --- a/graphx/src/main/scala/org/apache/spark/graphx/PartitionStrategy.scala +++ b/graphx/src/main/scala/org/apache/spark/graphx/PartitionStrategy.scala @@ -32,9 +32,9 @@ trait PartitionStrategy extends Serializable { object PartitionStrategy { /** * Assigns edges to partitions using a 2D partitioning of the sparse edge adjacency matrix, - * guaranteeing a `2 * sqrt(numParts)` bound on vertex replication. + * guaranteeing a `2 * sqrt(numParts) - 1` bound on vertex replication. * - * Suppose we have a graph with 11 vertices that we want to partition + * Suppose we have a graph with 12 vertices that we want to partition * over 9 machines. We can use the following sparse matrix representation: * * 
    @@ -61,7 +61,7 @@ object PartitionStrategy {
    * that edges adjacent to `v11` can only be in the first column of blocks `(P0, P3,
    * P6)` or the last
    * row of blocks `(P6, P7, P8)`.  As a consequence we can guarantee that `v11` will need to be
-   * replicated to at most `2 * sqrt(numParts)` machines.
+   * replicated to at most `2 * sqrt(numParts) - 1` machines.
    *
    * Notice that `P0` has many edges and as a consequence this partitioning would lead to poor work
    * balance.  To improve balance we first multiply each vertex id by a large prime to shuffle the

From 4cba6eb42031b1a4cc3308833116ca5d9ccb1a89 Mon Sep 17 00:00:00 2001
From: Sean Owen 
Date: Tue, 6 Jan 2015 12:02:08 -0800
Subject: [PATCH 177/320] SPARK-4159 [CORE] Maven build doesn't run JUnit test
 suites

This PR:

- Reenables `surefire`, and copies config from `scalatest` (which is itself an old fork of `surefire`, so similar)
- Tells `surefire` to test only Java tests
- Enables `surefire` and `scalatest` for all children, and in turn eliminates some duplication.

For me this causes the Scala and Java tests to be run once each, it seems, as desired. It doesn't affect the SBT build but works for Maven. I still need to verify that all of the Scala tests and Java tests are being run.

Author: Sean Owen 

Closes #3651 from srowen/SPARK-4159 and squashes the following commits:

2e8a0af [Sean Owen] Remove specialized SPARK_HOME setting for REPL, YARN tests as it appears to be obsolete
12e4558 [Sean Owen] Append to unit-test.log instead of overwriting, so that both surefire and scalatest output is preserved. Also standardize/correct comments a bit.
e6f8601 [Sean Owen] Reenable Java tests by reenabling surefire with config cloned from scalatest; centralize test config in the parent
---
 bagel/pom.xml                                 | 11 -----
 bagel/src/test/resources/log4j.properties     |  4 +-
 core/pom.xml                                  | 18 --------
 core/src/test/resources/log4j.properties      |  4 +-
 examples/pom.xml                              |  5 ---
 external/flume-sink/pom.xml                   |  9 ----
 .../src/test/resources/log4j.properties       |  3 +-
 external/flume/pom.xml                        | 11 -----
 .../flume/src/test/resources/log4j.properties |  5 +--
 external/kafka/pom.xml                        | 11 -----
 .../kafka/src/test/resources/log4j.properties |  5 +--
 external/mqtt/pom.xml                         | 11 -----
 .../mqtt/src/test/resources/log4j.properties  |  5 +--
 external/twitter/pom.xml                      | 11 -----
 .../src/test/resources/log4j.properties       |  5 +--
 external/zeromq/pom.xml                       | 11 -----
 .../src/test/resources/log4j.properties       |  5 +--
 extras/java8-tests/pom.xml                    | 15 -------
 .../src/test/resources/log4j.properties       |  2 +-
 extras/kinesis-asl/pom.xml                    | 11 -----
 .../src/test/resources/log4j.properties       |  5 ++-
 graphx/pom.xml                                | 11 -----
 graphx/src/test/resources/log4j.properties    |  4 +-
 mllib/pom.xml                                 | 11 -----
 mllib/src/test/resources/log4j.properties     |  4 +-
 network/common/pom.xml                        |  5 ---
 network/shuffle/pom.xml                       |  5 ---
 pom.xml                                       | 45 +++++++++++++++++--
 repl/pom.xml                                  | 14 ------
 repl/src/test/resources/log4j.properties      |  4 +-
 sql/catalyst/pom.xml                          | 10 -----
 sql/core/pom.xml                              | 11 -----
 sql/hive-thriftserver/pom.xml                 |  9 ----
 sql/hive/pom.xml                              |  5 ---
 streaming/pom.xml                             | 10 -----
 streaming/src/test/resources/log4j.properties |  5 +--
 tools/pom.xml                                 |  9 ----
 yarn/pom.xml                                  | 14 ------
 yarn/src/test/resources/log4j.properties      |  4 +-
 39 files changed, 70 insertions(+), 277 deletions(-)

diff --git a/bagel/pom.xml b/bagel/pom.xml
index 0327ffa402671..3bcd38fa3245c 100644
--- a/bagel/pom.xml
+++ b/bagel/pom.xml
@@ -44,11 +44,6 @@
       org.eclipse.jetty
       jetty-server
     
-    
-      org.scalatest
-      scalatest_${scala.binary.version}
-      test
-    
     
       org.scalacheck
       scalacheck_${scala.binary.version}
@@ -58,11 +53,5 @@
   
     target/scala-${scala.binary.version}/classes
     target/scala-${scala.binary.version}/test-classes
-    
-      
-        org.scalatest
-        scalatest-maven-plugin
-      
-    
   
 
diff --git a/bagel/src/test/resources/log4j.properties b/bagel/src/test/resources/log4j.properties
index 789869f72e3b0..853ef0ed2986f 100644
--- a/bagel/src/test/resources/log4j.properties
+++ b/bagel/src/test/resources/log4j.properties
@@ -15,10 +15,10 @@
 # limitations under the License.
 #
 
-# Set everything to be logged to the file bagel/target/unit-tests.log
+# Set everything to be logged to the file target/unit-tests.log
 log4j.rootCategory=INFO, file
 log4j.appender.file=org.apache.log4j.FileAppender
-log4j.appender.file.append=false
+log4j.appender.file.append=true
 log4j.appender.file.file=target/unit-tests.log
 log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
diff --git a/core/pom.xml b/core/pom.xml
index c5c41b2b5de42..d9a49c9e08afc 100644
--- a/core/pom.xml
+++ b/core/pom.xml
@@ -276,11 +276,6 @@
       selenium-java
       test
     
-    
-      org.scalatest
-      scalatest_${scala.binary.version}
-      test
-    
     
       org.mockito
       mockito-all
@@ -326,19 +321,6 @@
     target/scala-${scala.binary.version}/classes
     target/scala-${scala.binary.version}/test-classes
     
-      
-        org.scalatest
-        scalatest-maven-plugin
-        
-          
-            test
-            
-              test
-            
-          
-        
-      
-
       
       
         org.apache.maven.plugins
diff --git a/core/src/test/resources/log4j.properties b/core/src/test/resources/log4j.properties
index 9dd05f17f012b..287c8e3563503 100644
--- a/core/src/test/resources/log4j.properties
+++ b/core/src/test/resources/log4j.properties
@@ -15,10 +15,10 @@
 # limitations under the License.
 #
 
-# Set everything to be logged to the file core/target/unit-tests.log
+# Set everything to be logged to the file target/unit-tests.log
 log4j.rootCategory=INFO, file
 log4j.appender.file=org.apache.log4j.FileAppender
-log4j.appender.file.append=false
+log4j.appender.file.append=true
 log4j.appender.file.file=target/unit-tests.log
 log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
diff --git a/examples/pom.xml b/examples/pom.xml
index 8713230e1e8ed..bdc5d0562f3e1 100644
--- a/examples/pom.xml
+++ b/examples/pom.xml
@@ -244,11 +244,6 @@
       algebird-core_${scala.binary.version}
       0.8.1
     
-    
-      org.scalatest
-      scalatest_${scala.binary.version}
-      test
-    
     
       org.scalacheck
       scalacheck_${scala.binary.version}
diff --git a/external/flume-sink/pom.xml b/external/flume-sink/pom.xml
index 72618b6515f83..71f595d0a6800 100644
--- a/external/flume-sink/pom.xml
+++ b/external/flume-sink/pom.xml
@@ -65,11 +65,6 @@
         
       
     
-    
-      org.scalatest
-      scalatest_${scala.binary.version}
-      test
-    
     
       org.scala-lang
       scala-library
@@ -91,10 +86,6 @@
     target/scala-${scala.binary.version}/classes
     target/scala-${scala.binary.version}/test-classes
     
-      
-        org.scalatest
-        scalatest-maven-plugin
-      
       
         org.apache.avro
         avro-maven-plugin
diff --git a/external/flume-sink/src/test/resources/log4j.properties b/external/flume-sink/src/test/resources/log4j.properties
index 4411d6e20c52a..2a58e99817224 100644
--- a/external/flume-sink/src/test/resources/log4j.properties
+++ b/external/flume-sink/src/test/resources/log4j.properties
@@ -17,9 +17,8 @@
 
 # Set everything to be logged to the file streaming/target/unit-tests.log
 log4j.rootCategory=INFO, file
-# log4j.appender.file=org.apache.log4j.FileAppender
 log4j.appender.file=org.apache.log4j.FileAppender
-log4j.appender.file.append=false
+log4j.appender.file.append=true
 log4j.appender.file.file=target/unit-tests.log
 log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
diff --git a/external/flume/pom.xml b/external/flume/pom.xml
index a682f0e8471d8..0374262212e08 100644
--- a/external/flume/pom.xml
+++ b/external/flume/pom.xml
@@ -61,11 +61,6 @@
         
       
     
-    
-      org.scalatest
-      scalatest_${scala.binary.version}
-      test
-    
     
       org.scalacheck
       scalacheck_${scala.binary.version}
@@ -85,11 +80,5 @@
   
     target/scala-${scala.binary.version}/classes
     target/scala-${scala.binary.version}/test-classes
-    
-      
-        org.scalatest
-        scalatest-maven-plugin
-      
-    
   
 
diff --git a/external/flume/src/test/resources/log4j.properties b/external/flume/src/test/resources/log4j.properties
index 4411d6e20c52a..9697237bfa1a3 100644
--- a/external/flume/src/test/resources/log4j.properties
+++ b/external/flume/src/test/resources/log4j.properties
@@ -15,11 +15,10 @@
 # limitations under the License.
 #
 
-# Set everything to be logged to the file streaming/target/unit-tests.log
+# Set everything to be logged to the file target/unit-tests.log
 log4j.rootCategory=INFO, file
-# log4j.appender.file=org.apache.log4j.FileAppender
 log4j.appender.file=org.apache.log4j.FileAppender
-log4j.appender.file.append=false
+log4j.appender.file.append=true
 log4j.appender.file.file=target/unit-tests.log
 log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
diff --git a/external/kafka/pom.xml b/external/kafka/pom.xml
index b3f44471cd326..b29b0509656ba 100644
--- a/external/kafka/pom.xml
+++ b/external/kafka/pom.xml
@@ -74,11 +74,6 @@
       3.2
       test
     
-    
-      org.scalatest
-      scalatest_${scala.binary.version}
-      test
-    
     
       org.scalacheck
       scalacheck_${scala.binary.version}
@@ -98,11 +93,5 @@
   
     target/scala-${scala.binary.version}/classes
     target/scala-${scala.binary.version}/test-classes
-    
-      
-        org.scalatest
-        scalatest-maven-plugin
-      
-    
   
 
diff --git a/external/kafka/src/test/resources/log4j.properties b/external/kafka/src/test/resources/log4j.properties
index 4411d6e20c52a..9697237bfa1a3 100644
--- a/external/kafka/src/test/resources/log4j.properties
+++ b/external/kafka/src/test/resources/log4j.properties
@@ -15,11 +15,10 @@
 # limitations under the License.
 #
 
-# Set everything to be logged to the file streaming/target/unit-tests.log
+# Set everything to be logged to the file target/unit-tests.log
 log4j.rootCategory=INFO, file
-# log4j.appender.file=org.apache.log4j.FileAppender
 log4j.appender.file=org.apache.log4j.FileAppender
-log4j.appender.file.append=false
+log4j.appender.file.append=true
 log4j.appender.file.file=target/unit-tests.log
 log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
diff --git a/external/mqtt/pom.xml b/external/mqtt/pom.xml
index d478267b605ba..560c8b9d18276 100644
--- a/external/mqtt/pom.xml
+++ b/external/mqtt/pom.xml
@@ -46,11 +46,6 @@
       org.eclipse.paho.client.mqttv3
       1.0.1
     
-    
-      org.scalatest
-      scalatest_${scala.binary.version}
-      test
-    
     
       org.scalacheck
       scalacheck_${scala.binary.version}
@@ -76,11 +71,5 @@
   
     target/scala-${scala.binary.version}/classes
     target/scala-${scala.binary.version}/test-classes
-    
-      
-        org.scalatest
-        scalatest-maven-plugin
-      
-    
   
 
diff --git a/external/mqtt/src/test/resources/log4j.properties b/external/mqtt/src/test/resources/log4j.properties
index 4411d6e20c52a..9697237bfa1a3 100644
--- a/external/mqtt/src/test/resources/log4j.properties
+++ b/external/mqtt/src/test/resources/log4j.properties
@@ -15,11 +15,10 @@
 # limitations under the License.
 #
 
-# Set everything to be logged to the file streaming/target/unit-tests.log
+# Set everything to be logged to the file target/unit-tests.log
 log4j.rootCategory=INFO, file
-# log4j.appender.file=org.apache.log4j.FileAppender
 log4j.appender.file=org.apache.log4j.FileAppender
-log4j.appender.file.append=false
+log4j.appender.file.append=true
 log4j.appender.file.file=target/unit-tests.log
 log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
diff --git a/external/twitter/pom.xml b/external/twitter/pom.xml
index 000ace1446e5e..da6ffe7662f63 100644
--- a/external/twitter/pom.xml
+++ b/external/twitter/pom.xml
@@ -46,11 +46,6 @@
       twitter4j-stream
       3.0.3
     
-    
-      org.scalatest
-      scalatest_${scala.binary.version}
-      test
-    
     
       org.scalacheck
       scalacheck_${scala.binary.version}
@@ -70,11 +65,5 @@
   
     target/scala-${scala.binary.version}/classes
     target/scala-${scala.binary.version}/test-classes
-    
-      
-        org.scalatest
-        scalatest-maven-plugin
-      
-    
   
 
diff --git a/external/twitter/src/test/resources/log4j.properties b/external/twitter/src/test/resources/log4j.properties
index 4411d6e20c52a..64bfc5745088f 100644
--- a/external/twitter/src/test/resources/log4j.properties
+++ b/external/twitter/src/test/resources/log4j.properties
@@ -15,11 +15,10 @@
 # limitations under the License.
 #
 
-# Set everything to be logged to the file streaming/target/unit-tests.log
+# Set everything to be logged to the filetarget/unit-tests.log
 log4j.rootCategory=INFO, file
-# log4j.appender.file=org.apache.log4j.FileAppender
 log4j.appender.file=org.apache.log4j.FileAppender
-log4j.appender.file.append=false
+log4j.appender.file.append=true
 log4j.appender.file.file=target/unit-tests.log
 log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
diff --git a/external/zeromq/pom.xml b/external/zeromq/pom.xml
index 29c452093502e..2fb5f0ed2f57c 100644
--- a/external/zeromq/pom.xml
+++ b/external/zeromq/pom.xml
@@ -46,11 +46,6 @@
       akka-zeromq_${scala.binary.version}
       ${akka.version}
     
-    
-      org.scalatest
-      scalatest_${scala.binary.version}
-      test
-    
     
       org.scalacheck
       scalacheck_${scala.binary.version}
@@ -70,11 +65,5 @@
   
     target/scala-${scala.binary.version}/classes
     target/scala-${scala.binary.version}/test-classes
-    
-      
-        org.scalatest
-        scalatest-maven-plugin
-      
-    
   
 
diff --git a/external/zeromq/src/test/resources/log4j.properties b/external/zeromq/src/test/resources/log4j.properties
index 4411d6e20c52a..9697237bfa1a3 100644
--- a/external/zeromq/src/test/resources/log4j.properties
+++ b/external/zeromq/src/test/resources/log4j.properties
@@ -15,11 +15,10 @@
 # limitations under the License.
 #
 
-# Set everything to be logged to the file streaming/target/unit-tests.log
+# Set everything to be logged to the file target/unit-tests.log
 log4j.rootCategory=INFO, file
-# log4j.appender.file=org.apache.log4j.FileAppender
 log4j.appender.file=org.apache.log4j.FileAppender
-log4j.appender.file.append=false
+log4j.appender.file.append=true
 log4j.appender.file.file=target/unit-tests.log
 log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
diff --git a/extras/java8-tests/pom.xml b/extras/java8-tests/pom.xml
index c8477a6566311..0fb431808bacd 100644
--- a/extras/java8-tests/pom.xml
+++ b/extras/java8-tests/pom.xml
@@ -60,11 +60,6 @@
       junit-interface
       test
     
-    
-      org.scalatest
-      scalatest_${scala.binary.version}
-      test
-    
   
 
   
@@ -159,16 +154,6 @@
           
         
       
-      
-        org.scalatest
-        scalatest-maven-plugin
-        
-          
-            test
-            none
-          
-        
-      
     
   
 
diff --git a/extras/java8-tests/src/test/resources/log4j.properties b/extras/java8-tests/src/test/resources/log4j.properties
index bb0ab319a0080..287c8e3563503 100644
--- a/extras/java8-tests/src/test/resources/log4j.properties
+++ b/extras/java8-tests/src/test/resources/log4j.properties
@@ -18,7 +18,7 @@
 # Set everything to be logged to the file target/unit-tests.log
 log4j.rootCategory=INFO, file
 log4j.appender.file=org.apache.log4j.FileAppender
-log4j.appender.file.append=false
+log4j.appender.file.append=true
 log4j.appender.file.file=target/unit-tests.log
 log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
diff --git a/extras/kinesis-asl/pom.xml b/extras/kinesis-asl/pom.xml
index c0d3a61119113..c815eda52bda7 100644
--- a/extras/kinesis-asl/pom.xml
+++ b/extras/kinesis-asl/pom.xml
@@ -57,11 +57,6 @@
       aws-java-sdk
       ${aws.java.sdk.version}
     
-    
-      org.scalatest
-      scalatest_${scala.binary.version}
-      test
-    
     
       org.mockito
       mockito-all
@@ -86,11 +81,5 @@
   
     target/scala-${scala.binary.version}/classes
     target/scala-${scala.binary.version}/test-classes
-    
-      
-        org.scalatest
-        scalatest-maven-plugin
-      
-    
   
 
diff --git a/extras/kinesis-asl/src/test/resources/log4j.properties b/extras/kinesis-asl/src/test/resources/log4j.properties
index d9d08f68687d3..853ef0ed2986f 100644
--- a/extras/kinesis-asl/src/test/resources/log4j.properties
+++ b/extras/kinesis-asl/src/test/resources/log4j.properties
@@ -14,10 +14,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 #
+
+# Set everything to be logged to the file target/unit-tests.log
 log4j.rootCategory=INFO, file
-# log4j.appender.file=org.apache.log4j.FileAppender
 log4j.appender.file=org.apache.log4j.FileAppender
-log4j.appender.file.append=false
+log4j.appender.file.append=true
 log4j.appender.file.file=target/unit-tests.log
 log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
diff --git a/graphx/pom.xml b/graphx/pom.xml
index 9982b36f9b62f..91db799d244ad 100644
--- a/graphx/pom.xml
+++ b/graphx/pom.xml
@@ -49,11 +49,6 @@
       org.eclipse.jetty
       jetty-server
     
-    
-      org.scalatest
-      scalatest_${scala.binary.version}
-      test
-    
     
       org.scalacheck
       scalacheck_${scala.binary.version}
@@ -63,11 +58,5 @@
   
     target/scala-${scala.binary.version}/classes
     target/scala-${scala.binary.version}/test-classes
-    
-      
-        org.scalatest
-        scalatest-maven-plugin
-      
-    
   
 
diff --git a/graphx/src/test/resources/log4j.properties b/graphx/src/test/resources/log4j.properties
index 9dd05f17f012b..287c8e3563503 100644
--- a/graphx/src/test/resources/log4j.properties
+++ b/graphx/src/test/resources/log4j.properties
@@ -15,10 +15,10 @@
 # limitations under the License.
 #
 
-# Set everything to be logged to the file core/target/unit-tests.log
+# Set everything to be logged to the file target/unit-tests.log
 log4j.rootCategory=INFO, file
 log4j.appender.file=org.apache.log4j.FileAppender
-log4j.appender.file.append=false
+log4j.appender.file.append=true
 log4j.appender.file.file=target/unit-tests.log
 log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
diff --git a/mllib/pom.xml b/mllib/pom.xml
index 0a6dda0ab8c80..2198757481684 100644
--- a/mllib/pom.xml
+++ b/mllib/pom.xml
@@ -80,11 +80,6 @@
       org.apache.commons
       commons-math3
     
-    
-      org.scalatest
-      scalatest_${scala.binary.version}
-      test
-    
     
       org.scalacheck
       scalacheck_${scala.binary.version}
@@ -129,12 +124,6 @@
   
     target/scala-${scala.binary.version}/classes
     target/scala-${scala.binary.version}/test-classes
-    
-      
-        org.scalatest
-        scalatest-maven-plugin
-      
-    
     
       
         ../python
diff --git a/mllib/src/test/resources/log4j.properties b/mllib/src/test/resources/log4j.properties
index a469badf603c6..9697237bfa1a3 100644
--- a/mllib/src/test/resources/log4j.properties
+++ b/mllib/src/test/resources/log4j.properties
@@ -15,10 +15,10 @@
 # limitations under the License.
 #
 
-# Set everything to be logged to the file core/target/unit-tests.log
+# Set everything to be logged to the file target/unit-tests.log
 log4j.rootCategory=INFO, file
 log4j.appender.file=org.apache.log4j.FileAppender
-log4j.appender.file.append=false
+log4j.appender.file.append=true
 log4j.appender.file.file=target/unit-tests.log
 log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
diff --git a/network/common/pom.xml b/network/common/pom.xml
index baca859fa5011..245a96b8c4038 100644
--- a/network/common/pom.xml
+++ b/network/common/pom.xml
@@ -75,11 +75,6 @@
       mockito-all
       test
     
-    
-      org.scalatest
-      scalatest_${scala.binary.version}
-      test
-    
   
 
   
diff --git a/network/shuffle/pom.xml b/network/shuffle/pom.xml
index 12468567c3aed..5bfa1ac9c373e 100644
--- a/network/shuffle/pom.xml
+++ b/network/shuffle/pom.xml
@@ -83,11 +83,6 @@
       mockito-all
       test
     
-    
-      org.scalatest
-      scalatest_${scala.binary.version}
-      test
-    
   
 
   
diff --git a/pom.xml b/pom.xml
index 05f59a9b4140b..46ff211f91160 100644
--- a/pom.xml
+++ b/pom.xml
@@ -256,7 +256,7 @@
       1.0.0
     
     
@@ -266,6 +266,15 @@
       2.3.7
       provided
     
+    
+    
+      org.scalatest
+      scalatest_${scala.binary.version}
+      test
+    
   
   
     
@@ -935,19 +944,38 @@
             true
           
         
+        
         
           org.apache.maven.plugins
           maven-surefire-plugin
-          2.17
+          2.18
+          
           
-            
-            true
+            
+              **/Test*.java
+              **/*Test.java
+              **/*TestCase.java
+              **/*Suite.java
+            
+            ${project.build.directory}/surefire-reports
+            -Xmx3g -XX:MaxPermSize=${MaxPermGen} -XX:ReservedCodeCacheSize=512m
+            
+              true
+              ${session.executionRootDirectory}
+              1
+              false
+              false
+              ${test_classpath}
+              true
+            
           
         
+        
         
           org.scalatest
           scalatest-maven-plugin
           1.0
+          
           
             ${project.build.directory}/surefire-reports
             .
@@ -1159,6 +1187,15 @@
           
         
       
+      
+      
+        org.apache.maven.plugins
+        maven-surefire-plugin
+      
+      
+        org.scalatest
+        scalatest-maven-plugin
+      
     
   
 
diff --git a/repl/pom.xml b/repl/pom.xml
index 9b2290429fee5..97165e024926e 100644
--- a/repl/pom.xml
+++ b/repl/pom.xml
@@ -86,11 +86,6 @@
       org.slf4j
       jul-to-slf4j
     
-    
-      org.scalatest
-      scalatest_${scala.binary.version}
-      test
-    
     
       org.scalacheck
       scalacheck_${scala.binary.version}
@@ -115,15 +110,6 @@
           true
         
       
-      
-        org.scalatest
-        scalatest-maven-plugin
-        
-          
-            ${basedir}/..
-          
-        
-      
       
       
         org.codehaus.mojo
diff --git a/repl/src/test/resources/log4j.properties b/repl/src/test/resources/log4j.properties
index 52098993f5c3c..e7e4a4113174a 100644
--- a/repl/src/test/resources/log4j.properties
+++ b/repl/src/test/resources/log4j.properties
@@ -15,10 +15,10 @@
 # limitations under the License.
 #
 
-# Set everything to be logged to the repl/target/unit-tests.log
+# Set everything to be logged to the target/unit-tests.log
 log4j.rootCategory=INFO, file
 log4j.appender.file=org.apache.log4j.FileAppender
-log4j.appender.file.append=false
+log4j.appender.file.append=true
 log4j.appender.file.file=target/unit-tests.log
 log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
diff --git a/sql/catalyst/pom.xml b/sql/catalyst/pom.xml
index 1caa297e24e37..a1947fb022e54 100644
--- a/sql/catalyst/pom.xml
+++ b/sql/catalyst/pom.xml
@@ -50,11 +50,6 @@
       spark-core_${scala.binary.version}
       ${project.version}
     
-    
-      org.scalatest
-      scalatest_${scala.binary.version}
-      test
-    
     
       org.scalacheck
       scalacheck_${scala.binary.version}
@@ -65,11 +60,6 @@
     target/scala-${scala.binary.version}/classes
     target/scala-${scala.binary.version}/test-classes
     
-      
-        org.scalatest
-        scalatest-maven-plugin
-      
-
       
+    
+      hadoop-provided
+      
+        provided
+      
+    
+    
+      hive-provided
+      
+        provided
+      
+    
+    
+      parquet-provided
+      
+        provided
+      
+    
   
 
diff --git a/bagel/pom.xml b/bagel/pom.xml
index 3bcd38fa3245c..510e92640eff8 100644
--- a/bagel/pom.xml
+++ b/bagel/pom.xml
@@ -40,10 +40,6 @@
       spark-core_${scala.binary.version}
       ${project.version}
     
-    
-      org.eclipse.jetty
-      jetty-server
-    
     
       org.scalacheck
       scalacheck_${scala.binary.version}
diff --git a/bin/compute-classpath.cmd b/bin/compute-classpath.cmd
index a4c099fb45b14..088f993954d9e 100644
--- a/bin/compute-classpath.cmd
+++ b/bin/compute-classpath.cmd
@@ -109,6 +109,13 @@ if "x%YARN_CONF_DIR%"=="x" goto no_yarn_conf_dir
   set CLASSPATH=%CLASSPATH%;%YARN_CONF_DIR%
 :no_yarn_conf_dir
 
+rem To allow for distributions to append needed libraries to the classpath (e.g. when
+rem using the "hadoop-provided" profile to build Spark), check SPARK_DIST_CLASSPATH and
+rem append it to tbe final classpath.
+if not "x%$SPARK_DIST_CLASSPATH%"=="x" (
+  set CLASSPATH=%CLASSPATH%;%SPARK_DIST_CLASSPATH%
+)
+
 rem A bit of a hack to allow calling this script within run2.cmd without seeing output
 if "%DONT_PRINT_CLASSPATH%"=="1" goto exit
 
diff --git a/bin/compute-classpath.sh b/bin/compute-classpath.sh
index a31ea73d3ce19..8f3b396ffd086 100755
--- a/bin/compute-classpath.sh
+++ b/bin/compute-classpath.sh
@@ -146,4 +146,11 @@ if [ -n "$YARN_CONF_DIR" ]; then
   CLASSPATH="$CLASSPATH:$YARN_CONF_DIR"
 fi
 
+# To allow for distributions to append needed libraries to the classpath (e.g. when
+# using the "hadoop-provided" profile to build Spark), check SPARK_DIST_CLASSPATH and
+# append it to tbe final classpath.
+if [ -n "$SPARK_DIST_CLASSPATH" ]; then
+  CLASSPATH="$CLASSPATH:$SPARK_DIST_CLASSPATH"
+fi
+
 echo "$CLASSPATH"
diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/SparkDeploySchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/SparkDeploySchedulerBackend.scala
index 8c7de75600b5f..7eb87a564d6f5 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/cluster/SparkDeploySchedulerBackend.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/SparkDeploySchedulerBackend.scala
@@ -55,19 +55,26 @@ private[spark] class SparkDeploySchedulerBackend(
       "{{WORKER_URL}}")
     val extraJavaOpts = sc.conf.getOption("spark.executor.extraJavaOptions")
       .map(Utils.splitCommandString).getOrElse(Seq.empty)
-    val classPathEntries = sc.conf.getOption("spark.executor.extraClassPath").toSeq.flatMap { cp =>
-      cp.split(java.io.File.pathSeparator)
-    }
-    val libraryPathEntries =
-      sc.conf.getOption("spark.executor.extraLibraryPath").toSeq.flatMap { cp =>
-        cp.split(java.io.File.pathSeparator)
+    val classPathEntries = sc.conf.getOption("spark.executor.extraClassPath")
+      .map(_.split(java.io.File.pathSeparator).toSeq).getOrElse(Nil)
+    val libraryPathEntries = sc.conf.getOption("spark.executor.extraLibraryPath")
+      .map(_.split(java.io.File.pathSeparator).toSeq).getOrElse(Nil)
+
+    // When testing, expose the parent class path to the child. This is processed by
+    // compute-classpath.{cmd,sh} and makes all needed jars available to child processes
+    // when the assembly is built with the "*-provided" profiles enabled.
+    val testingClassPath =
+      if (sys.props.contains("spark.testing")) {
+        sys.props("java.class.path").split(java.io.File.pathSeparator).toSeq
+      } else {
+        Nil
       }
 
     // Start executors with a few necessary configs for registering with the scheduler
     val sparkJavaOpts = Utils.sparkJavaOpts(conf, SparkConf.isExecutorStartupConf)
     val javaOpts = sparkJavaOpts ++ extraJavaOpts
     val command = Command("org.apache.spark.executor.CoarseGrainedExecutorBackend",
-      args, sc.executorEnvs, classPathEntries, libraryPathEntries, javaOpts)
+      args, sc.executorEnvs, classPathEntries ++ testingClassPath, libraryPathEntries, javaOpts)
     val appUIAddress = sc.ui.map(_.appUIAddress).getOrElse("")
     val appDesc = new ApplicationDescription(sc.appName, maxCores, sc.executorMemory, command,
       appUIAddress, sc.eventLogDir)
diff --git a/core/src/main/scala/org/apache/spark/util/Utils.scala b/core/src/main/scala/org/apache/spark/util/Utils.scala
index 9d6b6161ce4da..c4f1898a2db15 100644
--- a/core/src/main/scala/org/apache/spark/util/Utils.scala
+++ b/core/src/main/scala/org/apache/spark/util/Utils.scala
@@ -990,11 +990,12 @@ private[spark] object Utils extends Logging {
     for ((key, value) <- extraEnvironment) {
       environment.put(key, value)
     }
+
     val process = builder.start()
     new Thread("read stderr for " + command(0)) {
       override def run() {
         for (line <- Source.fromInputStream(process.getErrorStream).getLines()) {
-          System.err.println(line)
+          logInfo(line)
         }
       }
     }.start()
@@ -1089,7 +1090,7 @@ private[spark] object Utils extends Logging {
     var firstUserLine = 0
     var insideSpark = true
     var callStack = new ArrayBuffer[String]() :+ ""
- 
+
     Thread.currentThread.getStackTrace().foreach { ste: StackTraceElement =>
       // When running under some profilers, the current stack trace might contain some bogus
       // frames. This is intended to ensure that we don't crash in these situations by
diff --git a/core/src/test/scala/org/apache/spark/DriverSuite.scala b/core/src/test/scala/org/apache/spark/DriverSuite.scala
index 541d8eac80556..8a54360e81795 100644
--- a/core/src/test/scala/org/apache/spark/DriverSuite.scala
+++ b/core/src/test/scala/org/apache/spark/DriverSuite.scala
@@ -35,7 +35,7 @@ class DriverSuite extends FunSuite with Timeouts {
     forAll(masters) { (master: String) =>
       failAfter(60 seconds) {
         Utils.executeAndGetOutput(
-          Seq("./bin/spark-class", "org.apache.spark.DriverWithoutCleanup", master),
+          Seq(s"$sparkHome/bin/spark-class", "org.apache.spark.DriverWithoutCleanup", master),
           new File(sparkHome),
           Map("SPARK_TESTING" -> "1", "SPARK_HOME" -> sparkHome))
       }
diff --git a/examples/pom.xml b/examples/pom.xml
index bdc5d0562f3e1..002d4458c4b3e 100644
--- a/examples/pom.xml
+++ b/examples/pom.xml
@@ -98,143 +98,145 @@
       ${project.version}
     
     
-      org.eclipse.jetty
-      jetty-server
+      org.apache.hbase
+      hbase-testing-util
+      ${hbase.version}
+      ${hbase.deps.scope}
+      
+        
+          
+          org.apache.hbase
+          hbase-annotations
+        
+        
+          org.jruby
+          jruby-complete
+        
+      
+    
+    
+      org.apache.hbase
+      hbase-protocol
+      ${hbase.version}
+      ${hbase.deps.scope}
+    
+    
+      org.apache.hbase
+      hbase-common
+      ${hbase.version}
+      ${hbase.deps.scope}
+      
+        
+          
+          org.apache.hbase
+          hbase-annotations
+        
+      
+    
+    
+      org.apache.hbase
+      hbase-client
+      ${hbase.version}
+      ${hbase.deps.scope}
+      
+        
+          
+          org.apache.hbase
+          hbase-annotations
+        
+       
+        io.netty
+        netty
+       
+     
+    
+    
+      org.apache.hbase
+      hbase-server
+      ${hbase.version}
+      ${hbase.deps.scope}
+      
+        
+          
+          org.apache.hbase
+          hbase-annotations
+        
+        
+          org.apache.hadoop
+          hadoop-core
+        
+        
+          org.apache.hadoop
+          hadoop-client
+        
+        
+          org.apache.hadoop
+          hadoop-mapreduce-client-jobclient
+        
+        
+          org.apache.hadoop
+          hadoop-mapreduce-client-core
+        
+        
+          org.apache.hadoop
+          hadoop-auth
+        
+        
+          org.apache.hadoop
+          hadoop-annotations
+        
+        
+          org.apache.hadoop
+          hadoop-hdfs
+        
+        
+          org.apache.hbase
+          hbase-hadoop1-compat
+        
+        
+          org.apache.commons
+          commons-math
+        
+        
+          com.sun.jersey
+          jersey-core
+        
+        
+          org.slf4j
+          slf4j-api
+        
+        
+          com.sun.jersey
+          jersey-server
+        
+        
+          com.sun.jersey
+          jersey-core
+        
+        
+          com.sun.jersey
+          jersey-json
+        
+        
+          
+          commons-io
+          commons-io
+        
+      
+    
+    
+      org.apache.hbase
+      hbase-hadoop-compat
+      ${hbase.version}
+      ${hbase.deps.scope}
+    
+    
+      org.apache.hbase
+      hbase-hadoop-compat
+      ${hbase.version}
+      test-jar
+      test
     
-      
-        org.apache.hbase
-        hbase-testing-util
-        ${hbase.version}
-        
-          
-            
-            org.apache.hbase
-            hbase-annotations
-          
-          
-            org.jruby
-            jruby-complete
-          
-        
-      
-      
-        org.apache.hbase
-        hbase-protocol
-        ${hbase.version}
-      
-      
-        org.apache.hbase
-        hbase-common
-        ${hbase.version}
-        
-          
-            
-            org.apache.hbase
-            hbase-annotations
-          
-        
-      
-      
-        org.apache.hbase
-        hbase-client
-        ${hbase.version}
-        
-          
-            
-            org.apache.hbase
-            hbase-annotations
-          
-         
-          io.netty
-          netty
-         
-       
-      
-      
-        org.apache.hbase
-        hbase-server
-        ${hbase.version}
-        
-          
-            org.apache.hadoop
-            hadoop-core
-          
-          
-            org.apache.hadoop
-            hadoop-client
-          
-          
-            org.apache.hadoop
-            hadoop-mapreduce-client-jobclient
-          
-          
-            org.apache.hadoop
-            hadoop-mapreduce-client-core
-          
-          
-            org.apache.hadoop
-            hadoop-auth
-          
-          
-            
-            org.apache.hbase
-            hbase-annotations
-          
-          
-            org.apache.hadoop
-            hadoop-annotations
-          
-          
-            org.apache.hadoop
-            hadoop-hdfs
-          
-          
-            org.apache.hbase
-            hbase-hadoop1-compat
-          
-          
-            org.apache.commons
-            commons-math
-          
-          
-            com.sun.jersey
-            jersey-core
-          
-          
-            org.slf4j
-            slf4j-api
-          
-          
-            com.sun.jersey
-            jersey-server
-          
-          
-            com.sun.jersey
-            jersey-core
-          
-          
-            com.sun.jersey
-            jersey-json
-          
-          
-            
-            commons-io
-            commons-io
-          
-        
-      
-      
-        org.apache.hbase
-        hbase-hadoop-compat
-        ${hbase.version}
-      
-      
-        org.apache.hbase
-        hbase-hadoop-compat
-        ${hbase.version}
-        test-jar
-        test
-      
     
       org.apache.commons
       commons-math3
@@ -308,31 +310,6 @@
       
         org.apache.maven.plugins
         maven-shade-plugin
-        
-          false
-          ${project.build.directory}/scala-${scala.binary.version}/spark-examples-${project.version}-hadoop${hadoop.version}.jar
-          
-            
-              *:*
-            
-          
-          
-            
-              com.google.guava:guava
-              
-                com/google/common/base/Optional*
-              
-            
-            
-              *:*
-              
-                META-INF/*.SF
-                META-INF/*.DSA
-                META-INF/*.RSA
-              
-            
-          
-        
         
           
             package
@@ -340,6 +317,34 @@
               shade
             
             
+            false
+            ${project.build.directory}/scala-${scala.binary.version}/spark-examples-${project.version}-hadoop${hadoop.version}.jar
+            
+              
+                *:*
+              
+            
+            
+              
+                com.google.guava:guava
+                
+                  
+                  **
+                
+              
+              
+                *:*
+                
+                  META-INF/*.SF
+                  META-INF/*.DSA
+                  META-INF/*.RSA
+                
+              
+            
               
                 
                   com.google
@@ -411,7 +416,7 @@
       
     
     
-      
       scala-2.10
       
@@ -449,5 +454,37 @@
         
       
     
+
+    
+    
+      flume-provided
+      
+        provided
+      
+    
+    
+      hadoop-provided
+      
+        provided
+      
+    
+    
+      hbase-provided
+      
+        provided
+      
+    
+    
+      hive-provided
+      
+        provided
+      
+    
+    
+      parquet-provided
+      
+        provided
+      
+    
   
 
diff --git a/external/flume-sink/pom.xml b/external/flume-sink/pom.xml
index 71f595d0a6800..0706f1ebf66e2 100644
--- a/external/flume-sink/pom.xml
+++ b/external/flume-sink/pom.xml
@@ -38,32 +38,10 @@
     
       org.apache.flume
       flume-ng-sdk
-      ${flume.version}
-      
-        
-          io.netty
-          netty
-        
-        
-          org.apache.thrift
-          libthrift
-        
-      
     
     
       org.apache.flume
       flume-ng-core
-      ${flume.version}
-      
-        
-          io.netty
-          netty
-        
-        
-          org.apache.thrift
-          libthrift
-        
-      
     
     
       org.scala-lang
diff --git a/external/flume/pom.xml b/external/flume/pom.xml
index 0374262212e08..1f2681394c583 100644
--- a/external/flume/pom.xml
+++ b/external/flume/pom.xml
@@ -46,20 +46,13 @@
       spark-streaming-flume-sink_${scala.binary.version}
       ${project.version}
     
+    
+      org.apache.flume
+      flume-ng-core
+    
     
       org.apache.flume
       flume-ng-sdk
-      ${flume.version}
-      
-        
-          io.netty
-          netty
-        
-        
-          org.apache.thrift
-          libthrift
-        
-      
     
     
       org.scalacheck
diff --git a/external/zeromq/pom.xml b/external/zeromq/pom.xml
index 2fb5f0ed2f57c..e919c2c9b19ea 100644
--- a/external/zeromq/pom.xml
+++ b/external/zeromq/pom.xml
@@ -44,7 +44,6 @@
     
       ${akka.group}
       akka-zeromq_${scala.binary.version}
-      ${akka.version}
     
     
       org.scalacheck
diff --git a/graphx/pom.xml b/graphx/pom.xml
index 91db799d244ad..72374aae6da9b 100644
--- a/graphx/pom.xml
+++ b/graphx/pom.xml
@@ -45,10 +45,6 @@
       jblas
       ${jblas.version}
     
-    
-      org.eclipse.jetty
-      jetty-server
-    
     
       org.scalacheck
       scalacheck_${scala.binary.version}
diff --git a/mllib/pom.xml b/mllib/pom.xml
index 2198757481684..a0bda89ccaa71 100644
--- a/mllib/pom.xml
+++ b/mllib/pom.xml
@@ -29,7 +29,7 @@
   spark-mllib_2.10
   
     mllib
-    
+  
   jar
   Spark Project ML Library
   http://spark.apache.org/
@@ -50,10 +50,6 @@
       spark-sql_${scala.binary.version}
       ${project.version}
     
-    
-      org.eclipse.jetty
-      jetty-server
-    
     
       org.jblas
       jblas
diff --git a/pom.xml b/pom.xml
index 46ff211f91160..703e5c47bf59b 100644
--- a/pom.xml
+++ b/pom.xml
@@ -123,8 +123,10 @@
     2.4.1
     ${hadoop.version}
     0.94.6
+    hbase
     1.4.0
     3.4.5
+    org.spark-project.hive
     
     0.13.1a
     
@@ -143,13 +145,36 @@
     4.2.6
     3.1.1
     ${project.build.directory}/spark-test-classpath.txt
-    64m
-    512m
     2.10.4
     2.10
     ${scala.version}
     org.scala-lang
-    1.8.8
+    1.8.8
+    1.1.1.6
+
+    
+    compile
+    compile
+    compile
+    compile
+    compile
+
+    
+    ${session.executionRootDirectory}
+
+    64m
+    512m
+    512m
   
 
   
@@ -244,21 +269,20 @@
       
     
   
-
   
-  
+    
     
       org.spark-project.spark
       unused
       1.0.0
     
     
     
       org.codehaus.groovy
@@ -369,11 +393,13 @@
         org.slf4j
         slf4j-api
         ${slf4j.version}
+        ${hadoop.deps.scope}
       
       
         org.slf4j
         slf4j-log4j12
         ${slf4j.version}
+        ${hadoop.deps.scope}
       
       
         org.slf4j
@@ -390,6 +416,7 @@
         log4j
         log4j
         ${log4j.version}
+        ${hadoop.deps.scope}
       
       
         com.ning
@@ -399,7 +426,8 @@
       
         org.xerial.snappy
         snappy-java
-        1.1.1.6
+        ${snappy.version}
+        ${hadoop.deps.scope}
       
       
         net.jpountz.lz4
@@ -427,6 +455,7 @@
         com.google.protobuf
         protobuf-java
         ${protobuf.version}
+        ${hadoop.deps.scope}
       
       
         ${akka.group}
@@ -448,6 +477,17 @@
         akka-testkit_${scala.binary.version}
         ${akka.version}
       
+      
+        ${akka.group}
+        akka-zeromq_${scala.binary.version}
+        ${akka.version}
+        
+          
+            ${akka.group}
+            akka-actor_${scala.binary.version}
+          
+        
+      
       
         org.apache.mesos
         mesos
@@ -577,6 +617,7 @@
         org.apache.curator
         curator-recipes
         2.4.0
+        ${hadoop.deps.scope}
         
           
             org.jboss.netty
@@ -588,6 +629,7 @@
         org.apache.hadoop
         hadoop-client
         ${hadoop.version}
+        ${hadoop.deps.scope}
         
           
             asm
@@ -623,11 +665,13 @@
         org.apache.avro
         avro
         ${avro.version}
+        ${hadoop.deps.scope}
       
       
         org.apache.avro
         avro-ipc
         ${avro.version}
+        ${hadoop.deps.scope}
         
           
             io.netty
@@ -656,6 +700,7 @@
         avro-mapred
         ${avro.version}
         ${avro.mapred.classifier}
+        ${hive.deps.scope}
         
           
             io.netty
@@ -684,6 +729,7 @@
         net.java.dev.jets3t
         jets3t
         ${jets3t.version}
+        ${hadoop.deps.scope}
         
           
             commons-logging
@@ -695,6 +741,7 @@
         org.apache.hadoop
         hadoop-yarn-api
         ${yarn.version}
+        ${hadoop.deps.scope}
         
           
             javax.servlet
@@ -722,6 +769,7 @@
         org.apache.hadoop
         hadoop-yarn-common
         ${yarn.version}
+        ${hadoop.deps.scope}
         
           
             asm
@@ -778,6 +826,7 @@
         org.apache.hadoop
         hadoop-yarn-server-web-proxy
         ${yarn.version}
+        ${hadoop.deps.scope}
         
           
             asm
@@ -805,6 +854,7 @@
         org.apache.hadoop
         hadoop-yarn-client
         ${yarn.version}
+        ${hadoop.deps.scope}
         
           
             asm
@@ -829,15 +879,126 @@
         
       
       
-        
-        org.codehaus.jackson
-        jackson-mapper-asl
-        ${jackson.version}
+        org.apache.zookeeper
+        zookeeper
+        ${zookeeper.version}
+        ${hadoop.deps.scope}
       
       
         org.codehaus.jackson
         jackson-core-asl
-        ${jackson.version}
+        ${codehaus.jackson.version}
+        ${hadoop.deps.scope}
+      
+      
+        org.codehaus.jackson
+        jackson-mapper-asl
+        ${codehaus.jackson.version}
+        ${hadoop.deps.scope}
+      
+      
+        ${hive.group}
+        hive-beeline
+        ${hive.version}
+        ${hive.deps.scope}
+      
+      
+        ${hive.group}
+        hive-cli
+        ${hive.version}
+        ${hive.deps.scope}
+      
+      
+        ${hive.group}
+        hive-exec
+        ${hive.version}
+        ${hive.deps.scope}
+        
+          
+            commons-logging
+            commons-logging
+          
+          
+            com.esotericsoftware.kryo
+            kryo
+          
+        
+      
+      
+        ${hive.group}
+        hive-jdbc
+        ${hive.version}
+        ${hive.deps.scope}
+      
+      
+        ${hive.group}
+        hive-metastore
+        ${hive.version}
+        ${hive.deps.scope}
+      
+      
+        ${hive.group}
+        hive-serde
+        ${hive.version}
+        ${hive.deps.scope}
+        
+          
+            commons-logging
+            commons-logging
+          
+          
+            commons-logging
+            commons-logging-api
+          
+        
+      
+      
+        com.twitter
+        parquet-column
+        ${parquet.version}
+        ${parquet.deps.scope}
+      
+      
+        com.twitter
+        parquet-hadoop
+        ${parquet.version}
+        ${parquet.deps.scope}
+      
+      
+        org.apache.flume
+        flume-ng-core
+        ${flume.version}
+        ${flume.deps.scope}
+        
+          
+            io.netty
+            netty
+          
+          
+            org.apache.thrift
+            libthrift
+          
+          
+            org.mortbay.jetty
+            servlet-api
+          
+        
+      
+      
+        org.apache.flume
+        flume-ng-sdk
+        ${flume.version}
+        ${flume.deps.scope}
+        
+          
+            io.netty
+            netty
+          
+          
+            org.apache.thrift
+            libthrift
+          
+        
       
     
   
@@ -914,6 +1075,7 @@
               -Xmx1024m
               -XX:PermSize=${PermGen}
               -XX:MaxPermSize=${MaxPermGen}
+              -XX:ReservedCodeCacheSize=${CodeCacheSize}
             
             
               -source
@@ -980,15 +1142,21 @@
             ${project.build.directory}/surefire-reports
             .
             SparkTestSuite.txt
-            -ea -Xmx3g -XX:MaxPermSize=${MaxPermGen} -XX:ReservedCodeCacheSize=512m
+            -ea -Xmx3g -XX:MaxPermSize=${MaxPermGen} -XX:ReservedCodeCacheSize=${CodeCacheSize}
             
+            
+              
+              ${test_classpath}
+            
             
               true
-              ${session.executionRootDirectory}
+              ${spark.test.home}
               1
               false
               false
-              ${test_classpath}
               true
             
           
@@ -1011,11 +1179,6 @@
           maven-antrun-plugin
           1.7
         
-        
-          org.apache.maven.plugins
-          maven-shade-plugin
-          2.2
-        
         
           org.apache.maven.plugins
           maven-source-plugin
@@ -1104,6 +1267,7 @@
       
         org.apache.maven.plugins
         maven-shade-plugin
+        2.2
         
           false
           
@@ -1373,53 +1537,6 @@
       
     
 
-    
-    
-      hadoop-provided
-      
-        
-          org.apache.hadoop
-          hadoop-client
-          provided
-        
-        
-          org.apache.hadoop
-          hadoop-yarn-api
-          provided
-        
-        
-          org.apache.hadoop
-          hadoop-yarn-common
-          provided
-        
-        
-          org.apache.hadoop
-          hadoop-yarn-server-web-proxy
-          provided
-        
-        
-          org.apache.hadoop
-          hadoop-yarn-client
-          provided
-        
-        
-          org.apache.avro
-          avro
-          provided
-        
-        
-          org.apache.avro
-          avro-ipc
-          provided
-        
-        
-          org.apache.zookeeper
-          zookeeper
-          ${zookeeper.version}
-          provided
-        
-      
-    
     
       hive-thriftserver
       
@@ -1472,5 +1589,25 @@
       
     
 
+    
+    
+      flume-provided
+    
+    
+      hadoop-provided
+    
+    
+      hbase-provided
+    
+    
+      hive-provided
+    
+    
+      parquet-provided
+    
   
 
diff --git a/repl/pom.xml b/repl/pom.xml
index 97165e024926e..0bc8bccf90a6d 100644
--- a/repl/pom.xml
+++ b/repl/pom.xml
@@ -68,10 +68,6 @@
       ${project.version}
       test
     
-    
-      org.eclipse.jetty
-      jetty-server
-    
     
       org.scala-lang
       scala-compiler
@@ -103,13 +99,6 @@
           true
         
       
-      
-        org.apache.maven.plugins
-        maven-install-plugin
-        
-          true
-        
-      
       
       
         org.codehaus.mojo
diff --git a/sql/core/pom.xml b/sql/core/pom.xml
index 023ce2041bb86..3e9ef07df9db6 100644
--- a/sql/core/pom.xml
+++ b/sql/core/pom.xml
@@ -56,12 +56,10 @@
     
       com.twitter
       parquet-column
-      ${parquet.version}
     
     
       com.twitter
       parquet-hadoop
-      ${parquet.version}
     
     
       com.fasterxml.jackson.core
diff --git a/sql/hive-thriftserver/pom.xml b/sql/hive-thriftserver/pom.xml
index d3a517375cf25..259eef0b80d03 100644
--- a/sql/hive-thriftserver/pom.xml
+++ b/sql/hive-thriftserver/pom.xml
@@ -42,19 +42,16 @@
       ${project.version}
     
     
-      org.spark-project.hive
+      ${hive.group}
       hive-cli
-      ${hive.version}
     
     
-      org.spark-project.hive
+      ${hive.group}
       hive-jdbc
-      ${hive.version}
     
     
-      org.spark-project.hive
+      ${hive.group}
       hive-beeline
-      ${hive.version}
     
   
   
diff --git a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/CliSuite.scala b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/CliSuite.scala
index e8ffbc5b954d4..60953576d0e37 100644
--- a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/CliSuite.scala
+++ b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/CliSuite.scala
@@ -48,6 +48,7 @@ class CliSuite extends FunSuite with BeforeAndAfterAll with Logging {
          |  --master local
          |  --hiveconf ${ConfVars.METASTORECONNECTURLKEY}=$jdbcUrl
          |  --hiveconf ${ConfVars.METASTOREWAREHOUSE}=$warehousePath
+         |  --driver-class-path ${sys.props("java.class.path")}
        """.stripMargin.split("\\s+").toSeq ++ extraArgs
     }
 
@@ -70,7 +71,7 @@ class CliSuite extends FunSuite with BeforeAndAfterAll with Logging {
     }
 
     // Searching expected output line from both stdout and stderr of the CLI process
-    val process = (Process(command) #< queryStream).run(
+    val process = (Process(command, None) #< queryStream).run(
       ProcessLogger(captureOutput("stdout"), captureOutput("stderr")))
 
     try {
diff --git a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suite.scala b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suite.scala
index 94d5ed4f1d15e..7814aa38f4146 100644
--- a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suite.scala
+++ b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suite.scala
@@ -142,6 +142,7 @@ class HiveThriftServer2Suite extends FunSuite with Logging {
              |  --hiveconf ${ConfVars.HIVE_SERVER2_THRIFT_BIND_HOST}=localhost
              |  --hiveconf ${ConfVars.HIVE_SERVER2_TRANSPORT_MODE}=http
              |  --hiveconf ${ConfVars.HIVE_SERVER2_THRIFT_HTTP_PORT}=$port
+             |  --driver-class-path ${sys.props("java.class.path")}
            """.stripMargin.split("\\s+").toSeq
       } else {
           s"""$startScript
@@ -151,6 +152,7 @@ class HiveThriftServer2Suite extends FunSuite with Logging {
              |  --hiveconf ${ConfVars.METASTOREWAREHOUSE}=$warehousePath
              |  --hiveconf ${ConfVars.HIVE_SERVER2_THRIFT_BIND_HOST}=localhost
              |  --hiveconf ${ConfVars.HIVE_SERVER2_THRIFT_PORT}=$port
+             |  --driver-class-path ${sys.props("java.class.path")}
            """.stripMargin.split("\\s+").toSeq
       }
 
@@ -179,8 +181,9 @@ class HiveThriftServer2Suite extends FunSuite with Logging {
       }
     }
 
-    // Resets SPARK_TESTING to avoid loading Log4J configurations in testing class paths
-    val env = Seq("SPARK_TESTING" -> "0")
+    val env = Seq(
+      // Resets SPARK_TESTING to avoid loading Log4J configurations in testing class paths
+      "SPARK_TESTING" -> "0")
 
     Process(command, None, env: _*).run(ProcessLogger(
       captureThriftServerOutput("stdout"),
@@ -214,7 +217,7 @@ class HiveThriftServer2Suite extends FunSuite with Logging {
     } finally {
       warehousePath.delete()
       metastorePath.delete()
-      Process(stopScript).run().exitValue()
+      Process(stopScript, None, env: _*).run().exitValue()
       // The `spark-daemon.sh' script uses kill, which is not synchronous, have to wait for a while.
       Thread.sleep(3.seconds.toMillis)
       Option(logTailingProcess).map(_.destroy())
diff --git a/sql/hive/pom.xml b/sql/hive/pom.xml
index 46aacad01113f..58b0722464be8 100644
--- a/sql/hive/pom.xml
+++ b/sql/hive/pom.xml
@@ -47,9 +47,8 @@
       ${project.version}
     
     
-      org.spark-project.hive
+      ${hive.group}
       hive-metastore
-      ${hive.version}
     
     
       commons-httpclient
@@ -57,51 +56,27 @@
       3.1
     
     
-      org.spark-project.hive
+      ${hive.group}
       hive-exec
-      ${hive.version}
-      
-        
-          commons-logging
-          commons-logging
-        
-        
-          com.esotericsoftware.kryo
-          kryo
-        
-      
     
     
       org.codehaus.jackson
       jackson-mapper-asl
     
     
-      org.spark-project.hive
+      ${hive.group}
       hive-serde
-      ${hive.version}
-      
-        
-          commons-logging
-          commons-logging
-        
-        
-          commons-logging
-          commons-logging-api
-        
-      
     
     
     
       org.apache.avro
       avro
-      ${avro.version}
     
     
     
       org.apache.avro
       avro-mapred
-      ${avro.version}
       ${avro.mapred.classifier}
     
     
diff --git a/streaming/pom.xml b/streaming/pom.xml
index 2023210d9b9be..d3c6d0347a622 100644
--- a/streaming/pom.xml
+++ b/streaming/pom.xml
@@ -68,13 +68,13 @@
     target/scala-${scala.binary.version}/classes
     target/scala-${scala.binary.version}/test-classes
     
-      
       
diff --git a/yarn/pom.xml b/yarn/pom.xml
index bcb77b3e3c70e..b86857db7bde6 100644
--- a/yarn/pom.xml
+++ b/yarn/pom.xml
@@ -131,13 +131,6 @@
           true
         
       
-      
-        org.apache.maven.plugins
-        maven-install-plugin
-        
-          true
-        
-      
     
 
     target/scala-${scala.binary.version}/classes
diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
index 8d0543771309b..c363d755c1752 100644
--- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
+++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
@@ -367,6 +367,10 @@ private[spark] class Client(
       }
     }
 
+    sys.env.get(ENV_DIST_CLASSPATH).foreach { dcp =>
+      env(ENV_DIST_CLASSPATH) = dcp
+    }
+
     env
   }
 
@@ -652,6 +656,9 @@ object Client extends Logging {
   val APP_FILE_PERMISSION: FsPermission =
     FsPermission.createImmutable(Integer.parseInt("644", 8).toShort)
 
+  // Distribution-defined classpath to add to processes
+  val ENV_DIST_CLASSPATH = "SPARK_DIST_CLASSPATH"
+
   /**
    * Find the user-defined Spark jar if configured, or return the jar containing this
    * class if not.

From 167a5ab0bd1d37f3ac23bec49e484a238610cf75 Mon Sep 17 00:00:00 2001
From: Nicholas Chammas 
Date: Thu, 8 Jan 2015 17:42:08 -0800
Subject: [PATCH 199/320] [SPARK-5122] Remove Shark from spark-ec2

I moved the Spark-Shark version map [to the wiki](https://cwiki.apache.org/confluence/display/SPARK/Spark-Shark+version+mapping).

This PR has a [matching PR in mesos/spark-ec2](https://github.com/mesos/spark-ec2/pull/89).

Author: Nicholas Chammas 

Closes #3939 from nchammas/remove-shark and squashes the following commits:

66e0841 [Nicholas Chammas] fix style
ceeab85 [Nicholas Chammas] show default Spark GitHub repo
7270126 [Nicholas Chammas] validate Spark hashes
db4935d [Nicholas Chammas] validate spark version upfront
fc0d5b9 [Nicholas Chammas] remove Shark
---
 ec2/spark_ec2.py | 78 +++++++++++++++++++++++++++---------------------
 1 file changed, 44 insertions(+), 34 deletions(-)

diff --git a/ec2/spark_ec2.py b/ec2/spark_ec2.py
index 485eea4f5e683..abab209a05ba0 100755
--- a/ec2/spark_ec2.py
+++ b/ec2/spark_ec2.py
@@ -39,10 +39,26 @@
 from optparse import OptionParser
 from sys import stderr
 
+VALID_SPARK_VERSIONS = set([
+    "0.7.3",
+    "0.8.0",
+    "0.8.1",
+    "0.9.0",
+    "0.9.1",
+    "0.9.2",
+    "1.0.0",
+    "1.0.1",
+    "1.0.2",
+    "1.1.0",
+    "1.1.1",
+    "1.2.0",
+])
+
 DEFAULT_SPARK_VERSION = "1.2.0"
+DEFAULT_SPARK_GITHUB_REPO = "https://github.com/apache/spark"
 SPARK_EC2_DIR = os.path.dirname(os.path.realpath(__file__))
-
 MESOS_SPARK_EC2_BRANCH = "branch-1.3"
+
 # A URL prefix from which to fetch AMI information
 AMI_PREFIX = "https://raw.github.com/mesos/spark-ec2/{b}/ami-list".format(b=MESOS_SPARK_EC2_BRANCH)
 
@@ -126,8 +142,8 @@ def parse_args():
         help="Version of Spark to use: 'X.Y.Z' or a specific git hash (default: %default)")
     parser.add_option(
         "--spark-git-repo",
-        default="https://github.com/apache/spark",
-        help="Github repo from which to checkout supplied commit hash")
+        default=DEFAULT_SPARK_GITHUB_REPO,
+        help="Github repo from which to checkout supplied commit hash (default: %default)")
     parser.add_option(
         "--hadoop-major-version", default="1",
         help="Major version of Hadoop (default: %default)")
@@ -236,6 +252,26 @@ def get_or_make_group(conn, name, vpc_id):
         return conn.create_security_group(name, "Spark EC2 group", vpc_id)
 
 
+def get_validate_spark_version(version, repo):
+    if "." in version:
+        version = version.replace("v", "")
+        if version not in VALID_SPARK_VERSIONS:
+            print >> stderr, "Don't know about Spark version: {v}".format(v=version)
+            sys.exit(1)
+        return version
+    else:
+        github_commit_url = "{repo}/commit/{commit_hash}".format(repo=repo, commit_hash=version)
+        request = urllib2.Request(github_commit_url)
+        request.get_method = lambda: 'HEAD'
+        try:
+            response = urllib2.urlopen(request)
+        except urllib2.HTTPError, e:
+            print >> stderr, "Couldn't validate Spark commit: {url}".format(url=github_commit_url)
+            print >> stderr, "Received HTTP response code of {code}.".format(code=e.code)
+            sys.exit(1)
+        return version
+
+
 # Check whether a given EC2 instance object is in a state we consider active,
 # i.e. not terminating or terminated. We count both stopping and stopped as
 # active since we can restart stopped clusters.
@@ -243,29 +279,6 @@ def is_active(instance):
     return (instance.state in ['pending', 'running', 'stopping', 'stopped'])
 
 
-# Return correct versions of Spark and Shark, given the supplied Spark version
-def get_spark_shark_version(opts):
-    spark_shark_map = {
-        "0.7.3": "0.7.1",
-        "0.8.0": "0.8.0",
-        "0.8.1": "0.8.1",
-        "0.9.0": "0.9.0",
-        "0.9.1": "0.9.1",
-        # These are dummy versions (no Shark versions after this)
-        "1.0.0": "1.0.0",
-        "1.0.1": "1.0.1",
-        "1.0.2": "1.0.2",
-        "1.1.0": "1.1.0",
-        "1.1.1": "1.1.1",
-        "1.2.0": "1.2.0",
-    }
-    version = opts.spark_version.replace("v", "")
-    if version not in spark_shark_map:
-        print >> stderr, "Don't know about Spark version: %s" % version
-        sys.exit(1)
-    return (version, spark_shark_map[version])
-
-
 # Attempt to resolve an appropriate AMI given the architecture and region of the request.
 # Source: http://aws.amazon.com/amazon-linux-ami/instance-type-matrix/
 # Last Updated: 2014-06-20
@@ -619,7 +632,7 @@ def setup_cluster(conn, master_nodes, slave_nodes, opts, deploy_ssh_key):
             print slave.public_dns_name
             ssh_write(slave.public_dns_name, opts, ['tar', 'x'], dot_ssh_tar)
 
-    modules = ['spark', 'shark', 'ephemeral-hdfs', 'persistent-hdfs',
+    modules = ['spark', 'ephemeral-hdfs', 'persistent-hdfs',
                'mapreduce', 'spark-standalone', 'tachyon']
 
     if opts.hadoop_major_version == "1":
@@ -706,9 +719,7 @@ def wait_for_cluster_state(conn, opts, cluster_instances, cluster_state):
     sys.stdout.flush()
 
     start_time = datetime.now()
-
     num_attempts = 0
-    conn = ec2.connect_to_region(opts.region)
 
     while True:
         time.sleep(5 * num_attempts)  # seconds
@@ -815,13 +826,11 @@ def deploy_files(conn, root_dir, opts, master_nodes, slave_nodes, modules):
     cluster_url = "%s:7077" % active_master
 
     if "." in opts.spark_version:
-        # Pre-built spark & shark deploy
-        (spark_v, shark_v) = get_spark_shark_version(opts)
+        # Pre-built Spark deploy
+        spark_v = get_validate_spark_version(opts.spark_version, opts.spark_git_repo)
     else:
         # Spark-only custom deploy
         spark_v = "%s|%s" % (opts.spark_git_repo, opts.spark_version)
-        shark_v = ""
-        modules = filter(lambda x: x != "shark", modules)
 
     template_vars = {
         "master_list": '\n'.join([i.public_dns_name for i in master_nodes]),
@@ -834,7 +843,6 @@ def deploy_files(conn, root_dir, opts, master_nodes, slave_nodes, modules):
         "swap": str(opts.swap),
         "modules": '\n'.join(modules),
         "spark_version": spark_v,
-        "shark_version": shark_v,
         "hadoop_major_version": opts.hadoop_major_version,
         "spark_worker_instances": "%d" % opts.worker_instances,
         "spark_master_opts": opts.master_opts
@@ -983,6 +991,8 @@ def real_main():
     (opts, action, cluster_name) = parse_args()
 
     # Input parameter validation
+    get_validate_spark_version(opts.spark_version, opts.spark_git_repo)
+
     if opts.wait is not None:
         # NOTE: DeprecationWarnings are silent in 2.7+ by default.
         #       To show them, run Python with the -Wdefault switch.

From f3da4bd7289d493014ad3c5176ada60794dfcfe0 Mon Sep 17 00:00:00 2001
From: WangTaoTheTonic 
Date: Fri, 9 Jan 2015 08:10:09 -0600
Subject: [PATCH 200/320] [SPARK-5169][YARN]fetch the correct max attempts

Soryy for fetching the wrong max attempts in this commit https://github.com/apache/spark/commit/8fdd48959c93b9cf809f03549e2ae6c4687d1fcd.
We need to fix it now.

tgravescs

If we set an spark.yarn.maxAppAttempts which is larger than `yarn.resourcemanager.am.max-attempts` in yarn side, it will be overrided as described here:
>The maximum number of application attempts. It's a global setting for all application masters. Each application master can specify its individual maximum number of application attempts via the API, but the individual number cannot be more than the global upper bound. If it is, the resourcemanager will override it. The default number is set to 2, to allow at least one retry for AM.

http://hadoop.apache.org/docs/r2.6.0/hadoop-yarn/hadoop-yarn-common/yarn-default.xml

Author: WangTaoTheTonic 

Closes #3942 from WangTaoTheTonic/HOTFIX and squashes the following commits:

9ac16ce [WangTaoTheTonic] fetch the correct max attempts
---
 .../org/apache/spark/deploy/yarn/YarnRMClient.scala  | 12 +++++++++---
 1 file changed, 9 insertions(+), 3 deletions(-)

diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnRMClient.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnRMClient.scala
index e183efccbb6f7..b45e599588ad3 100644
--- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnRMClient.scala
+++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnRMClient.scala
@@ -121,9 +121,15 @@ private[spark] class YarnRMClient(args: ApplicationMasterArguments) extends Logg
 
   /** Returns the maximum number of attempts to register the AM. */
   def getMaxRegAttempts(sparkConf: SparkConf, yarnConf: YarnConfiguration): Int = {
-    sparkConf.getOption("spark.yarn.maxAppAttempts").map(_.toInt).getOrElse(
-      yarnConf.getInt(
-        YarnConfiguration.RM_AM_MAX_ATTEMPTS, YarnConfiguration.DEFAULT_RM_AM_MAX_ATTEMPTS))
+    val sparkMaxAttempts = sparkConf.getOption("spark.yarn.maxAppAttempts").map(_.toInt)
+    val yarnMaxAttempts = yarnConf.getInt(
+      YarnConfiguration.RM_AM_MAX_ATTEMPTS, YarnConfiguration.DEFAULT_RM_AM_MAX_ATTEMPTS)
+    val retval: Int = sparkMaxAttempts match {
+      case Some(x) => if (x <= yarnMaxAttempts) x else yarnMaxAttempts
+      case None => yarnMaxAttempts
+    }
+
+    retval
   }
 
 }

From b4034c3f889bf24f60eb806802866b48e4cbe55c Mon Sep 17 00:00:00 2001
From: Aaron Davidson 
Date: Fri, 9 Jan 2015 09:20:16 -0800
Subject: [PATCH 201/320] [Minor] Fix test RetryingBlockFetcherSuite after
 changed config name

Flakey due to the default retry interval being the same as our test's wait timeout.

Author: Aaron Davidson 

Closes #3972 from aarondav/fix-test and squashes the following commits:

db77cab [Aaron Davidson] [Minor] Fix test after changed config name
---
 .../spark/network/shuffle/RetryingBlockFetcherSuite.java      | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/network/shuffle/src/test/java/org/apache/spark/network/shuffle/RetryingBlockFetcherSuite.java b/network/shuffle/src/test/java/org/apache/spark/network/shuffle/RetryingBlockFetcherSuite.java
index 0191fe529e1be..1ad0d72ae5ec5 100644
--- a/network/shuffle/src/test/java/org/apache/spark/network/shuffle/RetryingBlockFetcherSuite.java
+++ b/network/shuffle/src/test/java/org/apache/spark/network/shuffle/RetryingBlockFetcherSuite.java
@@ -54,13 +54,13 @@ public class RetryingBlockFetcherSuite {
   @Before
   public void beforeEach() {
     System.setProperty("spark.shuffle.io.maxRetries", "2");
-    System.setProperty("spark.shuffle.io.retryWaitMs", "0");
+    System.setProperty("spark.shuffle.io.retryWait", "0");
   }
 
   @After
   public void afterEach() {
     System.clearProperty("spark.shuffle.io.maxRetries");
-    System.clearProperty("spark.shuffle.io.retryWaitMs");
+    System.clearProperty("spark.shuffle.io.retryWait");
   }
 
   @Test

From 547df97715580f99ae573a49a86da12bf20cbc3d Mon Sep 17 00:00:00 2001
From: Sean Owen 
Date: Fri, 9 Jan 2015 09:35:46 -0800
Subject: [PATCH 202/320] SPARK-5136 [DOCS] Improve documentation around
 setting up Spark IntelliJ project

This PR simply points to the IntelliJ wiki page instead of also including IntelliJ notes in the docs. The intent however is to also update the wiki page with updated tips. This is the text I propose for the IntelliJ section on the wiki. I realize it omits some of the existing instructions on the wiki, about enabling Hive, but I think those are actually optional.

------

IntelliJ supports both Maven- and SBT-based projects. It is recommended, however, to import Spark as a Maven project. Choose "Import Project..." from the File menu, and select the `pom.xml` file in the Spark root directory.

It is fine to leave all settings at their default values in the Maven import wizard, with two caveats. First, it is usually useful to enable "Import Maven projects automatically", sincchanges to the project structure will automatically update the IntelliJ project.

Second, note the step that prompts you to choose active Maven build profiles. As documented above, some build configuration require specific profiles to be enabled. The same profiles that are enabled with `-P[profile name]` above may be enabled on this screen. For example, if developing for Hadoop 2.4 with YARN support, enable profiles `yarn` and `hadoop-2.4`.

These selections can be changed later by accessing the "Maven Projects" tool window from the View menu, and expanding the Profiles section.

"Rebuild Project" can fail the first time the project is compiled, because generate source files are not automatically generated. Try clicking the  "Generate Sources and Update Folders For All Projects" button in the "Maven Projects" tool window to manually generate these sources.

Compilation may fail with an error like "scalac: bad option: -P:/home/jakub/.m2/repository/org/scalamacros/paradise_2.10.4/2.0.1/paradise_2.10.4-2.0.1.jar". If so, go to Preferences > Build, Execution, Deployment > Scala Compiler and clear the "Additional compiler options" field. It will work then although the option will come back when the project reimports.

Author: Sean Owen 

Closes #3952 from srowen/SPARK-5136 and squashes the following commits:

f3baa66 [Sean Owen] Point to new IJ / Eclipse wiki link
016b7df [Sean Owen] Point to IntelliJ wiki page instead of also including IntelliJ notes in the docs
---
 docs/building-spark.md | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/docs/building-spark.md b/docs/building-spark.md
index c1bcd91b5b853..fb93017861ed0 100644
--- a/docs/building-spark.md
+++ b/docs/building-spark.md
@@ -151,9 +151,10 @@ Thus, the full flow for running continuous-compilation of the `core` submodule m
  $ mvn scala:cc
 ```
 
-# Using With IntelliJ IDEA
+# Building Spark with IntelliJ IDEA or Eclipse
 
-This setup works fine in IntelliJ IDEA 11.1.4. After opening the project via the pom.xml file in the project root folder, you only need to activate either the hadoop1 or hadoop2 profile in the "Maven Properties" popout. We have not tried Eclipse/Scala IDE with this.
+For help in setting up IntelliJ IDEA or Eclipse for Spark development, and troubleshooting, refer to the
+[wiki page for IDE setup](https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark#ContributingtoSpark-IDESetup).
 
 # Building Spark Debian Packages
 

From 1790b38695b46400a24b0b7e278e8e8388748211 Mon Sep 17 00:00:00 2001
From: Patrick Wendell 
Date: Fri, 9 Jan 2015 09:40:18 -0800
Subject: [PATCH 203/320] HOTFIX: Minor improvements to make-distribution.sh

1. Renames $FWDIR to $SPARK_HOME (vast majority of diff).
2. Use Spark-provided Maven.
3. Logs build flags in the RELEASE file.

Author: Patrick Wendell 

Closes #3973 from pwendell/master and squashes the following commits:

340a2fa [Patrick Wendell] HOTFIX: Minor improvements to make-distribution.sh
---
 make-distribution.sh | 61 ++++++++++++++++++++++++--------------------
 1 file changed, 34 insertions(+), 27 deletions(-)

diff --git a/make-distribution.sh b/make-distribution.sh
index 45c99e42e5a5b..4e2f400be3053 100755
--- a/make-distribution.sh
+++ b/make-distribution.sh
@@ -28,18 +28,20 @@ set -o pipefail
 set -e
 
 # Figure out where the Spark framework is installed
-FWDIR="$(cd "`dirname "$0"`"; pwd)"
-DISTDIR="$FWDIR/dist"
+SPARK_HOME="$(cd "`dirname "$0"`"; pwd)"
+DISTDIR="$SPARK_HOME/dist"
 
 SPARK_TACHYON=false
 MAKE_TGZ=false
 NAME=none
+MVN="$SPARK_HOME/build/mvn"
 
 function exit_with_usage {
   echo "make-distribution.sh - tool for making binary distributions of Spark"
   echo ""
   echo "usage:"
-  echo "./make-distribution.sh [--name] [--tgz] [--with-tachyon] "
+  cl_options="[--name] [--tgz] [--mvn ] [--with-tachyon]"
+  echo "./make-distribution.sh $cl_options "
   echo "See Spark's \"Building Spark\" doc for correct Maven options."
   echo ""
   exit 1
@@ -71,6 +73,10 @@ while (( "$#" )); do
     --tgz)
       MAKE_TGZ=true
       ;;
+    --mvn)
+      MVN="$2"
+      shift
+      ;;
     --name)
       NAME="$2"
       shift
@@ -109,9 +115,9 @@ if which git &>/dev/null; then
     unset GITREV
 fi
 
-if ! which mvn &>/dev/null; then
-    echo -e "You need Maven installed to build Spark."
-    echo -e "Download Maven from https://maven.apache.org/"
+if ! which $MVN &>/dev/null; then
+    echo -e "Could not locate Maven command: '$MVN'."
+    echo -e "Specify the Maven command with the --mvn flag"
     exit -1;
 fi
 
@@ -119,7 +125,7 @@ VERSION=$(mvn help:evaluate -Dexpression=project.version 2>/dev/null | grep -v "
 SPARK_HADOOP_VERSION=$(mvn help:evaluate -Dexpression=hadoop.version $@ 2>/dev/null\
     | grep -v "INFO"\
     | tail -n 1)
-SPARK_HIVE=$(mvn help:evaluate -Dexpression=project.activeProfiles -pl sql/hive $@ 2>/dev/null\
+SPARK_HIVE=$($MVN help:evaluate -Dexpression=project.activeProfiles -pl sql/hive $@ 2>/dev/null\
     | grep -v "INFO"\
     | fgrep --count "hive";\
     # Reset exit status to 0, otherwise the script stops here if the last grep finds nothing\
@@ -161,11 +167,11 @@ else
 fi
 
 # Build uber fat JAR
-cd "$FWDIR"
+cd "$SPARK_HOME"
 
 export MAVEN_OPTS="-Xmx2g -XX:MaxPermSize=512M -XX:ReservedCodeCacheSize=512m"
 
-BUILD_COMMAND="mvn clean package -DskipTests $@"
+BUILD_COMMAND="$MVN clean package -DskipTests $@"
 
 # Actually build the jar
 echo -e "\nBuilding with..."
@@ -177,41 +183,42 @@ ${BUILD_COMMAND}
 rm -rf "$DISTDIR"
 mkdir -p "$DISTDIR/lib"
 echo "Spark $VERSION$GITREVSTRING built for Hadoop $SPARK_HADOOP_VERSION" > "$DISTDIR/RELEASE"
+echo "Build flags: $@" >> "$DISTDIR/RELEASE"
 
 # Copy jars
-cp "$FWDIR"/assembly/target/scala*/*assembly*hadoop*.jar "$DISTDIR/lib/"
-cp "$FWDIR"/examples/target/scala*/spark-examples*.jar "$DISTDIR/lib/"
+cp "$SPARK_HOME"/assembly/target/scala*/*assembly*hadoop*.jar "$DISTDIR/lib/"
+cp "$SPARK_HOME"/examples/target/scala*/spark-examples*.jar "$DISTDIR/lib/"
 # This will fail if the -Pyarn profile is not provided
 # In this case, silence the error and ignore the return code of this command
-cp "$FWDIR"/network/yarn/target/scala*/spark-*-yarn-shuffle.jar "$DISTDIR/lib/" &> /dev/null || :
+cp "$SPARK_HOME"/network/yarn/target/scala*/spark-*-yarn-shuffle.jar "$DISTDIR/lib/" &> /dev/null || :
 
 # Copy example sources (needed for python and SQL)
 mkdir -p "$DISTDIR/examples/src/main"
-cp -r "$FWDIR"/examples/src/main "$DISTDIR/examples/src/"
+cp -r "$SPARK_HOME"/examples/src/main "$DISTDIR/examples/src/"
 
 if [ "$SPARK_HIVE" == "1" ]; then
-  cp "$FWDIR"/lib_managed/jars/datanucleus*.jar "$DISTDIR/lib/"
+  cp "$SPARK_HOME"/lib_managed/jars/datanucleus*.jar "$DISTDIR/lib/"
 fi
 
 # Copy license and ASF files
-cp "$FWDIR/LICENSE" "$DISTDIR"
-cp "$FWDIR/NOTICE" "$DISTDIR"
+cp "$SPARK_HOME/LICENSE" "$DISTDIR"
+cp "$SPARK_HOME/NOTICE" "$DISTDIR"
 
-if [ -e "$FWDIR"/CHANGES.txt ]; then
-  cp "$FWDIR/CHANGES.txt" "$DISTDIR"
+if [ -e "$SPARK_HOME"/CHANGES.txt ]; then
+  cp "$SPARK_HOME/CHANGES.txt" "$DISTDIR"
 fi
 
 # Copy data files
-cp -r "$FWDIR/data" "$DISTDIR"
+cp -r "$SPARK_HOME/data" "$DISTDIR"
 
 # Copy other things
 mkdir "$DISTDIR"/conf
-cp "$FWDIR"/conf/*.template "$DISTDIR"/conf
-cp "$FWDIR/README.md" "$DISTDIR"
-cp -r "$FWDIR/bin" "$DISTDIR"
-cp -r "$FWDIR/python" "$DISTDIR"
-cp -r "$FWDIR/sbin" "$DISTDIR"
-cp -r "$FWDIR/ec2" "$DISTDIR"
+cp "$SPARK_HOME"/conf/*.template "$DISTDIR"/conf
+cp "$SPARK_HOME/README.md" "$DISTDIR"
+cp -r "$SPARK_HOME/bin" "$DISTDIR"
+cp -r "$SPARK_HOME/python" "$DISTDIR"
+cp -r "$SPARK_HOME/sbin" "$DISTDIR"
+cp -r "$SPARK_HOME/ec2" "$DISTDIR"
 
 # Download and copy in tachyon, if requested
 if [ "$SPARK_TACHYON" == "true" ]; then
@@ -243,9 +250,9 @@ fi
 
 if [ "$MAKE_TGZ" == "true" ]; then
   TARDIR_NAME=spark-$VERSION-bin-$NAME
-  TARDIR="$FWDIR/$TARDIR_NAME"
+  TARDIR="$SPARK_HOME/$TARDIR_NAME"
   rm -rf "$TARDIR"
   cp -r "$DISTDIR" "$TARDIR"
-  tar czf "spark-$VERSION-bin-$NAME.tgz" -C "$FWDIR" "$TARDIR_NAME"
+  tar czf "spark-$VERSION-bin-$NAME.tgz" -C "$SPARK_HOME" "$TARDIR_NAME"
   rm -rf "$TARDIR"
 fi

From b6aa557300275b835cce7baa7bc8a80eb5425cbb Mon Sep 17 00:00:00 2001
From: Kay Ousterhout 
Date: Fri, 9 Jan 2015 09:47:06 -0800
Subject: [PATCH 204/320] [SPARK-1143] Separate pool tests into their own
 suite.

The current TaskSchedulerImplSuite includes some tests that are
actually for the TaskSchedulerImpl, but the remainder of the tests avoid using
the TaskSchedulerImpl entirely, and actually test the pool and scheduling
algorithm mechanisms. This commit separates the pool/scheduling algorithm
tests into their own suite, and also simplifies those tests.

The pull request replaces #339.

Author: Kay Ousterhout 

Closes #3967 from kayousterhout/SPARK-1143 and squashes the following commits:

8a898c4 [Kay Ousterhout] [SPARK-1143] Separate pool tests into their own suite.
---
 .../apache/spark/scheduler/PoolSuite.scala    | 183 ++++++++++++++
 .../scheduler/TaskSchedulerImplSuite.scala    | 230 ------------------
 2 files changed, 183 insertions(+), 230 deletions(-)
 create mode 100644 core/src/test/scala/org/apache/spark/scheduler/PoolSuite.scala

diff --git a/core/src/test/scala/org/apache/spark/scheduler/PoolSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/PoolSuite.scala
new file mode 100644
index 0000000000000..e8f461e2f56c9
--- /dev/null
+++ b/core/src/test/scala/org/apache/spark/scheduler/PoolSuite.scala
@@ -0,0 +1,183 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.scheduler
+
+import java.util.Properties
+
+import org.scalatest.FunSuite
+
+import org.apache.spark.{LocalSparkContext, SparkConf, SparkContext}
+
+/**
+ * Tests that pools and the associated scheduling algorithms for FIFO and fair scheduling work
+ * correctly.
+ */
+class PoolSuite extends FunSuite with LocalSparkContext {
+
+  def createTaskSetManager(stageId: Int, numTasks: Int, taskScheduler: TaskSchedulerImpl)
+    : TaskSetManager = {
+    val tasks = Array.tabulate[Task[_]](numTasks) { i =>
+      new FakeTask(i, Nil)
+    }
+    new TaskSetManager(taskScheduler, new TaskSet(tasks, stageId, 0, 0, null), 0)
+  }
+
+  def scheduleTaskAndVerifyId(taskId: Int, rootPool: Pool, expectedStageId: Int) {
+    val taskSetQueue = rootPool.getSortedTaskSetQueue
+    val nextTaskSetToSchedule =
+      taskSetQueue.find(t => (t.runningTasks + t.tasksSuccessful) < t.numTasks)
+    assert(nextTaskSetToSchedule.isDefined)
+    nextTaskSetToSchedule.get.addRunningTask(taskId)
+    assert(nextTaskSetToSchedule.get.stageId === expectedStageId)
+  }
+
+  test("FIFO Scheduler Test") {
+    sc = new SparkContext("local", "TaskSchedulerImplSuite")
+    val taskScheduler = new TaskSchedulerImpl(sc)
+
+    val rootPool = new Pool("", SchedulingMode.FIFO, 0, 0)
+    val schedulableBuilder = new FIFOSchedulableBuilder(rootPool)
+    schedulableBuilder.buildPools()
+
+    val taskSetManager0 = createTaskSetManager(0, 2, taskScheduler)
+    val taskSetManager1 = createTaskSetManager(1, 2, taskScheduler)
+    val taskSetManager2 = createTaskSetManager(2, 2, taskScheduler)
+    schedulableBuilder.addTaskSetManager(taskSetManager0, null)
+    schedulableBuilder.addTaskSetManager(taskSetManager1, null)
+    schedulableBuilder.addTaskSetManager(taskSetManager2, null)
+
+    scheduleTaskAndVerifyId(0, rootPool, 0)
+    scheduleTaskAndVerifyId(1, rootPool, 0)
+    scheduleTaskAndVerifyId(2, rootPool, 1)
+    scheduleTaskAndVerifyId(3, rootPool, 1)
+    scheduleTaskAndVerifyId(4, rootPool, 2)
+    scheduleTaskAndVerifyId(5, rootPool, 2)
+  }
+
+  /**
+   * This test creates three scheduling pools, and creates task set managers in the first
+   * two scheduling pools. The test verifies that as tasks are scheduled, the fair scheduling
+   * algorithm properly orders the two scheduling pools.
+   */
+  test("Fair Scheduler Test") {
+    val xmlPath = getClass.getClassLoader.getResource("fairscheduler.xml").getFile()
+    val conf = new SparkConf().set("spark.scheduler.allocation.file", xmlPath)
+    sc = new SparkContext("local", "TaskSchedulerImplSuite", conf)
+    val taskScheduler = new TaskSchedulerImpl(sc)
+
+    val rootPool = new Pool("", SchedulingMode.FAIR, 0, 0)
+    val schedulableBuilder = new FairSchedulableBuilder(rootPool, sc.conf)
+    schedulableBuilder.buildPools()
+
+    // Ensure that the XML file was read in correctly.
+    assert(rootPool.getSchedulableByName("default") != null)
+    assert(rootPool.getSchedulableByName("1") != null)
+    assert(rootPool.getSchedulableByName("2") != null)
+    assert(rootPool.getSchedulableByName("3") != null)
+    assert(rootPool.getSchedulableByName("1").minShare === 2)
+    assert(rootPool.getSchedulableByName("1").weight === 1)
+    assert(rootPool.getSchedulableByName("2").minShare === 3)
+    assert(rootPool.getSchedulableByName("2").weight === 1)
+    assert(rootPool.getSchedulableByName("3").minShare === 0)
+    assert(rootPool.getSchedulableByName("3").weight === 1)
+
+    val properties1 = new Properties()
+    properties1.setProperty("spark.scheduler.pool","1")
+    val properties2 = new Properties()
+    properties2.setProperty("spark.scheduler.pool","2")
+
+    val taskSetManager10 = createTaskSetManager(0, 1, taskScheduler)
+    val taskSetManager11 = createTaskSetManager(1, 1, taskScheduler)
+    val taskSetManager12 = createTaskSetManager(2, 2, taskScheduler)
+    schedulableBuilder.addTaskSetManager(taskSetManager10, properties1)
+    schedulableBuilder.addTaskSetManager(taskSetManager11, properties1)
+    schedulableBuilder.addTaskSetManager(taskSetManager12, properties1)
+
+    val taskSetManager23 = createTaskSetManager(3, 2, taskScheduler)
+    val taskSetManager24 = createTaskSetManager(4, 2, taskScheduler)
+    schedulableBuilder.addTaskSetManager(taskSetManager23, properties2)
+    schedulableBuilder.addTaskSetManager(taskSetManager24, properties2)
+
+    // Pool 1 share ratio: 0. Pool 2 share ratio: 0. 1 gets scheduled based on ordering of names.
+    scheduleTaskAndVerifyId(0, rootPool, 0)
+    // Pool 1 share ratio: 1/2. Pool 2 share ratio: 0. 2 gets scheduled because ratio is lower.
+    scheduleTaskAndVerifyId(1, rootPool, 3)
+    // Pool 1 share ratio: 1/2. Pool 2 share ratio: 1/3. 2 gets scheduled because ratio is lower.
+    scheduleTaskAndVerifyId(2, rootPool, 3)
+    // Pool 1 share ratio: 1/2. Pool 2 share ratio: 2/3. 1 gets scheduled because ratio is lower.
+    scheduleTaskAndVerifyId(3, rootPool, 1)
+    // Pool 1 share ratio: 1. Pool 2 share ratio: 2/3. 2 gets scheduled because ratio is lower.
+    scheduleTaskAndVerifyId(4, rootPool, 4)
+    // Neither pool is needy so ordering is based on number of running tasks.
+    // Pool 1 running tasks: 2, Pool 2 running tasks: 3. 1 gets scheduled because fewer running
+    // tasks.
+    scheduleTaskAndVerifyId(5, rootPool, 2)
+    // Pool 1 running tasks: 3, Pool 2 running tasks: 3. 1 gets scheduled because of naming
+    // ordering.
+    scheduleTaskAndVerifyId(6, rootPool, 2)
+    // Pool 1 running tasks: 4, Pool 2 running tasks: 3. 2 gets scheduled because fewer running
+    // tasks.
+    scheduleTaskAndVerifyId(7, rootPool, 4)
+  }
+
+  test("Nested Pool Test") {
+    sc = new SparkContext("local", "TaskSchedulerImplSuite")
+    val taskScheduler = new TaskSchedulerImpl(sc)
+
+    val rootPool = new Pool("", SchedulingMode.FAIR, 0, 0)
+    val pool0 = new Pool("0", SchedulingMode.FAIR, 3, 1)
+    val pool1 = new Pool("1", SchedulingMode.FAIR, 4, 1)
+    rootPool.addSchedulable(pool0)
+    rootPool.addSchedulable(pool1)
+
+    val pool00 = new Pool("00", SchedulingMode.FAIR, 2, 2)
+    val pool01 = new Pool("01", SchedulingMode.FAIR, 1, 1)
+    pool0.addSchedulable(pool00)
+    pool0.addSchedulable(pool01)
+
+    val pool10 = new Pool("10", SchedulingMode.FAIR, 2, 2)
+    val pool11 = new Pool("11", SchedulingMode.FAIR, 2, 1)
+    pool1.addSchedulable(pool10)
+    pool1.addSchedulable(pool11)
+
+    val taskSetManager000 = createTaskSetManager(0, 5, taskScheduler)
+    val taskSetManager001 = createTaskSetManager(1, 5, taskScheduler)
+    pool00.addSchedulable(taskSetManager000)
+    pool00.addSchedulable(taskSetManager001)
+
+    val taskSetManager010 = createTaskSetManager(2, 5, taskScheduler)
+    val taskSetManager011 = createTaskSetManager(3, 5, taskScheduler)
+    pool01.addSchedulable(taskSetManager010)
+    pool01.addSchedulable(taskSetManager011)
+
+    val taskSetManager100 = createTaskSetManager(4, 5, taskScheduler)
+    val taskSetManager101 = createTaskSetManager(5, 5, taskScheduler)
+    pool10.addSchedulable(taskSetManager100)
+    pool10.addSchedulable(taskSetManager101)
+
+    val taskSetManager110 = createTaskSetManager(6, 5, taskScheduler)
+    val taskSetManager111 = createTaskSetManager(7, 5, taskScheduler)
+    pool11.addSchedulable(taskSetManager110)
+    pool11.addSchedulable(taskSetManager111)
+
+    scheduleTaskAndVerifyId(0, rootPool, 0)
+    scheduleTaskAndVerifyId(1, rootPool, 4)
+    scheduleTaskAndVerifyId(2, rootPool, 6)
+    scheduleTaskAndVerifyId(3, rootPool, 2)
+  }
+}
diff --git a/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala
index 00812e6018d1f..8874cf00e9993 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala
@@ -30,238 +30,8 @@ class FakeSchedulerBackend extends SchedulerBackend {
   def defaultParallelism() = 1
 }
 
-class FakeTaskSetManager(
-    initPriority: Int,
-    initStageId: Int,
-    initNumTasks: Int,
-    taskScheduler: TaskSchedulerImpl,
-    taskSet: TaskSet)
-  extends TaskSetManager(taskScheduler, taskSet, 0) {
-
-  parent = null
-  weight = 1
-  minShare = 2
-  priority = initPriority
-  stageId = initStageId
-  name = "TaskSet_"+stageId
-  override val numTasks = initNumTasks
-  tasksSuccessful = 0
-
-  var numRunningTasks = 0
-  override def runningTasks = numRunningTasks
-
-  def increaseRunningTasks(taskNum: Int) {
-    numRunningTasks += taskNum
-    if (parent != null) {
-      parent.increaseRunningTasks(taskNum)
-    }
-  }
-
-  def decreaseRunningTasks(taskNum: Int) {
-    numRunningTasks -= taskNum
-    if (parent != null) {
-      parent.decreaseRunningTasks(taskNum)
-    }
-  }
-
-  override def addSchedulable(schedulable: Schedulable) {
-  }
-
-  override def removeSchedulable(schedulable: Schedulable) {
-  }
-
-  override def getSchedulableByName(name: String): Schedulable = {
-    null
-  }
-
-  override def executorLost(executorId: String, host: String): Unit = {
-  }
-
-  override def resourceOffer(
-      execId: String,
-      host: String,
-      maxLocality: TaskLocality.TaskLocality)
-    : Option[TaskDescription] =
-  {
-    if (tasksSuccessful + numRunningTasks < numTasks) {
-      increaseRunningTasks(1)
-      Some(new TaskDescription(0, execId, "task 0:0", 0, null))
-    } else {
-      None
-    }
-  }
-
-  override def checkSpeculatableTasks(): Boolean = {
-    true
-  }
-
-  def taskFinished() {
-    decreaseRunningTasks(1)
-    tasksSuccessful +=1
-    if (tasksSuccessful == numTasks) {
-      parent.removeSchedulable(this)
-    }
-  }
-
-  def abort() {
-    decreaseRunningTasks(numRunningTasks)
-    parent.removeSchedulable(this)
-  }
-}
-
 class TaskSchedulerImplSuite extends FunSuite with LocalSparkContext with Logging {
 
-  def createDummyTaskSetManager(priority: Int, stage: Int, numTasks: Int, cs: TaskSchedulerImpl,
-      taskSet: TaskSet): FakeTaskSetManager = {
-    new FakeTaskSetManager(priority, stage, numTasks, cs , taskSet)
-  }
-
-  def resourceOffer(rootPool: Pool): Int = {
-    val taskSetQueue = rootPool.getSortedTaskSetQueue
-    /* Just for Test*/
-    for (manager <- taskSetQueue) {
-       logInfo("parentName:%s, parent running tasks:%d, name:%s,runningTasks:%d".format(
-         manager.parent.name, manager.parent.runningTasks, manager.name, manager.runningTasks))
-    }
-    for (taskSet <- taskSetQueue) {
-      taskSet.resourceOffer("execId_1", "hostname_1", TaskLocality.ANY) match {
-        case Some(task) =>
-          return taskSet.stageId
-        case None => {}
-      }
-    }
-    -1
-  }
-
-  def checkTaskSetId(rootPool: Pool, expectedTaskSetId: Int) {
-    assert(resourceOffer(rootPool) === expectedTaskSetId)
-  }
-
-  test("FIFO Scheduler Test") {
-    sc = new SparkContext("local", "TaskSchedulerImplSuite")
-    val taskScheduler = new TaskSchedulerImpl(sc)
-    val taskSet = FakeTask.createTaskSet(1)
-
-    val rootPool = new Pool("", SchedulingMode.FIFO, 0, 0)
-    val schedulableBuilder = new FIFOSchedulableBuilder(rootPool)
-    schedulableBuilder.buildPools()
-
-    val taskSetManager0 = createDummyTaskSetManager(0, 0, 2, taskScheduler, taskSet)
-    val taskSetManager1 = createDummyTaskSetManager(0, 1, 2, taskScheduler, taskSet)
-    val taskSetManager2 = createDummyTaskSetManager(0, 2, 2, taskScheduler, taskSet)
-    schedulableBuilder.addTaskSetManager(taskSetManager0, null)
-    schedulableBuilder.addTaskSetManager(taskSetManager1, null)
-    schedulableBuilder.addTaskSetManager(taskSetManager2, null)
-
-    checkTaskSetId(rootPool, 0)
-    resourceOffer(rootPool)
-    checkTaskSetId(rootPool, 1)
-    resourceOffer(rootPool)
-    taskSetManager1.abort()
-    checkTaskSetId(rootPool, 2)
-  }
-
-  test("Fair Scheduler Test") {
-    val xmlPath = getClass.getClassLoader.getResource("fairscheduler.xml").getFile()
-    val conf = new SparkConf().set("spark.scheduler.allocation.file", xmlPath)
-    sc = new SparkContext("local", "TaskSchedulerImplSuite", conf)
-    val taskScheduler = new TaskSchedulerImpl(sc)
-    val taskSet = FakeTask.createTaskSet(1)
-
-    val rootPool = new Pool("", SchedulingMode.FAIR, 0, 0)
-    val schedulableBuilder = new FairSchedulableBuilder(rootPool, sc.conf)
-    schedulableBuilder.buildPools()
-
-    assert(rootPool.getSchedulableByName("default") != null)
-    assert(rootPool.getSchedulableByName("1") != null)
-    assert(rootPool.getSchedulableByName("2") != null)
-    assert(rootPool.getSchedulableByName("3") != null)
-    assert(rootPool.getSchedulableByName("1").minShare === 2)
-    assert(rootPool.getSchedulableByName("1").weight === 1)
-    assert(rootPool.getSchedulableByName("2").minShare === 3)
-    assert(rootPool.getSchedulableByName("2").weight === 1)
-    assert(rootPool.getSchedulableByName("3").minShare === 0)
-    assert(rootPool.getSchedulableByName("3").weight === 1)
-
-    val properties1 = new Properties()
-    properties1.setProperty("spark.scheduler.pool","1")
-    val properties2 = new Properties()
-    properties2.setProperty("spark.scheduler.pool","2")
-
-    val taskSetManager10 = createDummyTaskSetManager(1, 0, 1, taskScheduler, taskSet)
-    val taskSetManager11 = createDummyTaskSetManager(1, 1, 1, taskScheduler, taskSet)
-    val taskSetManager12 = createDummyTaskSetManager(1, 2, 2, taskScheduler, taskSet)
-    schedulableBuilder.addTaskSetManager(taskSetManager10, properties1)
-    schedulableBuilder.addTaskSetManager(taskSetManager11, properties1)
-    schedulableBuilder.addTaskSetManager(taskSetManager12, properties1)
-
-    val taskSetManager23 = createDummyTaskSetManager(2, 3, 2, taskScheduler, taskSet)
-    val taskSetManager24 = createDummyTaskSetManager(2, 4, 2, taskScheduler, taskSet)
-    schedulableBuilder.addTaskSetManager(taskSetManager23, properties2)
-    schedulableBuilder.addTaskSetManager(taskSetManager24, properties2)
-
-    checkTaskSetId(rootPool, 0)
-    checkTaskSetId(rootPool, 3)
-    checkTaskSetId(rootPool, 3)
-    checkTaskSetId(rootPool, 1)
-    checkTaskSetId(rootPool, 4)
-    checkTaskSetId(rootPool, 2)
-    checkTaskSetId(rootPool, 2)
-    checkTaskSetId(rootPool, 4)
-
-    taskSetManager12.taskFinished()
-    assert(rootPool.getSchedulableByName("1").runningTasks === 3)
-    taskSetManager24.abort()
-    assert(rootPool.getSchedulableByName("2").runningTasks === 2)
-  }
-
-  test("Nested Pool Test") {
-    sc = new SparkContext("local", "TaskSchedulerImplSuite")
-    val taskScheduler = new TaskSchedulerImpl(sc)
-    val taskSet = FakeTask.createTaskSet(1)
-
-    val rootPool = new Pool("", SchedulingMode.FAIR, 0, 0)
-    val pool0 = new Pool("0", SchedulingMode.FAIR, 3, 1)
-    val pool1 = new Pool("1", SchedulingMode.FAIR, 4, 1)
-    rootPool.addSchedulable(pool0)
-    rootPool.addSchedulable(pool1)
-
-    val pool00 = new Pool("00", SchedulingMode.FAIR, 2, 2)
-    val pool01 = new Pool("01", SchedulingMode.FAIR, 1, 1)
-    pool0.addSchedulable(pool00)
-    pool0.addSchedulable(pool01)
-
-    val pool10 = new Pool("10", SchedulingMode.FAIR, 2, 2)
-    val pool11 = new Pool("11", SchedulingMode.FAIR, 2, 1)
-    pool1.addSchedulable(pool10)
-    pool1.addSchedulable(pool11)
-
-    val taskSetManager000 = createDummyTaskSetManager(0, 0, 5, taskScheduler, taskSet)
-    val taskSetManager001 = createDummyTaskSetManager(0, 1, 5, taskScheduler, taskSet)
-    pool00.addSchedulable(taskSetManager000)
-    pool00.addSchedulable(taskSetManager001)
-
-    val taskSetManager010 = createDummyTaskSetManager(1, 2, 5, taskScheduler, taskSet)
-    val taskSetManager011 = createDummyTaskSetManager(1, 3, 5, taskScheduler, taskSet)
-    pool01.addSchedulable(taskSetManager010)
-    pool01.addSchedulable(taskSetManager011)
-
-    val taskSetManager100 = createDummyTaskSetManager(2, 4, 5, taskScheduler, taskSet)
-    val taskSetManager101 = createDummyTaskSetManager(2, 5, 5, taskScheduler, taskSet)
-    pool10.addSchedulable(taskSetManager100)
-    pool10.addSchedulable(taskSetManager101)
-
-    val taskSetManager110 = createDummyTaskSetManager(3, 6, 5, taskScheduler, taskSet)
-    val taskSetManager111 = createDummyTaskSetManager(3, 7, 5, taskScheduler, taskSet)
-    pool11.addSchedulable(taskSetManager110)
-    pool11.addSchedulable(taskSetManager111)
-
-    checkTaskSetId(rootPool, 0)
-    checkTaskSetId(rootPool, 4)
-    checkTaskSetId(rootPool, 6)
-    checkTaskSetId(rootPool, 2)
-  }
-
   test("Scheduler does not always schedule tasks on the same workers") {
     sc = new SparkContext("local", "TaskSchedulerImplSuite")
     val taskScheduler = new TaskSchedulerImpl(sc)

From e9ca16ec943b9553056482d0c085eacb6046821e Mon Sep 17 00:00:00 2001
From: Liang-Chi Hsieh 
Date: Fri, 9 Jan 2015 10:27:33 -0800
Subject: [PATCH 205/320] [SPARK-5145][Mllib] Add BLAS.dsyr and use it in
 GaussianMixtureEM

This pr uses BLAS.dsyr to replace few implementations in GaussianMixtureEM.

Author: Liang-Chi Hsieh 

Closes #3949 from viirya/blas_dsyr and squashes the following commits:

4e4d6cf [Liang-Chi Hsieh] Add unit test. Rename function name, modify doc and style.
3f57fd2 [Liang-Chi Hsieh] Add BLAS.dsyr and use it in GaussianMixtureEM.
---
 .../mllib/clustering/GaussianMixtureEM.scala  | 10 +++--
 .../org/apache/spark/mllib/linalg/BLAS.scala  | 26 ++++++++++++
 .../apache/spark/mllib/linalg/BLASSuite.scala | 41 +++++++++++++++++++
 3 files changed, 73 insertions(+), 4 deletions(-)

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureEM.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureEM.scala
index bdf984aee4dae..3a6c0e681e3fa 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureEM.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureEM.scala
@@ -21,7 +21,7 @@ import scala.collection.mutable.IndexedSeq
 
 import breeze.linalg.{DenseVector => BreezeVector, DenseMatrix => BreezeMatrix, diag, Transpose}
 import org.apache.spark.rdd.RDD
-import org.apache.spark.mllib.linalg.{Matrices, Vector, Vectors}
+import org.apache.spark.mllib.linalg.{Matrices, Vector, Vectors, DenseVector, DenseMatrix, BLAS}
 import org.apache.spark.mllib.stat.impl.MultivariateGaussian
 import org.apache.spark.mllib.util.MLUtils
 
@@ -151,9 +151,10 @@ class GaussianMixtureEM private (
       var i = 0
       while (i < k) {
         val mu = sums.means(i) / sums.weights(i)
-        val sigma = sums.sigmas(i) / sums.weights(i) - mu * new Transpose(mu) // TODO: Use BLAS.dsyr
+        BLAS.syr(-sums.weights(i), Vectors.fromBreeze(mu).asInstanceOf[DenseVector],
+          Matrices.fromBreeze(sums.sigmas(i)).asInstanceOf[DenseMatrix])
         weights(i) = sums.weights(i) / sumWeights
-        gaussians(i) = new MultivariateGaussian(mu, sigma)
+        gaussians(i) = new MultivariateGaussian(mu, sums.sigmas(i) / sums.weights(i))
         i = i + 1
       }
    
@@ -211,7 +212,8 @@ private object ExpectationSum {
       p(i) /= pSum
       sums.weights(i) += p(i)
       sums.means(i) += x * p(i)
-      sums.sigmas(i) += xxt * p(i) // TODO: use BLAS.dsyr
+      BLAS.syr(p(i), Vectors.fromBreeze(x).asInstanceOf[DenseVector],
+        Matrices.fromBreeze(sums.sigmas(i)).asInstanceOf[DenseMatrix])
       i = i + 1
     }
     sums
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/BLAS.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/BLAS.scala
index 9fed513becddc..3414daccd7ca4 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/BLAS.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/BLAS.scala
@@ -228,6 +228,32 @@ private[spark] object BLAS extends Serializable with Logging {
     }
     _nativeBLAS
   }
+ 
+  /**
+   * A := alpha * x * x^T^ + A
+   * @param alpha a real scalar that will be multiplied to x * x^T^.
+   * @param x the vector x that contains the n elements.
+   * @param A the symmetric matrix A. Size of n x n.
+   */
+  def syr(alpha: Double, x: DenseVector, A: DenseMatrix) {
+    val mA = A.numRows
+    val nA = A.numCols
+    require(mA == nA, s"A is not a symmetric matrix. A: $mA x $nA")
+    require(mA == x.size, s"The size of x doesn't match the rank of A. A: $mA x $nA, x: ${x.size}")
+
+    nativeBLAS.dsyr("U", x.size, alpha, x.values, 1, A.values, nA)
+
+    // Fill lower triangular part of A
+    var i = 0
+    while (i < mA) {
+      var j = i + 1
+      while (j < nA) {
+        A(j, i) = A(i, j)
+        j += 1
+      }
+      i += 1
+    }    
+  }
 
   /**
    * C := alpha * A * B + beta * C
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/BLASSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/BLASSuite.scala
index 5d70c914f14b0..771878e925ea7 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/BLASSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/BLASSuite.scala
@@ -127,6 +127,47 @@ class BLASSuite extends FunSuite {
     }
   }
 
+  test("syr") {
+    val dA = new DenseMatrix(4, 4,
+      Array(0.0, 1.2, 2.2, 3.1, 1.2, 3.2, 5.3, 4.6, 2.2, 5.3, 1.8, 3.0, 3.1, 4.6, 3.0, 0.8))
+    val x = new DenseVector(Array(0.0, 2.7, 3.5, 2.1))
+    val alpha = 0.15
+
+    val expected = new DenseMatrix(4, 4,
+      Array(0.0, 1.2, 2.2, 3.1, 1.2, 4.2935, 6.7175, 5.4505, 2.2, 6.7175, 3.6375, 4.1025, 3.1,
+        5.4505, 4.1025, 1.4615))
+
+    syr(alpha, x, dA)
+
+    assert(dA ~== expected absTol 1e-15)
+ 
+    val dB =
+      new DenseMatrix(3, 4, Array(0.0, 1.2, 2.2, 3.1, 1.2, 3.2, 5.3, 4.6, 2.2, 5.3, 1.8, 3.0))
+
+    withClue("Matrix A must be a symmetric Matrix") {
+      intercept[Exception] {
+        syr(alpha, x, dB)
+      }
+    }
+ 
+    val dC =
+      new DenseMatrix(3, 3, Array(0.0, 1.2, 2.2, 1.2, 3.2, 5.3, 2.2, 5.3, 1.8))
+
+    withClue("Size of vector must match the rank of matrix") {
+      intercept[Exception] {
+        syr(alpha, x, dC)
+      }
+    }
+ 
+    val y = new DenseVector(Array(0.0, 2.7, 3.5, 2.1, 1.5))
+
+    withClue("Size of vector must match the rank of matrix") {
+      intercept[Exception] {
+        syr(alpha, y, dA)
+      }
+    }
+  }
+
   test("gemm") {
 
     val dA =

From 454fe129ee97b859bf079db8b9158e115a219ad5 Mon Sep 17 00:00:00 2001
From: Jongyoul Lee 
Date: Fri, 9 Jan 2015 10:47:08 -0800
Subject: [PATCH 206/320] [SPARK-3619] Upgrade to Mesos 0.21 to work around
 MESOS-1688

- update version from 0.18.1 to 0.21.0
- I'm doing some tests in order to verify some spark jobs work fine on mesos 0.21.0 environment.

Author: Jongyoul Lee 

Closes #3934 from jongyoul/SPARK-3619 and squashes the following commits:

ab994fa [Jongyoul Lee] [SPARK-3619] Upgrade to Mesos 0.21 to work around MESOS-1688 - update version from 0.18.1 to 0.21.0
---
 pom.xml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pom.xml b/pom.xml
index 703e5c47bf59b..aadcdfd1083c5 100644
--- a/pom.xml
+++ b/pom.xml
@@ -115,7 +115,7 @@
     1.6
     spark
     2.0.1
-    0.18.1
+    0.21.0
     shaded-protobuf
     1.7.5
     1.2.17

From 7e8e62aec11c43c983055adc475b96006412199a Mon Sep 17 00:00:00 2001
From: "Joseph K. Bradley" 
Date: Fri, 9 Jan 2015 13:00:15 -0800
Subject: [PATCH 207/320] [SPARK-5015] [mllib] Random seed for GMM + make test
 suite deterministic

Issues:
* From JIRA: GaussianMixtureEM uses randomness but does not take a random seed. It should take one as a parameter.
* This also makes the test suite flaky since initialization can fail due to stochasticity.

Fix:
* Add random seed
* Use it in test suite

CC: mengxr  tgaloppo

Author: Joseph K. Bradley 

Closes #3981 from jkbradley/gmm-seed and squashes the following commits:

f0df4fd [Joseph K. Bradley] Added seed parameter to GMM.  Updated test suite to use seed to prevent flakiness
---
 .../mllib/clustering/GaussianMixtureEM.scala  | 26 ++++++++++++++-----
 .../GMMExpectationMaximizationSuite.scala     | 14 +++++-----
 2 files changed, 27 insertions(+), 13 deletions(-)

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureEM.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureEM.scala
index 3a6c0e681e3fa..b3c5631cc4cc6 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureEM.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureEM.scala
@@ -24,6 +24,7 @@ import org.apache.spark.rdd.RDD
 import org.apache.spark.mllib.linalg.{Matrices, Vector, Vectors, DenseVector, DenseMatrix, BLAS}
 import org.apache.spark.mllib.stat.impl.MultivariateGaussian
 import org.apache.spark.mllib.util.MLUtils
+import org.apache.spark.util.Utils
 
 /**
  * This class performs expectation maximization for multivariate Gaussian
@@ -45,10 +46,11 @@ import org.apache.spark.mllib.util.MLUtils
 class GaussianMixtureEM private (
     private var k: Int, 
     private var convergenceTol: Double, 
-    private var maxIterations: Int) extends Serializable {
+    private var maxIterations: Int,
+    private var seed: Long) extends Serializable {
   
   /** A default instance, 2 Gaussians, 100 iterations, 0.01 log-likelihood threshold */
-  def this() = this(2, 0.01, 100)
+  def this() = this(2, 0.01, 100, Utils.random.nextLong())
   
   // number of samples per cluster to use when initializing Gaussians
   private val nSamples = 5
@@ -100,11 +102,21 @@ class GaussianMixtureEM private (
     this
   }
   
-  /** Return the largest change in log-likelihood at which convergence is
-   *  considered to have occurred.
+  /**
+   * Return the largest change in log-likelihood at which convergence is
+   * considered to have occurred.
    */
   def getConvergenceTol: Double = convergenceTol
-  
+
+  /** Set the random seed */
+  def setSeed(seed: Long): this.type = {
+    this.seed = seed
+    this
+  }
+
+  /** Return the random seed */
+  def getSeed: Long = seed
+
   /** Perform expectation maximization */
   def run(data: RDD[Vector]): GaussianMixtureModel = {
     val sc = data.sparkContext
@@ -113,7 +125,7 @@ class GaussianMixtureEM private (
     val breezeData = data.map(u => u.toBreeze.toDenseVector).cache()
     
     // Get length of the input vectors
-    val d = breezeData.first.length 
+    val d = breezeData.first().length
     
     // Determine initial weights and corresponding Gaussians.
     // If the user supplied an initial GMM, we use those values, otherwise
@@ -126,7 +138,7 @@ class GaussianMixtureEM private (
       })
       
       case None => {
-        val samples = breezeData.takeSample(true, k * nSamples, scala.util.Random.nextInt)
+        val samples = breezeData.takeSample(withReplacement = true, k * nSamples, seed)
         (Array.fill(k)(1.0 / k), Array.tabulate(k) { i => 
           val slice = samples.view(i * nSamples, (i + 1) * nSamples)
           new MultivariateGaussian(vectorMean(slice), initCovariance(slice)) 
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/clustering/GMMExpectationMaximizationSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/clustering/GMMExpectationMaximizationSuite.scala
index 23feb82874b70..9da5495741a80 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/clustering/GMMExpectationMaximizationSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/clustering/GMMExpectationMaximizationSuite.scala
@@ -35,12 +35,14 @@ class GMMExpectationMaximizationSuite extends FunSuite with MLlibTestSparkContex
     val Ew = 1.0
     val Emu = Vectors.dense(5.0, 10.0)
     val Esigma = Matrices.dense(2, 2, Array(2.0 / 3.0, -2.0 / 3.0, -2.0 / 3.0, 2.0 / 3.0))
-    
-    val gmm = new GaussianMixtureEM().setK(1).run(data)
-                
-    assert(gmm.weight(0) ~== Ew absTol 1E-5)
-    assert(gmm.mu(0) ~== Emu absTol 1E-5)
-    assert(gmm.sigma(0) ~== Esigma absTol 1E-5)
+
+    val seeds = Array(314589, 29032897, 50181, 494821, 4660)
+    seeds.foreach { seed =>
+      val gmm = new GaussianMixtureEM().setK(1).setSeed(seed).run(data)
+      assert(gmm.weight(0) ~== Ew absTol 1E-5)
+      assert(gmm.mu(0) ~== Emu absTol 1E-5)
+      assert(gmm.sigma(0) ~== Esigma absTol 1E-5)
+    }
   }
   
   test("two clusters") {

From e96645206006a009e5c1a23bbd177dcaf3ef9b83 Mon Sep 17 00:00:00 2001
From: WangTaoTheTonic 
Date: Fri, 9 Jan 2015 13:20:32 -0800
Subject: [PATCH 208/320] [SPARK-1953][YARN]yarn client mode Application Master
 memory size is same as driver memory...

... size

Ways to set Application Master's memory on yarn-client mode:
1.  `spark.yarn.am.memory` in SparkConf or System Properties
2.  default value 512m

Note: this arguments is only available in yarn-client mode.

Author: WangTaoTheTonic 

Closes #3607 from WangTaoTheTonic/SPARK4181 and squashes the following commits:

d5ceb1b [WangTaoTheTonic] spark.driver.memeory is used in both modes
6c1b264 [WangTaoTheTonic] rebase
b8410c0 [WangTaoTheTonic] minor optiminzation
ddcd592 [WangTaoTheTonic] fix the bug produced in rebase and some improvements
3bf70cc [WangTaoTheTonic] rebase and give proper hint
987b99d [WangTaoTheTonic] disable --driver-memory in client mode
2b27928 [WangTaoTheTonic] inaccurate description
b7acbb2 [WangTaoTheTonic] incorrect method invoked
2557c5e [WangTaoTheTonic] missing a single blank
42075b0 [WangTaoTheTonic] arrange the args and warn logging
69c7dba [WangTaoTheTonic] rebase
1960d16 [WangTaoTheTonic] fix wrong comment
7fa9e2e [WangTaoTheTonic] log a warning
f6bee0e [WangTaoTheTonic] docs issue
d619996 [WangTaoTheTonic] Merge branch 'master' into SPARK4181
b09c309 [WangTaoTheTonic] use code format
ab16bb5 [WangTaoTheTonic] fix bug and add comments
44e48c2 [WangTaoTheTonic] minor fix
6fd13e1 [WangTaoTheTonic] add overhead mem and remove some configs
0566bb8 [WangTaoTheTonic] yarn client mode Application Master memory size is same as driver memory size
---
 .../spark/deploy/SparkSubmitArguments.scala   |  3 +-
 docs/running-on-yarn.md                       | 19 +++++++++-
 .../org/apache/spark/deploy/yarn/Client.scala |  2 +-
 .../spark/deploy/yarn/ClientArguments.scala   | 37 ++++++++++++++-----
 .../cluster/YarnClientSchedulerBackend.scala  |  2 -
 5 files changed, 48 insertions(+), 15 deletions(-)

diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala
index 1faabe91f49a8..f14ef4d299383 100644
--- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala
+++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala
@@ -405,7 +405,8 @@ private[spark] class SparkSubmitArguments(args: Seq[String], env: Map[String, St
         |  --queue QUEUE_NAME          The YARN queue to submit to (Default: "default").
         |  --num-executors NUM         Number of executors to launch (Default: 2).
         |  --archives ARCHIVES         Comma separated list of archives to be extracted into the
-        |                              working directory of each executor.""".stripMargin
+        |                              working directory of each executor.
+      """.stripMargin
     )
     SparkSubmit.exitFn()
   }
diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md
index 183698ffe9304..4f273098c5db3 100644
--- a/docs/running-on-yarn.md
+++ b/docs/running-on-yarn.md
@@ -21,6 +21,14 @@ Most of the configs are the same for Spark on YARN as for other deployment modes
    spark.ui.retainedJobs 1000 - How many stages the Spark UI and status APIs remember before garbage + How many jobs the Spark UI and status APIs remember before garbage collecting.
    If set to true, validates the output specification (e.g. checking if the output directory already exists) used in saveAsHadoopFile and other variants. This can be disabled to silence exceptions due to pre-existing output directories. We recommend that users do not disable this except if trying to achieve compatibility with - previous versions of Spark. Simply use Hadoop's FileSystem API to delete output directories by hand.
    spark.hadoop.cloneConf
    spark.network.timeout100 + Default timeout for all network interactions, in seconds. This config will be used in + place of spark.core.connection.ack.wait.timeout, spark.akka.timeout, + spark.storage.blockManagerSlaveTimeoutMs or spark.shuffle.io.connectionTimeout, + if they are not configured. +
    spark.akka.heartbeat.pauses 6000
    spark.network.timeout100120 Default timeout for all network interactions, in seconds. This config will be used in place of spark.core.connection.ack.wait.timeout, spark.akka.timeout, - spark.storage.blockManagerSlaveTimeoutMs or spark.shuffle.io.connectionTimeout, - if they are not configured. + spark.storage.blockManagerSlaveTimeoutMs or + spark.shuffle.io.connectionTimeout, if they are not configured.
    + + + + + @@ -90,7 +98,14 @@ Most of the configs are the same for Spark on YARN as for other deployment modes + + + + + @@ -145,7 +160,7 @@ Most of the configs are the same for Spark on YARN as for other deployment modes diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala index c363d755c1752..032106371cd60 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala @@ -65,7 +65,7 @@ private[spark] class Client( private val amMemoryOverhead = args.amMemoryOverhead // MB private val executorMemoryOverhead = args.executorMemoryOverhead // MB private val distCacheMgr = new ClientDistributedCacheManager() - private val isClusterMode = args.userClass != null + private val isClusterMode = args.isClusterMode def stop(): Unit = yarnClient.stop() diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala index 39f1021c9d942..fdbf9f8eed029 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala @@ -38,23 +38,27 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf) var amMemory: Int = 512 // MB var appName: String = "Spark" var priority = 0 + def isClusterMode: Boolean = userClass != null + + private var driverMemory: Int = 512 // MB + private val driverMemOverheadKey = "spark.yarn.driver.memoryOverhead" + private val amMemKey = "spark.yarn.am.memory" + private val amMemOverheadKey = "spark.yarn.am.memoryOverhead" + private val isDynamicAllocationEnabled = + sparkConf.getBoolean("spark.dynamicAllocation.enabled", false) parseArgs(args.toList) + loadEnvironmentArgs() + validateArgs() // Additional memory to allocate to containers - // For now, use driver's memory overhead as our AM container's memory overhead - val amMemoryOverhead = sparkConf.getInt("spark.yarn.driver.memoryOverhead", + val amMemoryOverheadConf = if (isClusterMode) driverMemOverheadKey else amMemOverheadKey + val amMemoryOverhead = sparkConf.getInt(amMemoryOverheadConf, math.max((MEMORY_OVERHEAD_FACTOR * amMemory).toInt, MEMORY_OVERHEAD_MIN)) val executorMemoryOverhead = sparkConf.getInt("spark.yarn.executor.memoryOverhead", math.max((MEMORY_OVERHEAD_FACTOR * executorMemory).toInt, MEMORY_OVERHEAD_MIN)) - private val isDynamicAllocationEnabled = - sparkConf.getBoolean("spark.dynamicAllocation.enabled", false) - - loadEnvironmentArgs() - validateArgs() - /** Load any default arguments provided through environment variables and Spark properties. */ private def loadEnvironmentArgs(): Unit = { // For backward compatibility, SPARK_YARN_DIST_{ARCHIVES/FILES} should be resolved to hdfs://, @@ -87,6 +91,21 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf) throw new IllegalArgumentException( "You must specify at least 1 executor!\n" + getUsageMessage()) } + if (isClusterMode) { + for (key <- Seq(amMemKey, amMemOverheadKey)) { + if (sparkConf.contains(key)) { + println(s"$key is set but does not apply in cluster mode.") + } + } + amMemory = driverMemory + } else { + if (sparkConf.contains(driverMemOverheadKey)) { + println(s"$driverMemOverheadKey is set but does not apply in client mode.") + } + sparkConf.getOption(amMemKey) + .map(Utils.memoryStringToMb) + .foreach { mem => amMemory = mem } + } } private def parseArgs(inputArgs: List[String]): Unit = { @@ -118,7 +137,7 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf) if (args(0) == "--master-memory") { println("--master-memory is deprecated. Use --driver-memory instead.") } - amMemory = value + driverMemory = value args = tail case ("--num-workers" | "--num-executors") :: IntParam(value) :: tail => diff --git a/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala b/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala index 09597bd0e6ab9..f99291553b7b8 100644 --- a/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala +++ b/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala @@ -68,8 +68,6 @@ private[spark] class YarnClientSchedulerBackend( // List of (target Client argument, environment variable, Spark property) val optionTuples = List( - ("--driver-memory", "SPARK_MASTER_MEMORY", "spark.master.memory"), - ("--driver-memory", "SPARK_DRIVER_MEMORY", "spark.driver.memory"), ("--num-executors", "SPARK_WORKER_INSTANCES", "spark.executor.instances"), ("--num-executors", "SPARK_EXECUTOR_INSTANCES", "spark.executor.instances"), ("--executor-memory", "SPARK_WORKER_MEMORY", "spark.executor.memory"), From e0f28e010cdd67a2a4c8aebd35323d69a3182ba8 Mon Sep 17 00:00:00 2001 From: mcheah Date: Fri, 9 Jan 2015 14:16:20 -0800 Subject: [PATCH 209/320] [SPARK-4737] Task set manager properly handles serialization errors Dealing with [SPARK-4737], the handling of serialization errors should not be the DAGScheduler's responsibility. The task set manager now catches the error and aborts the stage. If the TaskSetManager throws a TaskNotSerializableException, the TaskSchedulerImpl will return an empty list of task descriptions, because no tasks were started. The scheduler should abort the stage gracefully. Note that I'm not too familiar with this part of the codebase and its place in the overall architecture of the Spark stack. If implementing it this way will have any averse side effects please voice that loudly. Author: mcheah Closes #3638 from mccheah/task-set-manager-properly-handle-ser-err and squashes the following commits: 1545984 [mcheah] Some more style fixes from Andrew Or. 5267929 [mcheah] Fixing style suggestions from Andrew Or. dfa145b [mcheah] Fixing style from Josh Rosen's feedback b2a430d [mcheah] Not returning empty seq when a task set cannot be serialized. 94844d7 [mcheah] Fixing compilation error, one brace too many 5f486f4 [mcheah] Adding license header for fake task class bf5e706 [mcheah] Fixing indentation. 097e7a2 [mcheah] [SPARK-4737] Catching task serialization exception in TaskSetManager --- .../spark/TaskNotSerializableException.scala | 25 +++++++++ .../apache/spark/scheduler/DAGScheduler.scala | 20 ------- .../spark/scheduler/TaskSchedulerImpl.scala | 54 +++++++++++++------ .../spark/scheduler/TaskSetManager.scala | 18 +++++-- .../org/apache/spark/SharedSparkContext.scala | 2 +- .../scala/org/apache/spark/rdd/RDDSuite.scala | 21 ++++++++ .../scheduler/NotSerializableFakeTask.scala | 40 ++++++++++++++ .../scheduler/TaskSchedulerImplSuite.scala | 30 +++++++++++ .../spark/scheduler/TaskSetManagerSuite.scala | 14 +++++ 9 files changed, 182 insertions(+), 42 deletions(-) create mode 100644 core/src/main/scala/org/apache/spark/TaskNotSerializableException.scala create mode 100644 core/src/test/scala/org/apache/spark/scheduler/NotSerializableFakeTask.scala diff --git a/core/src/main/scala/org/apache/spark/TaskNotSerializableException.scala b/core/src/main/scala/org/apache/spark/TaskNotSerializableException.scala new file mode 100644 index 0000000000000..9df61062e1f85 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/TaskNotSerializableException.scala @@ -0,0 +1,25 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark + +import org.apache.spark.annotation.DeveloperApi + +/** + * Exception thrown when a task cannot be serialized. + */ +private[spark] class TaskNotSerializableException(error: Throwable) extends Exception(error) diff --git a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala index 259621d263d7c..61d09d73e17cb 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala @@ -866,26 +866,6 @@ class DAGScheduler( } if (tasks.size > 0) { - // Preemptively serialize a task to make sure it can be serialized. We are catching this - // exception here because it would be fairly hard to catch the non-serializable exception - // down the road, where we have several different implementations for local scheduler and - // cluster schedulers. - // - // We've already serialized RDDs and closures in taskBinary, but here we check for all other - // objects such as Partition. - try { - closureSerializer.serialize(tasks.head) - } catch { - case e: NotSerializableException => - abortStage(stage, "Task not serializable: " + e.toString) - runningStages -= stage - return - case NonFatal(e) => // Other exceptions, such as IllegalArgumentException from Kryo. - abortStage(stage, s"Task serialization failed: $e\n${e.getStackTraceString}") - runningStages -= stage - return - } - logInfo("Submitting " + tasks.size + " missing tasks from " + stage + " (" + stage.rdd + ")") stage.pendingTasks ++= tasks logDebug("New pending tasks: " + stage.pendingTasks) diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala index a41f3eef195d2..a1dfb01062591 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala @@ -31,6 +31,7 @@ import scala.util.Random import org.apache.spark._ import org.apache.spark.TaskState.TaskState import org.apache.spark.scheduler.SchedulingMode.SchedulingMode +import org.apache.spark.scheduler.TaskLocality.TaskLocality import org.apache.spark.util.Utils import org.apache.spark.executor.TaskMetrics import org.apache.spark.storage.BlockManagerId @@ -209,6 +210,40 @@ private[spark] class TaskSchedulerImpl( .format(manager.taskSet.id, manager.parent.name)) } + private def resourceOfferSingleTaskSet( + taskSet: TaskSetManager, + maxLocality: TaskLocality, + shuffledOffers: Seq[WorkerOffer], + availableCpus: Array[Int], + tasks: Seq[ArrayBuffer[TaskDescription]]) : Boolean = { + var launchedTask = false + for (i <- 0 until shuffledOffers.size) { + val execId = shuffledOffers(i).executorId + val host = shuffledOffers(i).host + if (availableCpus(i) >= CPUS_PER_TASK) { + try { + for (task <- taskSet.resourceOffer(execId, host, maxLocality)) { + tasks(i) += task + val tid = task.taskId + taskIdToTaskSetId(tid) = taskSet.taskSet.id + taskIdToExecutorId(tid) = execId + executorsByHost(host) += execId + availableCpus(i) -= CPUS_PER_TASK + assert(availableCpus(i) >= 0) + launchedTask = true + } + } catch { + case e: TaskNotSerializableException => + logError(s"Resource offer failed, task set ${taskSet.name} was not serializable") + // Do not offer resources for this task, but don't throw an error to allow other + // task sets to be submitted. + return launchedTask + } + } + } + return launchedTask + } + /** * Called by cluster manager to offer resources on slaves. We respond by asking our active task * sets for tasks in order of priority. We fill each node with tasks in a round-robin manner so @@ -251,23 +286,8 @@ private[spark] class TaskSchedulerImpl( var launchedTask = false for (taskSet <- sortedTaskSets; maxLocality <- taskSet.myLocalityLevels) { do { - launchedTask = false - for (i <- 0 until shuffledOffers.size) { - val execId = shuffledOffers(i).executorId - val host = shuffledOffers(i).host - if (availableCpus(i) >= CPUS_PER_TASK) { - for (task <- taskSet.resourceOffer(execId, host, maxLocality)) { - tasks(i) += task - val tid = task.taskId - taskIdToTaskSetId(tid) = taskSet.taskSet.id - taskIdToExecutorId(tid) = execId - executorsByHost(host) += execId - availableCpus(i) -= CPUS_PER_TASK - assert(availableCpus(i) >= 0) - launchedTask = true - } - } - } + launchedTask = resourceOfferSingleTaskSet( + taskSet, maxLocality, shuffledOffers, availableCpus, tasks) } while (launchedTask) } diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala index 28e6147509f78..4667850917151 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala @@ -18,12 +18,14 @@ package org.apache.spark.scheduler import java.io.NotSerializableException +import java.nio.ByteBuffer import java.util.Arrays import scala.collection.mutable.ArrayBuffer import scala.collection.mutable.HashMap import scala.collection.mutable.HashSet import scala.math.{min, max} +import scala.util.control.NonFatal import org.apache.spark._ import org.apache.spark.executor.TaskMetrics @@ -417,6 +419,7 @@ private[spark] class TaskSetManager( * @param host the host Id of the offered resource * @param maxLocality the maximum locality we want to schedule the tasks at */ + @throws[TaskNotSerializableException] def resourceOffer( execId: String, host: String, @@ -456,10 +459,17 @@ private[spark] class TaskSetManager( } // Serialize and return the task val startTime = clock.getTime() - // We rely on the DAGScheduler to catch non-serializable closures and RDDs, so in here - // we assume the task can be serialized without exceptions. - val serializedTask = Task.serializeWithDependencies( - task, sched.sc.addedFiles, sched.sc.addedJars, ser) + val serializedTask: ByteBuffer = try { + Task.serializeWithDependencies(task, sched.sc.addedFiles, sched.sc.addedJars, ser) + } catch { + // If the task cannot be serialized, then there's no point to re-attempt the task, + // as it will always fail. So just abort the whole task-set. + case NonFatal(e) => + val msg = s"Failed to serialize task $taskId, not attempting to retry it." + logError(msg, e) + abort(s"$msg Exception during serialization: $e") + throw new TaskNotSerializableException(e) + } if (serializedTask.limit > TaskSetManager.TASK_SIZE_TO_WARN_KB * 1024 && !emittedTaskSizeWarning) { emittedTaskSizeWarning = true diff --git a/core/src/test/scala/org/apache/spark/SharedSparkContext.scala b/core/src/test/scala/org/apache/spark/SharedSparkContext.scala index 0b6511a80df1d..3d2700b7e6be4 100644 --- a/core/src/test/scala/org/apache/spark/SharedSparkContext.scala +++ b/core/src/test/scala/org/apache/spark/SharedSparkContext.scala @@ -30,7 +30,7 @@ trait SharedSparkContext extends BeforeAndAfterAll { self: Suite => var conf = new SparkConf(false) override def beforeAll() { - _sc = new SparkContext("local", "test", conf) + _sc = new SparkContext("local[4]", "test", conf) super.beforeAll() } diff --git a/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala b/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala index 6836e9ab0fd6b..0deb9b18b8688 100644 --- a/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala +++ b/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala @@ -17,6 +17,10 @@ package org.apache.spark.rdd +import java.io.{ObjectInputStream, ObjectOutputStream, IOException} + +import com.esotericsoftware.kryo.KryoException + import scala.collection.mutable.{ArrayBuffer, HashMap} import scala.collection.JavaConverters._ import scala.reflect.ClassTag @@ -887,6 +891,23 @@ class RDDSuite extends FunSuite with SharedSparkContext { assert(ancestors6.count(_.isInstanceOf[CyclicalDependencyRDD[_]]) === 3) } + test("task serialization exception should not hang scheduler") { + class BadSerializable extends Serializable { + @throws(classOf[IOException]) + private def writeObject(out: ObjectOutputStream): Unit = throw new KryoException("Bad serialization") + + @throws(classOf[IOException]) + private def readObject(in: ObjectInputStream): Unit = {} + } + // Note that in the original bug, SPARK-4349, that this verifies, the job would only hang if there were + // more threads in the Spark Context than there were number of objects in this sequence. + intercept[Throwable] { + sc.parallelize(Seq(new BadSerializable, new BadSerializable)).collect + } + // Check that the context has not crashed + sc.parallelize(1 to 100).map(x => x*2).collect + } + /** A contrived RDD that allows the manual addition of dependencies after creation. */ private class CyclicalDependencyRDD[T: ClassTag] extends RDD[T](sc, Nil) { private val mutableDependencies: ArrayBuffer[Dependency[_]] = ArrayBuffer.empty diff --git a/core/src/test/scala/org/apache/spark/scheduler/NotSerializableFakeTask.scala b/core/src/test/scala/org/apache/spark/scheduler/NotSerializableFakeTask.scala new file mode 100644 index 0000000000000..6b75c98839e03 --- /dev/null +++ b/core/src/test/scala/org/apache/spark/scheduler/NotSerializableFakeTask.scala @@ -0,0 +1,40 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler + +import java.io.{ObjectInputStream, ObjectOutputStream, IOException} + +import org.apache.spark.TaskContext + +/** + * A Task implementation that fails to serialize. + */ +private[spark] class NotSerializableFakeTask(myId: Int, stageId: Int) extends Task[Array[Byte]](stageId, 0) { + override def runTask(context: TaskContext): Array[Byte] = Array.empty[Byte] + override def preferredLocations: Seq[TaskLocation] = Seq[TaskLocation]() + + @throws(classOf[IOException]) + private def writeObject(out: ObjectOutputStream): Unit = { + if (stageId == 0) { + throw new IllegalStateException("Cannot serialize") + } + } + + @throws(classOf[IOException]) + private def readObject(in: ObjectInputStream): Unit = {} +} diff --git a/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala index 8874cf00e9993..add13f5b21765 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/TaskSchedulerImplSuite.scala @@ -100,4 +100,34 @@ class TaskSchedulerImplSuite extends FunSuite with LocalSparkContext with Loggin assert(1 === taskDescriptions.length) assert("executor0" === taskDescriptions(0).executorId) } + + test("Scheduler does not crash when tasks are not serializable") { + sc = new SparkContext("local", "TaskSchedulerImplSuite") + val taskCpus = 2 + + sc.conf.set("spark.task.cpus", taskCpus.toString) + val taskScheduler = new TaskSchedulerImpl(sc) + taskScheduler.initialize(new FakeSchedulerBackend) + // Need to initialize a DAGScheduler for the taskScheduler to use for callbacks. + val dagScheduler = new DAGScheduler(sc, taskScheduler) { + override def taskStarted(task: Task[_], taskInfo: TaskInfo) {} + override def executorAdded(execId: String, host: String) {} + } + val numFreeCores = 1 + taskScheduler.setDAGScheduler(dagScheduler) + var taskSet = new TaskSet(Array(new NotSerializableFakeTask(1, 0), new NotSerializableFakeTask(0, 1)), 0, 0, 0, null) + val multiCoreWorkerOffers = Seq(new WorkerOffer("executor0", "host0", taskCpus), + new WorkerOffer("executor1", "host1", numFreeCores)) + taskScheduler.submitTasks(taskSet) + var taskDescriptions = taskScheduler.resourceOffers(multiCoreWorkerOffers).flatten + assert(0 === taskDescriptions.length) + + // Now check that we can still submit tasks + // Even if one of the tasks has not-serializable tasks, the other task set should still be processed without error + taskScheduler.submitTasks(taskSet) + taskScheduler.submitTasks(FakeTask.createTaskSet(1)) + taskDescriptions = taskScheduler.resourceOffers(multiCoreWorkerOffers).flatten + assert(taskDescriptions.map(_.executorId) === Seq("executor0")) + } + } diff --git a/core/src/test/scala/org/apache/spark/scheduler/TaskSetManagerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/TaskSetManagerSuite.scala index 472191551a01f..84b9b788237bf 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/TaskSetManagerSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/TaskSetManagerSuite.scala @@ -17,6 +17,7 @@ package org.apache.spark.scheduler +import java.io.{ObjectInputStream, ObjectOutputStream, IOException} import java.util.Random import scala.collection.mutable.ArrayBuffer @@ -563,6 +564,19 @@ class TaskSetManagerSuite extends FunSuite with LocalSparkContext with Logging { assert(manager.emittedTaskSizeWarning) } + test("Not serializable exception thrown if the task cannot be serialized") { + sc = new SparkContext("local", "test") + val sched = new FakeTaskScheduler(sc, ("exec1", "host1")) + + val taskSet = new TaskSet(Array(new NotSerializableFakeTask(1, 0), new NotSerializableFakeTask(0, 1)), 0, 0, 0, null) + val manager = new TaskSetManager(sched, taskSet, MAX_TASK_FAILURES) + + intercept[TaskNotSerializableException] { + manager.resourceOffer("exec1", "host1", ANY) + } + assert(manager.isZombie) + } + test("abort the job if total size of results is too large") { val conf = new SparkConf().set("spark.driver.maxResultSize", "2m") sc = new SparkContext("local", "test", conf) From ae628725abce9ffe34b9a7110d5ac51a076454aa Mon Sep 17 00:00:00 2001 From: Kousuke Saruta Date: Fri, 9 Jan 2015 14:40:45 -0800 Subject: [PATCH 210/320] [DOC] Fixed Mesos version in doc from 0.18.1 to 0.21.0 #3934 upgraded Mesos version so we should also fix docs right? This issue is really minor so I don't file in JIRA. Author: Kousuke Saruta Closes #3982 from sarutak/fix-mesos-version and squashes the following commits: 9a86ee3 [Kousuke Saruta] Fixed mesos version from 0.18.1 to 0.21.0 --- docs/_config.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/_config.yml b/docs/_config.yml index a96a76dd9ab5e..e2db274e1f619 100644 --- a/docs/_config.yml +++ b/docs/_config.yml @@ -17,6 +17,6 @@ SPARK_VERSION: 1.3.0-SNAPSHOT SPARK_VERSION_SHORT: 1.3.0 SCALA_BINARY_VERSION: "2.10" SCALA_VERSION: "2.10.4" -MESOS_VERSION: 0.18.1 +MESOS_VERSION: 0.21.0 SPARK_ISSUE_TRACKER_URL: https://issues.apache.org/jira/browse/SPARK SPARK_GITHUB_URL: https://github.com/apache/spark From 4e1f12d997426560226648d62ee17c90352613e7 Mon Sep 17 00:00:00 2001 From: bilna Date: Fri, 9 Jan 2015 14:45:28 -0800 Subject: [PATCH 211/320] [Minor] Fix import order and other coding style fixed import order and other coding style Author: bilna Author: Bilna P Closes #3966 from Bilna/master and squashes the following commits: 5e76f04 [bilna] fix import order and other coding style 5718d66 [bilna] Merge remote-tracking branch 'upstream/master' ae56514 [bilna] Merge remote-tracking branch 'upstream/master' acea3a3 [bilna] Adding dependency with scope test 28681fa [bilna] Merge remote-tracking branch 'upstream/master' fac3904 [bilna] Correction in Indentation and coding style ed9db4c [bilna] Merge remote-tracking branch 'upstream/master' 4b34ee7 [Bilna P] Update MQTTStreamSuite.scala 04503cf [bilna] Added embedded broker service for mqtt test 89d804e [bilna] Merge remote-tracking branch 'upstream/master' fc8eb28 [bilna] Merge remote-tracking branch 'upstream/master' 4b58094 [Bilna P] Update MQTTStreamSuite.scala b1ac4ad [bilna] Added BeforeAndAfter 5f6bfd2 [bilna] Added BeforeAndAfter e8b6623 [Bilna P] Update MQTTStreamSuite.scala 5ca6691 [Bilna P] Update MQTTStreamSuite.scala 8616495 [bilna] [SPARK-4631] unit test for MQTT --- .../spark/streaming/mqtt/MQTTStreamSuite.scala | 17 +++++++++++------ 1 file changed, 11 insertions(+), 6 deletions(-) diff --git a/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala b/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala index 98fe6cb301f52..39eb8b183488f 100644 --- a/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala +++ b/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala @@ -19,16 +19,19 @@ package org.apache.spark.streaming.mqtt import java.net.{URI, ServerSocket} +import scala.concurrent.duration._ + import org.apache.activemq.broker.{TransportConnector, BrokerService} -import org.apache.spark.util.Utils +import org.eclipse.paho.client.mqttv3._ +import org.eclipse.paho.client.mqttv3.persist.MqttDefaultFilePersistence + import org.scalatest.{BeforeAndAfter, FunSuite} import org.scalatest.concurrent.Eventually -import scala.concurrent.duration._ + import org.apache.spark.streaming.{Milliseconds, StreamingContext} import org.apache.spark.storage.StorageLevel import org.apache.spark.streaming.dstream.ReceiverInputDStream -import org.eclipse.paho.client.mqttv3._ -import org.eclipse.paho.client.mqttv3.persist.MqttDefaultFilePersistence +import org.apache.spark.util.Utils class MQTTStreamSuite extends FunSuite with Eventually with BeforeAndAfter { @@ -38,8 +41,9 @@ class MQTTStreamSuite extends FunSuite with Eventually with BeforeAndAfter { private val freePort = findFreePort() private val brokerUri = "//localhost:" + freePort private val topic = "def" - private var ssc: StreamingContext = _ private val persistenceDir = Utils.createTempDir() + + private var ssc: StreamingContext = _ private var broker: BrokerService = _ private var connector: TransportConnector = _ @@ -115,8 +119,9 @@ class MQTTStreamSuite extends FunSuite with Eventually with BeforeAndAfter { val message: MqttMessage = new MqttMessage(data.getBytes("utf-8")) message.setQos(1) message.setRetained(true) - for (i <- 0 to 100) + for (i <- 0 to 100) { msgTopic.publish(message) + } } } finally { client.disconnect() From 8782eb992f461502238c41ece3a3002efa67a792 Mon Sep 17 00:00:00 2001 From: WangTaoTheTonic Date: Fri, 9 Jan 2015 17:10:02 -0800 Subject: [PATCH 212/320] [SPARK-4990][Deploy]to find default properties file, search SPARK_CONF_DIR first https://issues.apache.org/jira/browse/SPARK-4990 Author: WangTaoTheTonic Author: WangTao Closes #3823 from WangTaoTheTonic/SPARK-4990 and squashes the following commits: 133c43e [WangTao] Update spark-submit2.cmd b1ab402 [WangTao] Update spark-submit 4cc7f34 [WangTaoTheTonic] rebase 55300bc [WangTaoTheTonic] use export to make it global d8d3cb7 [WangTaoTheTonic] remove blank line 07b9ebf [WangTaoTheTonic] check SPARK_CONF_DIR instead of checking properties file c5a85eb [WangTaoTheTonic] to find default properties file, search SPARK_CONF_DIR first --- bin/spark-submit | 5 ++++- bin/spark-submit2.cmd | 6 +++++- 2 files changed, 9 insertions(+), 2 deletions(-) diff --git a/bin/spark-submit b/bin/spark-submit index aefd38a0a2b90..3e5cbdbb24394 100755 --- a/bin/spark-submit +++ b/bin/spark-submit @@ -44,7 +44,10 @@ while (($#)); do shift done -DEFAULT_PROPERTIES_FILE="$SPARK_HOME/conf/spark-defaults.conf" +if [ -z "$SPARK_CONF_DIR" ]; then + export SPARK_CONF_DIR="$SPARK_HOME/conf" +fi +DEFAULT_PROPERTIES_FILE="$SPARK_CONF_DIR/spark-defaults.conf" if [ "$MASTER" == "yarn-cluster" ]; then SPARK_SUBMIT_DEPLOY_MODE=cluster fi diff --git a/bin/spark-submit2.cmd b/bin/spark-submit2.cmd index daf0284db9230..12244a9cb04fb 100644 --- a/bin/spark-submit2.cmd +++ b/bin/spark-submit2.cmd @@ -24,7 +24,11 @@ set ORIG_ARGS=%* rem Reset the values of all variables used set SPARK_SUBMIT_DEPLOY_MODE=client -set SPARK_SUBMIT_PROPERTIES_FILE=%SPARK_HOME%\conf\spark-defaults.conf + +if not defined %SPARK_CONF_DIR% ( + set SPARK_CONF_DIR=%SPARK_HOME%\conf +) +set SPARK_SUBMIT_PROPERTIES_FILE=%SPARK_CONF_DIR%\spark-defaults.conf set SPARK_SUBMIT_DRIVER_MEMORY= set SPARK_SUBMIT_LIBRARY_PATH= set SPARK_SUBMIT_CLASSPATH= From 4554529dce8fe8ca937d887109ef072eef52bf51 Mon Sep 17 00:00:00 2001 From: MechCoder Date: Fri, 9 Jan 2015 17:45:18 -0800 Subject: [PATCH 213/320] [SPARK-4406] [MLib] FIX: Validate k in SVD Raise exception when k is non-positive in SVD Author: MechCoder Closes #3945 from MechCoder/spark-4406 and squashes the following commits: 64e6d2d [MechCoder] TST: Add better test errors and messages 12dae73 [MechCoder] [SPARK-4406] FIX: Validate k in SVD --- .../spark/mllib/linalg/distributed/IndexedRowMatrix.scala | 3 +++ .../apache/spark/mllib/linalg/distributed/RowMatrix.scala | 2 +- .../mllib/linalg/distributed/IndexedRowMatrixSuite.scala | 7 +++++++ .../spark/mllib/linalg/distributed/RowMatrixSuite.scala | 8 ++++++++ 4 files changed, 19 insertions(+), 1 deletion(-) diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrix.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrix.scala index 36d8cadd2bdd7..181f507516485 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrix.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrix.scala @@ -102,6 +102,9 @@ class IndexedRowMatrix( k: Int, computeU: Boolean = false, rCond: Double = 1e-9): SingularValueDecomposition[IndexedRowMatrix, Matrix] = { + + val n = numCols().toInt + require(k > 0 && k <= n, s"Requested k singular values but got k=$k and numCols=$n.") val indices = rows.map(_.index) val svd = toRowMatrix().computeSVD(k, computeU, rCond) val U = if (computeU) { diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala index fbd35e372f9b1..d5abba6a4b645 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala @@ -212,7 +212,7 @@ class RowMatrix( tol: Double, mode: String): SingularValueDecomposition[RowMatrix, Matrix] = { val n = numCols().toInt - require(k > 0 && k <= n, s"Request up to n singular values but got k=$k and n=$n.") + require(k > 0 && k <= n, s"Requested k singular values but got k=$k and numCols=$n.") object SVDMode extends Enumeration { val LocalARPACK, LocalLAPACK, DistARPACK = Value diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrixSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrixSuite.scala index e25bc02b06c9a..741cd4997b853 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrixSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrixSuite.scala @@ -113,6 +113,13 @@ class IndexedRowMatrixSuite extends FunSuite with MLlibTestSparkContext { assert(closeToZero(U * brzDiag(s) * V.t - localA)) } + test("validate k in svd") { + val A = new IndexedRowMatrix(indexedRows) + intercept[IllegalArgumentException] { + A.computeSVD(-1) + } + } + def closeToZero(G: BDM[Double]): Boolean = { G.valuesIterator.map(math.abs).sum < 1e-6 } diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/RowMatrixSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/RowMatrixSuite.scala index dbf55ff81ca99..3309713e91f87 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/RowMatrixSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/RowMatrixSuite.scala @@ -171,6 +171,14 @@ class RowMatrixSuite extends FunSuite with MLlibTestSparkContext { } } + test("validate k in svd") { + for (mat <- Seq(denseMat, sparseMat)) { + intercept[IllegalArgumentException] { + mat.computeSVD(-1) + } + } + } + def closeToZero(G: BDM[Double]): Boolean = { G.valuesIterator.map(math.abs).sum < 1e-6 } From 545dfcb92f2ff82a51877d35d9669094ea81f466 Mon Sep 17 00:00:00 2001 From: luogankun Date: Fri, 9 Jan 2015 20:38:41 -0800 Subject: [PATCH 214/320] [SPARK-5141][SQL]CaseInsensitiveMap throws java.io.NotSerializableException CaseInsensitiveMap throws java.io.NotSerializableException. Author: luogankun Closes #3944 from luogankun/SPARK-5141 and squashes the following commits: b6d63d5 [luogankun] [SPARK-5141]CaseInsensitiveMap throws java.io.NotSerializableException --- sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala index 8a66ac31f2dfb..364bacec83b98 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala @@ -110,7 +110,8 @@ private[sql] case class CreateTableUsing( /** * Builds a map in which keys are case insensitive */ -protected class CaseInsensitiveMap(map: Map[String, String]) extends Map[String, String] { +protected class CaseInsensitiveMap(map: Map[String, String]) extends Map[String, String] + with Serializable { val baseMap = map.map(kv => kv.copy(_1 = kv._1.toLowerCase)) From 1e56eba5d906bef793dfd6f199db735a6116a764 Mon Sep 17 00:00:00 2001 From: Alex Liu Date: Sat, 10 Jan 2015 13:19:12 -0800 Subject: [PATCH 215/320] [SPARK-4925][SQL] Publish Spark SQL hive-thriftserver maven artifact Author: Alex Liu Closes #3766 from alexliu68/SPARK-SQL-4925 and squashes the following commits: 3137b51 [Alex Liu] [SPARK-4925][SQL] Remove sql/hive-thriftserver module from pom.xml 15f2e38 [Alex Liu] [SPARK-4925][SQL] Publish Spark SQL hive-thriftserver maven artifact --- sql/hive-thriftserver/pom.xml | 7 ------- 1 file changed, 7 deletions(-) diff --git a/sql/hive-thriftserver/pom.xml b/sql/hive-thriftserver/pom.xml index 259eef0b80d03..123a1f629ab1c 100644 --- a/sql/hive-thriftserver/pom.xml +++ b/sql/hive-thriftserver/pom.xml @@ -76,13 +76,6 @@ - - org.apache.maven.plugins - maven-deploy-plugin - - true - - From 4b39fd1e63188821fc84a13f7ccb6e94277f4be7 Mon Sep 17 00:00:00 2001 From: Alex Liu Date: Sat, 10 Jan 2015 13:23:09 -0800 Subject: [PATCH 216/320] [SPARK-4943][SQL] Allow table name having dot for db/catalog The pull only fixes the parsing error and changes API to use tableIdentifier. Joining different catalog datasource related change is not done in this pull. Author: Alex Liu Closes #3941 from alexliu68/SPARK-SQL-4943-3 and squashes the following commits: 343ae27 [Alex Liu] [SPARK-4943][SQL] refactoring according to review 29e5e55 [Alex Liu] [SPARK-4943][SQL] fix failed Hive CTAS tests 6ae77ce [Alex Liu] [SPARK-4943][SQL] fix TestHive matching error 3652997 [Alex Liu] [SPARK-4943][SQL] Allow table name having dot to support db/catalog ... --- .../apache/spark/sql/catalyst/SqlParser.scala | 6 +- .../sql/catalyst/analysis/Analyzer.scala | 8 +- .../spark/sql/catalyst/analysis/Catalog.scala | 106 +++++++++--------- .../sql/catalyst/analysis/unresolved.scala | 3 +- .../spark/sql/catalyst/dsl/package.scala | 2 +- .../sql/catalyst/analysis/AnalysisSuite.scala | 20 ++-- .../analysis/DecimalPrecisionSuite.scala | 2 +- .../org/apache/spark/sql/SQLContext.scala | 6 +- .../org/apache/spark/sql/SchemaRDDLike.scala | 4 +- .../org/apache/spark/sql/JoinSuite.scala | 4 +- .../apache/spark/sql/hive/HiveContext.scala | 2 +- .../spark/sql/hive/HiveMetastoreCatalog.scala | 52 ++++++--- .../org/apache/spark/sql/hive/HiveQl.scala | 29 +++-- .../org/apache/spark/sql/hive/TestHive.scala | 2 +- .../hive/execution/CreateTableAsSelect.scala | 4 +- .../spark/sql/hive/execution/commands.scala | 2 +- .../spark/sql/hive/StatisticsSuite.scala | 4 +- 17 files changed, 143 insertions(+), 113 deletions(-) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala index f79d4ff444dc0..fc7b8745590d1 100755 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala @@ -178,10 +178,10 @@ class SqlParser extends AbstractSparkSQLParser { joinedRelation | relationFactor protected lazy val relationFactor: Parser[LogicalPlan] = - ( ident ~ (opt(AS) ~> opt(ident)) ^^ { - case tableName ~ alias => UnresolvedRelation(None, tableName, alias) + ( rep1sep(ident, ".") ~ (opt(AS) ~> opt(ident)) ^^ { + case tableIdent ~ alias => UnresolvedRelation(tableIdent, alias) } - | ("(" ~> start <~ ")") ~ (AS.? ~> ident) ^^ { case s ~ a => Subquery(a, s) } + | ("(" ~> start <~ ")") ~ (AS.? ~> ident) ^^ { case s ~ a => Subquery(a, s) } ) protected lazy val joinedRelation: Parser[LogicalPlan] = diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala index 72680f37a0b4d..c009cc1e1e85c 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala @@ -228,11 +228,11 @@ class Analyzer(catalog: Catalog, */ object ResolveRelations extends Rule[LogicalPlan] { def apply(plan: LogicalPlan): LogicalPlan = plan transform { - case i @ InsertIntoTable(UnresolvedRelation(databaseName, name, alias), _, _, _) => + case i @ InsertIntoTable(UnresolvedRelation(tableIdentifier, alias), _, _, _) => i.copy( - table = EliminateAnalysisOperators(catalog.lookupRelation(databaseName, name, alias))) - case UnresolvedRelation(databaseName, name, alias) => - catalog.lookupRelation(databaseName, name, alias) + table = EliminateAnalysisOperators(catalog.lookupRelation(tableIdentifier, alias))) + case UnresolvedRelation(tableIdentifier, alias) => + catalog.lookupRelation(tableIdentifier, alias) } } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Catalog.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Catalog.scala index 0415d74bd8141..df8d03b86c533 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Catalog.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Catalog.scala @@ -28,77 +28,74 @@ trait Catalog { def caseSensitive: Boolean - def tableExists(db: Option[String], tableName: String): Boolean + def tableExists(tableIdentifier: Seq[String]): Boolean def lookupRelation( - databaseName: Option[String], - tableName: String, - alias: Option[String] = None): LogicalPlan + tableIdentifier: Seq[String], + alias: Option[String] = None): LogicalPlan - def registerTable(databaseName: Option[String], tableName: String, plan: LogicalPlan): Unit + def registerTable(tableIdentifier: Seq[String], plan: LogicalPlan): Unit - def unregisterTable(databaseName: Option[String], tableName: String): Unit + def unregisterTable(tableIdentifier: Seq[String]): Unit def unregisterAllTables(): Unit - protected def processDatabaseAndTableName( - databaseName: Option[String], - tableName: String): (Option[String], String) = { + protected def processTableIdentifier(tableIdentifier: Seq[String]): Seq[String] = { if (!caseSensitive) { - (databaseName.map(_.toLowerCase), tableName.toLowerCase) + tableIdentifier.map(_.toLowerCase) } else { - (databaseName, tableName) + tableIdentifier } } - protected def processDatabaseAndTableName( - databaseName: String, - tableName: String): (String, String) = { - if (!caseSensitive) { - (databaseName.toLowerCase, tableName.toLowerCase) + protected def getDbTableName(tableIdent: Seq[String]): String = { + val size = tableIdent.size + if (size <= 2) { + tableIdent.mkString(".") } else { - (databaseName, tableName) + tableIdent.slice(size - 2, size).mkString(".") } } + + protected def getDBTable(tableIdent: Seq[String]) : (Option[String], String) = { + (tableIdent.lift(tableIdent.size - 2), tableIdent.last) + } } class SimpleCatalog(val caseSensitive: Boolean) extends Catalog { val tables = new mutable.HashMap[String, LogicalPlan]() override def registerTable( - databaseName: Option[String], - tableName: String, + tableIdentifier: Seq[String], plan: LogicalPlan): Unit = { - val (dbName, tblName) = processDatabaseAndTableName(databaseName, tableName) - tables += ((tblName, plan)) + val tableIdent = processTableIdentifier(tableIdentifier) + tables += ((getDbTableName(tableIdent), plan)) } - override def unregisterTable( - databaseName: Option[String], - tableName: String) = { - val (dbName, tblName) = processDatabaseAndTableName(databaseName, tableName) - tables -= tblName + override def unregisterTable(tableIdentifier: Seq[String]) = { + val tableIdent = processTableIdentifier(tableIdentifier) + tables -= getDbTableName(tableIdent) } override def unregisterAllTables() = { tables.clear() } - override def tableExists(db: Option[String], tableName: String): Boolean = { - val (dbName, tblName) = processDatabaseAndTableName(db, tableName) - tables.get(tblName) match { + override def tableExists(tableIdentifier: Seq[String]): Boolean = { + val tableIdent = processTableIdentifier(tableIdentifier) + tables.get(getDbTableName(tableIdent)) match { case Some(_) => true case None => false } } override def lookupRelation( - databaseName: Option[String], - tableName: String, + tableIdentifier: Seq[String], alias: Option[String] = None): LogicalPlan = { - val (dbName, tblName) = processDatabaseAndTableName(databaseName, tableName) - val table = tables.getOrElse(tblName, sys.error(s"Table Not Found: $tableName")) - val tableWithQualifiers = Subquery(tblName, table) + val tableIdent = processTableIdentifier(tableIdentifier) + val tableFullName = getDbTableName(tableIdent) + val table = tables.getOrElse(tableFullName, sys.error(s"Table Not Found: $tableFullName")) + val tableWithQualifiers = Subquery(tableIdent.last, table) // If an alias was specified by the lookup, wrap the plan in a subquery so that attributes are // properly qualified with this alias. @@ -117,41 +114,39 @@ trait OverrideCatalog extends Catalog { // TODO: This doesn't work when the database changes... val overrides = new mutable.HashMap[(Option[String],String), LogicalPlan]() - abstract override def tableExists(db: Option[String], tableName: String): Boolean = { - val (dbName, tblName) = processDatabaseAndTableName(db, tableName) - overrides.get((dbName, tblName)) match { + abstract override def tableExists(tableIdentifier: Seq[String]): Boolean = { + val tableIdent = processTableIdentifier(tableIdentifier) + overrides.get(getDBTable(tableIdent)) match { case Some(_) => true - case None => super.tableExists(db, tableName) + case None => super.tableExists(tableIdentifier) } } abstract override def lookupRelation( - databaseName: Option[String], - tableName: String, + tableIdentifier: Seq[String], alias: Option[String] = None): LogicalPlan = { - val (dbName, tblName) = processDatabaseAndTableName(databaseName, tableName) - val overriddenTable = overrides.get((dbName, tblName)) - val tableWithQualifers = overriddenTable.map(r => Subquery(tblName, r)) + val tableIdent = processTableIdentifier(tableIdentifier) + val overriddenTable = overrides.get(getDBTable(tableIdent)) + val tableWithQualifers = overriddenTable.map(r => Subquery(tableIdent.last, r)) // If an alias was specified by the lookup, wrap the plan in a subquery so that attributes are // properly qualified with this alias. val withAlias = tableWithQualifers.map(r => alias.map(a => Subquery(a, r)).getOrElse(r)) - withAlias.getOrElse(super.lookupRelation(dbName, tblName, alias)) + withAlias.getOrElse(super.lookupRelation(tableIdentifier, alias)) } override def registerTable( - databaseName: Option[String], - tableName: String, + tableIdentifier: Seq[String], plan: LogicalPlan): Unit = { - val (dbName, tblName) = processDatabaseAndTableName(databaseName, tableName) - overrides.put((dbName, tblName), plan) + val tableIdent = processTableIdentifier(tableIdentifier) + overrides.put(getDBTable(tableIdent), plan) } - override def unregisterTable(databaseName: Option[String], tableName: String): Unit = { - val (dbName, tblName) = processDatabaseAndTableName(databaseName, tableName) - overrides.remove((dbName, tblName)) + override def unregisterTable(tableIdentifier: Seq[String]): Unit = { + val tableIdent = processTableIdentifier(tableIdentifier) + overrides.remove(getDBTable(tableIdent)) } override def unregisterAllTables(): Unit = { @@ -167,22 +162,21 @@ object EmptyCatalog extends Catalog { val caseSensitive: Boolean = true - def tableExists(db: Option[String], tableName: String): Boolean = { + def tableExists(tableIdentifier: Seq[String]): Boolean = { throw new UnsupportedOperationException } def lookupRelation( - databaseName: Option[String], - tableName: String, + tableIdentifier: Seq[String], alias: Option[String] = None) = { throw new UnsupportedOperationException } - def registerTable(databaseName: Option[String], tableName: String, plan: LogicalPlan): Unit = { + def registerTable(tableIdentifier: Seq[String], plan: LogicalPlan): Unit = { throw new UnsupportedOperationException } - def unregisterTable(databaseName: Option[String], tableName: String): Unit = { + def unregisterTable(tableIdentifier: Seq[String]): Unit = { throw new UnsupportedOperationException } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/unresolved.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/unresolved.scala index 77d84e1687e1b..71a738a0b2ca0 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/unresolved.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/unresolved.scala @@ -34,8 +34,7 @@ class UnresolvedException[TreeType <: TreeNode[_]](tree: TreeType, function: Str * Holds the name of a relation that has yet to be looked up in a [[Catalog]]. */ case class UnresolvedRelation( - databaseName: Option[String], - tableName: String, + tableIdentifier: Seq[String], alias: Option[String] = None) extends LeafNode { override def output = Nil override lazy val resolved = false diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala index 9608e15c0f302..b2262e5e6efb6 100755 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala @@ -290,7 +290,7 @@ package object dsl { def insertInto(tableName: String, overwrite: Boolean = false) = InsertIntoTable( - analysis.UnresolvedRelation(None, tableName), Map.empty, logicalPlan, overwrite) + analysis.UnresolvedRelation(Seq(tableName)), Map.empty, logicalPlan, overwrite) def analyze = analysis.SimpleAnalyzer(logicalPlan) } diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala index 82f2101d8ce17..f430057ef7191 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala @@ -44,8 +44,8 @@ class AnalysisSuite extends FunSuite with BeforeAndAfter { AttributeReference("e", ShortType)()) before { - caseSensitiveCatalog.registerTable(None, "TaBlE", testRelation) - caseInsensitiveCatalog.registerTable(None, "TaBlE", testRelation) + caseSensitiveCatalog.registerTable(Seq("TaBlE"), testRelation) + caseInsensitiveCatalog.registerTable(Seq("TaBlE"), testRelation) } test("union project *") { @@ -64,45 +64,45 @@ class AnalysisSuite extends FunSuite with BeforeAndAfter { assert( caseSensitiveAnalyze( Project(Seq(UnresolvedAttribute("TbL.a")), - UnresolvedRelation(None, "TaBlE", Some("TbL")))) === + UnresolvedRelation(Seq("TaBlE"), Some("TbL")))) === Project(testRelation.output, testRelation)) val e = intercept[TreeNodeException[_]] { caseSensitiveAnalyze( Project(Seq(UnresolvedAttribute("tBl.a")), - UnresolvedRelation(None, "TaBlE", Some("TbL")))) + UnresolvedRelation(Seq("TaBlE"), Some("TbL")))) } assert(e.getMessage().toLowerCase.contains("unresolved")) assert( caseInsensitiveAnalyze( Project(Seq(UnresolvedAttribute("TbL.a")), - UnresolvedRelation(None, "TaBlE", Some("TbL")))) === + UnresolvedRelation(Seq("TaBlE"), Some("TbL")))) === Project(testRelation.output, testRelation)) assert( caseInsensitiveAnalyze( Project(Seq(UnresolvedAttribute("tBl.a")), - UnresolvedRelation(None, "TaBlE", Some("TbL")))) === + UnresolvedRelation(Seq("TaBlE"), Some("TbL")))) === Project(testRelation.output, testRelation)) } test("resolve relations") { val e = intercept[RuntimeException] { - caseSensitiveAnalyze(UnresolvedRelation(None, "tAbLe", None)) + caseSensitiveAnalyze(UnresolvedRelation(Seq("tAbLe"), None)) } assert(e.getMessage == "Table Not Found: tAbLe") assert( - caseSensitiveAnalyze(UnresolvedRelation(None, "TaBlE", None)) === + caseSensitiveAnalyze(UnresolvedRelation(Seq("TaBlE"), None)) === testRelation) assert( - caseInsensitiveAnalyze(UnresolvedRelation(None, "tAbLe", None)) === + caseInsensitiveAnalyze(UnresolvedRelation(Seq("tAbLe"), None)) === testRelation) assert( - caseInsensitiveAnalyze(UnresolvedRelation(None, "TaBlE", None)) === + caseInsensitiveAnalyze(UnresolvedRelation(Seq("TaBlE"), None)) === testRelation) } diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/DecimalPrecisionSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/DecimalPrecisionSuite.scala index 3677a6e72e23a..bbbeb4f2e4fe3 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/DecimalPrecisionSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/DecimalPrecisionSuite.scala @@ -41,7 +41,7 @@ class DecimalPrecisionSuite extends FunSuite with BeforeAndAfter { val f: Expression = UnresolvedAttribute("f") before { - catalog.registerTable(None, "table", relation) + catalog.registerTable(Seq("table"), relation) } private def checkType(expression: Expression, expectedType: DataType): Unit = { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala index 6a1a4d995bf61..9962937277dad 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala @@ -276,7 +276,7 @@ class SQLContext(@transient val sparkContext: SparkContext) * @group userf */ def registerRDDAsTable(rdd: SchemaRDD, tableName: String): Unit = { - catalog.registerTable(None, tableName, rdd.queryExecution.logical) + catalog.registerTable(Seq(tableName), rdd.queryExecution.logical) } /** @@ -289,7 +289,7 @@ class SQLContext(@transient val sparkContext: SparkContext) */ def dropTempTable(tableName: String): Unit = { tryUncacheQuery(table(tableName)) - catalog.unregisterTable(None, tableName) + catalog.unregisterTable(Seq(tableName)) } /** @@ -308,7 +308,7 @@ class SQLContext(@transient val sparkContext: SparkContext) /** Returns the specified table as a SchemaRDD */ def table(tableName: String): SchemaRDD = - new SchemaRDD(this, catalog.lookupRelation(None, tableName)) + new SchemaRDD(this, catalog.lookupRelation(Seq(tableName))) /** * :: DeveloperApi :: diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDDLike.scala b/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDDLike.scala index fd5f4abcbcd65..3cf9209465b76 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDDLike.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDDLike.scala @@ -97,8 +97,8 @@ private[sql] trait SchemaRDDLike { */ @Experimental def insertInto(tableName: String, overwrite: Boolean): Unit = - sqlContext.executePlan( - InsertIntoTable(UnresolvedRelation(None, tableName), Map.empty, logicalPlan, overwrite)).toRdd + sqlContext.executePlan(InsertIntoTable(UnresolvedRelation(Seq(tableName)), + Map.empty, logicalPlan, overwrite)).toRdd /** * :: Experimental :: diff --git a/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala index 1a4232dab86e7..c7e136388fce8 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala @@ -302,8 +302,8 @@ class JoinSuite extends QueryTest with BeforeAndAfterEach { upperCaseData.where('N <= 4).registerTempTable("left") upperCaseData.where('N >= 3).registerTempTable("right") - val left = UnresolvedRelation(None, "left", None) - val right = UnresolvedRelation(None, "right", None) + val left = UnresolvedRelation(Seq("left"), None) + val right = UnresolvedRelation(Seq("right"), None) checkAnswer( left.join(right, FullOuter, Some("left.N".attr === "right.N".attr)), diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala index 982e0593fcfd1..1648fa826b900 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala @@ -124,7 +124,7 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { * in the Hive metastore. */ def analyze(tableName: String) { - val relation = EliminateAnalysisOperators(catalog.lookupRelation(None, tableName)) + val relation = EliminateAnalysisOperators(catalog.lookupRelation(Seq(tableName))) relation match { case relation: MetastoreRelation => diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala index b31a3ec25096b..2c859894cf8d3 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala @@ -30,6 +30,7 @@ import org.apache.hadoop.hive.metastore.TableType import org.apache.hadoop.hive.metastore.api.FieldSchema import org.apache.hadoop.hive.metastore.api.{Table => TTable, Partition => TPartition} import org.apache.hadoop.hive.ql.metadata.{Hive, Partition, Table, HiveException} +import org.apache.hadoop.hive.ql.metadata.InvalidTableException import org.apache.hadoop.hive.ql.plan.CreateTableDesc import org.apache.hadoop.hive.serde.serdeConstants import org.apache.hadoop.hive.serde2.{Deserializer, SerDeException} @@ -57,18 +58,25 @@ private[hive] class HiveMetastoreCatalog(hive: HiveContext) extends Catalog with val caseSensitive: Boolean = false - def tableExists(db: Option[String], tableName: String): Boolean = { - val (databaseName, tblName) = processDatabaseAndTableName( - db.getOrElse(hive.sessionState.getCurrentDatabase), tableName) - client.getTable(databaseName, tblName, false) != null + def tableExists(tableIdentifier: Seq[String]): Boolean = { + val tableIdent = processTableIdentifier(tableIdentifier) + val databaseName = tableIdent.lift(tableIdent.size - 2).getOrElse( + hive.sessionState.getCurrentDatabase) + val tblName = tableIdent.last + try { + client.getTable(databaseName, tblName) != null + } catch { + case ie: InvalidTableException => false + } } def lookupRelation( - db: Option[String], - tableName: String, + tableIdentifier: Seq[String], alias: Option[String]): LogicalPlan = synchronized { - val (databaseName, tblName) = - processDatabaseAndTableName(db.getOrElse(hive.sessionState.getCurrentDatabase), tableName) + val tableIdent = processTableIdentifier(tableIdentifier) + val databaseName = tableIdent.lift(tableIdent.size - 2).getOrElse( + hive.sessionState.getCurrentDatabase) + val tblName = tableIdent.last val table = client.getTable(databaseName, tblName) if (table.isView) { // if the unresolved relation is from hive view @@ -251,6 +259,26 @@ private[hive] class HiveMetastoreCatalog(hive: HiveContext) extends Catalog with } } + protected def processDatabaseAndTableName( + databaseName: Option[String], + tableName: String): (Option[String], String) = { + if (!caseSensitive) { + (databaseName.map(_.toLowerCase), tableName.toLowerCase) + } else { + (databaseName, tableName) + } + } + + protected def processDatabaseAndTableName( + databaseName: String, + tableName: String): (String, String) = { + if (!caseSensitive) { + (databaseName.toLowerCase, tableName.toLowerCase) + } else { + (databaseName, tableName) + } + } + /** * Creates any tables required for query execution. * For example, because of a CREATE TABLE X AS statement. @@ -270,7 +298,7 @@ private[hive] class HiveMetastoreCatalog(hive: HiveContext) extends Catalog with val databaseName = dbName.getOrElse(hive.sessionState.getCurrentDatabase) // Get the CreateTableDesc from Hive SemanticAnalyzer - val desc: Option[CreateTableDesc] = if (tableExists(Some(databaseName), tblName)) { + val desc: Option[CreateTableDesc] = if (tableExists(Seq(databaseName, tblName))) { None } else { val sa = new SemanticAnalyzer(hive.hiveconf) { @@ -352,15 +380,13 @@ private[hive] class HiveMetastoreCatalog(hive: HiveContext) extends Catalog with * UNIMPLEMENTED: It needs to be decided how we will persist in-memory tables to the metastore. * For now, if this functionality is desired mix in the in-memory [[OverrideCatalog]]. */ - override def registerTable( - databaseName: Option[String], tableName: String, plan: LogicalPlan): Unit = ??? + override def registerTable(tableIdentifier: Seq[String], plan: LogicalPlan): Unit = ??? /** * UNIMPLEMENTED: It needs to be decided how we will persist in-memory tables to the metastore. * For now, if this functionality is desired mix in the in-memory [[OverrideCatalog]]. */ - override def unregisterTable( - databaseName: Option[String], tableName: String): Unit = ??? + override def unregisterTable(tableIdentifier: Seq[String]): Unit = ??? override def unregisterAllTables() = {} } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala index 8a9613cf96e54..c2ab3579c1f95 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala @@ -386,6 +386,15 @@ private[hive] object HiveQl { (db, tableName) } + protected def extractTableIdent(tableNameParts: Node): Seq[String] = { + tableNameParts.getChildren.map { case Token(part, Nil) => cleanIdentifier(part) } match { + case Seq(tableOnly) => Seq(tableOnly) + case Seq(databaseName, table) => Seq(databaseName, table) + case other => sys.error("Hive only supports tables names like 'tableName' " + + s"or 'databaseName.tableName', found '$other'") + } + } + /** * SELECT MAX(value) FROM src GROUP BY k1, k2, k3 GROUPING SETS((k1, k2), (k2)) * is equivalent to @@ -475,16 +484,16 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C case Token(".", dbName :: tableName :: Nil) => // It is describing a table with the format like "describe db.table". // TODO: Actually, a user may mean tableName.columnName. Need to resolve this issue. - val (db, tableName) = extractDbNameTableName(nameParts.head) + val tableIdent = extractTableIdent(nameParts.head) DescribeCommand( - UnresolvedRelation(db, tableName, None), extended.isDefined) + UnresolvedRelation(tableIdent, None), extended.isDefined) case Token(".", dbName :: tableName :: colName :: Nil) => // It is describing a column with the format like "describe db.table column". NativePlaceholder case tableName => // It is describing a table with the format like "describe table". DescribeCommand( - UnresolvedRelation(None, tableName.getText, None), + UnresolvedRelation(Seq(tableName.getText), None), extended.isDefined) } } @@ -757,13 +766,15 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C nonAliasClauses) } - val (db, tableName) = + val tableIdent = tableNameParts.getChildren.map{ case Token(part, Nil) => cleanIdentifier(part)} match { - case Seq(tableOnly) => (None, tableOnly) - case Seq(databaseName, table) => (Some(databaseName), table) + case Seq(tableOnly) => Seq(tableOnly) + case Seq(databaseName, table) => Seq(databaseName, table) + case other => sys.error("Hive only supports tables names like 'tableName' " + + s"or 'databaseName.tableName', found '$other'") } val alias = aliasClause.map { case Token(a, Nil) => cleanIdentifier(a) } - val relation = UnresolvedRelation(db, tableName, alias) + val relation = UnresolvedRelation(tableIdent, alias) // Apply sampling if requested. (bucketSampleClause orElse splitSampleClause).map { @@ -882,7 +893,7 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C val Some(tableNameParts) :: partitionClause :: Nil = getClauses(Seq("TOK_TABNAME", "TOK_PARTSPEC"), tableArgs) - val (db, tableName) = extractDbNameTableName(tableNameParts) + val tableIdent = extractTableIdent(tableNameParts) val partitionKeys = partitionClause.map(_.getChildren.map { // Parse partitions. We also make keys case insensitive. @@ -892,7 +903,7 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C cleanIdentifier(key.toLowerCase) -> None }.toMap).getOrElse(Map.empty) - InsertIntoTable(UnresolvedRelation(db, tableName, None), partitionKeys, query, overwrite) + InsertIntoTable(UnresolvedRelation(tableIdent, None), partitionKeys, query, overwrite) case a: ASTNode => throw new NotImplementedError(s"No parse rules for:\n ${dumpTree(a).toString} ") diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala index b2149bd95a336..8f2311cf83eb8 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala @@ -167,7 +167,7 @@ class TestHiveContext(sc: SparkContext) extends HiveContext(sc) { // Make sure any test tables referenced are loaded. val referencedTables = describedTables ++ - logical.collect { case UnresolvedRelation(databaseName, name, _) => name } + logical.collect { case UnresolvedRelation(tableIdent, _) => tableIdent.last } val referencedTestTables = referencedTables.filter(testTables.contains) logDebug(s"Query references test tables: ${referencedTestTables.mkString(", ")}") referencedTestTables.foreach(loadTestTable) diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateTableAsSelect.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateTableAsSelect.scala index fe21454e7fb38..a547babcebfff 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateTableAsSelect.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateTableAsSelect.scala @@ -53,14 +53,14 @@ case class CreateTableAsSelect( hiveContext.catalog.createTable(database, tableName, query.output, allowExisting, desc) // Get the Metastore Relation - hiveContext.catalog.lookupRelation(Some(database), tableName, None) match { + hiveContext.catalog.lookupRelation(Seq(database, tableName), None) match { case r: MetastoreRelation => r } } // TODO ideally, we should get the output data ready first and then // add the relation into catalog, just in case of failure occurs while data // processing. - if (hiveContext.catalog.tableExists(Some(database), tableName)) { + if (hiveContext.catalog.tableExists(Seq(database, tableName))) { if (allowExisting) { // table already exists, will do nothing, to keep consistent with Hive } else { diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala index 6fc4153f6a5df..6b733a280e6d5 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala @@ -53,7 +53,7 @@ case class DropTable( val hiveContext = sqlContext.asInstanceOf[HiveContext] val ifExistsClause = if (ifExists) "IF EXISTS " else "" hiveContext.runSqlHive(s"DROP TABLE $ifExistsClause$tableName") - hiveContext.catalog.unregisterTable(None, tableName) + hiveContext.catalog.unregisterTable(Seq(tableName)) Seq.empty[Row] } } diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala index 4b6a9308b9811..a758f921e0417 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala @@ -72,7 +72,7 @@ class StatisticsSuite extends QueryTest with BeforeAndAfterAll { test("analyze MetastoreRelations") { def queryTotalSize(tableName: String): BigInt = - catalog.lookupRelation(None, tableName).statistics.sizeInBytes + catalog.lookupRelation(Seq(tableName)).statistics.sizeInBytes // Non-partitioned table sql("CREATE TABLE analyzeTable (key STRING, value STRING)").collect() @@ -123,7 +123,7 @@ class StatisticsSuite extends QueryTest with BeforeAndAfterAll { intercept[NotImplementedError] { analyze("tempTable") } - catalog.unregisterTable(None, "tempTable") + catalog.unregisterTable(Seq("tempTable")) } test("estimates the size of a test MetastoreRelation") { From 693a323a70aba91e6c100dd5561d218a75b7895e Mon Sep 17 00:00:00 2001 From: scwf Date: Sat, 10 Jan 2015 13:53:21 -0800 Subject: [PATCH 217/320] [SPARK-4574][SQL] Adding support for defining schema in foreign DDL commands. Adding support for defining schema in foreign DDL commands. Now foreign DDL support commands like: ``` CREATE TEMPORARY TABLE avroTable USING org.apache.spark.sql.avro OPTIONS (path "../hive/src/test/resources/data/files/episodes.avro") ``` With this PR user can define schema instead of infer from file, so support ddl command as follows: ``` CREATE TEMPORARY TABLE avroTable(a int, b string) USING org.apache.spark.sql.avro OPTIONS (path "../hive/src/test/resources/data/files/episodes.avro") ``` Author: scwf Author: Yin Huai Author: Fei Wang Author: wangfei Closes #3431 from scwf/ddl and squashes the following commits: 7e79ce5 [Fei Wang] Merge pull request #22 from yhuai/pr3431yin 38f634e [Yin Huai] Remove Option from createRelation. 65e9c73 [Yin Huai] Revert all changes since applying a given schema has not been testd. a852b10 [scwf] remove cleanIdentifier f336a16 [Fei Wang] Merge pull request #21 from yhuai/pr3431yin baf79b5 [Yin Huai] Test special characters quoted by backticks. 50a03b0 [Yin Huai] Use JsonRDD.nullTypeToStringType to convert NullType to StringType. 1eeb769 [Fei Wang] Merge pull request #20 from yhuai/pr3431yin f5c22b0 [Yin Huai] Refactor code and update test cases. f1cffe4 [Yin Huai] Revert "minor refactory" b621c8f [scwf] minor refactory d02547f [scwf] fix HiveCompatibilitySuite test failure 8dfbf7a [scwf] more tests for complex data type ddab984 [Fei Wang] Merge pull request #19 from yhuai/pr3431yin 91ad91b [Yin Huai] Parse data types in DDLParser. cf982d2 [scwf] fixed test failure 445b57b [scwf] address comments 02a662c [scwf] style issue 44eb70c [scwf] fix decimal parser issue 83b6fc3 [scwf] minor fix 9bf12f8 [wangfei] adding test case 7787ec7 [wangfei] added SchemaRelationProvider 0ba70df [wangfei] draft version --- .../apache/spark/sql/json/JSONRelation.scala | 35 +++- .../org/apache/spark/sql/sources/ddl.scala | 138 +++++++++++-- .../apache/spark/sql/sources/interfaces.scala | 29 ++- .../spark/sql/sources/TableScanSuite.scala | 192 ++++++++++++++++++ .../spark/sql/hive/HiveMetastoreCatalog.scala | 114 +++-------- .../sql/hive/HiveMetastoreCatalogSuite.scala | 5 +- 6 files changed, 400 insertions(+), 113 deletions(-) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/json/JSONRelation.scala b/sql/core/src/main/scala/org/apache/spark/sql/json/JSONRelation.scala index fc70c183437f6..a9a6696cb15e4 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/json/JSONRelation.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/json/JSONRelation.scala @@ -18,31 +18,48 @@ package org.apache.spark.sql.json import org.apache.spark.sql.SQLContext +import org.apache.spark.sql.catalyst.types.StructType import org.apache.spark.sql.sources._ -private[sql] class DefaultSource extends RelationProvider { - /** Returns a new base relation with the given parameters. */ +private[sql] class DefaultSource extends RelationProvider with SchemaRelationProvider { + + /** Returns a new base relation with the parameters. */ override def createRelation( sqlContext: SQLContext, parameters: Map[String, String]): BaseRelation = { val fileName = parameters.getOrElse("path", sys.error("Option 'path' not specified")) val samplingRatio = parameters.get("samplingRatio").map(_.toDouble).getOrElse(1.0) - JSONRelation(fileName, samplingRatio)(sqlContext) + JSONRelation(fileName, samplingRatio, None)(sqlContext) + } + + /** Returns a new base relation with the given schema and parameters. */ + override def createRelation( + sqlContext: SQLContext, + parameters: Map[String, String], + schema: StructType): BaseRelation = { + val fileName = parameters.getOrElse("path", sys.error("Option 'path' not specified")) + val samplingRatio = parameters.get("samplingRatio").map(_.toDouble).getOrElse(1.0) + + JSONRelation(fileName, samplingRatio, Some(schema))(sqlContext) } } -private[sql] case class JSONRelation(fileName: String, samplingRatio: Double)( +private[sql] case class JSONRelation( + fileName: String, + samplingRatio: Double, + userSpecifiedSchema: Option[StructType])( @transient val sqlContext: SQLContext) extends TableScan { private def baseRDD = sqlContext.sparkContext.textFile(fileName) - override val schema = - JsonRDD.inferSchema( - baseRDD, - samplingRatio, - sqlContext.columnNameOfCorruptRecord) + override val schema = userSpecifiedSchema.getOrElse( + JsonRDD.nullTypeToStringType( + JsonRDD.inferSchema( + baseRDD, + samplingRatio, + sqlContext.columnNameOfCorruptRecord))) override def buildScan() = JsonRDD.jsonStringToRow(baseRDD, schema, sqlContext.columnNameOfCorruptRecord) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala index 364bacec83b98..fe2c4d8436b2b 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala @@ -17,16 +17,15 @@ package org.apache.spark.sql.sources -import org.apache.spark.Logging -import org.apache.spark.sql.SQLContext -import org.apache.spark.sql.execution.RunnableCommand -import org.apache.spark.util.Utils - import scala.language.implicitConversions -import scala.util.parsing.combinator.lexical.StdLexical import scala.util.parsing.combinator.syntactical.StandardTokenParsers import scala.util.parsing.combinator.PackratParsers +import org.apache.spark.Logging +import org.apache.spark.sql.SQLContext +import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.execution.RunnableCommand +import org.apache.spark.util.Utils import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.SqlLexical @@ -44,6 +43,14 @@ private[sql] class DDLParser extends StandardTokenParsers with PackratParsers wi } } + def parseType(input: String): DataType = { + phrase(dataType)(new lexical.Scanner(input)) match { + case Success(r, x) => r + case x => + sys.error(s"Unsupported dataType: $x") + } + } + protected case class Keyword(str: String) protected implicit def asParser(k: Keyword): Parser[String] = @@ -55,6 +62,24 @@ private[sql] class DDLParser extends StandardTokenParsers with PackratParsers wi protected val USING = Keyword("USING") protected val OPTIONS = Keyword("OPTIONS") + // Data types. + protected val STRING = Keyword("STRING") + protected val BINARY = Keyword("BINARY") + protected val BOOLEAN = Keyword("BOOLEAN") + protected val TINYINT = Keyword("TINYINT") + protected val SMALLINT = Keyword("SMALLINT") + protected val INT = Keyword("INT") + protected val BIGINT = Keyword("BIGINT") + protected val FLOAT = Keyword("FLOAT") + protected val DOUBLE = Keyword("DOUBLE") + protected val DECIMAL = Keyword("DECIMAL") + protected val DATE = Keyword("DATE") + protected val TIMESTAMP = Keyword("TIMESTAMP") + protected val VARCHAR = Keyword("VARCHAR") + protected val ARRAY = Keyword("ARRAY") + protected val MAP = Keyword("MAP") + protected val STRUCT = Keyword("STRUCT") + // Use reflection to find the reserved words defined in this class. protected val reservedWords = this.getClass @@ -67,15 +92,25 @@ private[sql] class DDLParser extends StandardTokenParsers with PackratParsers wi protected lazy val ddl: Parser[LogicalPlan] = createTable /** - * CREATE TEMPORARY TABLE avroTable + * `CREATE TEMPORARY TABLE avroTable * USING org.apache.spark.sql.avro - * OPTIONS (path "../hive/src/test/resources/data/files/episodes.avro") + * OPTIONS (path "../hive/src/test/resources/data/files/episodes.avro")` + * or + * `CREATE TEMPORARY TABLE avroTable(intField int, stringField string...) + * USING org.apache.spark.sql.avro + * OPTIONS (path "../hive/src/test/resources/data/files/episodes.avro")` */ protected lazy val createTable: Parser[LogicalPlan] = - CREATE ~ TEMPORARY ~ TABLE ~> ident ~ (USING ~> className) ~ (OPTIONS ~> options) ^^ { - case tableName ~ provider ~ opts => - CreateTableUsing(tableName, provider, opts) + ( + CREATE ~ TEMPORARY ~ TABLE ~> ident + ~ (tableCols).? ~ (USING ~> className) ~ (OPTIONS ~> options) ^^ { + case tableName ~ columns ~ provider ~ opts => + val userSpecifiedSchema = columns.flatMap(fields => Some(StructType(fields))) + CreateTableUsing(tableName, userSpecifiedSchema, provider, opts) } + ) + + protected lazy val tableCols: Parser[Seq[StructField]] = "(" ~> repsep(column, ",") <~ ")" protected lazy val options: Parser[Map[String, String]] = "(" ~> repsep(pair, ",") <~ ")" ^^ { case s: Seq[(String, String)] => s.toMap } @@ -83,10 +118,66 @@ private[sql] class DDLParser extends StandardTokenParsers with PackratParsers wi protected lazy val className: Parser[String] = repsep(ident, ".") ^^ { case s => s.mkString(".")} protected lazy val pair: Parser[(String, String)] = ident ~ stringLit ^^ { case k ~ v => (k,v) } + + protected lazy val column: Parser[StructField] = + ident ~ dataType ^^ { case columnName ~ typ => + StructField(columnName, typ) + } + + protected lazy val primitiveType: Parser[DataType] = + STRING ^^^ StringType | + BINARY ^^^ BinaryType | + BOOLEAN ^^^ BooleanType | + TINYINT ^^^ ByteType | + SMALLINT ^^^ ShortType | + INT ^^^ IntegerType | + BIGINT ^^^ LongType | + FLOAT ^^^ FloatType | + DOUBLE ^^^ DoubleType | + fixedDecimalType | // decimal with precision/scale + DECIMAL ^^^ DecimalType.Unlimited | // decimal with no precision/scale + DATE ^^^ DateType | + TIMESTAMP ^^^ TimestampType | + VARCHAR ~ "(" ~ numericLit ~ ")" ^^^ StringType + + protected lazy val fixedDecimalType: Parser[DataType] = + (DECIMAL ~ "(" ~> numericLit) ~ ("," ~> numericLit <~ ")") ^^ { + case precision ~ scale => DecimalType(precision.toInt, scale.toInt) + } + + protected lazy val arrayType: Parser[DataType] = + ARRAY ~> "<" ~> dataType <~ ">" ^^ { + case tpe => ArrayType(tpe) + } + + protected lazy val mapType: Parser[DataType] = + MAP ~> "<" ~> dataType ~ "," ~ dataType <~ ">" ^^ { + case t1 ~ _ ~ t2 => MapType(t1, t2) + } + + protected lazy val structField: Parser[StructField] = + ident ~ ":" ~ dataType ^^ { + case fieldName ~ _ ~ tpe => StructField(fieldName, tpe, nullable = true) + } + + protected lazy val structType: Parser[DataType] = + (STRUCT ~> "<" ~> repsep(structField, ",") <~ ">" ^^ { + case fields => new StructType(fields) + }) | + (STRUCT ~> "<>" ^^ { + case fields => new StructType(Nil) + }) + + private[sql] lazy val dataType: Parser[DataType] = + arrayType | + mapType | + structType | + primitiveType } private[sql] case class CreateTableUsing( tableName: String, + userSpecifiedSchema: Option[StructType], provider: String, options: Map[String, String]) extends RunnableCommand { @@ -99,8 +190,29 @@ private[sql] case class CreateTableUsing( sys.error(s"Failed to load class for data source: $provider") } } - val dataSource = clazz.newInstance().asInstanceOf[org.apache.spark.sql.sources.RelationProvider] - val relation = dataSource.createRelation(sqlContext, new CaseInsensitiveMap(options)) + + val relation = userSpecifiedSchema match { + case Some(schema: StructType) => { + clazz.newInstance match { + case dataSource: org.apache.spark.sql.sources.SchemaRelationProvider => + dataSource + .asInstanceOf[org.apache.spark.sql.sources.SchemaRelationProvider] + .createRelation(sqlContext, new CaseInsensitiveMap(options), schema) + case _ => + sys.error(s"${clazz.getCanonicalName} should extend SchemaRelationProvider.") + } + } + case None => { + clazz.newInstance match { + case dataSource: org.apache.spark.sql.sources.RelationProvider => + dataSource + .asInstanceOf[org.apache.spark.sql.sources.RelationProvider] + .createRelation(sqlContext, new CaseInsensitiveMap(options)) + case _ => + sys.error(s"${clazz.getCanonicalName} should extend RelationProvider.") + } + } + } sqlContext.baseRelationToSchemaRDD(relation).registerTempTable(tableName) Seq.empty diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala index 02eff80456dbe..990f7e0e74bcf 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala @@ -18,7 +18,7 @@ package org.apache.spark.sql.sources import org.apache.spark.annotation.{Experimental, DeveloperApi} import org.apache.spark.rdd.RDD -import org.apache.spark.sql.{SQLConf, Row, SQLContext, StructType} +import org.apache.spark.sql.{Row, SQLContext, StructType} import org.apache.spark.sql.catalyst.expressions.{Expression, Attribute} /** @@ -44,6 +44,33 @@ trait RelationProvider { def createRelation(sqlContext: SQLContext, parameters: Map[String, String]): BaseRelation } +/** + * ::DeveloperApi:: + * Implemented by objects that produce relations for a specific kind of data source. When + * Spark SQL is given a DDL operation with + * 1. USING clause: to specify the implemented SchemaRelationProvider + * 2. User defined schema: users can define schema optionally when create table + * + * Users may specify the fully qualified class name of a given data source. When that class is + * not found Spark SQL will append the class name `DefaultSource` to the path, allowing for + * less verbose invocation. For example, 'org.apache.spark.sql.json' would resolve to the + * data source 'org.apache.spark.sql.json.DefaultSource' + * + * A new instance of this class with be instantiated each time a DDL call is made. + */ +@DeveloperApi +trait SchemaRelationProvider { + /** + * Returns a new base relation with the given parameters and user defined schema. + * Note: the parameters' keywords are case insensitive and this insensitivity is enforced + * by the Map that is passed to the function. + */ + def createRelation( + sqlContext: SQLContext, + parameters: Map[String, String], + schema: StructType): BaseRelation +} + /** * ::DeveloperApi:: * Represents a collection of tuples with a known schema. Classes that extend BaseRelation must diff --git a/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala index 3cd7b0115d567..605190f5ae6a2 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala @@ -17,7 +17,10 @@ package org.apache.spark.sql.sources +import java.sql.{Timestamp, Date} + import org.apache.spark.sql._ +import org.apache.spark.sql.catalyst.types.DecimalType class DefaultSource extends SimpleScanSource @@ -38,9 +41,77 @@ case class SimpleScan(from: Int, to: Int)(@transient val sqlContext: SQLContext) override def buildScan() = sqlContext.sparkContext.parallelize(from to to).map(Row(_)) } +class AllDataTypesScanSource extends SchemaRelationProvider { + override def createRelation( + sqlContext: SQLContext, + parameters: Map[String, String], + schema: StructType): BaseRelation = { + AllDataTypesScan(parameters("from").toInt, parameters("TO").toInt, schema)(sqlContext) + } +} + +case class AllDataTypesScan( + from: Int, + to: Int, + userSpecifiedSchema: StructType)(@transient val sqlContext: SQLContext) + extends TableScan { + + override def schema = userSpecifiedSchema + + override def buildScan() = { + sqlContext.sparkContext.parallelize(from to to).map { i => + Row( + s"str_$i", + s"str_$i".getBytes(), + i % 2 == 0, + i.toByte, + i.toShort, + i, + i.toLong, + i.toFloat, + i.toDouble, + BigDecimal(i), + BigDecimal(i), + new Date((i + 1) * 8640000), + new Timestamp(20000 + i), + s"varchar_$i", + Seq(i, i + 1), + Seq(Map(s"str_$i" -> Row(i.toLong))), + Map(i -> i.toString), + Map(Map(s"str_$i" -> i.toFloat) -> Row(i.toLong)), + Row(i, i.toString), + Row(Seq(s"str_$i", s"str_${i + 1}"), Row(Seq(new Date((i + 2) * 8640000))))) + } + } +} + class TableScanSuite extends DataSourceTest { import caseInsensisitiveContext._ + var tableWithSchemaExpected = (1 to 10).map { i => + Row( + s"str_$i", + s"str_$i", + i % 2 == 0, + i.toByte, + i.toShort, + i, + i.toLong, + i.toFloat, + i.toDouble, + BigDecimal(i), + BigDecimal(i), + new Date((i + 1) * 8640000), + new Timestamp(20000 + i), + s"varchar_$i", + Seq(i, i + 1), + Seq(Map(s"str_$i" -> Row(i.toLong))), + Map(i -> i.toString), + Map(Map(s"str_$i" -> i.toFloat) -> Row(i.toLong)), + Row(i, i.toString), + Row(Seq(s"str_$i", s"str_${i + 1}"), Row(Seq(new Date((i + 2) * 8640000))))) + }.toSeq + before { sql( """ @@ -51,6 +122,37 @@ class TableScanSuite extends DataSourceTest { | To '10' |) """.stripMargin) + + sql( + """ + |CREATE TEMPORARY TABLE tableWithSchema ( + |`string$%Field` stRIng, + |binaryField binary, + |`booleanField` boolean, + |ByteField tinyint, + |shortField smaLlint, + |int_Field iNt, + |`longField_:,<>=+/~^` Bigint, + |floatField flOat, + |doubleField doubLE, + |decimalField1 decimal, + |decimalField2 decimal(9,2), + |dateField dAte, + |timestampField tiMestamp, + |varcharField varchaR(12), + |arrayFieldSimple Array, + |arrayFieldComplex Array>>, + |mapFieldSimple MAP, + |mapFieldComplex Map, Struct>, + |structFieldSimple StRuct, + |structFieldComplex StRuct, Value:struct<`value_(2)`:Array>> + |) + |USING org.apache.spark.sql.sources.AllDataTypesScanSource + |OPTIONS ( + | From '1', + | To '10' + |) + """.stripMargin) } sqlTest( @@ -73,6 +175,96 @@ class TableScanSuite extends DataSourceTest { "SELECT a.i, b.i FROM oneToTen a JOIN oneToTen b ON a.i = b.i + 1", (2 to 10).map(i => Row(i, i - 1)).toSeq) + test("Schema and all fields") { + val expectedSchema = StructType( + StructField("string$%Field", StringType, true) :: + StructField("binaryField", BinaryType, true) :: + StructField("booleanField", BooleanType, true) :: + StructField("ByteField", ByteType, true) :: + StructField("shortField", ShortType, true) :: + StructField("int_Field", IntegerType, true) :: + StructField("longField_:,<>=+/~^", LongType, true) :: + StructField("floatField", FloatType, true) :: + StructField("doubleField", DoubleType, true) :: + StructField("decimalField1", DecimalType.Unlimited, true) :: + StructField("decimalField2", DecimalType(9, 2), true) :: + StructField("dateField", DateType, true) :: + StructField("timestampField", TimestampType, true) :: + StructField("varcharField", StringType, true) :: + StructField("arrayFieldSimple", ArrayType(IntegerType), true) :: + StructField("arrayFieldComplex", + ArrayType( + MapType(StringType, StructType(StructField("key", LongType, true) :: Nil))), true) :: + StructField("mapFieldSimple", MapType(IntegerType, StringType), true) :: + StructField("mapFieldComplex", + MapType( + MapType(StringType, FloatType), + StructType(StructField("key", LongType, true) :: Nil)), true) :: + StructField("structFieldSimple", + StructType( + StructField("key", IntegerType, true) :: + StructField("Value", StringType, true) :: Nil), true) :: + StructField("structFieldComplex", + StructType( + StructField("key", ArrayType(StringType), true) :: + StructField("Value", + StructType( + StructField("value_(2)", ArrayType(DateType), true) :: Nil), true) :: Nil), true) :: + Nil + ) + + assert(expectedSchema == table("tableWithSchema").schema) + + checkAnswer( + sql( + """SELECT + | `string$%Field`, + | cast(binaryField as string), + | booleanField, + | byteField, + | shortField, + | int_Field, + | `longField_:,<>=+/~^`, + | floatField, + | doubleField, + | decimalField1, + | decimalField2, + | dateField, + | timestampField, + | varcharField, + | arrayFieldSimple, + | arrayFieldComplex, + | mapFieldSimple, + | mapFieldComplex, + | structFieldSimple, + | structFieldComplex FROM tableWithSchema""".stripMargin), + tableWithSchemaExpected + ) + } + + sqlTest( + "SELECT count(*) FROM tableWithSchema", + 10) + + sqlTest( + "SELECT `string$%Field` FROM tableWithSchema", + (1 to 10).map(i => Row(s"str_$i")).toSeq) + + sqlTest( + "SELECT int_Field FROM tableWithSchema WHERE int_Field < 5", + (1 to 4).map(Row(_)).toSeq) + + sqlTest( + "SELECT `longField_:,<>=+/~^` * 2 FROM tableWithSchema", + (1 to 10).map(i => Row(i * 2.toLong)).toSeq) + + sqlTest( + "SELECT structFieldSimple.key, arrayFieldSimple[1] FROM tableWithSchema a where int_Field=1", + Seq(Seq(1, 2))) + + sqlTest( + "SELECT structFieldComplex.Value.`value_(2)` FROM tableWithSchema", + (1 to 10).map(i => Row(Seq(new Date((i + 2) * 8640000)))).toSeq) test("Caching") { // Cached Query Execution diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala index 2c859894cf8d3..c25288e000122 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala @@ -20,12 +20,7 @@ package org.apache.spark.sql.hive import java.io.IOException import java.util.{List => JList} -import org.apache.spark.sql.execution.SparkPlan - -import scala.util.parsing.combinator.RegexParsers - import org.apache.hadoop.util.ReflectionUtils - import org.apache.hadoop.hive.metastore.TableType import org.apache.hadoop.hive.metastore.api.FieldSchema import org.apache.hadoop.hive.metastore.api.{Table => TTable, Partition => TPartition} @@ -37,7 +32,6 @@ import org.apache.hadoop.hive.serde2.{Deserializer, SerDeException} import org.apache.hadoop.hive.serde2.`lazy`.LazySimpleSerDe import org.apache.spark.Logging -import org.apache.spark.annotation.DeveloperApi import org.apache.spark.sql.SQLContext import org.apache.spark.sql.catalyst.analysis.{Catalog, OverrideCatalog} import org.apache.spark.sql.catalyst.expressions._ @@ -412,88 +406,6 @@ private[hive] case class InsertIntoHiveTable( } } -/** - * :: DeveloperApi :: - * Provides conversions between Spark SQL data types and Hive Metastore types. - */ -@DeveloperApi -object HiveMetastoreTypes extends RegexParsers { - protected lazy val primitiveType: Parser[DataType] = - "string" ^^^ StringType | - "float" ^^^ FloatType | - "int" ^^^ IntegerType | - "tinyint" ^^^ ByteType | - "smallint" ^^^ ShortType | - "double" ^^^ DoubleType | - "bigint" ^^^ LongType | - "binary" ^^^ BinaryType | - "boolean" ^^^ BooleanType | - fixedDecimalType | // Hive 0.13+ decimal with precision/scale - "decimal" ^^^ DecimalType.Unlimited | // Hive 0.12 decimal with no precision/scale - "date" ^^^ DateType | - "timestamp" ^^^ TimestampType | - "varchar\\((\\d+)\\)".r ^^^ StringType - - protected lazy val fixedDecimalType: Parser[DataType] = - ("decimal" ~> "(" ~> "\\d+".r) ~ ("," ~> "\\d+".r <~ ")") ^^ { - case precision ~ scale => - DecimalType(precision.toInt, scale.toInt) - } - - protected lazy val arrayType: Parser[DataType] = - "array" ~> "<" ~> dataType <~ ">" ^^ { - case tpe => ArrayType(tpe) - } - - protected lazy val mapType: Parser[DataType] = - "map" ~> "<" ~> dataType ~ "," ~ dataType <~ ">" ^^ { - case t1 ~ _ ~ t2 => MapType(t1, t2) - } - - protected lazy val structField: Parser[StructField] = - "[a-zA-Z0-9_]*".r ~ ":" ~ dataType ^^ { - case name ~ _ ~ tpe => StructField(name, tpe, nullable = true) - } - - protected lazy val structType: Parser[DataType] = - "struct" ~> "<" ~> repsep(structField,",") <~ ">" ^^ { - case fields => new StructType(fields) - } - - protected lazy val dataType: Parser[DataType] = - arrayType | - mapType | - structType | - primitiveType - - def toDataType(metastoreType: String): DataType = parseAll(dataType, metastoreType) match { - case Success(result, _) => result - case failure: NoSuccess => sys.error(s"Unsupported dataType: $metastoreType") - } - - def toMetastoreType(dt: DataType): String = dt match { - case ArrayType(elementType, _) => s"array<${toMetastoreType(elementType)}>" - case StructType(fields) => - s"struct<${fields.map(f => s"${f.name}:${toMetastoreType(f.dataType)}").mkString(",")}>" - case MapType(keyType, valueType, _) => - s"map<${toMetastoreType(keyType)},${toMetastoreType(valueType)}>" - case StringType => "string" - case FloatType => "float" - case IntegerType => "int" - case ByteType => "tinyint" - case ShortType => "smallint" - case DoubleType => "double" - case LongType => "bigint" - case BinaryType => "binary" - case BooleanType => "boolean" - case DateType => "date" - case d: DecimalType => HiveShim.decimalMetastoreString(d) - case TimestampType => "timestamp" - case NullType => "void" - case udt: UserDefinedType[_] => toMetastoreType(udt.sqlType) - } -} - private[hive] case class MetastoreRelation (databaseName: String, tableName: String, alias: Option[String]) (val table: TTable, val partitions: Seq[TPartition]) @@ -551,7 +463,7 @@ private[hive] case class MetastoreRelation implicit class SchemaAttribute(f: FieldSchema) { def toAttribute = AttributeReference( f.getName, - HiveMetastoreTypes.toDataType(f.getType), + sqlContext.ddlParser.parseType(f.getType), // Since data can be dumped in randomly with no validation, everything is nullable. nullable = true )(qualifiers = Seq(alias.getOrElse(tableName))) @@ -571,3 +483,27 @@ private[hive] case class MetastoreRelation /** An attribute map for determining the ordinal for non-partition columns. */ val columnOrdinals = AttributeMap(attributes.zipWithIndex) } + +object HiveMetastoreTypes { + def toMetastoreType(dt: DataType): String = dt match { + case ArrayType(elementType, _) => s"array<${toMetastoreType(elementType)}>" + case StructType(fields) => + s"struct<${fields.map(f => s"${f.name}:${toMetastoreType(f.dataType)}").mkString(",")}>" + case MapType(keyType, valueType, _) => + s"map<${toMetastoreType(keyType)},${toMetastoreType(valueType)}>" + case StringType => "string" + case FloatType => "float" + case IntegerType => "int" + case ByteType => "tinyint" + case ShortType => "smallint" + case DoubleType => "double" + case LongType => "bigint" + case BinaryType => "binary" + case BooleanType => "boolean" + case DateType => "date" + case d: DecimalType => HiveShim.decimalMetastoreString(d) + case TimestampType => "timestamp" + case NullType => "void" + case udt: UserDefinedType[_] => toMetastoreType(udt.sqlType) + } +} diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveMetastoreCatalogSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveMetastoreCatalogSuite.scala index 86535f8dd4f58..041a36f1295ef 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveMetastoreCatalogSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveMetastoreCatalogSuite.scala @@ -20,6 +20,7 @@ package org.apache.spark.sql.hive import org.scalatest.FunSuite import org.apache.spark.sql.catalyst.types.StructType +import org.apache.spark.sql.sources.DDLParser import org.apache.spark.sql.test.ExamplePointUDT class HiveMetastoreCatalogSuite extends FunSuite { @@ -27,7 +28,9 @@ class HiveMetastoreCatalogSuite extends FunSuite { test("struct field should accept underscore in sub-column name") { val metastr = "struct" - val datatype = HiveMetastoreTypes.toDataType(metastr) + val ddlParser = new DDLParser + + val datatype = ddlParser.parseType(metastr) assert(datatype.isInstanceOf[StructType]) } From b3e86dc62476abb03b330f86a788aa19a6565317 Mon Sep 17 00:00:00 2001 From: scwf Date: Sat, 10 Jan 2015 14:08:04 -0800 Subject: [PATCH 218/320] [SPARK-4861][SQL] Refactory command in spark sql Follow up for #3712. This PR finally remove ```CommandStrategy``` and make all commands follow ```RunnableCommand``` so they can go with ```case r: RunnableCommand => ExecutedCommand(r) :: Nil```. One exception is the ```DescribeCommand``` of hive, which is a special case and need to distinguish hive table and temporary table, so still keep ```HiveCommandStrategy``` here. Author: scwf Closes #3948 from scwf/followup-SPARK-4861 and squashes the following commits: 6b48e64 [scwf] minor style fix 2c62e9d [scwf] fix for hive module 5a7a819 [scwf] Refactory command in spark sql --- ...ser.scala => AbstractSparkSQLParser.scala} | 69 ------------- .../sql/catalyst/plans/logical/commands.scala | 48 +-------- .../org/apache/spark/sql/SQLContext.scala | 3 +- .../org/apache/spark/sql/SparkSQLParser.scala | 97 +++++++++++++++++++ .../spark/sql/execution/SparkStrategies.scala | 20 +--- .../apache/spark/sql/execution/commands.scala | 2 +- .../spark/sql/hive/thriftserver/Shim12.scala | 4 +- .../spark/sql/hive/thriftserver/Shim13.scala | 4 +- .../apache/spark/sql/hive/HiveContext.scala | 4 +- .../org/apache/spark/sql/hive/HiveQl.scala | 31 +++++- .../spark/sql/hive/HiveStrategies.scala | 5 +- .../org/apache/spark/sql/hive/TestHive.scala | 3 +- .../hive/execution/HiveComparisonTest.scala | 2 + 13 files changed, 141 insertions(+), 151 deletions(-) rename sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/{SparkSQLParser.scala => AbstractSparkSQLParser.scala} (62%) create mode 100644 sql/core/src/main/scala/org/apache/spark/sql/SparkSQLParser.scala diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SparkSQLParser.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/AbstractSparkSQLParser.scala similarity index 62% rename from sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SparkSQLParser.scala rename to sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/AbstractSparkSQLParser.scala index f1a1ca6616a21..93d74adbcc957 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SparkSQLParser.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/AbstractSparkSQLParser.scala @@ -105,72 +105,3 @@ class SqlLexical(val keywords: Seq[String]) extends StdLexical { } } } - -/** - * The top level Spark SQL parser. This parser recognizes syntaxes that are available for all SQL - * dialects supported by Spark SQL, and delegates all the other syntaxes to the `fallback` parser. - * - * @param fallback A function that parses an input string to a logical plan - */ -private[sql] class SparkSQLParser(fallback: String => LogicalPlan) extends AbstractSparkSQLParser { - - // A parser for the key-value part of the "SET [key = [value ]]" syntax - private object SetCommandParser extends RegexParsers { - private val key: Parser[String] = "(?m)[^=]+".r - - private val value: Parser[String] = "(?m).*$".r - - private val pair: Parser[LogicalPlan] = - (key ~ ("=".r ~> value).?).? ^^ { - case None => SetCommand(None) - case Some(k ~ v) => SetCommand(Some(k.trim -> v.map(_.trim))) - } - - def apply(input: String): LogicalPlan = parseAll(pair, input) match { - case Success(plan, _) => plan - case x => sys.error(x.toString) - } - } - - protected val AS = Keyword("AS") - protected val CACHE = Keyword("CACHE") - protected val LAZY = Keyword("LAZY") - protected val SET = Keyword("SET") - protected val TABLE = Keyword("TABLE") - protected val UNCACHE = Keyword("UNCACHE") - - protected implicit def asParser(k: Keyword): Parser[String] = - lexical.allCaseVersions(k.str).map(x => x : Parser[String]).reduce(_ | _) - - private val reservedWords: Seq[String] = - this - .getClass - .getMethods - .filter(_.getReturnType == classOf[Keyword]) - .map(_.invoke(this).asInstanceOf[Keyword].str) - - override val lexical = new SqlLexical(reservedWords) - - override protected lazy val start: Parser[LogicalPlan] = cache | uncache | set | others - - private lazy val cache: Parser[LogicalPlan] = - CACHE ~> LAZY.? ~ (TABLE ~> ident) ~ (AS ~> restInput).? ^^ { - case isLazy ~ tableName ~ plan => - CacheTableCommand(tableName, plan.map(fallback), isLazy.isDefined) - } - - private lazy val uncache: Parser[LogicalPlan] = - UNCACHE ~ TABLE ~> ident ^^ { - case tableName => UncacheTableCommand(tableName) - } - - private lazy val set: Parser[LogicalPlan] = - SET ~> restInput ^^ { - case input => SetCommandParser(input) - } - - private lazy val others: Parser[LogicalPlan] = - wholeInput ^^ { - case input => fallback(input) - } -} diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/commands.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/commands.scala index 5a1863953eae9..45905f8ef98c5 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/commands.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/commands.scala @@ -17,8 +17,7 @@ package org.apache.spark.sql.catalyst.plans.logical -import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeReference} -import org.apache.spark.sql.catalyst.types.StringType +import org.apache.spark.sql.catalyst.expressions.Attribute /** * A logical node that represents a non-query command to be executed by the system. For example, @@ -28,48 +27,3 @@ abstract class Command extends LeafNode { self: Product => def output: Seq[Attribute] = Seq.empty } - -/** - * - * Commands of the form "SET [key [= value] ]". - */ -case class SetCommand(kv: Option[(String, Option[String])]) extends Command { - override def output = Seq( - AttributeReference("", StringType, nullable = false)()) -} - -/** - * Returned by a parser when the users only wants to see what query plan would be executed, without - * actually performing the execution. - */ -case class ExplainCommand(plan: LogicalPlan, extended: Boolean = false) extends Command { - override def output = - Seq(AttributeReference("plan", StringType, nullable = false)()) -} - -/** - * Returned for the "CACHE TABLE tableName [AS SELECT ...]" command. - */ -case class CacheTableCommand(tableName: String, plan: Option[LogicalPlan], isLazy: Boolean) - extends Command - -/** - * Returned for the "UNCACHE TABLE tableName" command. - */ -case class UncacheTableCommand(tableName: String) extends Command - -/** - * Returned for the "DESCRIBE [EXTENDED] [dbName.]tableName" command. - * @param table The table to be described. - * @param isExtended True if "DESCRIBE EXTENDED" is used. Otherwise, false. - * It is effective only when the table is a Hive table. - */ -case class DescribeCommand( - table: LogicalPlan, - isExtended: Boolean) extends Command { - override def output = Seq( - // Column names are based on Hive. - AttributeReference("col_name", StringType, nullable = false)(), - AttributeReference("data_type", StringType, nullable = false)(), - AttributeReference("comment", StringType, nullable = false)()) -} diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala index 9962937277dad..6c575dd727b46 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala @@ -76,7 +76,7 @@ class SQLContext(@transient val sparkContext: SparkContext) @transient protected[sql] val sqlParser = { val fallback = new catalyst.SqlParser - new catalyst.SparkSQLParser(fallback(_)) + new SparkSQLParser(fallback(_)) } protected[sql] def parseSql(sql: String): LogicalPlan = { @@ -329,7 +329,6 @@ class SQLContext(@transient val sparkContext: SparkContext) def strategies: Seq[Strategy] = extraStrategies ++ ( - CommandStrategy :: DataSourceStrategy :: TakeOrdered :: HashAggregation :: diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SparkSQLParser.scala b/sql/core/src/main/scala/org/apache/spark/sql/SparkSQLParser.scala new file mode 100644 index 0000000000000..65358b7d4ea8e --- /dev/null +++ b/sql/core/src/main/scala/org/apache/spark/sql/SparkSQLParser.scala @@ -0,0 +1,97 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql + +import org.apache.spark.sql.catalyst.{SqlLexical, AbstractSparkSQLParser} +import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeReference} +import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan +import org.apache.spark.sql.execution.{UncacheTableCommand, CacheTableCommand, SetCommand} + +import scala.util.parsing.combinator.RegexParsers + +/** + * The top level Spark SQL parser. This parser recognizes syntaxes that are available for all SQL + * dialects supported by Spark SQL, and delegates all the other syntaxes to the `fallback` parser. + * + * @param fallback A function that parses an input string to a logical plan + */ +private[sql] class SparkSQLParser(fallback: String => LogicalPlan) extends AbstractSparkSQLParser { + + // A parser for the key-value part of the "SET [key = [value ]]" syntax + private object SetCommandParser extends RegexParsers { + private val key: Parser[String] = "(?m)[^=]+".r + + private val value: Parser[String] = "(?m).*$".r + + private val output: Seq[Attribute] = Seq(AttributeReference("", StringType, nullable = false)()) + + private val pair: Parser[LogicalPlan] = + (key ~ ("=".r ~> value).?).? ^^ { + case None => SetCommand(None, output) + case Some(k ~ v) => SetCommand(Some(k.trim -> v.map(_.trim)), output) + } + + def apply(input: String): LogicalPlan = parseAll(pair, input) match { + case Success(plan, _) => plan + case x => sys.error(x.toString) + } + } + + protected val AS = Keyword("AS") + protected val CACHE = Keyword("CACHE") + protected val LAZY = Keyword("LAZY") + protected val SET = Keyword("SET") + protected val TABLE = Keyword("TABLE") + protected val UNCACHE = Keyword("UNCACHE") + + protected implicit def asParser(k: Keyword): Parser[String] = + lexical.allCaseVersions(k.str).map(x => x : Parser[String]).reduce(_ | _) + + private val reservedWords: Seq[String] = + this + .getClass + .getMethods + .filter(_.getReturnType == classOf[Keyword]) + .map(_.invoke(this).asInstanceOf[Keyword].str) + + override val lexical = new SqlLexical(reservedWords) + + override protected lazy val start: Parser[LogicalPlan] = cache | uncache | set | others + + private lazy val cache: Parser[LogicalPlan] = + CACHE ~> LAZY.? ~ (TABLE ~> ident) ~ (AS ~> restInput).? ^^ { + case isLazy ~ tableName ~ plan => + CacheTableCommand(tableName, plan.map(fallback), isLazy.isDefined) + } + + private lazy val uncache: Parser[LogicalPlan] = + UNCACHE ~ TABLE ~> ident ^^ { + case tableName => UncacheTableCommand(tableName) + } + + private lazy val set: Parser[LogicalPlan] = + SET ~> restInput ^^ { + case input => SetCommandParser(input) + } + + private lazy val others: Parser[LogicalPlan] = + wholeInput ^^ { + case input => fallback(input) + } + +} diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala index ce878c137e627..99b6611d3bbcf 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala @@ -259,6 +259,8 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { def numPartitions = self.numPartitions def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match { + case r: RunnableCommand => ExecutedCommand(r) :: Nil + case logical.Distinct(child) => execution.Distinct(partial = false, execution.Distinct(partial = true, planLater(child))) :: Nil @@ -308,22 +310,4 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { case _ => Nil } } - - case object CommandStrategy extends Strategy { - def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match { - case r: RunnableCommand => ExecutedCommand(r) :: Nil - case logical.SetCommand(kv) => - Seq(ExecutedCommand(execution.SetCommand(kv, plan.output))) - case logical.ExplainCommand(logicalPlan, extended) => - Seq(ExecutedCommand( - execution.ExplainCommand(logicalPlan, plan.output, extended))) - case logical.CacheTableCommand(tableName, optPlan, isLazy) => - Seq(ExecutedCommand( - execution.CacheTableCommand(tableName, optPlan, isLazy))) - case logical.UncacheTableCommand(tableName) => - Seq(ExecutedCommand( - execution.UncacheTableCommand(tableName))) - case _ => Nil - } - } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala index b8fa4b019953e..0d765c4c92f85 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala @@ -113,7 +113,7 @@ case class SetCommand( @DeveloperApi case class ExplainCommand( logicalPlan: LogicalPlan, - override val output: Seq[Attribute], extended: Boolean) extends RunnableCommand { + override val output: Seq[Attribute], extended: Boolean = false) extends RunnableCommand { // Run through the optimizer to generate the physical plan. override def run(sqlContext: SQLContext) = try { diff --git a/sql/hive-thriftserver/v0.12.0/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim12.scala b/sql/hive-thriftserver/v0.12.0/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim12.scala index 5550183621fb6..80733ea1db93b 100644 --- a/sql/hive-thriftserver/v0.12.0/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim12.scala +++ b/sql/hive-thriftserver/v0.12.0/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim12.scala @@ -33,8 +33,8 @@ import org.apache.hive.service.cli.operation.ExecuteStatementOperation import org.apache.hive.service.cli.session.HiveSession import org.apache.spark.Logging -import org.apache.spark.sql.catalyst.plans.logical.SetCommand import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.execution.SetCommand import org.apache.spark.sql.hive.thriftserver.ReflectionUtils._ import org.apache.spark.sql.hive.{HiveContext, HiveMetastoreTypes} import org.apache.spark.sql.{SQLConf, SchemaRDD, Row => SparkRow} @@ -190,7 +190,7 @@ private[hive] class SparkExecuteStatementOperation( result = hiveContext.sql(statement) logDebug(result.queryExecution.toString()) result.queryExecution.logical match { - case SetCommand(Some((SQLConf.THRIFTSERVER_POOL, Some(value)))) => + case SetCommand(Some((SQLConf.THRIFTSERVER_POOL, Some(value))), _) => sessionToActivePool(parentSession.getSessionHandle) = value logInfo(s"Setting spark.scheduler.pool=$value for future statements in this session.") case _ => diff --git a/sql/hive-thriftserver/v0.13.1/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim13.scala b/sql/hive-thriftserver/v0.13.1/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim13.scala index 798a690a20427..19d85140071ea 100644 --- a/sql/hive-thriftserver/v0.13.1/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim13.scala +++ b/sql/hive-thriftserver/v0.13.1/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim13.scala @@ -31,7 +31,7 @@ import org.apache.hive.service.cli.operation.ExecuteStatementOperation import org.apache.hive.service.cli.session.HiveSession import org.apache.spark.Logging -import org.apache.spark.sql.catalyst.plans.logical.SetCommand +import org.apache.spark.sql.execution.SetCommand import org.apache.spark.sql.catalyst.types._ import org.apache.spark.sql.hive.thriftserver.ReflectionUtils._ import org.apache.spark.sql.hive.{HiveContext, HiveMetastoreTypes} @@ -161,7 +161,7 @@ private[hive] class SparkExecuteStatementOperation( result = hiveContext.sql(statement) logDebug(result.queryExecution.toString()) result.queryExecution.logical match { - case SetCommand(Some((SQLConf.THRIFTSERVER_POOL, Some(value)))) => + case SetCommand(Some((SQLConf.THRIFTSERVER_POOL, Some(value))), _) => sessionToActivePool(parentSession.getSessionHandle) = value logInfo(s"Setting spark.scheduler.pool=$value for future statements in this session.") case _ => diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala index 1648fa826b900..02eac43b2103f 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala @@ -38,8 +38,7 @@ import org.apache.spark.sql.catalyst.ScalaReflection import org.apache.spark.sql.catalyst.analysis.{Analyzer, EliminateAnalysisOperators, OverrideCatalog, OverrideFunctionRegistry} import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.types.DecimalType -import org.apache.spark.sql.catalyst.types.decimal.Decimal -import org.apache.spark.sql.execution.{SparkPlan, ExecutedCommand, ExtractPythonUdfs, QueryExecutionException} +import org.apache.spark.sql.execution.{ExecutedCommand, ExtractPythonUdfs, SetCommand, QueryExecutionException} import org.apache.spark.sql.hive.execution.{HiveNativeCommand, DescribeHiveTableCommand} import org.apache.spark.sql.sources.DataSourceStrategy @@ -340,7 +339,6 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { override def strategies: Seq[Strategy] = extraStrategies ++ Seq( DataSourceStrategy, - CommandStrategy, HiveCommandStrategy(self), TakeOrdered, ParquetOperations, diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala index c2ab3579c1f95..28de03c38997b 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala @@ -24,8 +24,8 @@ import org.apache.hadoop.hive.ql.lib.Node import org.apache.hadoop.hive.ql.metadata.Table import org.apache.hadoop.hive.ql.parse._ import org.apache.hadoop.hive.ql.plan.PlanUtils +import org.apache.spark.sql.SparkSQLParser -import org.apache.spark.sql.catalyst.SparkSQLParser import org.apache.spark.sql.catalyst.analysis._ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans._ @@ -33,6 +33,7 @@ import org.apache.spark.sql.catalyst.plans.logical import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.types._ import org.apache.spark.sql.catalyst.types.decimal.Decimal +import org.apache.spark.sql.execution.ExplainCommand import org.apache.spark.sql.hive.execution.{HiveNativeCommand, DropTable, AnalyzeTable} /* Implicit conversions */ @@ -45,6 +46,22 @@ import scala.collection.JavaConversions._ */ private[hive] case object NativePlaceholder extends Command +/** + * Returned for the "DESCRIBE [EXTENDED] [dbName.]tableName" command. + * @param table The table to be described. + * @param isExtended True if "DESCRIBE EXTENDED" is used. Otherwise, false. + * It is effective only when the table is a Hive table. + */ +case class DescribeCommand( + table: LogicalPlan, + isExtended: Boolean) extends Command { + override def output = Seq( + // Column names are based on Hive. + AttributeReference("col_name", StringType, nullable = false)(), + AttributeReference("data_type", StringType, nullable = false)(), + AttributeReference("comment", StringType, nullable = false)()) +} + /** Provides a mapping from HiveQL statements to catalyst logical plans and expression trees. */ private[hive] object HiveQl { protected val nativeCommands = Seq( @@ -457,17 +474,23 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C // Just fake explain for any of the native commands. case Token("TOK_EXPLAIN", explainArgs) if noExplainCommands.contains(explainArgs.head.getText) => - ExplainCommand(NoRelation) + ExplainCommand(NoRelation, Seq(AttributeReference("plan", StringType, nullable = false)())) case Token("TOK_EXPLAIN", explainArgs) if "TOK_CREATETABLE" == explainArgs.head.getText => val Some(crtTbl) :: _ :: extended :: Nil = getClauses(Seq("TOK_CREATETABLE", "FORMATTED", "EXTENDED"), explainArgs) - ExplainCommand(nodeToPlan(crtTbl), extended != None) + ExplainCommand( + nodeToPlan(crtTbl), + Seq(AttributeReference("plan", StringType,nullable = false)()), + extended != None) case Token("TOK_EXPLAIN", explainArgs) => // Ignore FORMATTED if present. val Some(query) :: _ :: extended :: Nil = getClauses(Seq("TOK_QUERY", "FORMATTED", "EXTENDED"), explainArgs) - ExplainCommand(nodeToPlan(query), extended != None) + ExplainCommand( + nodeToPlan(query), + Seq(AttributeReference("plan", StringType, nullable = false)()), + extended != None) case Token("TOK_DESCTABLE", describeArgs) => // Reference: https://cwiki.apache.org/confluence/display/Hive/LanguageManual+DDL diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala index d3f6381b69a4d..c439b9ebfe104 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala @@ -25,6 +25,7 @@ import org.apache.spark.sql.catalyst.planning._ import org.apache.spark.sql.catalyst.plans._ import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan import org.apache.spark.sql.catalyst.types.StringType +import org.apache.spark.sql.execution.{DescribeCommand => RunnableDescribeCommand} import org.apache.spark.sql.execution._ import org.apache.spark.sql.hive import org.apache.spark.sql.hive.execution._ @@ -209,14 +210,14 @@ private[hive] trait HiveStrategies { case class HiveCommandStrategy(context: HiveContext) extends Strategy { def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match { - case describe: logical.DescribeCommand => + case describe: DescribeCommand => val resolvedTable = context.executePlan(describe.table).analyzed resolvedTable match { case t: MetastoreRelation => ExecutedCommand( DescribeHiveTableCommand(t, describe.output, describe.isExtended)) :: Nil case o: LogicalPlan => - ExecutedCommand(DescribeCommand(planLater(o), describe.output)) :: Nil + ExecutedCommand(RunnableDescribeCommand(planLater(o), describe.output)) :: Nil } case _ => Nil diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala index 8f2311cf83eb8..1358a0eccb353 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala @@ -34,8 +34,9 @@ import org.apache.hadoop.hive.serde2.avro.AvroSerDe import org.apache.spark.{SparkConf, SparkContext} import org.apache.spark.util.Utils import org.apache.spark.sql.catalyst.analysis._ -import org.apache.spark.sql.catalyst.plans.logical.{CacheTableCommand, LogicalPlan} +import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan import org.apache.spark.sql.catalyst.util._ +import org.apache.spark.sql.execution.CacheTableCommand import org.apache.spark.sql.hive._ import org.apache.spark.sql.SQLConf import org.apache.spark.sql.hive.execution.HiveNativeCommand diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala index 4104df8f8e022..f8a957d55d57e 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveComparisonTest.scala @@ -22,6 +22,8 @@ import java.io._ import org.scalatest.{BeforeAndAfterAll, FunSuite, GivenWhenThen} import org.apache.spark.Logging +import org.apache.spark.sql.execution.{SetCommand, ExplainCommand} +import org.apache.spark.sql.hive.DescribeCommand import org.apache.spark.sql.catalyst.planning.PhysicalOperation import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.util._ From 77106df69147aba5eb1784adb84e2b574927c6de Mon Sep 17 00:00:00 2001 From: Yanbo Liang Date: Sat, 10 Jan 2015 14:16:37 -0800 Subject: [PATCH 219/320] SPARK-4963 [SQL] Add copy to SQL's Sample operator https://issues.apache.org/jira/browse/SPARK-4963 SchemaRDD.sample() return wrong results due to GapSamplingIterator operating on mutable row. HiveTableScan make RDD with SpecificMutableRow and SchemaRDD.sample() will return GapSamplingIterator for iterating. override def next(): T = { val r = data.next() advance r } GapSamplingIterator.next() return the current underlying element and assigned it to r. However if the underlying iterator is mutable row just like what HiveTableScan returned, underlying iterator and r will point to the same object. After advance operation, we drop some underlying elments and it also changed r which is not expected. Then we return the wrong value different from initial r. To fix this issue, the most direct way is to make HiveTableScan return mutable row with copy just like the initial commit that I have made. This solution will make HiveTableScan can not get the full advantage of reusable MutableRow, but it can make sample operation return correct result. Further more, we need to investigate GapSamplingIterator.next() and make it can implement copy operation inside it. To achieve this, we should define every elements that RDD can store implement the function like cloneable and it will make huge change. Author: Yanbo Liang Closes #3827 from yanbohappy/spark-4963 and squashes the following commits: 0912ca0 [Yanbo Liang] code format keep 65c4e7c [Yanbo Liang] import file and clear annotation 55c7c56 [Yanbo Liang] better output of test case cea7e2e [Yanbo Liang] SchemaRDD add copy operation before Sample operator e840829 [Yanbo Liang] HiveTableScan return mutable row with copy --- .../apache/spark/sql/execution/basicOperators.scala | 2 +- .../spark/sql/hive/execution/SQLQuerySuite.scala | 12 ++++++++++++ 2 files changed, 13 insertions(+), 1 deletion(-) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala index e53723c176569..16ca4be5587c4 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala @@ -70,7 +70,7 @@ case class Sample(fraction: Double, withReplacement: Boolean, seed: Long, child: override def output = child.output // TODO: How to pick seed? - override def execute() = child.execute().sample(withReplacement, fraction, seed) + override def execute() = child.execute().map(_.copy()).sample(withReplacement, fraction, seed) } /** diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala index 5d0fb7237011f..c1c3683f84ab2 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala @@ -21,6 +21,7 @@ import org.apache.spark.sql.QueryTest import org.apache.spark.sql.Row import org.apache.spark.sql.hive.test.TestHive._ +import org.apache.spark.util.Utils case class Nested1(f1: Nested2) case class Nested2(f2: Nested3) @@ -202,4 +203,15 @@ class SQLQuerySuite extends QueryTest { checkAnswer(sql("SELECT sum( distinct key) FROM src group by key order by key"), sql("SELECT distinct key FROM src order by key").collect().toSeq) } + + test("SPARK-4963 SchemaRDD sample on mutable row return wrong result") { + sql("SELECT * FROM src WHERE key % 2 = 0") + .sample(withReplacement = false, fraction = 0.3) + .registerTempTable("sampled") + (1 to 10).foreach { i => + checkAnswer( + sql("SELECT * FROM sampled WHERE key % 2 = 1"), + Seq.empty[Row]) + } + } } From 3684fd21e1ffdc0adaad8ff6b31394b637e866ce Mon Sep 17 00:00:00 2001 From: Michael Armbrust Date: Sat, 10 Jan 2015 14:25:45 -0800 Subject: [PATCH 220/320] [SPARK-5187][SQL] Fix caching of tables with HiveUDFs in the WHERE clause Author: Michael Armbrust Closes #3987 from marmbrus/hiveUdfCaching and squashes the following commits: 8bca2fa [Michael Armbrust] [SPARK-5187][SQL] Fix caching of tables with HiveUDFs in the WHERE clause --- .../scala/org/apache/spark/sql/hive/CachedTableSuite.scala | 6 ++++++ .../src/main/scala/org/apache/spark/sql/hive/Shim12.scala | 2 +- .../src/main/scala/org/apache/spark/sql/hive/Shim13.scala | 2 +- 3 files changed, 8 insertions(+), 2 deletions(-) diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/CachedTableSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/CachedTableSuite.scala index 2060e1f1a7a4b..f95a6b43af357 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/CachedTableSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/CachedTableSuite.scala @@ -158,4 +158,10 @@ class CachedTableSuite extends QueryTest { uncacheTable("src") assert(!isMaterialized(rddId), "Uncached in-memory table should have been unpersisted") } + + test("CACHE TABLE with Hive UDF") { + sql("CACHE TABLE udfTest AS SELECT * FROM src WHERE floor(key) = 1") + assertCached(table("udfTest")) + uncacheTable("udfTest") + } } diff --git a/sql/hive/v0.12.0/src/main/scala/org/apache/spark/sql/hive/Shim12.scala b/sql/hive/v0.12.0/src/main/scala/org/apache/spark/sql/hive/Shim12.scala index 2d01a85067518..25fdf5c5f3da6 100644 --- a/sql/hive/v0.12.0/src/main/scala/org/apache/spark/sql/hive/Shim12.scala +++ b/sql/hive/v0.12.0/src/main/scala/org/apache/spark/sql/hive/Shim12.scala @@ -44,7 +44,7 @@ import scala.language.implicitConversions import org.apache.spark.sql.catalyst.types.DecimalType -class HiveFunctionWrapper(var functionClassName: String) extends java.io.Serializable { +case class HiveFunctionWrapper(functionClassName: String) extends java.io.Serializable { // for Serialization def this() = this(null) diff --git a/sql/hive/v0.13.1/src/main/scala/org/apache/spark/sql/hive/Shim13.scala b/sql/hive/v0.13.1/src/main/scala/org/apache/spark/sql/hive/Shim13.scala index b78c75798e988..e47002cb0b8c8 100644 --- a/sql/hive/v0.13.1/src/main/scala/org/apache/spark/sql/hive/Shim13.scala +++ b/sql/hive/v0.13.1/src/main/scala/org/apache/spark/sql/hive/Shim13.scala @@ -53,7 +53,7 @@ import scala.language.implicitConversions * * @param functionClassName UDF class name */ -class HiveFunctionWrapper(var functionClassName: String) extends java.io.Externalizable { +case class HiveFunctionWrapper(var functionClassName: String) extends java.io.Externalizable { // for Serialization def this() = this(null) From 0ca51cc31d5dd16aa458956e582eec58bbc31711 Mon Sep 17 00:00:00 2001 From: YanTangZhai Date: Sat, 10 Jan 2015 15:05:23 -0800 Subject: [PATCH 221/320] [SPARK-4692] [SQL] Support ! boolean logic operator like NOT Support ! boolean logic operator like NOT in sql as follows select * from for_test where !(col1 > col2) Author: YanTangZhai Author: Michael Armbrust Closes #3555 from YanTangZhai/SPARK-4692 and squashes the following commits: 1a9f605 [YanTangZhai] Update HiveQuerySuite.scala 7c03c68 [YanTangZhai] Merge pull request #23 from apache/master 992046e [YanTangZhai] Update HiveQuerySuite.scala ea618f4 [YanTangZhai] Update HiveQuerySuite.scala 192411d [YanTangZhai] Merge pull request #17 from YanTangZhai/master e4c2c0a [YanTangZhai] Merge pull request #15 from apache/master 1e1ebb4 [YanTangZhai] Update HiveQuerySuite.scala efc4210 [YanTangZhai] Update HiveQuerySuite.scala bd2c444 [YanTangZhai] Update HiveQuerySuite.scala 1893956 [YanTangZhai] Merge pull request #14 from marmbrus/pr/3555 59e4de9 [Michael Armbrust] make hive test 718afeb [YanTangZhai] Merge pull request #12 from apache/master 950b21e [YanTangZhai] Update HiveQuerySuite.scala 74175b4 [YanTangZhai] Update HiveQuerySuite.scala 92242c7 [YanTangZhai] Update HiveQl.scala 6e643f8 [YanTangZhai] Merge pull request #11 from apache/master e249846 [YanTangZhai] Merge pull request #10 from apache/master d26d982 [YanTangZhai] Merge pull request #9 from apache/master 76d4027 [YanTangZhai] Merge pull request #8 from apache/master 03b62b0 [YanTangZhai] Merge pull request #7 from apache/master 8a00106 [YanTangZhai] Merge pull request #6 from apache/master cbcba66 [YanTangZhai] Merge pull request #3 from apache/master cdef539 [YanTangZhai] Merge pull request #1 from apache/master --- .../src/main/scala/org/apache/spark/sql/hive/HiveQl.scala | 1 + .../golden/! operator-0-81d1a187c7f4a6337baf081510a5dc5e | 1 + .../apache/spark/sql/hive/execution/HiveQuerySuite.scala | 8 ++++++++ 3 files changed, 10 insertions(+) create mode 100644 sql/hive/src/test/resources/golden/! operator-0-81d1a187c7f4a6337baf081510a5dc5e diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala index 28de03c38997b..34622b5f57873 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala @@ -1111,6 +1111,7 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C case Token(AND(), left :: right:: Nil) => And(nodeToExpr(left), nodeToExpr(right)) case Token(OR(), left :: right:: Nil) => Or(nodeToExpr(left), nodeToExpr(right)) case Token(NOT(), child :: Nil) => Not(nodeToExpr(child)) + case Token("!", child :: Nil) => Not(nodeToExpr(child)) /* Case statements */ case Token("TOK_FUNCTION", Token(WHEN(), Nil) :: branches) => diff --git a/sql/hive/src/test/resources/golden/! operator-0-81d1a187c7f4a6337baf081510a5dc5e b/sql/hive/src/test/resources/golden/! operator-0-81d1a187c7f4a6337baf081510a5dc5e new file mode 100644 index 0000000000000..d00491fd7e5bb --- /dev/null +++ b/sql/hive/src/test/resources/golden/! operator-0-81d1a187c7f4a6337baf081510a5dc5e @@ -0,0 +1 @@ +1 diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala index fb6da33e88ef6..700a45edb11d6 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala @@ -62,6 +62,14 @@ class HiveQuerySuite extends HiveComparisonTest with BeforeAndAfter { sql("SHOW TABLES") } } + + createQueryTest("! operator", + """ + |SELECT a FROM ( + | SELECT 1 AS a FROM src LIMIT 1 UNION ALL + | SELECT 2 AS a FROM src LIMIT 1) table + |WHERE !(a>1) + """.stripMargin) createQueryTest("constant object inspector for generic udf", """SELECT named_struct( From f0d558b6e6ec0c97280d5844c98fb92c24954cbb Mon Sep 17 00:00:00 2001 From: CodingCat Date: Sat, 10 Jan 2015 15:35:41 -0800 Subject: [PATCH 222/320] [SPARK-5181] do not print writing WAL log when WAL is disabled https://issues.apache.org/jira/browse/SPARK-5181 Currently, even the logManager is not created, we still see the log entry s"Writing to log $record" a simple fix to make log more accurate Author: CodingCat Closes #3985 from CodingCat/SPARK-5181 and squashes the following commits: 0e27dc5 [CodingCat] do not print writing WAL log when WAL is disabled --- .../spark/streaming/scheduler/ReceivedBlockTracker.scala | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceivedBlockTracker.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceivedBlockTracker.scala index 2ce458cddec1a..c3d9d7b6813d3 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceivedBlockTracker.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceivedBlockTracker.scala @@ -203,9 +203,11 @@ private[streaming] class ReceivedBlockTracker( /** Write an update to the tracker to the write ahead log */ private def writeToLog(record: ReceivedBlockTrackerLogEvent) { - logDebug(s"Writing to log $record") - logManagerOption.foreach { logManager => + if (isLogManagerEnabled) { + logDebug(s"Writing to log $record") + logManagerOption.foreach { logManager => logManager.writeToLog(ByteBuffer.wrap(Utils.serialize(record))) + } } } From 8a29dc716e3452fdf546852ddc18238018b73891 Mon Sep 17 00:00:00 2001 From: GuoQiang Li Date: Sat, 10 Jan 2015 15:38:43 -0800 Subject: [PATCH 223/320] [Minor]Resolve sbt warnings during build (MQTTStreamSuite.scala). cc andrewor14 Author: GuoQiang Li Closes #3989 from witgo/MQTTStreamSuite and squashes the following commits: a6e967e [GuoQiang Li] Resolve sbt warnings during build (MQTTStreamSuite.scala). --- .../scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala | 1 + 1 file changed, 1 insertion(+) diff --git a/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala b/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala index 39eb8b183488f..30727dfa64437 100644 --- a/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala +++ b/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala @@ -20,6 +20,7 @@ package org.apache.spark.streaming.mqtt import java.net.{URI, ServerSocket} import scala.concurrent.duration._ +import scala.language.postfixOps import org.apache.activemq.broker.{TransportConnector, BrokerService} import org.eclipse.paho.client.mqttv3._ From 92d9a704ce1232bddc570bca13758b11ff9ddb1f Mon Sep 17 00:00:00 2001 From: wangfei Date: Sat, 10 Jan 2015 17:04:56 -0800 Subject: [PATCH 224/320] [SPARK-4871][SQL] Show sql statement in spark ui when run sql with spark-sql Author: wangfei Closes #3718 from scwf/sparksqlui and squashes the following commits: e0d6b5d [wangfei] format fix 383b505 [wangfei] fix conflicts 4d2038a [wangfei] using setJobDescription df79837 [wangfei] fix compile error 92ce834 [wangfei] show sql statement in spark ui when run sql use spark-sql --- core/src/main/scala/org/apache/spark/SparkContext.scala | 1 - .../spark/sql/hive/thriftserver/AbstractSparkSQLDriver.scala | 1 + .../org/apache/spark/sql/hive/thriftserver/Shim12.scala | 5 +---- .../org/apache/spark/sql/hive/thriftserver/Shim13.scala | 5 +---- 4 files changed, 3 insertions(+), 9 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala index 3bf3acd245d8f..ff5d796ee2766 100644 --- a/core/src/main/scala/org/apache/spark/SparkContext.scala +++ b/core/src/main/scala/org/apache/spark/SparkContext.scala @@ -458,7 +458,6 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli Option(localProperties.get).map(_.getProperty(key)).getOrElse(null) /** Set a human readable description of the current job. */ - @deprecated("use setJobGroup", "0.8.1") def setJobDescription(value: String) { setLocalProperty(SparkContext.SPARK_JOB_DESCRIPTION, value) } diff --git a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/AbstractSparkSQLDriver.scala b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/AbstractSparkSQLDriver.scala index 7a3d76c61c3a1..59f3a75768082 100644 --- a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/AbstractSparkSQLDriver.scala +++ b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/AbstractSparkSQLDriver.scala @@ -53,6 +53,7 @@ private[hive] abstract class AbstractSparkSQLDriver( override def run(command: String): CommandProcessorResponse = { // TODO unify the error code try { + context.sparkContext.setJobDescription(command) val execution = context.executePlan(context.sql(command).logicalPlan) hiveResponse = execution.stringResult() tableSchema = getResultSetSchema(execution) diff --git a/sql/hive-thriftserver/v0.12.0/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim12.scala b/sql/hive-thriftserver/v0.12.0/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim12.scala index 80733ea1db93b..742acba58d776 100644 --- a/sql/hive-thriftserver/v0.12.0/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim12.scala +++ b/sql/hive-thriftserver/v0.12.0/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim12.scala @@ -22,7 +22,6 @@ import java.util.{ArrayList => JArrayList, Map => JMap} import scala.collection.JavaConversions._ import scala.collection.mutable.{ArrayBuffer, Map => SMap} -import scala.math._ import org.apache.hadoop.hive.common.`type`.HiveDecimal import org.apache.hadoop.hive.metastore.api.FieldSchema @@ -195,9 +194,7 @@ private[hive] class SparkExecuteStatementOperation( logInfo(s"Setting spark.scheduler.pool=$value for future statements in this session.") case _ => } - - val groupId = round(random * 1000000).toString - hiveContext.sparkContext.setJobGroup(groupId, statement) + hiveContext.sparkContext.setJobDescription(statement) sessionToActivePool.get(parentSession.getSessionHandle).foreach { pool => hiveContext.sparkContext.setLocalProperty("spark.scheduler.pool", pool) } diff --git a/sql/hive-thriftserver/v0.13.1/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim13.scala b/sql/hive-thriftserver/v0.13.1/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim13.scala index 19d85140071ea..b82156427a88c 100644 --- a/sql/hive-thriftserver/v0.13.1/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim13.scala +++ b/sql/hive-thriftserver/v0.13.1/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim13.scala @@ -22,7 +22,6 @@ import java.util.{ArrayList => JArrayList, List => JList, Map => JMap} import scala.collection.JavaConversions._ import scala.collection.mutable.{ArrayBuffer, Map => SMap} -import scala.math._ import org.apache.hadoop.hive.metastore.api.FieldSchema import org.apache.hadoop.security.UserGroupInformation @@ -166,9 +165,7 @@ private[hive] class SparkExecuteStatementOperation( logInfo(s"Setting spark.scheduler.pool=$value for future statements in this session.") case _ => } - - val groupId = round(random * 1000000).toString - hiveContext.sparkContext.setJobGroup(groupId, statement) + hiveContext.sparkContext.setJobDescription(statement) sessionToActivePool.get(parentSession.getSessionHandle).foreach { pool => hiveContext.sparkContext.setLocalProperty("spark.scheduler.pool", pool) } From d22a31f5e84e27e27a059f540d08a8a441fc17fa Mon Sep 17 00:00:00 2001 From: scwf Date: Sat, 10 Jan 2015 17:07:34 -0800 Subject: [PATCH 225/320] [SPARK-5029][SQL] Enable from follow multiple brackets Enable from follow multiple brackets: ``` select key from ((select * from testData limit 1) union all (select * from testData limit 1)) x limit 1 ``` Author: scwf Closes #3853 from scwf/from and squashes the following commits: 14f110a [scwf] enable from follow multiple brackets --- .../apache/spark/sql/catalyst/SqlParser.scala | 2 +- .../org/apache/spark/sql/SQLQuerySuite.scala | 17 +++++++++++++++++ 2 files changed, 18 insertions(+), 1 deletion(-) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala index fc7b8745590d1..5d974df98b699 100755 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala @@ -125,7 +125,7 @@ class SqlParser extends AbstractSparkSQLParser { } protected lazy val start: Parser[LogicalPlan] = - ( select * + ( (select | ("(" ~> select <~ ")")) * ( UNION ~ ALL ^^^ { (q1: LogicalPlan, q2: LogicalPlan) => Union(q1, q2) } | INTERSECT ^^^ { (q1: LogicalPlan, q2: LogicalPlan) => Intersect(q1, q2) } | EXCEPT ^^^ { (q1: LogicalPlan, q2: LogicalPlan) => Except(q1, q2)} diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala index add4e218a22ee..d9de5686dce48 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala @@ -272,6 +272,23 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll { mapData.collect().take(1).toSeq) } + test("from follow multiple brackets") { + checkAnswer(sql( + "select key from ((select * from testData limit 1) union all (select * from testData limit 1)) x limit 1"), + 1 + ) + + checkAnswer(sql( + "select key from (select * from testData) x limit 1"), + 1 + ) + + checkAnswer(sql( + "select key from (select * from testData limit 1 union all select * from testData limit 1) x limit 1"), + 1 + ) + } + test("average") { checkAnswer( sql("SELECT AVG(a) FROM testData2"), From 33132609096d7fa45001c6a67724ec60bcaefaa9 Mon Sep 17 00:00:00 2001 From: "Joseph K. Bradley" Date: Sat, 10 Jan 2015 17:25:39 -0800 Subject: [PATCH 226/320] [SPARK-5032] [graphx] Remove GraphX MIMA exclude for 1.3 Since GraphX is no longer alpha as of 1.2, MimaExcludes should not exclude GraphX for 1.3 Here are the individual excludes I had to add + the associated commits: ``` // SPARK-4444 ProblemFilters.exclude[IncompatibleResultTypeProblem]( "org.apache.spark.graphx.EdgeRDD.fromEdges"), ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.graphx.EdgeRDD.filter"), ProblemFilters.exclude[IncompatibleResultTypeProblem]( "org.apache.spark.graphx.impl.EdgeRDDImpl.filter"), ``` [https://github.com/apache/spark/commit/9ac2bb18ede2e9f73c255fa33445af89aaf8a000] ``` // SPARK-3623 ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.graphx.Graph.checkpoint") ``` [https://github.com/apache/spark/commit/e895e0cbecbbec1b412ff21321e57826d2d0a982] ``` // SPARK-4620 ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.graphx.Graph.unpersist"), ``` [https://github.com/apache/spark/commit/8817fc7fe8785d7b11138ca744f22f7e70f1f0a0] CC: rxin Author: Joseph K. Bradley Closes #3856 from jkbradley/graphx-mima and squashes the following commits: 1eea2f6 [Joseph K. Bradley] moved cleanup to run-tests 527ccd9 [Joseph K. Bradley] fixed jenkins script to remove ivy2 cache 802e252 [Joseph K. Bradley] Removed GraphX MIMA excludes and added line to clear spark from .m2 dir before Jenkins tests. This may not work yet... 30f8bb4 [Joseph K. Bradley] added individual mima excludes for graphx a3fea42 [Joseph K. Bradley] removed graphx mima exclude for 1.3 --- dev/run-tests | 4 +++- project/MimaExcludes.scala | 1 - 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/dev/run-tests b/dev/run-tests index 20603fc089239..2257a566bb1bb 100755 --- a/dev/run-tests +++ b/dev/run-tests @@ -21,8 +21,10 @@ FWDIR="$(cd "`dirname $0`"/..; pwd)" cd "$FWDIR" -# Remove work directory +# Clean up work directory and caches rm -rf ./work +rm -rf ~/.ivy2/local/org.apache.spark +rm -rf ~/.ivy2/cache/org.apache.spark source "$FWDIR/dev/run-tests-codes.sh" diff --git a/project/MimaExcludes.scala b/project/MimaExcludes.scala index 31d4c317ae569..51e8bd4cf6419 100644 --- a/project/MimaExcludes.scala +++ b/project/MimaExcludes.scala @@ -36,7 +36,6 @@ object MimaExcludes { case v if v.startsWith("1.3") => Seq( MimaBuild.excludeSparkPackage("deploy"), - MimaBuild.excludeSparkPackage("graphx"), // These are needed if checking against the sbt build, since they are part of // the maven-generated artifacts in the 1.2 build. MimaBuild.excludeSparkPackage("unused"), From 1656aae2b4e8b026f8cfe782519f72d32ed2b291 Mon Sep 17 00:00:00 2001 From: lewuathe Date: Sun, 11 Jan 2015 13:50:42 -0800 Subject: [PATCH 227/320] [SPARK-5073] spark.storage.memoryMapThreshold have two default value Because major OS page sizes is about 4KB, the default value of spark.storage.memoryMapThreshold is integrated to 2 * 4096 Author: lewuathe Closes #3900 from Lewuathe/integrate-memoryMapThreshold and squashes the following commits: e417acd [lewuathe] [SPARK-5073] Update docs/configuration 834aba4 [lewuathe] [SPARK-5073] Fix style adcea33 [lewuathe] [SPARK-5073] Integrate memory map threshold to 2MB fcce2e5 [lewuathe] [SPARK-5073] spark.storage.memoryMapThreshold have two default value --- core/src/main/scala/org/apache/spark/storage/DiskStore.scala | 3 ++- docs/configuration.md | 2 +- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/storage/DiskStore.scala b/core/src/main/scala/org/apache/spark/storage/DiskStore.scala index 8dadf6794039e..61ef5ff168791 100644 --- a/core/src/main/scala/org/apache/spark/storage/DiskStore.scala +++ b/core/src/main/scala/org/apache/spark/storage/DiskStore.scala @@ -31,7 +31,8 @@ import org.apache.spark.util.Utils private[spark] class DiskStore(blockManager: BlockManager, diskManager: DiskBlockManager) extends BlockStore(blockManager) with Logging { - val minMemoryMapBytes = blockManager.conf.getLong("spark.storage.memoryMapThreshold", 2 * 4096L) + val minMemoryMapBytes = blockManager.conf.getLong( + "spark.storage.memoryMapThreshold", 2 * 1024L * 1024L) override def getSize(blockId: BlockId): Long = { diskManager.getFile(blockId.name).length diff --git a/docs/configuration.md b/docs/configuration.md index 2add48569bece..f292bfbb7dcd6 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -678,7 +678,7 @@ Apart from these, the following properties are also available, and may be useful - + - + - - + + @@ -117,6 +116,14 @@ of the most common options to set are: (e.g. 512m, 2g). + + + + + diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md index 4f273098c5db3..68ab127bcf087 100644 --- a/docs/running-on-yarn.md +++ b/docs/running-on-yarn.md @@ -29,6 +29,23 @@ Most of the configs are the same for Spark on YARN as for other deployment modes In cluster mode, use spark.driver.memory instead. + + + + + + + + + + diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala index 032106371cd60..d4eeccf64275f 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala @@ -127,6 +127,7 @@ private[spark] class Client( } val capability = Records.newRecord(classOf[Resource]) capability.setMemory(args.amMemory + amMemoryOverhead) + capability.setVirtualCores(args.amCores) appContext.setResource(capability) appContext } diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala index 461a9ccd3c216..79bead77ba6e4 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala @@ -36,14 +36,18 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf) var numExecutors = DEFAULT_NUMBER_EXECUTORS var amQueue = sparkConf.get("spark.yarn.queue", "default") var amMemory: Int = 512 // MB + var amCores: Int = 1 var appName: String = "Spark" var priority = 0 def isClusterMode: Boolean = userClass != null private var driverMemory: Int = 512 // MB + private var driverCores: Int = 1 private val driverMemOverheadKey = "spark.yarn.driver.memoryOverhead" private val amMemKey = "spark.yarn.am.memory" private val amMemOverheadKey = "spark.yarn.am.memoryOverhead" + private val driverCoresKey = "spark.driver.cores" + private val amCoresKey = "spark.yarn.am.cores" private val isDynamicAllocationEnabled = sparkConf.getBoolean("spark.dynamicAllocation.enabled", false) @@ -92,19 +96,25 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf) "You must specify at least 1 executor!\n" + getUsageMessage()) } if (isClusterMode) { - for (key <- Seq(amMemKey, amMemOverheadKey)) { + for (key <- Seq(amMemKey, amMemOverheadKey, amCoresKey)) { if (sparkConf.contains(key)) { println(s"$key is set but does not apply in cluster mode.") } } amMemory = driverMemory + amCores = driverCores } else { - if (sparkConf.contains(driverMemOverheadKey)) { - println(s"$driverMemOverheadKey is set but does not apply in client mode.") + for (key <- Seq(driverMemOverheadKey, driverCoresKey)) { + if (sparkConf.contains(key)) { + println(s"$key is set but does not apply in client mode.") + } } sparkConf.getOption(amMemKey) .map(Utils.memoryStringToMb) .foreach { mem => amMemory = mem } + sparkConf.getOption(amCoresKey) + .map(_.toInt) + .foreach { cores => amCores = cores } } } @@ -140,6 +150,10 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf) driverMemory = value args = tail + case ("--driver-cores") :: IntParam(value) :: tail => + driverCores = value + args = tail + case ("--num-workers" | "--num-executors") :: IntParam(value) :: tail => if (args(0) == "--num-workers") { println("--num-workers is deprecated. Use --num-executors instead.") @@ -198,7 +212,8 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf) private def getUsageMessage(unknownParam: List[String] = null): String = { val message = if (unknownParam != null) s"Unknown/unsupported param $unknownParam\n" else "" - message + """ + message + + """ |Usage: org.apache.spark.deploy.yarn.Client [options] |Options: | --jar JAR_PATH Path to your application's JAR file (required in yarn-cluster @@ -209,6 +224,7 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf) | --num-executors NUM Number of executors to start (Default: 2) | --executor-cores NUM Number of cores for the executors (Default: 1). | --driver-memory MEM Memory for driver (e.g. 1000M, 2G) (Default: 512 Mb) + | --driver-cores NUM Number of cores used by the driver (Default: 1). | --executor-memory MEM Memory per executor (e.g. 1000M, 2G) (Default: 1G) | --name NAME The name of your application (Default: Spark) | --queue QUEUE The hadoop queue to use for allocation requests (Default: From e200ac8e53a533d64a79c18561b557ea445f1cc9 Mon Sep 17 00:00:00 2001 From: Ye Xianjin Date: Fri, 16 Jan 2015 09:20:53 -0800 Subject: [PATCH 265/320] [SPARK-5201][CORE] deal with int overflow in the ParallelCollectionRDD.slice method There is an int overflow in the ParallelCollectionRDD.slice method. That's originally reported by SaintBacchus. ``` sc.makeRDD(1 to (Int.MaxValue)).count // result = 0 sc.makeRDD(1 to (Int.MaxValue - 1)).count // result = 2147483646 = Int.MaxValue - 1 sc.makeRDD(1 until (Int.MaxValue)).count // result = 2147483646 = Int.MaxValue - 1 ``` see https://github.com/apache/spark/pull/2874 for more details. This pr try to fix the overflow. However, There's another issue I don't address. ``` val largeRange = Int.MinValue to Int.MaxValue largeRange.length // throws java.lang.IllegalArgumentException: -2147483648 to 2147483647 by 1: seqs cannot contain more than Int.MaxValue elements. ``` So, the range we feed to sc.makeRDD cannot contain more than Int.MaxValue elements. This is the limitation of Scala. However I think we may want to support that kind of range. But the fix is beyond this pr. srowen andrewor14 would you mind take a look at this pr? Author: Ye Xianjin Closes #4002 from advancedxy/SPARk-5201 and squashes the following commits: 96265a1 [Ye Xianjin] Update slice method comment and some responding docs. e143d7a [Ye Xianjin] Update inclusive range check for splitting inclusive range. b3f5577 [Ye Xianjin] We can include the last element in the last slice in general for inclusive range, hence eliminate the need to check Int.MaxValue or Int.MinValue. 7d39b9e [Ye Xianjin] Convert the two cases pattern matching to one case. 651c959 [Ye Xianjin] rename sign to needsInclusiveRange. add some comments 196f8a8 [Ye Xianjin] Add test cases for ranges end with Int.MaxValue or Int.MinValue e66e60a [Ye Xianjin] Deal with inclusive and exclusive ranges in one case. If the range is inclusive and the end of the range is (Int.MaxValue or Int.MinValue), we should use inclusive range instead of exclusive --- .../scala/org/apache/spark/SparkContext.scala | 7 +++--- .../spark/rdd/ParallelCollectionRDD.scala | 21 +++++++--------- .../rdd/ParallelCollectionSplitSuite.scala | 25 +++++++++++++++++++ 3 files changed, 37 insertions(+), 16 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala index ff5d796ee2766..6a354ed4d1486 100644 --- a/core/src/main/scala/org/apache/spark/SparkContext.scala +++ b/core/src/main/scala/org/apache/spark/SparkContext.scala @@ -520,10 +520,9 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli /** Distribute a local Scala collection to form an RDD. * - * @note Parallelize acts lazily. If `seq` is a mutable collection and is - * altered after the call to parallelize and before the first action on the - * RDD, the resultant RDD will reflect the modified collection. Pass a copy of - * the argument to avoid this. + * @note Parallelize acts lazily. If `seq` is a mutable collection and is altered after the call + * to parallelize and before the first action on the RDD, the resultant RDD will reflect the + * modified collection. Pass a copy of the argument to avoid this. */ def parallelize[T: ClassTag](seq: Seq[T], numSlices: Int = defaultParallelism): RDD[T] = { new ParallelCollectionRDD[T](this, seq, numSlices, Map[Int, Seq[String]]()) diff --git a/core/src/main/scala/org/apache/spark/rdd/ParallelCollectionRDD.scala b/core/src/main/scala/org/apache/spark/rdd/ParallelCollectionRDD.scala index 87b22de6ae697..f12d0cffaba34 100644 --- a/core/src/main/scala/org/apache/spark/rdd/ParallelCollectionRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/ParallelCollectionRDD.scala @@ -111,7 +111,8 @@ private object ParallelCollectionRDD { /** * Slice a collection into numSlices sub-collections. One extra thing we do here is to treat Range * collections specially, encoding the slices as other Ranges to minimize memory cost. This makes - * it efficient to run Spark over RDDs representing large sets of numbers. + * it efficient to run Spark over RDDs representing large sets of numbers. And if the collection + * is an inclusive Range, we use inclusive range for the last slice. */ def slice[T: ClassTag](seq: Seq[T], numSlices: Int): Seq[Seq[T]] = { if (numSlices < 1) { @@ -127,19 +128,15 @@ private object ParallelCollectionRDD { }) } seq match { - case r: Range.Inclusive => { - val sign = if (r.step < 0) { - -1 - } else { - 1 - } - slice(new Range( - r.start, r.end + sign, r.step).asInstanceOf[Seq[T]], numSlices) - } case r: Range => { - positions(r.length, numSlices).map({ - case (start, end) => + positions(r.length, numSlices).zipWithIndex.map({ case ((start, end), index) => + // If the range is inclusive, use inclusive range for the last slice + if (r.isInclusive && index == numSlices - 1) { + new Range.Inclusive(r.start + start * r.step, r.end, r.step) + } + else { new Range(r.start + start * r.step, r.start + end * r.step, r.step) + } }).toSeq.asInstanceOf[Seq[Seq[T]]] } case nr: NumericRange[_] => { diff --git a/core/src/test/scala/org/apache/spark/rdd/ParallelCollectionSplitSuite.scala b/core/src/test/scala/org/apache/spark/rdd/ParallelCollectionSplitSuite.scala index 1b112f1a41ca9..cd193ae4f5238 100644 --- a/core/src/test/scala/org/apache/spark/rdd/ParallelCollectionSplitSuite.scala +++ b/core/src/test/scala/org/apache/spark/rdd/ParallelCollectionSplitSuite.scala @@ -76,6 +76,7 @@ class ParallelCollectionSplitSuite extends FunSuite with Checkers { assert(slices(0).mkString(",") === (0 to 32).mkString(",")) assert(slices(1).mkString(",") === (33 to 66).mkString(",")) assert(slices(2).mkString(",") === (67 to 100).mkString(",")) + assert(slices(2).isInstanceOf[Range.Inclusive]) } test("empty data") { @@ -227,4 +228,28 @@ class ParallelCollectionSplitSuite extends FunSuite with Checkers { assert(slices.map(_.size).reduceLeft(_+_) === 100) assert(slices.forall(_.isInstanceOf[NumericRange[_]])) } + + test("inclusive ranges with Int.MaxValue and Int.MinValue") { + val data1 = 1 to Int.MaxValue + val slices1 = ParallelCollectionRDD.slice(data1, 3) + assert(slices1.size === 3) + assert(slices1.map(_.size).sum === Int.MaxValue) + assert(slices1(2).isInstanceOf[Range.Inclusive]) + val data2 = -2 to Int.MinValue by -1 + val slices2 = ParallelCollectionRDD.slice(data2, 3) + assert(slices2.size == 3) + assert(slices2.map(_.size).sum === Int.MaxValue) + assert(slices2(2).isInstanceOf[Range.Inclusive]) + } + + test("empty ranges with Int.MaxValue and Int.MinValue") { + val data1 = Int.MaxValue until Int.MaxValue + val slices1 = ParallelCollectionRDD.slice(data1, 5) + assert(slices1.size === 5) + for (i <- 0 until 5) assert(slices1(i).size === 0) + val data2 = Int.MaxValue until Int.MaxValue + val slices2 = ParallelCollectionRDD.slice(data2, 5) + assert(slices2.size === 5) + for (i <- 0 until 5) assert(slices2(i).size === 0) + } } From f6b852aade7668c99f37c69f606c64763cb265d2 Mon Sep 17 00:00:00 2001 From: Sean Owen Date: Fri, 16 Jan 2015 09:28:44 -0800 Subject: [PATCH 266/320] [DOCS] Fix typo in return type of cogroup This fixes a simple typo in the cogroup docs noted in http://mail-archives.apache.org/mod_mbox/spark-user/201501.mbox/%3CCAMAsSdJ8_24evMAMg7fOZCQjwimisbYWa9v8BN6Rc3JCauja6wmail.gmail.com%3E I didn't bother with a JIRA Author: Sean Owen Closes #4072 from srowen/CogroupDocFix and squashes the following commits: 43c850b [Sean Owen] Fix typo in return type of cogroup --- docs/programming-guide.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/programming-guide.md b/docs/programming-guide.md index 5e0d5c15d7069..0211bbabc1132 100644 --- a/docs/programming-guide.md +++ b/docs/programming-guide.md @@ -913,7 +913,7 @@ for details. - + From e8422c521bc76bc4b03c337605f136403ea9f64a Mon Sep 17 00:00:00 2001 From: Kousuke Saruta Date: Fri, 16 Jan 2015 10:05:11 -0800 Subject: [PATCH 267/320] [SPARK-5231][WebUI] History Server shows wrong job submission time. History Server doesn't show collect job submission time. It's because `JobProgressListener` updates job submission time every time `onJobStart` method is invoked from `ReplayListenerBus`. Author: Kousuke Saruta Closes #4029 from sarutak/SPARK-5231 and squashes the following commits: 0af9e22 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-5231 da8bd14 [Kousuke Saruta] Made submissionTime in SparkListenerJobStartas and completionTime in SparkListenerJobEnd as regular Long 0412a6a [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-5231 26b9b99 [Kousuke Saruta] Fixed the test cases 2d47bd3 [Kousuke Saruta] Fixed to record job submission time and completion time collectly --- .../apache/spark/scheduler/DAGScheduler.scala | 16 ++++++---- .../spark/scheduler/SparkListener.scala | 7 ++++- .../apache/spark/ui/jobs/AllJobsPage.scala | 15 +++++---- .../spark/ui/jobs/JobProgressListener.scala | 10 +++--- .../org/apache/spark/ui/jobs/UIData.scala | 6 ++-- .../org/apache/spark/util/JsonProtocol.scala | 11 +++++-- .../spark/scheduler/SparkListenerSuite.scala | 10 +++--- .../ui/jobs/JobProgressListenerSuite.scala | 6 ++-- .../apache/spark/util/JsonProtocolSuite.scala | 31 ++++++++++++++++--- 9 files changed, 77 insertions(+), 35 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala index 8cb15918baa8c..3bca59e0646d0 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala @@ -661,7 +661,7 @@ class DAGScheduler( // completion events or stage abort stageIdToStage -= s.id jobIdToStageIds -= job.jobId - listenerBus.post(SparkListenerJobEnd(job.jobId, jobResult)) + listenerBus.post(SparkListenerJobEnd(job.jobId, clock.getTime(), jobResult)) } } @@ -710,7 +710,7 @@ class DAGScheduler( stage.latestInfo.stageFailed(stageFailedMessage) listenerBus.post(SparkListenerStageCompleted(stage.latestInfo)) } - listenerBus.post(SparkListenerJobEnd(job.jobId, JobFailed(error))) + listenerBus.post(SparkListenerJobEnd(job.jobId, clock.getTime(), JobFailed(error))) } } @@ -749,9 +749,11 @@ class DAGScheduler( logInfo("Missing parents: " + getMissingParentStages(finalStage)) val shouldRunLocally = localExecutionEnabled && allowLocal && finalStage.parents.isEmpty && partitions.length == 1 + val jobSubmissionTime = clock.getTime() if (shouldRunLocally) { // Compute very short actions like first() or take() with no parent stages locally. - listenerBus.post(SparkListenerJobStart(job.jobId, Seq.empty, properties)) + listenerBus.post( + SparkListenerJobStart(job.jobId, jobSubmissionTime, Seq.empty, properties)) runLocally(job) } else { jobIdToActiveJob(jobId) = job @@ -759,7 +761,8 @@ class DAGScheduler( finalStage.resultOfJob = Some(job) val stageIds = jobIdToStageIds(jobId).toArray val stageInfos = stageIds.flatMap(id => stageIdToStage.get(id).map(_.latestInfo)) - listenerBus.post(SparkListenerJobStart(job.jobId, stageInfos, properties)) + listenerBus.post( + SparkListenerJobStart(job.jobId, jobSubmissionTime, stageInfos, properties)) submitStage(finalStage) } } @@ -965,7 +968,8 @@ class DAGScheduler( if (job.numFinished == job.numPartitions) { markStageAsFinished(stage) cleanupStateForJobAndIndependentStages(job) - listenerBus.post(SparkListenerJobEnd(job.jobId, JobSucceeded)) + listenerBus.post( + SparkListenerJobEnd(job.jobId, clock.getTime(), JobSucceeded)) } // taskSucceeded runs some user code that might throw an exception. Make sure @@ -1234,7 +1238,7 @@ class DAGScheduler( if (ableToCancelStages) { job.listener.jobFailed(error) cleanupStateForJobAndIndependentStages(job) - listenerBus.post(SparkListenerJobEnd(job.jobId, JobFailed(error))) + listenerBus.post(SparkListenerJobEnd(job.jobId, clock.getTime(), JobFailed(error))) } } diff --git a/core/src/main/scala/org/apache/spark/scheduler/SparkListener.scala b/core/src/main/scala/org/apache/spark/scheduler/SparkListener.scala index 4840d8bd2d2f0..e5d1eb767e109 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/SparkListener.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/SparkListener.scala @@ -59,6 +59,7 @@ case class SparkListenerTaskEnd( @DeveloperApi case class SparkListenerJobStart( jobId: Int, + time: Long, stageInfos: Seq[StageInfo], properties: Properties = null) extends SparkListenerEvent { @@ -68,7 +69,11 @@ case class SparkListenerJobStart( } @DeveloperApi -case class SparkListenerJobEnd(jobId: Int, jobResult: JobResult) extends SparkListenerEvent +case class SparkListenerJobEnd( + jobId: Int, + time: Long, + jobResult: JobResult) + extends SparkListenerEvent @DeveloperApi case class SparkListenerEnvironmentUpdate(environmentDetails: Map[String, Seq[(String, String)]]) diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/AllJobsPage.scala b/core/src/main/scala/org/apache/spark/ui/jobs/AllJobsPage.scala index 1d1c701878447..81212708ba524 100644 --- a/core/src/main/scala/org/apache/spark/ui/jobs/AllJobsPage.scala +++ b/core/src/main/scala/org/apache/spark/ui/jobs/AllJobsPage.scala @@ -21,7 +21,6 @@ import scala.xml.{Node, NodeSeq} import javax.servlet.http.HttpServletRequest -import org.apache.spark.JobExecutionStatus import org.apache.spark.ui.{WebUIPage, UIUtils} import org.apache.spark.ui.jobs.UIData.JobUIData @@ -51,13 +50,13 @@ private[ui] class AllJobsPage(parent: JobsTab) extends WebUIPage("") { val lastStageName = lastStageInfo.map(_.name).getOrElse("(Unknown Stage Name)") val lastStageDescription = lastStageData.flatMap(_.description).getOrElse("") val duration: Option[Long] = { - job.startTime.map { start => - val end = job.endTime.getOrElse(System.currentTimeMillis()) + job.submissionTime.map { start => + val end = job.completionTime.getOrElse(System.currentTimeMillis()) end - start } } val formattedDuration = duration.map(d => UIUtils.formatDuration(d)).getOrElse("Unknown") - val formattedSubmissionTime = job.startTime.map(UIUtils.formatDate).getOrElse("Unknown") + val formattedSubmissionTime = job.submissionTime.map(UIUtils.formatDate).getOrElse("Unknown") val detailUrl = "%s/jobs/job?id=%s".format(UIUtils.prependBaseUri(parent.basePath), job.jobId) @@ -68,7 +67,7 @@ private[ui] class AllJobsPage(parent: JobsTab) extends WebUIPage("") {
    {lastStageDescription}
    {lastStageName} - @@ -101,11 +100,11 @@ private[ui] class AllJobsPage(parent: JobsTab) extends WebUIPage("") { val now = System.currentTimeMillis val activeJobsTable = - jobsTable(activeJobs.sortBy(_.startTime.getOrElse(-1L)).reverse) + jobsTable(activeJobs.sortBy(_.submissionTime.getOrElse(-1L)).reverse) val completedJobsTable = - jobsTable(completedJobs.sortBy(_.endTime.getOrElse(-1L)).reverse) + jobsTable(completedJobs.sortBy(_.completionTime.getOrElse(-1L)).reverse) val failedJobsTable = - jobsTable(failedJobs.sortBy(_.endTime.getOrElse(-1L)).reverse) + jobsTable(failedJobs.sortBy(_.completionTime.getOrElse(-1L)).reverse) val shouldShowActiveJobs = activeJobs.nonEmpty val shouldShowCompletedJobs = completedJobs.nonEmpty diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/JobProgressListener.scala b/core/src/main/scala/org/apache/spark/ui/jobs/JobProgressListener.scala index 72935beb3a34a..b0d3bed1300b3 100644 --- a/core/src/main/scala/org/apache/spark/ui/jobs/JobProgressListener.scala +++ b/core/src/main/scala/org/apache/spark/ui/jobs/JobProgressListener.scala @@ -153,14 +153,13 @@ class JobProgressListener(conf: SparkConf) extends SparkListener with Logging { val jobData: JobUIData = new JobUIData( jobId = jobStart.jobId, - startTime = Some(System.currentTimeMillis), - endTime = None, + submissionTime = Option(jobStart.time).filter(_ >= 0), stageIds = jobStart.stageIds, jobGroup = jobGroup, status = JobExecutionStatus.RUNNING) // Compute (a potential underestimate of) the number of tasks that will be run by this job. // This may be an underestimate because the job start event references all of the result - // stages's transitive stage dependencies, but some of these stages might be skipped if their + // stages' transitive stage dependencies, but some of these stages might be skipped if their // output is available from earlier runs. // See https://github.com/apache/spark/pull/3009 for a more extensive discussion. jobData.numTasks = { @@ -186,7 +185,8 @@ class JobProgressListener(conf: SparkConf) extends SparkListener with Logging { logWarning(s"Job completed for unknown job ${jobEnd.jobId}") new JobUIData(jobId = jobEnd.jobId) } - jobData.endTime = Some(System.currentTimeMillis()) + jobData.completionTime = Option(jobEnd.time).filter(_ >= 0) + jobEnd.jobResult match { case JobSucceeded => completedJobs += jobData @@ -309,7 +309,7 @@ class JobProgressListener(conf: SparkConf) extends SparkListener with Logging { override def onTaskEnd(taskEnd: SparkListenerTaskEnd) = synchronized { val info = taskEnd.taskInfo // If stage attempt id is -1, it means the DAGScheduler had no idea which attempt this task - // compeletion event is for. Let's just drop it here. This means we might have some speculation + // completion event is for. Let's just drop it here. This means we might have some speculation // tasks on the web ui that's never marked as complete. if (info != null && taskEnd.stageAttemptId != -1) { val stageData = stageIdToData.getOrElseUpdate((taskEnd.stageId, taskEnd.stageAttemptId), { diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/UIData.scala b/core/src/main/scala/org/apache/spark/ui/jobs/UIData.scala index 48fd7caa1a1ed..01f7e23212c3d 100644 --- a/core/src/main/scala/org/apache/spark/ui/jobs/UIData.scala +++ b/core/src/main/scala/org/apache/spark/ui/jobs/UIData.scala @@ -40,15 +40,15 @@ private[jobs] object UIData { class JobUIData( var jobId: Int = -1, - var startTime: Option[Long] = None, - var endTime: Option[Long] = None, + var submissionTime: Option[Long] = None, + var completionTime: Option[Long] = None, var stageIds: Seq[Int] = Seq.empty, var jobGroup: Option[String] = None, var status: JobExecutionStatus = JobExecutionStatus.UNKNOWN, /* Tasks */ // `numTasks` is a potential underestimate of the true number of tasks that this job will run. // This may be an underestimate because the job start event references all of the result - // stages's transitive stage dependencies, but some of these stages might be skipped if their + // stages' transitive stage dependencies, but some of these stages might be skipped if their // output is available from earlier runs. // See https://github.com/apache/spark/pull/3009 for a more extensive discussion. var numTasks: Int = 0, diff --git a/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala b/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala index ee3756c226fe3..76709a230f836 100644 --- a/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala +++ b/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala @@ -32,6 +32,7 @@ import org.apache.spark.executor._ import org.apache.spark.scheduler._ import org.apache.spark.storage._ import org.apache.spark._ +import org.apache.hadoop.hdfs.web.JsonUtil /** * Serializes SparkListener events to/from JSON. This protocol provides strong backwards- @@ -141,6 +142,7 @@ private[spark] object JsonProtocol { val properties = propertiesToJson(jobStart.properties) ("Event" -> Utils.getFormattedClassName(jobStart)) ~ ("Job ID" -> jobStart.jobId) ~ + ("Submission Time" -> jobStart.time) ~ ("Stage Infos" -> jobStart.stageInfos.map(stageInfoToJson)) ~ // Added in Spark 1.2.0 ("Stage IDs" -> jobStart.stageIds) ~ ("Properties" -> properties) @@ -150,6 +152,7 @@ private[spark] object JsonProtocol { val jobResult = jobResultToJson(jobEnd.jobResult) ("Event" -> Utils.getFormattedClassName(jobEnd)) ~ ("Job ID" -> jobEnd.jobId) ~ + ("Completion Time" -> jobEnd.time) ~ ("Job Result" -> jobResult) } @@ -492,6 +495,8 @@ private[spark] object JsonProtocol { def jobStartFromJson(json: JValue): SparkListenerJobStart = { val jobId = (json \ "Job ID").extract[Int] + val submissionTime = + Utils.jsonOption(json \ "Submission Time").map(_.extract[Long]).getOrElse(-1L) val stageIds = (json \ "Stage IDs").extract[List[JValue]].map(_.extract[Int]) val properties = propertiesFromJson(json \ "Properties") // The "Stage Infos" field was added in Spark 1.2.0 @@ -499,13 +504,15 @@ private[spark] object JsonProtocol { .map(_.extract[Seq[JValue]].map(stageInfoFromJson)).getOrElse { stageIds.map(id => new StageInfo(id, 0, "unknown", 0, Seq.empty, "unknown")) } - SparkListenerJobStart(jobId, stageInfos, properties) + SparkListenerJobStart(jobId, submissionTime, stageInfos, properties) } def jobEndFromJson(json: JValue): SparkListenerJobEnd = { val jobId = (json \ "Job ID").extract[Int] + val completionTime = + Utils.jsonOption(json \ "Completion Time").map(_.extract[Long]).getOrElse(-1L) val jobResult = jobResultFromJson(json \ "Job Result") - SparkListenerJobEnd(jobId, jobResult) + SparkListenerJobEnd(jobId, completionTime, jobResult) } def environmentUpdateFromJson(json: JValue): SparkListenerEnvironmentUpdate = { diff --git a/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala index 24f41bf8cccda..0fb1bdd30d975 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala @@ -34,6 +34,8 @@ class SparkListenerSuite extends FunSuite with LocalSparkContext with Matchers /** Length of time to wait while draining listener events. */ val WAIT_TIMEOUT_MILLIS = 10000 + val jobCompletionTime = 1421191296660L + before { sc = new SparkContext("local", "SparkListenerSuite") } @@ -44,7 +46,7 @@ class SparkListenerSuite extends FunSuite with LocalSparkContext with Matchers bus.addListener(counter) // Listener bus hasn't started yet, so posting events should not increment counter - (1 to 5).foreach { _ => bus.post(SparkListenerJobEnd(0, JobSucceeded)) } + (1 to 5).foreach { _ => bus.post(SparkListenerJobEnd(0, jobCompletionTime, JobSucceeded)) } assert(counter.count === 0) // Starting listener bus should flush all buffered events @@ -54,7 +56,7 @@ class SparkListenerSuite extends FunSuite with LocalSparkContext with Matchers // After listener bus has stopped, posting events should not increment counter bus.stop() - (1 to 5).foreach { _ => bus.post(SparkListenerJobEnd(0, JobSucceeded)) } + (1 to 5).foreach { _ => bus.post(SparkListenerJobEnd(0, jobCompletionTime, JobSucceeded)) } assert(counter.count === 5) // Listener bus must not be started twice @@ -99,7 +101,7 @@ class SparkListenerSuite extends FunSuite with LocalSparkContext with Matchers bus.addListener(blockingListener) bus.start() - bus.post(SparkListenerJobEnd(0, JobSucceeded)) + bus.post(SparkListenerJobEnd(0, jobCompletionTime, JobSucceeded)) listenerStarted.acquire() // Listener should be blocked after start @@ -345,7 +347,7 @@ class SparkListenerSuite extends FunSuite with LocalSparkContext with Matchers bus.start() // Post events to all listeners, and wait until the queue is drained - (1 to 5).foreach { _ => bus.post(SparkListenerJobEnd(0, JobSucceeded)) } + (1 to 5).foreach { _ => bus.post(SparkListenerJobEnd(0, jobCompletionTime, JobSucceeded)) } assert(bus.waitUntilEmpty(WAIT_TIMEOUT_MILLIS)) // The exception should be caught, and the event should be propagated to other listeners diff --git a/core/src/test/scala/org/apache/spark/ui/jobs/JobProgressListenerSuite.scala b/core/src/test/scala/org/apache/spark/ui/jobs/JobProgressListenerSuite.scala index f865d8ca04d1b..c9417ea1ed8f6 100644 --- a/core/src/test/scala/org/apache/spark/ui/jobs/JobProgressListenerSuite.scala +++ b/core/src/test/scala/org/apache/spark/ui/jobs/JobProgressListenerSuite.scala @@ -28,6 +28,8 @@ import org.apache.spark.util.Utils class JobProgressListenerSuite extends FunSuite with LocalSparkContext with Matchers { + val jobSubmissionTime = 1421191042750L + val jobCompletionTime = 1421191296660L private def createStageStartEvent(stageId: Int) = { val stageInfo = new StageInfo(stageId, 0, stageId.toString, 0, null, "") @@ -46,12 +48,12 @@ class JobProgressListenerSuite extends FunSuite with LocalSparkContext with Matc val stageInfos = stageIds.map { stageId => new StageInfo(stageId, 0, stageId.toString, 0, null, "") } - SparkListenerJobStart(jobId, stageInfos) + SparkListenerJobStart(jobId, jobSubmissionTime, stageInfos) } private def createJobEndEvent(jobId: Int, failed: Boolean = false) = { val result = if (failed) JobFailed(new Exception("dummy failure")) else JobSucceeded - SparkListenerJobEnd(jobId, result) + SparkListenerJobEnd(jobId, jobCompletionTime, result) } private def runJob(listener: SparkListener, jobId: Int, shouldFail: Boolean = false) { diff --git a/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala b/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala index 71dfed1289850..db400b4162910 100644 --- a/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala +++ b/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala @@ -34,6 +34,9 @@ import org.apache.spark.storage._ class JsonProtocolSuite extends FunSuite { + val jobSubmissionTime = 1421191042750L + val jobCompletionTime = 1421191296660L + test("SparkListenerEvent") { val stageSubmitted = SparkListenerStageSubmitted(makeStageInfo(100, 200, 300, 400L, 500L), properties) @@ -54,9 +57,9 @@ class JsonProtocolSuite extends FunSuite { val stageIds = Seq[Int](1, 2, 3, 4) val stageInfos = stageIds.map(x => makeStageInfo(x, x * 200, x * 300, x * 400L, x * 500L)) - SparkListenerJobStart(10, stageInfos, properties) + SparkListenerJobStart(10, jobSubmissionTime, stageInfos, properties) } - val jobEnd = SparkListenerJobEnd(20, JobSucceeded) + val jobEnd = SparkListenerJobEnd(20, jobCompletionTime, JobSucceeded) val environmentUpdate = SparkListenerEnvironmentUpdate(Map[String, Seq[(String, String)]]( "JVM Information" -> Seq(("GC speed", "9999 objects/s"), ("Java home", "Land of coffee")), "Spark Properties" -> Seq(("Job throughput", "80000 jobs/s, regardless of job type")), @@ -247,13 +250,31 @@ class JsonProtocolSuite extends FunSuite { val stageInfos = stageIds.map(x => makeStageInfo(x, x * 200, x * 300, x * 400, x * 500)) val dummyStageInfos = stageIds.map(id => new StageInfo(id, 0, "unknown", 0, Seq.empty, "unknown")) - val jobStart = SparkListenerJobStart(10, stageInfos, properties) + val jobStart = SparkListenerJobStart(10, jobSubmissionTime, stageInfos, properties) val oldEvent = JsonProtocol.jobStartToJson(jobStart).removeField({_._1 == "Stage Infos"}) val expectedJobStart = - SparkListenerJobStart(10, dummyStageInfos, properties) + SparkListenerJobStart(10, jobSubmissionTime, dummyStageInfos, properties) assertEquals(expectedJobStart, JsonProtocol.jobStartFromJson(oldEvent)) } + test("SparkListenerJobStart and SparkListenerJobEnd backward compatibility") { + // Prior to Spark 1.3.0, SparkListenerJobStart did not have a "Submission Time" property. + // Also, SparkListenerJobEnd did not have a "Completion Time" property. + val stageIds = Seq[Int](1, 2, 3, 4) + val stageInfos = stageIds.map(x => makeStageInfo(x * 10, x * 20, x * 30, x * 40, x * 50)) + val jobStart = SparkListenerJobStart(11, jobSubmissionTime, stageInfos, properties) + val oldStartEvent = JsonProtocol.jobStartToJson(jobStart) + .removeField({ _._1 == "Submission Time"}) + val expectedJobStart = SparkListenerJobStart(11, -1, stageInfos, properties) + assertEquals(expectedJobStart, JsonProtocol.jobStartFromJson(oldStartEvent)) + + val jobEnd = SparkListenerJobEnd(11, jobCompletionTime, JobSucceeded) + val oldEndEvent = JsonProtocol.jobEndToJson(jobEnd) + .removeField({ _._1 == "Completion Time"}) + val expectedJobEnd = SparkListenerJobEnd(11, -1, JobSucceeded) + assertEquals(expectedJobEnd, JsonProtocol.jobEndFromJson(oldEndEvent)) + } + /** -------------------------- * | Helper test running methods | * --------------------------- */ @@ -1075,6 +1096,7 @@ class JsonProtocolSuite extends FunSuite { |{ | "Event": "SparkListenerJobStart", | "Job ID": 10, + | "Submission Time": 1421191042750, | "Stage Infos": [ | { | "Stage ID": 1, @@ -1349,6 +1371,7 @@ class JsonProtocolSuite extends FunSuite { |{ | "Event": "SparkListenerJobEnd", | "Job ID": 20, + | "Completion Time": 1421191296660, | "Job Result": { | "Result": "JobSucceeded" | } From ecf943d35342191a1362d80bb26f2a098c152f27 Mon Sep 17 00:00:00 2001 From: Kousuke Saruta Date: Fri, 16 Jan 2015 12:19:08 -0800 Subject: [PATCH 268/320] [WebUI] Fix collapse of WebUI layout When we decrease the width of browsers, the header of WebUI wraps and collapses like as following image. ![2015-01-11 19 49 37](https://cloud.githubusercontent.com/assets/4736016/5698887/b0b9aeee-99cd-11e4-9020-08f3f0014de0.png) Author: Kousuke Saruta Closes #3995 from sarutak/fixed-collapse-webui-layout and squashes the following commits: 3e60b5b [Kousuke Saruta] Modified line-height property in webui.css 7bfb5fb [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into fixed-collapse-webui-layout 5d83e18 [Kousuke Saruta] Fixed collapse of WebUI layout --- .../main/resources/org/apache/spark/ui/static/webui.css | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/core/src/main/resources/org/apache/spark/ui/static/webui.css b/core/src/main/resources/org/apache/spark/ui/static/webui.css index 5751964b792ce..f02b035a980b1 100644 --- a/core/src/main/resources/org/apache/spark/ui/static/webui.css +++ b/core/src/main/resources/org/apache/spark/ui/static/webui.css @@ -19,6 +19,7 @@ height: 50px; font-size: 15px; margin-bottom: 15px; + min-width: 1200px } .navbar .navbar-inner { @@ -39,12 +40,12 @@ .navbar .nav > li a { height: 30px; - line-height: 30px; + line-height: 2; } .navbar-text { height: 50px; - line-height: 50px; + line-height: 3.3; } table.sortable thead { @@ -170,7 +171,7 @@ span.additional-metric-title { } .version { - line-height: 30px; + line-height: 2.5; vertical-align: bottom; font-size: 12px; padding: 0; From d05c9ee6e8441e54732e40de45d1d2311307908f Mon Sep 17 00:00:00 2001 From: Chip Senkbeil Date: Fri, 16 Jan 2015 12:56:40 -0800 Subject: [PATCH 269/320] [SPARK-4923][REPL] Add Developer API to REPL to allow re-publishing the REPL jar As requested in [SPARK-4923](https://issues.apache.org/jira/browse/SPARK-4923), I've provided a rough DeveloperApi for the repl. I've only done this for Scala 2.10 because it does not appear that Scala 2.11 is implemented. The Scala 2.11 repl still has the old `scala.tools.nsc` package and the SparkIMain does not appear to have the class server needed for shipping code over (unless this functionality has been moved elsewhere?). I also left alone the `ExecutorClassLoader` and `ConstructorCleaner` as I have no experience working with those classes. This marks the majority of methods in `SparkIMain` as _private_ with a few special cases being _private[repl]_ as other classes within the same package access them. Any public method has been marked with `DeveloperApi` as suggested by pwendell and I took the liberty of writing up a Scaladoc for each one to further elaborate their usage. As the Scala 2.11 REPL [conforms]((https://github.com/scala/scala/pull/2206)) to [JSR-223](http://docs.oracle.com/javase/8/docs/technotes/guides/scripting/), the [Spark Kernel](https://github.com/ibm-et/spark-kernel) uses the SparkIMain of Scala 2.10 in the same manner. So, I've taken care to expose methods predominately related to necessary functionality towards a JSR-223 scripting engine implementation. 1. The ability to _get_ variables from the interpreter (and other information like class/symbol/type) 2. The ability to _put_ variables into the interpreter 3. The ability to _compile_ code 4. The ability to _execute_ code 5. The ability to get contextual information regarding the scripting environment Additional functionality that I marked as exposed included the following: 1. The blocking initialization method (needed to actually start SparkIMain instance) 2. The class server uri (needed to set the _spark.repl.class.uri_ property after initialization), reduced from the entire class server 3. The class output directory (beneficial for tools like ours that need to inspect and use the directory where class files are served) 4. Suppression (quiet/silence) mechanics for output 5. Ability to add a jar to the compile/runtime classpath 6. The reset/close functionality 7. Metric information (last variable assignment, "needed" for extracting results from last execution, real variable name for better debugging) 8. Execution wrapper (useful to have, but debatable) Aside from `SparkIMain`, I updated other classes/traits and their methods in the _repl_ package to be private/package protected where possible. A few odd cases (like the SparkHelper being in the scala.tools.nsc package to expose a private variable) still exist, but I did my best at labelling them. `SparkCommandLine` has proven useful to extract settings and `SparkJLineCompletion` has proven to be useful in implementing auto-completion in the [Spark Kernel](https://github.com/ibm-et/spark-kernel) project. Other than those - and `SparkIMain` - my experience has yielded that other classes/methods are not necessary for interactive applications taking advantage of the REPL API. Tested via the following: $ export MAVEN_OPTS="-Xmx2g -XX:MaxPermSize=512M -XX:ReservedCodeCacheSize=512m" $ mvn -Phadoop-2.3 -DskipTests clean package && mvn -Phadoop-2.3 test Also did a quick verification that I could start the shell and execute some code: $ ./bin/spark-shell ... scala> val x = 3 x: Int = 3 scala> sc.parallelize(1 to 10).reduce(_+_) ... res1: Int = 55 Author: Chip Senkbeil Author: Chip Senkbeil Closes #4034 from rcsenkbeil/AddDeveloperApiToRepl and squashes the following commits: 053ca75 [Chip Senkbeil] Fixed failed build by adding missing DeveloperApi import c1b88aa [Chip Senkbeil] Added DeveloperApi to public classes in repl 6dc1ee2 [Chip Senkbeil] Added missing method to expose error reporting flag 26fd286 [Chip Senkbeil] Refactored other Scala 2.10 classes and methods to be private/package protected where possible 925c112 [Chip Senkbeil] Added DeveloperApi and Scaladocs to SparkIMain for Scala 2.10 --- .../apache/spark/repl/SparkCommandLine.scala | 9 +- .../apache/spark/repl/SparkExprTyper.scala | 2 +- .../org/apache/spark/repl/SparkHelper.scala | 17 + .../org/apache/spark/repl/SparkILoop.scala | 150 +++-- .../apache/spark/repl/SparkILoopInit.scala | 2 +- .../org/apache/spark/repl/SparkIMain.scala | 592 ++++++++++++++---- .../org/apache/spark/repl/SparkImports.scala | 2 +- .../spark/repl/SparkJLineCompletion.scala | 56 +- .../apache/spark/repl/SparkJLineReader.scala | 4 +- .../spark/repl/SparkMemberHandlers.scala | 2 +- .../spark/repl/SparkRunnerSettings.scala | 3 +- 11 files changed, 644 insertions(+), 195 deletions(-) diff --git a/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkCommandLine.scala b/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkCommandLine.scala index 05816941b54b3..6480e2d24e044 100644 --- a/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkCommandLine.scala +++ b/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkCommandLine.scala @@ -19,14 +19,21 @@ package org.apache.spark.repl import scala.tools.nsc.{Settings, CompilerCommand} import scala.Predef._ +import org.apache.spark.annotation.DeveloperApi /** * Command class enabling Spark-specific command line options (provided by * org.apache.spark.repl.SparkRunnerSettings). + * + * @example new SparkCommandLine(Nil).settings + * + * @param args The list of command line arguments + * @param settings The underlying settings to associate with this set of + * command-line options */ +@DeveloperApi class SparkCommandLine(args: List[String], override val settings: Settings) extends CompilerCommand(args, settings) { - def this(args: List[String], error: String => Unit) { this(args, new SparkRunnerSettings(error)) } diff --git a/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkExprTyper.scala b/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkExprTyper.scala index f8432c8af6ed2..5fb378112ef92 100644 --- a/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkExprTyper.scala +++ b/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkExprTyper.scala @@ -15,7 +15,7 @@ import scala.tools.nsc.ast.parser.Tokens.EOF import org.apache.spark.Logging -trait SparkExprTyper extends Logging { +private[repl] trait SparkExprTyper extends Logging { val repl: SparkIMain import repl._ diff --git a/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkHelper.scala b/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkHelper.scala index 5340951d91331..955be17a73b85 100644 --- a/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkHelper.scala +++ b/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkHelper.scala @@ -17,6 +17,23 @@ package scala.tools.nsc +import org.apache.spark.annotation.DeveloperApi + +// NOTE: Forced to be public (and in scala.tools.nsc package) to access the +// settings "explicitParentLoader" method + +/** + * Provides exposure for the explicitParentLoader method on settings instances. + */ +@DeveloperApi object SparkHelper { + /** + * Retrieves the explicit parent loader for the provided settings. + * + * @param settings The settings whose explicit parent loader to retrieve + * + * @return The Optional classloader representing the explicit parent loader + */ + @DeveloperApi def explicitParentLoader(settings: Settings) = settings.explicitParentLoader } diff --git a/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkILoop.scala b/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkILoop.scala index e56b74edba88c..72c1a989999b4 100644 --- a/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkILoop.scala +++ b/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkILoop.scala @@ -10,6 +10,8 @@ package org.apache.spark.repl import java.net.URL +import org.apache.spark.annotation.DeveloperApi + import scala.reflect.io.AbstractFile import scala.tools.nsc._ import scala.tools.nsc.backend.JavaPlatform @@ -57,20 +59,22 @@ import org.apache.spark.util.Utils * @author Lex Spoon * @version 1.2 */ -class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, - val master: Option[String]) - extends AnyRef - with LoopCommands - with SparkILoopInit - with Logging -{ +@DeveloperApi +class SparkILoop( + private val in0: Option[BufferedReader], + protected val out: JPrintWriter, + val master: Option[String] +) extends AnyRef with LoopCommands with SparkILoopInit with Logging { def this(in0: BufferedReader, out: JPrintWriter, master: String) = this(Some(in0), out, Some(master)) def this(in0: BufferedReader, out: JPrintWriter) = this(Some(in0), out, None) def this() = this(None, new JPrintWriter(Console.out, true), None) - var in: InteractiveReader = _ // the input stream from which commands come - var settings: Settings = _ - var intp: SparkIMain = _ + private var in: InteractiveReader = _ // the input stream from which commands come + + // NOTE: Exposed in package for testing + private[repl] var settings: Settings = _ + + private[repl] var intp: SparkIMain = _ @deprecated("Use `intp` instead.", "2.9.0") def interpreter = intp @deprecated("Use `intp` instead.", "2.9.0") def interpreter_= (i: SparkIMain): Unit = intp = i @@ -123,6 +127,8 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, } } + // NOTE: Must be public for visibility + @DeveloperApi var sparkContext: SparkContext = _ override def echoCommandMessage(msg: String) { @@ -130,45 +136,45 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, } // def isAsync = !settings.Yreplsync.value - def isAsync = false + private[repl] def isAsync = false // lazy val power = new Power(intp, new StdReplVals(this))(tagOfStdReplVals, classTag[StdReplVals]) - def history = in.history + private def history = in.history /** The context class loader at the time this object was created */ protected val originalClassLoader = Utils.getContextOrSparkClassLoader // classpath entries added via :cp - var addedClasspath: String = "" + private var addedClasspath: String = "" /** A reverse list of commands to replay if the user requests a :replay */ - var replayCommandStack: List[String] = Nil + private var replayCommandStack: List[String] = Nil /** A list of commands to replay if the user requests a :replay */ - def replayCommands = replayCommandStack.reverse + private def replayCommands = replayCommandStack.reverse /** Record a command for replay should the user request a :replay */ - def addReplay(cmd: String) = replayCommandStack ::= cmd + private def addReplay(cmd: String) = replayCommandStack ::= cmd - def savingReplayStack[T](body: => T): T = { + private def savingReplayStack[T](body: => T): T = { val saved = replayCommandStack try body finally replayCommandStack = saved } - def savingReader[T](body: => T): T = { + private def savingReader[T](body: => T): T = { val saved = in try body finally in = saved } - def sparkCleanUp(){ + private def sparkCleanUp(){ echo("Stopping spark context.") intp.beQuietDuring { command("sc.stop()") } } /** Close the interpreter and set the var to null. */ - def closeInterpreter() { + private def closeInterpreter() { if (intp ne null) { sparkCleanUp() intp.close() @@ -179,14 +185,16 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, class SparkILoopInterpreter extends SparkIMain(settings, out) { outer => - override lazy val formatting = new Formatting { + override private[repl] lazy val formatting = new Formatting { def prompt = SparkILoop.this.prompt } override protected def parentClassLoader = SparkHelper.explicitParentLoader(settings).getOrElse(classOf[SparkILoop].getClassLoader) } - /** Create a new interpreter. */ - def createInterpreter() { + /** + * Constructs a new interpreter. + */ + protected def createInterpreter() { require(settings != null) if (addedClasspath != "") settings.classpath.append(addedClasspath) @@ -207,7 +215,7 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, } /** print a friendly help message */ - def helpCommand(line: String): Result = { + private def helpCommand(line: String): Result = { if (line == "") helpSummary() else uniqueCommand(line) match { case Some(lc) => echo("\n" + lc.longHelp) @@ -258,7 +266,7 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, } /** Show the history */ - lazy val historyCommand = new LoopCommand("history", "show the history (optional num is commands to show)") { + private lazy val historyCommand = new LoopCommand("history", "show the history (optional num is commands to show)") { override def usage = "[num]" def defaultLines = 20 @@ -279,21 +287,21 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, // When you know you are most likely breaking into the middle // of a line being typed. This softens the blow. - protected def echoAndRefresh(msg: String) = { + private[repl] def echoAndRefresh(msg: String) = { echo("\n" + msg) in.redrawLine() } - protected def echo(msg: String) = { + private[repl] def echo(msg: String) = { out println msg out.flush() } - protected def echoNoNL(msg: String) = { + private def echoNoNL(msg: String) = { out print msg out.flush() } /** Search the history */ - def searchHistory(_cmdline: String) { + private def searchHistory(_cmdline: String) { val cmdline = _cmdline.toLowerCase val offset = history.index - history.size + 1 @@ -302,14 +310,27 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, } private var currentPrompt = Properties.shellPromptString + + /** + * Sets the prompt string used by the REPL. + * + * @param prompt The new prompt string + */ + @DeveloperApi def setPrompt(prompt: String) = currentPrompt = prompt - /** Prompt to print when awaiting input */ + + /** + * Represents the current prompt string used by the REPL. + * + * @return The current prompt string + */ + @DeveloperApi def prompt = currentPrompt import LoopCommand.{ cmd, nullary } /** Standard commands */ - lazy val standardCommands = List( + private lazy val standardCommands = List( cmd("cp", "", "add a jar or directory to the classpath", addClasspath), cmd("help", "[command]", "print this summary or command-specific help", helpCommand), historyCommand, @@ -333,7 +354,7 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, ) /** Power user commands */ - lazy val powerCommands: List[LoopCommand] = List( + private lazy val powerCommands: List[LoopCommand] = List( // cmd("phase", "", "set the implicit phase for power commands", phaseCommand) ) @@ -459,7 +480,7 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, } } - protected def newJavap() = new JavapClass(addToolsJarToLoader(), new SparkIMain.ReplStrippingWriter(intp)) { + private def newJavap() = new JavapClass(addToolsJarToLoader(), new SparkIMain.ReplStrippingWriter(intp)) { override def tryClass(path: String): Array[Byte] = { val hd :: rest = path split '.' toList; // If there are dots in the name, the first segment is the @@ -581,7 +602,12 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, // } // } - /** Available commands */ + /** + * Provides a list of available commands. + * + * @return The list of commands + */ + @DeveloperApi def commands: List[LoopCommand] = standardCommands /*++ ( if (isReplPower) powerCommands else Nil )*/ @@ -613,7 +639,7 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, * command() for each line of input, and stops when * command() returns false. */ - def loop() { + private def loop() { def readOneLine() = { out.flush() in readLine prompt @@ -642,7 +668,7 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, } /** interpret all lines from a specified file */ - def interpretAllFrom(file: File) { + private def interpretAllFrom(file: File) { savingReader { savingReplayStack { file applyReader { reader => @@ -655,7 +681,7 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, } /** create a new interpreter and replay the given commands */ - def replay() { + private def replay() { reset() if (replayCommandStack.isEmpty) echo("Nothing to replay.") @@ -665,7 +691,7 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, echo("") } } - def resetCommand() { + private def resetCommand() { echo("Resetting repl state.") if (replayCommandStack.nonEmpty) { echo("Forgetting this session history:\n") @@ -681,13 +707,13 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, reset() } - def reset() { + private def reset() { intp.reset() // unleashAndSetPhase() } /** fork a shell and run a command */ - lazy val shCommand = new LoopCommand("sh", "run a shell command (result is implicitly => List[String])") { + private lazy val shCommand = new LoopCommand("sh", "run a shell command (result is implicitly => List[String])") { override def usage = "" def apply(line: String): Result = line match { case "" => showUsage() @@ -698,14 +724,14 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, } } - def withFile(filename: String)(action: File => Unit) { + private def withFile(filename: String)(action: File => Unit) { val f = File(filename) if (f.exists) action(f) else echo("That file does not exist") } - def loadCommand(arg: String) = { + private def loadCommand(arg: String) = { var shouldReplay: Option[String] = None withFile(arg)(f => { interpretAllFrom(f) @@ -714,7 +740,7 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, Result(true, shouldReplay) } - def addAllClasspath(args: Seq[String]): Unit = { + private def addAllClasspath(args: Seq[String]): Unit = { var added = false var totalClasspath = "" for (arg <- args) { @@ -729,7 +755,7 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, } } - def addClasspath(arg: String): Unit = { + private def addClasspath(arg: String): Unit = { val f = File(arg).normalize if (f.exists) { addedClasspath = ClassPath.join(addedClasspath, f.path) @@ -741,12 +767,12 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, } - def powerCmd(): Result = { + private def powerCmd(): Result = { if (isReplPower) "Already in power mode." else enablePowerMode(false) } - def enablePowerMode(isDuringInit: Boolean) = { + private[repl] def enablePowerMode(isDuringInit: Boolean) = { // replProps.power setValue true // unleashAndSetPhase() // asyncEcho(isDuringInit, power.banner) @@ -759,12 +785,12 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, // } // } - def asyncEcho(async: Boolean, msg: => String) { + private def asyncEcho(async: Boolean, msg: => String) { if (async) asyncMessage(msg) else echo(msg) } - def verbosity() = { + private def verbosity() = { // val old = intp.printResults // intp.printResults = !old // echo("Switched " + (if (old) "off" else "on") + " result printing.") @@ -773,7 +799,7 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, /** Run one command submitted by the user. Two values are returned: * (1) whether to keep running, (2) the line to record for replay, * if any. */ - def command(line: String): Result = { + private[repl] def command(line: String): Result = { if (line startsWith ":") { val cmd = line.tail takeWhile (x => !x.isWhitespace) uniqueCommand(cmd) match { @@ -789,7 +815,7 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, Iterator continually in.readLine("") takeWhile (x => x != null && cond(x)) } - def pasteCommand(): Result = { + private def pasteCommand(): Result = { echo("// Entering paste mode (ctrl-D to finish)\n") val code = readWhile(_ => true) mkString "\n" echo("\n// Exiting paste mode, now interpreting.\n") @@ -820,7 +846,7 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, * read, go ahead and interpret it. Return the full string * to be recorded for replay, if any. */ - def interpretStartingWith(code: String): Option[String] = { + private def interpretStartingWith(code: String): Option[String] = { // signal completion non-completion input has been received in.completion.resetVerbosity() @@ -874,7 +900,7 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, } // runs :load `file` on any files passed via -i - def loadFiles(settings: Settings) = settings match { + private def loadFiles(settings: Settings) = settings match { case settings: SparkRunnerSettings => for (filename <- settings.loadfiles.value) { val cmd = ":load " + filename @@ -889,7 +915,7 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, * unless settings or properties are such that it should start * with SimpleReader. */ - def chooseReader(settings: Settings): InteractiveReader = { + private def chooseReader(settings: Settings): InteractiveReader = { if (settings.Xnojline.value || Properties.isEmacsShell) SimpleReader() else try new SparkJLineReader( @@ -903,8 +929,8 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, } } - val u: scala.reflect.runtime.universe.type = scala.reflect.runtime.universe - val m = u.runtimeMirror(Utils.getSparkClassLoader) + private val u: scala.reflect.runtime.universe.type = scala.reflect.runtime.universe + private val m = u.runtimeMirror(Utils.getSparkClassLoader) private def tagOfStaticClass[T: ClassTag]: u.TypeTag[T] = u.TypeTag[T]( m, @@ -913,7 +939,7 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, m.staticClass(classTag[T].runtimeClass.getName).toTypeConstructor.asInstanceOf[U # Type] }) - def process(settings: Settings): Boolean = savingContextLoader { + private def process(settings: Settings): Boolean = savingContextLoader { if (getMaster() == "yarn-client") System.setProperty("SPARK_YARN_MODE", "true") this.settings = settings @@ -972,6 +998,8 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, true } + // NOTE: Must be public for visibility + @DeveloperApi def createSparkContext(): SparkContext = { val execUri = System.getenv("SPARK_EXECUTOR_URI") val jars = SparkILoop.getAddedJars @@ -979,7 +1007,7 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, .setMaster(getMaster()) .setAppName("Spark shell") .setJars(jars) - .set("spark.repl.class.uri", intp.classServer.uri) + .set("spark.repl.class.uri", intp.classServerUri) if (execUri != null) { conf.set("spark.executor.uri", execUri) } @@ -1014,7 +1042,7 @@ class SparkILoop(in0: Option[BufferedReader], protected val out: JPrintWriter, } @deprecated("Use `process` instead", "2.9.0") - def main(settings: Settings): Unit = process(settings) + private def main(settings: Settings): Unit = process(settings) } object SparkILoop { @@ -1033,7 +1061,7 @@ object SparkILoop { // Designed primarily for use by test code: take a String with a // bunch of code, and prints out a transcript of what it would look // like if you'd just typed it into the repl. - def runForTranscript(code: String, settings: Settings): String = { + private[repl] def runForTranscript(code: String, settings: Settings): String = { import java.io.{ BufferedReader, StringReader, OutputStreamWriter } stringFromStream { ostream => @@ -1071,7 +1099,7 @@ object SparkILoop { /** Creates an interpreter loop with default settings and feeds * the given code to it as input. */ - def run(code: String, sets: Settings = new Settings): String = { + private[repl] def run(code: String, sets: Settings = new Settings): String = { import java.io.{ BufferedReader, StringReader, OutputStreamWriter } stringFromStream { ostream => @@ -1087,5 +1115,5 @@ object SparkILoop { } } } - def run(lines: List[String]): String = run(lines map (_ + "\n") mkString) + private[repl] def run(lines: List[String]): String = run(lines map (_ + "\n") mkString) } diff --git a/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkILoopInit.scala b/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkILoopInit.scala index da4286c5e4874..99bd777c04fdb 100644 --- a/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkILoopInit.scala +++ b/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkILoopInit.scala @@ -19,7 +19,7 @@ import org.apache.spark.SPARK_VERSION /** * Machinery for the asynchronous initialization of the repl. */ -trait SparkILoopInit { +private[repl] trait SparkILoopInit { self: SparkILoop => /** Print a welcome message */ diff --git a/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkIMain.scala b/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkIMain.scala index b646f0b6f0868..35fb625645022 100644 --- a/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkIMain.scala +++ b/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkIMain.scala @@ -39,6 +39,7 @@ import scala.util.control.ControlThrowable import org.apache.spark.{Logging, HttpServer, SecurityManager, SparkConf} import org.apache.spark.util.Utils +import org.apache.spark.annotation.DeveloperApi // /** directory to save .class files to */ // private class ReplVirtualDirectory(out: JPrintWriter) extends VirtualDirectory("((memory))", None) { @@ -84,17 +85,18 @@ import org.apache.spark.util.Utils * @author Moez A. Abdel-Gawad * @author Lex Spoon */ + @DeveloperApi class SparkIMain( initialSettings: Settings, val out: JPrintWriter, propagateExceptions: Boolean = false) extends SparkImports with Logging { imain => - val conf = new SparkConf() + private val conf = new SparkConf() - val SPARK_DEBUG_REPL: Boolean = (System.getenv("SPARK_DEBUG_REPL") == "1") + private val SPARK_DEBUG_REPL: Boolean = (System.getenv("SPARK_DEBUG_REPL") == "1") /** Local directory to save .class files too */ - lazy val outputDir = { + private lazy val outputDir = { val tmp = System.getProperty("java.io.tmpdir") val rootDir = conf.get("spark.repl.classdir", tmp) Utils.createTempDir(rootDir) @@ -103,13 +105,20 @@ import org.apache.spark.util.Utils echo("Output directory: " + outputDir) } - val virtualDirectory = new PlainFile(outputDir) // "directory" for classfiles + /** + * Returns the path to the output directory containing all generated + * class files that will be served by the REPL class server. + */ + @DeveloperApi + lazy val getClassOutputDirectory = outputDir + + private val virtualDirectory = new PlainFile(outputDir) // "directory" for classfiles /** Jetty server that will serve our classes to worker nodes */ - val classServerPort = conf.getInt("spark.replClassServer.port", 0) - val classServer = new HttpServer(conf, outputDir, new SecurityManager(conf), classServerPort, "HTTP class server") + private val classServerPort = conf.getInt("spark.replClassServer.port", 0) + private val classServer = new HttpServer(conf, outputDir, new SecurityManager(conf), classServerPort, "HTTP class server") private var currentSettings: Settings = initialSettings - var printResults = true // whether to print result lines - var totalSilence = false // whether to print anything + private var printResults = true // whether to print result lines + private var totalSilence = false // whether to print anything private var _initializeComplete = false // compiler is initialized private var _isInitialized: Future[Boolean] = null // set up initialization future private var bindExceptions = true // whether to bind the lastException variable @@ -123,6 +132,14 @@ import org.apache.spark.util.Utils echo("Class server started, URI = " + classServer.uri) } + /** + * URI of the class server used to feed REPL compiled classes. + * + * @return The string representing the class server uri + */ + @DeveloperApi + def classServerUri = classServer.uri + /** We're going to go to some trouble to initialize the compiler asynchronously. * It's critical that nothing call into it until it's been initialized or we will * run into unrecoverable issues, but the perceived repl startup time goes @@ -141,17 +158,18 @@ import org.apache.spark.util.Utils () => { counter += 1 ; counter } } - def compilerClasspath: Seq[URL] = ( + private def compilerClasspath: Seq[URL] = ( if (isInitializeComplete) global.classPath.asURLs else new PathResolver(settings).result.asURLs // the compiler's classpath ) - def settings = currentSettings - def mostRecentLine = prevRequestList match { + // NOTE: Exposed to repl package since accessed indirectly from SparkIMain + private[repl] def settings = currentSettings + private def mostRecentLine = prevRequestList match { case Nil => "" case req :: _ => req.originalLine } // Run the code body with the given boolean settings flipped to true. - def withoutWarnings[T](body: => T): T = beQuietDuring { + private def withoutWarnings[T](body: => T): T = beQuietDuring { val saved = settings.nowarn.value if (!saved) settings.nowarn.value = true @@ -164,16 +182,28 @@ import org.apache.spark.util.Utils def this(settings: Settings) = this(settings, new NewLinePrintWriter(new ConsoleWriter, true)) def this() = this(new Settings()) - lazy val repllog: Logger = new Logger { + private lazy val repllog: Logger = new Logger { val out: JPrintWriter = imain.out val isInfo: Boolean = BooleanProp keyExists "scala.repl.info" val isDebug: Boolean = BooleanProp keyExists "scala.repl.debug" val isTrace: Boolean = BooleanProp keyExists "scala.repl.trace" } - lazy val formatting: Formatting = new Formatting { + private[repl] lazy val formatting: Formatting = new Formatting { val prompt = Properties.shellPromptString } - lazy val reporter: ConsoleReporter = new SparkIMain.ReplReporter(this) + + // NOTE: Exposed to repl package since used by SparkExprTyper and SparkILoop + private[repl] lazy val reporter: ConsoleReporter = new SparkIMain.ReplReporter(this) + + /** + * Determines if errors were reported (typically during compilation). + * + * @note This is not for runtime errors + * + * @return True if had errors, otherwise false + */ + @DeveloperApi + def isReportingErrors = reporter.hasErrors import formatting._ import reporter.{ printMessage, withoutTruncating } @@ -193,7 +223,8 @@ import org.apache.spark.util.Utils private def tquoted(s: String) = "\"\"\"" + s + "\"\"\"" // argument is a thunk to execute after init is done - def initialize(postInitSignal: => Unit) { + // NOTE: Exposed to repl package since used by SparkILoop + private[repl] def initialize(postInitSignal: => Unit) { synchronized { if (_isInitialized == null) { _isInitialized = io.spawn { @@ -203,15 +234,27 @@ import org.apache.spark.util.Utils } } } + + /** + * Initializes the underlying compiler/interpreter in a blocking fashion. + * + * @note Must be executed before using SparkIMain! + */ + @DeveloperApi def initializeSynchronous(): Unit = { if (!isInitializeComplete) { _initialize() assert(global != null, global) } } - def isInitializeComplete = _initializeComplete + private def isInitializeComplete = _initializeComplete /** the public, go through the future compiler */ + + /** + * The underlying compiler used to generate ASTs and execute code. + */ + @DeveloperApi lazy val global: Global = { if (isInitializeComplete) _compiler else { @@ -226,13 +269,13 @@ import org.apache.spark.util.Utils } } @deprecated("Use `global` for access to the compiler instance.", "2.9.0") - lazy val compiler: global.type = global + private lazy val compiler: global.type = global import global._ import definitions.{ScalaPackage, JavaLangPackage, termMember, typeMember} import rootMirror.{RootClass, getClassIfDefined, getModuleIfDefined, getRequiredModule, getRequiredClass} - implicit class ReplTypeOps(tp: Type) { + private implicit class ReplTypeOps(tp: Type) { def orElse(other: => Type): Type = if (tp ne NoType) tp else other def andAlso(fn: Type => Type): Type = if (tp eq NoType) tp else fn(tp) } @@ -240,7 +283,8 @@ import org.apache.spark.util.Utils // TODO: If we try to make naming a lazy val, we run into big time // scalac unhappiness with what look like cycles. It has not been easy to // reduce, but name resolution clearly takes different paths. - object naming extends { + // NOTE: Exposed to repl package since used by SparkExprTyper + private[repl] object naming extends { val global: imain.global.type = imain.global } with Naming { // make sure we don't overwrite their unwisely named res3 etc. @@ -254,22 +298,43 @@ import org.apache.spark.util.Utils } import naming._ - object deconstruct extends { + // NOTE: Exposed to repl package since used by SparkILoop + private[repl] object deconstruct extends { val global: imain.global.type = imain.global } with StructuredTypeStrings - lazy val memberHandlers = new { + // NOTE: Exposed to repl package since used by SparkImports + private[repl] lazy val memberHandlers = new { val intp: imain.type = imain } with SparkMemberHandlers import memberHandlers._ - /** Temporarily be quiet */ + /** + * Suppresses overwriting print results during the operation. + * + * @param body The block to execute + * @tparam T The return type of the block + * + * @return The result from executing the block + */ + @DeveloperApi def beQuietDuring[T](body: => T): T = { val saved = printResults printResults = false try body finally printResults = saved } + + /** + * Completely masks all output during the operation (minus JVM standard + * out and error). + * + * @param operation The block to execute + * @tparam T The return type of the block + * + * @return The result from executing the block + */ + @DeveloperApi def beSilentDuring[T](operation: => T): T = { val saved = totalSilence totalSilence = true @@ -277,10 +342,10 @@ import org.apache.spark.util.Utils finally totalSilence = saved } - def quietRun[T](code: String) = beQuietDuring(interpret(code)) + // NOTE: Exposed to repl package since used by SparkILoop + private[repl] def quietRun[T](code: String) = beQuietDuring(interpret(code)) - - private def logAndDiscard[T](label: String, alt: => T): PartialFunction[Throwable, T] = { + private def logAndDiscard[T](label: String, alt: => T): PartialFunction[Throwable, T] = { case t: ControlThrowable => throw t case t: Throwable => logDebug(label + ": " + unwrap(t)) @@ -298,14 +363,44 @@ import org.apache.spark.util.Utils finally bindExceptions = true } + /** + * Contains the code (in string form) representing a wrapper around all + * code executed by this instance. + * + * @return The wrapper code as a string + */ + @DeveloperApi def executionWrapper = _executionWrapper + + /** + * Sets the code to use as a wrapper around all code executed by this + * instance. + * + * @param code The wrapper code as a string + */ + @DeveloperApi def setExecutionWrapper(code: String) = _executionWrapper = code + + /** + * Clears the code used as a wrapper around all code executed by + * this instance. + */ + @DeveloperApi def clearExecutionWrapper() = _executionWrapper = "" /** interpreter settings */ - lazy val isettings = new SparkISettings(this) + private lazy val isettings = new SparkISettings(this) - /** Instantiate a compiler. Overridable. */ + /** + * Instantiates a new compiler used by SparkIMain. Overridable to provide + * own instance of a compiler. + * + * @param settings The settings to provide the compiler + * @param reporter The reporter to use for compiler output + * + * @return The compiler as a Global + */ + @DeveloperApi protected def newCompiler(settings: Settings, reporter: Reporter): ReplGlobal = { settings.outputDirs setSingleOutput virtualDirectory settings.exposeEmptyPackage.value = true @@ -320,13 +415,14 @@ import org.apache.spark.util.Utils * @note Currently only supports jars, not directories * @param urls The list of items to add to the compile and runtime classpaths */ + @DeveloperApi def addUrlsToClassPath(urls: URL*): Unit = { new Run // Needed to force initialization of "something" to correctly load Scala classes from jars urls.foreach(_runtimeClassLoader.addNewUrl) // Add jars/classes to runtime for execution updateCompilerClassPath(urls: _*) // Add jars/classes to compile time for compiling } - protected def updateCompilerClassPath(urls: URL*): Unit = { + private def updateCompilerClassPath(urls: URL*): Unit = { require(!global.forMSIL) // Only support JavaPlatform val platform = global.platform.asInstanceOf[JavaPlatform] @@ -342,7 +438,7 @@ import org.apache.spark.util.Utils global.invalidateClassPathEntries(urls.map(_.getPath): _*) } - protected def mergeUrlsIntoClassPath(platform: JavaPlatform, urls: URL*): MergedClassPath[AbstractFile] = { + private def mergeUrlsIntoClassPath(platform: JavaPlatform, urls: URL*): MergedClassPath[AbstractFile] = { // Collect our new jars/directories and add them to the existing set of classpaths val allClassPaths = ( platform.classPath.asInstanceOf[MergedClassPath[AbstractFile]].entries ++ @@ -365,7 +461,13 @@ import org.apache.spark.util.Utils new MergedClassPath(allClassPaths, platform.classPath.context) } - /** Parent classloader. Overridable. */ + /** + * Represents the parent classloader used by this instance. Can be + * overridden to provide alternative classloader. + * + * @return The classloader used as the parent loader of this instance + */ + @DeveloperApi protected def parentClassLoader: ClassLoader = SparkHelper.explicitParentLoader(settings).getOrElse( this.getClass.getClassLoader() ) @@ -382,16 +484,18 @@ import org.apache.spark.util.Utils shadow the old ones, and old code objects refer to the old definitions. */ - def resetClassLoader() = { + private def resetClassLoader() = { logDebug("Setting new classloader: was " + _classLoader) _classLoader = null ensureClassLoader() } - final def ensureClassLoader() { + private final def ensureClassLoader() { if (_classLoader == null) _classLoader = makeClassLoader() } - def classLoader: AbstractFileClassLoader = { + + // NOTE: Exposed to repl package since used by SparkILoop + private[repl] def classLoader: AbstractFileClassLoader = { ensureClassLoader() _classLoader } @@ -418,27 +522,58 @@ import org.apache.spark.util.Utils _runtimeClassLoader }) - def getInterpreterClassLoader() = classLoader + private def getInterpreterClassLoader() = classLoader // Set the current Java "context" class loader to this interpreter's class loader - def setContextClassLoader() = classLoader.setAsContext() + // NOTE: Exposed to repl package since used by SparkILoopInit + private[repl] def setContextClassLoader() = classLoader.setAsContext() - /** Given a simple repl-defined name, returns the real name of - * the class representing it, e.g. for "Bippy" it may return - * {{{ - * $line19.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$Bippy - * }}} + /** + * Returns the real name of a class based on its repl-defined name. + * + * ==Example== + * Given a simple repl-defined name, returns the real name of + * the class representing it, e.g. for "Bippy" it may return + * {{{ + * $line19.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$Bippy + * }}} + * + * @param simpleName The repl-defined name whose real name to retrieve + * + * @return Some real name if the simple name exists, else None */ + @DeveloperApi def generatedName(simpleName: String): Option[String] = { if (simpleName endsWith nme.MODULE_SUFFIX_STRING) optFlatName(simpleName.init) map (_ + nme.MODULE_SUFFIX_STRING) else optFlatName(simpleName) } - def flatName(id: String) = optFlatName(id) getOrElse id - def optFlatName(id: String) = requestForIdent(id) map (_ fullFlatName id) + // NOTE: Exposed to repl package since used by SparkILoop + private[repl] def flatName(id: String) = optFlatName(id) getOrElse id + // NOTE: Exposed to repl package since used by SparkILoop + private[repl] def optFlatName(id: String) = requestForIdent(id) map (_ fullFlatName id) + + /** + * Retrieves all simple names contained in the current instance. + * + * @return A list of sorted names + */ + @DeveloperApi def allDefinedNames = definedNameMap.keys.toList.sorted - def pathToType(id: String): String = pathToName(newTypeName(id)) - def pathToTerm(id: String): String = pathToName(newTermName(id)) + + private def pathToType(id: String): String = pathToName(newTypeName(id)) + // NOTE: Exposed to repl package since used by SparkILoop + private[repl] def pathToTerm(id: String): String = pathToName(newTermName(id)) + + /** + * Retrieves the full code path to access the specified simple name + * content. + * + * @param name The simple name of the target whose path to determine + * + * @return The full path used to access the specified target (name) + */ + @DeveloperApi def pathToName(name: Name): String = { if (definedNameMap contains name) definedNameMap(name) fullPath name @@ -457,13 +592,13 @@ import org.apache.spark.util.Utils } /** Stubs for work in progress. */ - def handleTypeRedefinition(name: TypeName, old: Request, req: Request) = { + private def handleTypeRedefinition(name: TypeName, old: Request, req: Request) = { for (t1 <- old.simpleNameOfType(name) ; t2 <- req.simpleNameOfType(name)) { logDebug("Redefining type '%s'\n %s -> %s".format(name, t1, t2)) } } - def handleTermRedefinition(name: TermName, old: Request, req: Request) = { + private def handleTermRedefinition(name: TermName, old: Request, req: Request) = { for (t1 <- old.compilerTypeOf get name ; t2 <- req.compilerTypeOf get name) { // Printing the types here has a tendency to cause assertion errors, like // assertion failed: fatal: has owner value x, but a class owner is required @@ -473,7 +608,7 @@ import org.apache.spark.util.Utils } } - def recordRequest(req: Request) { + private def recordRequest(req: Request) { if (req == null || referencedNameMap == null) return @@ -504,12 +639,12 @@ import org.apache.spark.util.Utils } } - def replwarn(msg: => String) { + private def replwarn(msg: => String) { if (!settings.nowarnings.value) printMessage(msg) } - def isParseable(line: String): Boolean = { + private def isParseable(line: String): Boolean = { beSilentDuring { try parse(line) match { case Some(xs) => xs.nonEmpty // parses as-is @@ -522,22 +657,32 @@ import org.apache.spark.util.Utils } } - def compileSourcesKeepingRun(sources: SourceFile*) = { + private def compileSourcesKeepingRun(sources: SourceFile*) = { val run = new Run() reporter.reset() run compileSources sources.toList (!reporter.hasErrors, run) } - /** Compile an nsc SourceFile. Returns true if there are - * no compilation errors, or false otherwise. + /** + * Compiles specified source files. + * + * @param sources The sequence of source files to compile + * + * @return True if successful, otherwise false */ + @DeveloperApi def compileSources(sources: SourceFile*): Boolean = compileSourcesKeepingRun(sources: _*)._1 - /** Compile a string. Returns true if there are no - * compilation errors, or false otherwise. + /** + * Compiles a string of code. + * + * @param code The string of code to compile + * + * @return True if successful, otherwise false */ + @DeveloperApi def compileString(code: String): Boolean = compileSources(new BatchSourceFile("
    Property NameDefaultMeaning
    spark.yarn.am.memory512m + Amount of memory to use for the YARN Application Master in client mode, in the same format as JVM memory strings (e.g. 512m, 2g). + In cluster mode, use spark.driver.memory instead. +
    spark.yarn.am.waitTime 100000spark.yarn.driver.memoryOverhead driverMemory * 0.07, with minimum of 384 - The amount of off heap memory (in megabytes) to be allocated per driver. This is memory that accounts for things like VM overheads, interned strings, other native overheads, etc. This tends to grow with the container size (typically 6-10%). + The amount of off heap memory (in megabytes) to be allocated per driver in cluster mode. This is memory that accounts for things like VM overheads, interned strings, other native overheads, etc. This tends to grow with the container size (typically 6-10%). +
    spark.yarn.am.memoryOverheadAM memory * 0.07, with minimum of 384 + Same as spark.yarn.driver.memoryOverhead, but for the Application Master in client mode.
    spark.yarn.am.extraJavaOptions (none) - A string of extra JVM options to pass to the Yarn ApplicationMaster in client mode. + A string of extra JVM options to pass to the YARN Application Master in client mode. In cluster mode, use spark.driver.extraJavaOptions instead.
    spark.storage.memoryMapThreshold81922097152 Size of a block, in bytes, above which Spark memory maps when reading a block from disk. This prevents Spark from memory mapping very small blocks. In general, memory From 6942b974adad396cba2799eac1fa90448cea4da7 Mon Sep 17 00:00:00 2001 From: zsxwing Date: Sun, 11 Jan 2015 16:23:28 -0800 Subject: [PATCH 228/320] [SPARK-4951][Core] Fix the issue that a busy executor may be killed A few changes to fix this issue: 1. Handle the case that receiving `SparkListenerTaskStart` before `SparkListenerBlockManagerAdded`. 2. Don't add `executorId` to `removeTimes` when the executor is busy. 3. Use `HashMap.retain` to safely traverse the HashMap and remove items. 4. Use the same lock in ExecutorAllocationManager and ExecutorAllocationListener to fix the race condition in `totalPendingTasks`. 5. Move the blocking codes out of the message processing code in YarnSchedulerActor. Author: zsxwing Closes #3783 from zsxwing/SPARK-4951 and squashes the following commits: d51fa0d [zsxwing] Add comments 2e365ce [zsxwing] Remove expired executors from 'removeTimes' and add idle executors back when a new executor joins 49f61a9 [zsxwing] Eliminate duplicate executor registered warnings d4c4e9a [zsxwing] Minor fixes for the code style 05f6238 [zsxwing] Move the blocking codes out of the message processing code 105ba3a [zsxwing] Fix the race condition in totalPendingTasks d5c615d [zsxwing] Fix the issue that a busy executor may be killed --- .../spark/ExecutorAllocationManager.scala | 117 ++++++++++++------ .../cluster/YarnSchedulerBackend.scala | 23 +++- .../ExecutorAllocationManagerSuite.scala | 49 +++++++- 3 files changed, 144 insertions(+), 45 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala b/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala index e9e90e3f2f65a..a0ee2a7cbb2a2 100644 --- a/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala +++ b/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala @@ -65,6 +65,9 @@ private[spark] class ExecutorAllocationManager( listenerBus: LiveListenerBus, conf: SparkConf) extends Logging { + + allocationManager => + import ExecutorAllocationManager._ // Lower and upper bounds on the number of executors. These are required. @@ -121,7 +124,7 @@ private[spark] class ExecutorAllocationManager( private var clock: Clock = new RealClock // Listener for Spark events that impact the allocation policy - private val listener = new ExecutorAllocationListener(this) + private val listener = new ExecutorAllocationListener /** * Verify that the settings specified through the config are valid. @@ -209,11 +212,12 @@ private[spark] class ExecutorAllocationManager( addTime += sustainedSchedulerBacklogTimeout * 1000 } - removeTimes.foreach { case (executorId, expireTime) => - if (now >= expireTime) { + removeTimes.retain { case (executorId, expireTime) => + val expired = now >= expireTime + if (expired) { removeExecutor(executorId) - removeTimes.remove(executorId) } + !expired } } @@ -291,7 +295,7 @@ private[spark] class ExecutorAllocationManager( // Do not kill the executor if we have already reached the lower bound val numExistingExecutors = executorIds.size - executorsPendingToRemove.size if (numExistingExecutors - 1 < minNumExecutors) { - logInfo(s"Not removing idle executor $executorId because there are only " + + logDebug(s"Not removing idle executor $executorId because there are only " + s"$numExistingExecutors executor(s) left (limit $minNumExecutors)") return false } @@ -315,7 +319,11 @@ private[spark] class ExecutorAllocationManager( private def onExecutorAdded(executorId: String): Unit = synchronized { if (!executorIds.contains(executorId)) { executorIds.add(executorId) - executorIds.foreach(onExecutorIdle) + // If an executor (call this executor X) is not removed because the lower bound + // has been reached, it will no longer be marked as idle. When new executors join, + // however, we are no longer at the lower bound, and so we must mark executor X + // as idle again so as not to forget that it is a candidate for removal. (see SPARK-4951) + executorIds.filter(listener.isExecutorIdle).foreach(onExecutorIdle) logInfo(s"New executor $executorId has registered (new total is ${executorIds.size})") if (numExecutorsPending > 0) { numExecutorsPending -= 1 @@ -373,10 +381,14 @@ private[spark] class ExecutorAllocationManager( * the executor is not already marked as idle. */ private def onExecutorIdle(executorId: String): Unit = synchronized { - if (!removeTimes.contains(executorId) && !executorsPendingToRemove.contains(executorId)) { - logDebug(s"Starting idle timer for $executorId because there are no more tasks " + - s"scheduled to run on the executor (to expire in $executorIdleTimeout seconds)") - removeTimes(executorId) = clock.getTimeMillis + executorIdleTimeout * 1000 + if (executorIds.contains(executorId)) { + if (!removeTimes.contains(executorId) && !executorsPendingToRemove.contains(executorId)) { + logDebug(s"Starting idle timer for $executorId because there are no more tasks " + + s"scheduled to run on the executor (to expire in $executorIdleTimeout seconds)") + removeTimes(executorId) = clock.getTimeMillis + executorIdleTimeout * 1000 + } + } else { + logWarning(s"Attempted to mark unknown executor $executorId idle") } } @@ -396,25 +408,24 @@ private[spark] class ExecutorAllocationManager( * and consistency of events returned by the listener. For simplicity, it does not account * for speculated tasks. */ - private class ExecutorAllocationListener(allocationManager: ExecutorAllocationManager) - extends SparkListener { + private class ExecutorAllocationListener extends SparkListener { private val stageIdToNumTasks = new mutable.HashMap[Int, Int] private val stageIdToTaskIndices = new mutable.HashMap[Int, mutable.HashSet[Int]] private val executorIdToTaskIds = new mutable.HashMap[String, mutable.HashSet[Long]] override def onStageSubmitted(stageSubmitted: SparkListenerStageSubmitted): Unit = { - synchronized { - val stageId = stageSubmitted.stageInfo.stageId - val numTasks = stageSubmitted.stageInfo.numTasks + val stageId = stageSubmitted.stageInfo.stageId + val numTasks = stageSubmitted.stageInfo.numTasks + allocationManager.synchronized { stageIdToNumTasks(stageId) = numTasks allocationManager.onSchedulerBacklogged() } } override def onStageCompleted(stageCompleted: SparkListenerStageCompleted): Unit = { - synchronized { - val stageId = stageCompleted.stageInfo.stageId + val stageId = stageCompleted.stageInfo.stageId + allocationManager.synchronized { stageIdToNumTasks -= stageId stageIdToTaskIndices -= stageId @@ -426,39 +437,49 @@ private[spark] class ExecutorAllocationManager( } } - override def onTaskStart(taskStart: SparkListenerTaskStart): Unit = synchronized { + override def onTaskStart(taskStart: SparkListenerTaskStart): Unit = { val stageId = taskStart.stageId val taskId = taskStart.taskInfo.taskId val taskIndex = taskStart.taskInfo.index val executorId = taskStart.taskInfo.executorId - // If this is the last pending task, mark the scheduler queue as empty - stageIdToTaskIndices.getOrElseUpdate(stageId, new mutable.HashSet[Int]) += taskIndex - val numTasksScheduled = stageIdToTaskIndices(stageId).size - val numTasksTotal = stageIdToNumTasks.getOrElse(stageId, -1) - if (numTasksScheduled == numTasksTotal) { - // No more pending tasks for this stage - stageIdToNumTasks -= stageId - if (stageIdToNumTasks.isEmpty) { - allocationManager.onSchedulerQueueEmpty() + allocationManager.synchronized { + // This guards against the race condition in which the `SparkListenerTaskStart` + // event is posted before the `SparkListenerBlockManagerAdded` event, which is + // possible because these events are posted in different threads. (see SPARK-4951) + if (!allocationManager.executorIds.contains(executorId)) { + allocationManager.onExecutorAdded(executorId) + } + + // If this is the last pending task, mark the scheduler queue as empty + stageIdToTaskIndices.getOrElseUpdate(stageId, new mutable.HashSet[Int]) += taskIndex + val numTasksScheduled = stageIdToTaskIndices(stageId).size + val numTasksTotal = stageIdToNumTasks.getOrElse(stageId, -1) + if (numTasksScheduled == numTasksTotal) { + // No more pending tasks for this stage + stageIdToNumTasks -= stageId + if (stageIdToNumTasks.isEmpty) { + allocationManager.onSchedulerQueueEmpty() + } } - } - // Mark the executor on which this task is scheduled as busy - executorIdToTaskIds.getOrElseUpdate(executorId, new mutable.HashSet[Long]) += taskId - allocationManager.onExecutorBusy(executorId) + // Mark the executor on which this task is scheduled as busy + executorIdToTaskIds.getOrElseUpdate(executorId, new mutable.HashSet[Long]) += taskId + allocationManager.onExecutorBusy(executorId) + } } - override def onTaskEnd(taskEnd: SparkListenerTaskEnd): Unit = synchronized { + override def onTaskEnd(taskEnd: SparkListenerTaskEnd): Unit = { val executorId = taskEnd.taskInfo.executorId val taskId = taskEnd.taskInfo.taskId - - // If the executor is no longer running scheduled any tasks, mark it as idle - if (executorIdToTaskIds.contains(executorId)) { - executorIdToTaskIds(executorId) -= taskId - if (executorIdToTaskIds(executorId).isEmpty) { - executorIdToTaskIds -= executorId - allocationManager.onExecutorIdle(executorId) + allocationManager.synchronized { + // If the executor is no longer running scheduled any tasks, mark it as idle + if (executorIdToTaskIds.contains(executorId)) { + executorIdToTaskIds(executorId) -= taskId + if (executorIdToTaskIds(executorId).isEmpty) { + executorIdToTaskIds -= executorId + allocationManager.onExecutorIdle(executorId) + } } } } @@ -466,7 +487,12 @@ private[spark] class ExecutorAllocationManager( override def onBlockManagerAdded(blockManagerAdded: SparkListenerBlockManagerAdded): Unit = { val executorId = blockManagerAdded.blockManagerId.executorId if (executorId != SparkContext.DRIVER_IDENTIFIER) { - allocationManager.onExecutorAdded(executorId) + // This guards against the race condition in which the `SparkListenerTaskStart` + // event is posted before the `SparkListenerBlockManagerAdded` event, which is + // possible because these events are posted in different threads. (see SPARK-4951) + if (!allocationManager.executorIds.contains(executorId)) { + allocationManager.onExecutorAdded(executorId) + } } } @@ -478,12 +504,23 @@ private[spark] class ExecutorAllocationManager( /** * An estimate of the total number of pending tasks remaining for currently running stages. Does * not account for tasks which may have failed and been resubmitted. + * + * Note: This is not thread-safe without the caller owning the `allocationManager` lock. */ def totalPendingTasks(): Int = { stageIdToNumTasks.map { case (stageId, numTasks) => numTasks - stageIdToTaskIndices.get(stageId).map(_.size).getOrElse(0) }.sum } + + /** + * Return true if an executor is not currently running a task, and false otherwise. + * + * Note: This is not thread-safe without the caller owning the `allocationManager` lock. + */ + def isExecutorIdle(executorId: String): Boolean = { + !executorIdToTaskIds.contains(executorId) + } } } diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/YarnSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/YarnSchedulerBackend.scala index 50721b9d6cd6c..f14aaeea0a25c 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/cluster/YarnSchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/YarnSchedulerBackend.scala @@ -17,6 +17,8 @@ package org.apache.spark.scheduler.cluster +import scala.concurrent.{Future, ExecutionContext} + import akka.actor.{Actor, ActorRef, Props} import akka.remote.{DisassociatedEvent, RemotingLifecycleEvent} @@ -24,7 +26,9 @@ import org.apache.spark.SparkContext import org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages._ import org.apache.spark.scheduler.TaskSchedulerImpl import org.apache.spark.ui.JettyUtils -import org.apache.spark.util.AkkaUtils +import org.apache.spark.util.{AkkaUtils, Utils} + +import scala.util.control.NonFatal /** * Abstract Yarn scheduler backend that contains common logic @@ -97,6 +101,9 @@ private[spark] abstract class YarnSchedulerBackend( private class YarnSchedulerActor extends Actor { private var amActor: Option[ActorRef] = None + implicit val askAmActorExecutor = ExecutionContext.fromExecutor( + Utils.newDaemonCachedThreadPool("yarn-scheduler-ask-am-executor")) + override def preStart(): Unit = { // Listen for disassociation events context.system.eventStream.subscribe(self, classOf[RemotingLifecycleEvent]) @@ -110,7 +117,12 @@ private[spark] abstract class YarnSchedulerBackend( case r: RequestExecutors => amActor match { case Some(actor) => - sender ! AkkaUtils.askWithReply[Boolean](r, actor, askTimeout) + val driverActor = sender + Future { + driverActor ! AkkaUtils.askWithReply[Boolean](r, actor, askTimeout) + } onFailure { + case NonFatal(e) => logError(s"Sending $r to AM was unsuccessful", e) + } case None => logWarning("Attempted to request executors before the AM has registered!") sender ! false @@ -119,7 +131,12 @@ private[spark] abstract class YarnSchedulerBackend( case k: KillExecutors => amActor match { case Some(actor) => - sender ! AkkaUtils.askWithReply[Boolean](k, actor, askTimeout) + val driverActor = sender + Future { + driverActor ! AkkaUtils.askWithReply[Boolean](k, actor, askTimeout) + } onFailure { + case NonFatal(e) => logError(s"Sending $k to AM was unsuccessful", e) + } case None => logWarning("Attempted to kill executors before the AM has registered!") sender ! false diff --git a/core/src/test/scala/org/apache/spark/ExecutorAllocationManagerSuite.scala b/core/src/test/scala/org/apache/spark/ExecutorAllocationManagerSuite.scala index c817f6dcede75..0e4df17c1bf87 100644 --- a/core/src/test/scala/org/apache/spark/ExecutorAllocationManagerSuite.scala +++ b/core/src/test/scala/org/apache/spark/ExecutorAllocationManagerSuite.scala @@ -17,6 +17,8 @@ package org.apache.spark +import scala.collection.mutable + import org.scalatest.{FunSuite, PrivateMethodTester} import org.apache.spark.executor.TaskMetrics import org.apache.spark.scheduler._ @@ -143,11 +145,17 @@ class ExecutorAllocationManagerSuite extends FunSuite with LocalSparkContext { // Verify that running a task reduces the cap sc.listenerBus.postToAll(SparkListenerStageSubmitted(createStageInfo(1, 3))) + sc.listenerBus.postToAll(SparkListenerBlockManagerAdded( + 0L, BlockManagerId("executor-1", "host1", 1), 100L)) sc.listenerBus.postToAll(SparkListenerTaskStart(1, 0, createTaskInfo(0, 0, "executor-1"))) + assert(numExecutorsPending(manager) === 4) assert(addExecutors(manager) === 1) - assert(numExecutorsPending(manager) === 6) + assert(numExecutorsPending(manager) === 5) assert(numExecutorsToAdd(manager) === 2) - assert(addExecutors(manager) === 1) + assert(addExecutors(manager) === 2) + assert(numExecutorsPending(manager) === 7) + assert(numExecutorsToAdd(manager) === 4) + assert(addExecutors(manager) === 0) assert(numExecutorsPending(manager) === 7) assert(numExecutorsToAdd(manager) === 1) @@ -325,6 +333,8 @@ class ExecutorAllocationManagerSuite extends FunSuite with LocalSparkContext { val manager = sc.executorAllocationManager.get manager.setClock(clock) + executorIds(manager).asInstanceOf[mutable.Set[String]] ++= List("1", "2", "3") + // Starting remove timer is idempotent for each executor assert(removeTimes(manager).isEmpty) onExecutorIdle(manager, "1") @@ -597,6 +607,41 @@ class ExecutorAllocationManagerSuite extends FunSuite with LocalSparkContext { assert(removeTimes(manager).size === 1) } + test("SPARK-4951: call onTaskStart before onBlockManagerAdded") { + sc = createSparkContext(2, 10) + val manager = sc.executorAllocationManager.get + assert(executorIds(manager).isEmpty) + assert(removeTimes(manager).isEmpty) + + sc.listenerBus.postToAll(SparkListenerTaskStart(0, 0, createTaskInfo(0, 0, "executor-1"))) + sc.listenerBus.postToAll(SparkListenerBlockManagerAdded( + 0L, BlockManagerId("executor-1", "host1", 1), 100L)) + assert(executorIds(manager).size === 1) + assert(executorIds(manager).contains("executor-1")) + assert(removeTimes(manager).size === 0) + } + + test("SPARK-4951: onExecutorAdded should not add a busy executor to removeTimes") { + sc = createSparkContext(2, 10) + val manager = sc.executorAllocationManager.get + assert(executorIds(manager).isEmpty) + assert(removeTimes(manager).isEmpty) + sc.listenerBus.postToAll(SparkListenerBlockManagerAdded( + 0L, BlockManagerId("executor-1", "host1", 1), 100L)) + sc.listenerBus.postToAll(SparkListenerTaskStart(0, 0, createTaskInfo(0, 0, "executor-1"))) + + assert(executorIds(manager).size === 1) + assert(executorIds(manager).contains("executor-1")) + assert(removeTimes(manager).size === 0) + + sc.listenerBus.postToAll(SparkListenerBlockManagerAdded( + 0L, BlockManagerId("executor-2", "host1", 1), 100L)) + assert(executorIds(manager).size === 2) + assert(executorIds(manager).contains("executor-2")) + assert(removeTimes(manager).size === 1) + assert(removeTimes(manager).contains("executor-2")) + assert(!removeTimes(manager).contains("executor-1")) + } } /** From f38ef6586c2980183c983b2aa14a5ddc1856b7b7 Mon Sep 17 00:00:00 2001 From: huangzhaowei Date: Sun, 11 Jan 2015 16:32:47 -0800 Subject: [PATCH 229/320] [SPARK-4033][Examples]Input of the SparkPi too big causes the emption exception If input of the SparkPi args is larger than the 25000, the integer 'n' inside the code will be overflow, and may be a negative number. And it causes the (0 until n) Seq as an empty seq, then doing the action 'reduce' will throw the UnsupportedOperationException("empty collection"). The max size of the input of sc.parallelize is Int.MaxValue - 1, not the Int.MaxValue. Author: huangzhaowei Closes #2874 from SaintBacchus/SparkPi and squashes the following commits: 62d7cd7 [huangzhaowei] Add a commit to explain the modify 4cdc388 [huangzhaowei] Update SparkPi.scala 9a2fb7b [huangzhaowei] Input of the SparkPi is too big --- .../src/main/scala/org/apache/spark/examples/SparkPi.scala | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/examples/src/main/scala/org/apache/spark/examples/SparkPi.scala b/examples/src/main/scala/org/apache/spark/examples/SparkPi.scala index 9fbb0a800d735..35b8dd6c29b66 100644 --- a/examples/src/main/scala/org/apache/spark/examples/SparkPi.scala +++ b/examples/src/main/scala/org/apache/spark/examples/SparkPi.scala @@ -27,8 +27,8 @@ object SparkPi { val conf = new SparkConf().setAppName("Spark Pi") val spark = new SparkContext(conf) val slices = if (args.length > 0) args(0).toInt else 2 - val n = 100000 * slices - val count = spark.parallelize(1 to n, slices).map { i => + val n = math.min(100000L * slices, Int.MaxValue).toInt // avoid overflow + val count = spark.parallelize(1 until n, slices).map { i => val x = random * 2 - 1 val y = random * 2 - 1 if (x*x + y*y < 1) 1 else 0 From 2130de9d8f50f52b9b2d296b377df81d840546b3 Mon Sep 17 00:00:00 2001 From: Travis Galoppo Date: Sun, 11 Jan 2015 21:31:16 -0800 Subject: [PATCH 230/320] SPARK-5018 [MLlib] [WIP] Make MultivariateGaussian public Moving MutlivariateGaussian from private[mllib] to public. The class uses Breeze vectors internally, so this involves creating a public interface using MLlib vectors and matrices. This initial commit provides public construction, accessors for mean/covariance, density and log-density. Other potential methods include entropy and sample generation. Author: Travis Galoppo Closes #3923 from tgaloppo/spark-5018 and squashes the following commits: 2b15587 [Travis Galoppo] Style correction b4121b4 [Travis Galoppo] Merge remote-tracking branch 'upstream/master' into spark-5018 e30a100 [Travis Galoppo] Made mu, sigma private[mllib] members of MultivariateGaussian Moved MultivariateGaussian (and test suite) from stat.impl to stat.distribution (required updates in GaussianMixture{EM,Model}.scala) Marked MultivariateGaussian as @DeveloperApi Fixed style error 9fa3bb7 [Travis Galoppo] Style improvements 91a5fae [Travis Galoppo] Rearranged equation for part of density function 8c35381 [Travis Galoppo] Fixed accessor methods to match member variable names. Modified calculations to avoid log(pow(x,y)) calculations 0943dc4 [Travis Galoppo] SPARK-5018 4dee9e1 [Travis Galoppo] SPARK-5018 --- .../mllib/clustering/GaussianMixtureEM.scala | 11 +-- .../clustering/GaussianMixtureModel.scala | 2 +- .../MultivariateGaussian.scala | 70 ++++++++++++++----- .../MultivariateGaussianSuite.scala | 33 +++++---- 4 files changed, 75 insertions(+), 41 deletions(-) rename mllib/src/main/scala/org/apache/spark/mllib/stat/{impl => distribution}/MultivariateGaussian.scala (61%) rename mllib/src/test/scala/org/apache/spark/mllib/stat/{impl => distribution}/MultivariateGaussianSuite.scala (72%) diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureEM.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureEM.scala index b3c5631cc4cc6..d8e134619411b 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureEM.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureEM.scala @@ -20,10 +20,11 @@ package org.apache.spark.mllib.clustering import scala.collection.mutable.IndexedSeq import breeze.linalg.{DenseVector => BreezeVector, DenseMatrix => BreezeMatrix, diag, Transpose} -import org.apache.spark.rdd.RDD + import org.apache.spark.mllib.linalg.{Matrices, Vector, Vectors, DenseVector, DenseMatrix, BLAS} -import org.apache.spark.mllib.stat.impl.MultivariateGaussian +import org.apache.spark.mllib.stat.distribution.MultivariateGaussian import org.apache.spark.mllib.util.MLUtils +import org.apache.spark.rdd.RDD import org.apache.spark.util.Utils /** @@ -134,7 +135,7 @@ class GaussianMixtureEM private ( // derived from the samples val (weights, gaussians) = initialModel match { case Some(gmm) => (gmm.weight, gmm.mu.zip(gmm.sigma).map { case(mu, sigma) => - new MultivariateGaussian(mu.toBreeze.toDenseVector, sigma.toBreeze.toDenseMatrix) + new MultivariateGaussian(mu, sigma) }) case None => { @@ -176,8 +177,8 @@ class GaussianMixtureEM private ( } // Need to convert the breeze matrices to MLlib matrices - val means = Array.tabulate(k) { i => Vectors.fromBreeze(gaussians(i).mu) } - val sigmas = Array.tabulate(k) { i => Matrices.fromBreeze(gaussians(i).sigma) } + val means = Array.tabulate(k) { i => gaussians(i).mu } + val sigmas = Array.tabulate(k) { i => gaussians(i).sigma } new GaussianMixtureModel(weights, means, sigmas) } diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala index b461ea4f0f06e..416cad080c408 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/GaussianMixtureModel.scala @@ -21,7 +21,7 @@ import breeze.linalg.{DenseVector => BreezeVector} import org.apache.spark.rdd.RDD import org.apache.spark.mllib.linalg.{Matrix, Vector} -import org.apache.spark.mllib.stat.impl.MultivariateGaussian +import org.apache.spark.mllib.stat.distribution.MultivariateGaussian import org.apache.spark.mllib.util.MLUtils /** diff --git a/mllib/src/main/scala/org/apache/spark/mllib/stat/impl/MultivariateGaussian.scala b/mllib/src/main/scala/org/apache/spark/mllib/stat/distribution/MultivariateGaussian.scala similarity index 61% rename from mllib/src/main/scala/org/apache/spark/mllib/stat/impl/MultivariateGaussian.scala rename to mllib/src/main/scala/org/apache/spark/mllib/stat/distribution/MultivariateGaussian.scala index bc7f6c5197ac7..fd186b5ee6f72 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/stat/impl/MultivariateGaussian.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/stat/distribution/MultivariateGaussian.scala @@ -15,13 +15,16 @@ * limitations under the License. */ -package org.apache.spark.mllib.stat.impl +package org.apache.spark.mllib.stat.distribution import breeze.linalg.{DenseVector => DBV, DenseMatrix => DBM, diag, max, eigSym} +import org.apache.spark.annotation.DeveloperApi; +import org.apache.spark.mllib.linalg.{Vectors, Vector, Matrices, Matrix} import org.apache.spark.mllib.util.MLUtils /** + * :: DeveloperApi :: * This class provides basic functionality for a Multivariate Gaussian (Normal) Distribution. In * the event that the covariance matrix is singular, the density will be computed in a * reduced dimensional subspace under which the distribution is supported. @@ -30,33 +33,64 @@ import org.apache.spark.mllib.util.MLUtils * @param mu The mean vector of the distribution * @param sigma The covariance matrix of the distribution */ -private[mllib] class MultivariateGaussian( - val mu: DBV[Double], - val sigma: DBM[Double]) extends Serializable { +@DeveloperApi +class MultivariateGaussian ( + val mu: Vector, + val sigma: Matrix) extends Serializable { + require(sigma.numCols == sigma.numRows, "Covariance matrix must be square") + require(mu.size == sigma.numCols, "Mean vector length must match covariance matrix size") + + private val breezeMu = mu.toBreeze.toDenseVector + + /** + * private[mllib] constructor + * + * @param mu The mean vector of the distribution + * @param sigma The covariance matrix of the distribution + */ + private[mllib] def this(mu: DBV[Double], sigma: DBM[Double]) = { + this(Vectors.fromBreeze(mu), Matrices.fromBreeze(sigma)) + } + /** * Compute distribution dependent constants: - * rootSigmaInv = D^(-1/2) * U, where sigma = U * D * U.t - * u = (2*pi)^(-k/2) * det(sigma)^(-1/2) + * rootSigmaInv = D^(-1/2)^ * U, where sigma = U * D * U.t + * u = log((2*pi)^(-k/2)^ * det(sigma)^(-1/2)^) */ private val (rootSigmaInv: DBM[Double], u: Double) = calculateCovarianceConstants /** Returns density of this multivariate Gaussian at given point, x */ - def pdf(x: DBV[Double]): Double = { - val delta = x - mu + def pdf(x: Vector): Double = { + pdf(x.toBreeze.toDenseVector) + } + + /** Returns the log-density of this multivariate Gaussian at given point, x */ + def logpdf(x: Vector): Double = { + logpdf(x.toBreeze.toDenseVector) + } + + /** Returns density of this multivariate Gaussian at given point, x */ + private[mllib] def pdf(x: DBV[Double]): Double = { + math.exp(logpdf(x)) + } + + /** Returns the log-density of this multivariate Gaussian at given point, x */ + private[mllib] def logpdf(x: DBV[Double]): Double = { + val delta = x - breezeMu val v = rootSigmaInv * delta - u * math.exp(v.t * v * -0.5) + u + v.t * v * -0.5 } /** * Calculate distribution dependent components used for the density function: - * pdf(x) = (2*pi)^(-k/2) * det(sigma)^(-1/2) * exp( (-1/2) * (x-mu).t * inv(sigma) * (x-mu) ) + * pdf(x) = (2*pi)^(-k/2)^ * det(sigma)^(-1/2)^ * exp((-1/2) * (x-mu).t * inv(sigma) * (x-mu)) * where k is length of the mean vector. * * We here compute distribution-fixed parts - * (2*pi)^(-k/2) * det(sigma)^(-1/2) + * log((2*pi)^(-k/2)^ * det(sigma)^(-1/2)^) * and - * D^(-1/2) * U, where sigma = U * D * U.t + * D^(-1/2)^ * U, where sigma = U * D * U.t * * Both the determinant and the inverse can be computed from the singular value decomposition * of sigma. Noting that covariance matrices are always symmetric and positive semi-definite, @@ -65,11 +99,11 @@ private[mllib] class MultivariateGaussian( * * sigma = U * D * U.t * inv(Sigma) = U * inv(D) * U.t - * = (D^{-1/2} * U).t * (D^{-1/2} * U) + * = (D^{-1/2}^ * U).t * (D^{-1/2}^ * U) * * and thus * - * -0.5 * (x-mu).t * inv(Sigma) * (x-mu) = -0.5 * norm(D^{-1/2} * U * (x-mu))^2 + * -0.5 * (x-mu).t * inv(Sigma) * (x-mu) = -0.5 * norm(D^{-1/2}^ * U * (x-mu))^2^ * * To guard against singular covariance matrices, this method computes both the * pseudo-determinant and the pseudo-inverse (Moore-Penrose). Singular values are considered @@ -77,21 +111,21 @@ private[mllib] class MultivariateGaussian( * relation to the maximum singular value (same tolerance used by, e.g., Octave). */ private def calculateCovarianceConstants: (DBM[Double], Double) = { - val eigSym.EigSym(d, u) = eigSym(sigma) // sigma = u * diag(d) * u.t + val eigSym.EigSym(d, u) = eigSym(sigma.toBreeze.toDenseMatrix) // sigma = u * diag(d) * u.t // For numerical stability, values are considered to be non-zero only if they exceed tol. // This prevents any inverted value from exceeding (eps * n * max(d))^-1 val tol = MLUtils.EPSILON * max(d) * d.length try { - // pseudo-determinant is product of all non-zero singular values - val pdetSigma = d.activeValuesIterator.filter(_ > tol).reduce(_ * _) + // log(pseudo-determinant) is sum of the logs of all non-zero singular values + val logPseudoDetSigma = d.activeValuesIterator.filter(_ > tol).map(math.log).sum // calculate the root-pseudo-inverse of the diagonal matrix of singular values // by inverting the square root of all non-zero values val pinvS = diag(new DBV(d.map(v => if (v > tol) math.sqrt(1.0 / v) else 0.0).toArray)) - (pinvS * u, math.pow(2.0 * math.Pi, -mu.length / 2.0) * math.pow(pdetSigma, -0.5)) + (pinvS * u, -0.5 * (mu.size * math.log(2.0 * math.Pi) + logPseudoDetSigma)) } catch { case uex: UnsupportedOperationException => throw new IllegalArgumentException("Covariance matrix has no non-zero singular values") diff --git a/mllib/src/test/scala/org/apache/spark/mllib/stat/impl/MultivariateGaussianSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/stat/distribution/MultivariateGaussianSuite.scala similarity index 72% rename from mllib/src/test/scala/org/apache/spark/mllib/stat/impl/MultivariateGaussianSuite.scala rename to mllib/src/test/scala/org/apache/spark/mllib/stat/distribution/MultivariateGaussianSuite.scala index d58f2587e55aa..fac2498e4dcb3 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/stat/impl/MultivariateGaussianSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/stat/distribution/MultivariateGaussianSuite.scala @@ -15,54 +15,53 @@ * limitations under the License. */ -package org.apache.spark.mllib.stat.impl +package org.apache.spark.mllib.stat.distribution import org.scalatest.FunSuite -import breeze.linalg.{ DenseVector => BDV, DenseMatrix => BDM } - +import org.apache.spark.mllib.linalg.{ Vectors, Matrices } import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.mllib.util.TestingUtils._ class MultivariateGaussianSuite extends FunSuite with MLlibTestSparkContext { test("univariate") { - val x1 = new BDV(Array(0.0)) - val x2 = new BDV(Array(1.5)) + val x1 = Vectors.dense(0.0) + val x2 = Vectors.dense(1.5) - val mu = new BDV(Array(0.0)) - val sigma1 = new BDM(1, 1, Array(1.0)) + val mu = Vectors.dense(0.0) + val sigma1 = Matrices.dense(1, 1, Array(1.0)) val dist1 = new MultivariateGaussian(mu, sigma1) assert(dist1.pdf(x1) ~== 0.39894 absTol 1E-5) assert(dist1.pdf(x2) ~== 0.12952 absTol 1E-5) - val sigma2 = new BDM(1, 1, Array(4.0)) + val sigma2 = Matrices.dense(1, 1, Array(4.0)) val dist2 = new MultivariateGaussian(mu, sigma2) assert(dist2.pdf(x1) ~== 0.19947 absTol 1E-5) assert(dist2.pdf(x2) ~== 0.15057 absTol 1E-5) } test("multivariate") { - val x1 = new BDV(Array(0.0, 0.0)) - val x2 = new BDV(Array(1.0, 1.0)) + val x1 = Vectors.dense(0.0, 0.0) + val x2 = Vectors.dense(1.0, 1.0) - val mu = new BDV(Array(0.0, 0.0)) - val sigma1 = new BDM(2, 2, Array(1.0, 0.0, 0.0, 1.0)) + val mu = Vectors.dense(0.0, 0.0) + val sigma1 = Matrices.dense(2, 2, Array(1.0, 0.0, 0.0, 1.0)) val dist1 = new MultivariateGaussian(mu, sigma1) assert(dist1.pdf(x1) ~== 0.15915 absTol 1E-5) assert(dist1.pdf(x2) ~== 0.05855 absTol 1E-5) - val sigma2 = new BDM(2, 2, Array(4.0, -1.0, -1.0, 2.0)) + val sigma2 = Matrices.dense(2, 2, Array(4.0, -1.0, -1.0, 2.0)) val dist2 = new MultivariateGaussian(mu, sigma2) assert(dist2.pdf(x1) ~== 0.060155 absTol 1E-5) assert(dist2.pdf(x2) ~== 0.033971 absTol 1E-5) } test("multivariate degenerate") { - val x1 = new BDV(Array(0.0, 0.0)) - val x2 = new BDV(Array(1.0, 1.0)) + val x1 = Vectors.dense(0.0, 0.0) + val x2 = Vectors.dense(1.0, 1.0) - val mu = new BDV(Array(0.0, 0.0)) - val sigma = new BDM(2, 2, Array(1.0, 1.0, 1.0, 1.0)) + val mu = Vectors.dense(0.0, 0.0) + val sigma = Matrices.dense(2, 2, Array(1.0, 1.0, 1.0, 1.0)) val dist = new MultivariateGaussian(mu, sigma) assert(dist.pdf(x1) ~== 0.11254 absTol 1E-5) assert(dist.pdf(x2) ~== 0.068259 absTol 1E-5) From 82fd38dcdcc9f7df18930c0e08cc8ec34eaee828 Mon Sep 17 00:00:00 2001 From: Josh Rosen Date: Mon, 12 Jan 2015 10:47:12 -0800 Subject: [PATCH 231/320] [SPARK-5200] Disable web UI in Hive ThriftServer tests Disables the Spark web UI in HiveThriftServer2Suite in order to prevent Jenkins test failures due to port contention. Author: Josh Rosen Closes #3998 from JoshRosen/SPARK-5200 and squashes the following commits: a384416 [Josh Rosen] [SPARK-5200] Disable web UI in Hive Thriftserver tests. --- .../spark/sql/hive/thriftserver/HiveThriftServer2Suite.scala | 2 ++ 1 file changed, 2 insertions(+) diff --git a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suite.scala b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suite.scala index 7814aa38f4146..b52a51d11e4ad 100644 --- a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suite.scala +++ b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suite.scala @@ -143,6 +143,7 @@ class HiveThriftServer2Suite extends FunSuite with Logging { | --hiveconf ${ConfVars.HIVE_SERVER2_TRANSPORT_MODE}=http | --hiveconf ${ConfVars.HIVE_SERVER2_THRIFT_HTTP_PORT}=$port | --driver-class-path ${sys.props("java.class.path")} + | --conf spark.ui.enabled=false """.stripMargin.split("\\s+").toSeq } else { s"""$startScript @@ -153,6 +154,7 @@ class HiveThriftServer2Suite extends FunSuite with Logging { | --hiveconf ${ConfVars.HIVE_SERVER2_THRIFT_BIND_HOST}=localhost | --hiveconf ${ConfVars.HIVE_SERVER2_THRIFT_PORT}=$port | --driver-class-path ${sys.props("java.class.path")} + | --conf spark.ui.enabled=false """.stripMargin.split("\\s+").toSeq } From ef9224e08010420b570c21a0b9208d22792a24fe Mon Sep 17 00:00:00 2001 From: lianhuiwang Date: Mon, 12 Jan 2015 10:57:12 -0800 Subject: [PATCH 232/320] [SPARK-5102][Core]subclass of MapStatus needs to be registered with Kryo CompressedMapStatus and HighlyCompressedMapStatus needs to be registered with Kryo, because they are subclass of MapStatus. Author: lianhuiwang Closes #4007 from lianhuiwang/SPARK-5102 and squashes the following commits: 9d2238a [lianhuiwang] remove register of MapStatus 05a285d [lianhuiwang] subclass of MapStatus needs to be registered with Kryo --- .../scala/org/apache/spark/serializer/KryoSerializer.scala | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala b/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala index d2947dcea4f7c..d56e23ce4478a 100644 --- a/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala +++ b/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala @@ -29,7 +29,7 @@ import org.apache.spark._ import org.apache.spark.api.python.PythonBroadcast import org.apache.spark.broadcast.HttpBroadcast import org.apache.spark.network.nio.{PutBlock, GotBlock, GetBlock} -import org.apache.spark.scheduler.MapStatus +import org.apache.spark.scheduler.{CompressedMapStatus, HighlyCompressedMapStatus} import org.apache.spark.storage._ import org.apache.spark.util.BoundedPriorityQueue import org.apache.spark.util.collection.CompactBuffer @@ -207,7 +207,8 @@ private[serializer] object KryoSerializer { classOf[PutBlock], classOf[GotBlock], classOf[GetBlock], - classOf[MapStatus], + classOf[CompressedMapStatus], + classOf[HighlyCompressedMapStatus], classOf[CompactBuffer[_]], classOf[BlockManagerId], classOf[Array[Byte]], From 13e610b88eb83b11785737ab1d99927f676f81c6 Mon Sep 17 00:00:00 2001 From: Sean Owen Date: Mon, 12 Jan 2015 11:00:56 -0800 Subject: [PATCH 233/320] SPARK-4159 [BUILD] Addendum: improve running of single test after enabling Java tests https://issues.apache.org/jira/browse/SPARK-4159 was resolved but as Sandy points out, the guidance in https://cwiki.apache.org/confluence/display/SPARK/Useful+Developer+Tools under "Running Individual Tests" no longer quite works, not optimally. This minor change is not really the important change, which is an update to the wiki text. The correct way to run one Scala test suite in Maven is now: ``` mvn test -DwildcardSuites=org.apache.spark.io.CompressionCodecSuite -Dtests=none ``` The correct way to run one Java test is ``` mvn test -DwildcardSuites=none -Dtests=org.apache.spark.streaming.JavaAPISuite ``` Basically, you have to set two properties in order to suppress all of one type of test (with a non-existent test name like 'none') and all but one test of the other type. The change in the PR just prevents Surefire from barfing when it finds no "none" test. Author: Sean Owen Closes #3993 from srowen/SPARK-4159 and squashes the following commits: 83106d7 [Sean Owen] Default failIfNoTests to false to enable the -DwildcardSuites=... -Dtests=... syntax for running one test to work --- pom.xml | 1 + 1 file changed, 1 insertion(+) diff --git a/pom.xml b/pom.xml index aadcdfd1083c5..0403c008be4f4 100644 --- a/pom.xml +++ b/pom.xml @@ -1130,6 +1130,7 @@ ${test_classpath} true + false From a3978f3e156e0ca67e978f1795b238ddd69ff9a6 Mon Sep 17 00:00:00 2001 From: Michael Armbrust Date: Mon, 12 Jan 2015 11:57:59 -0800 Subject: [PATCH 234/320] [SPARK-5078] Optionally read from SPARK_LOCAL_HOSTNAME Current spark lets you set the ip address using SPARK_LOCAL_IP, but then this is given to akka after doing a reverse DNS lookup. This makes it difficult to run spark in Docker. You can already change the hostname that is used programmatically, but it would be nice to be able to do this with an environment variable as well. Author: Michael Armbrust Closes #3893 from marmbrus/localHostnameEnv and squashes the following commits: 85045b6 [Michael Armbrust] Optionally read from SPARK_LOCAL_HOSTNAME --- core/src/main/scala/org/apache/spark/util/Utils.scala | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/core/src/main/scala/org/apache/spark/util/Utils.scala b/core/src/main/scala/org/apache/spark/util/Utils.scala index c4f1898a2db15..578f1a9cf4868 100644 --- a/core/src/main/scala/org/apache/spark/util/Utils.scala +++ b/core/src/main/scala/org/apache/spark/util/Utils.scala @@ -701,7 +701,7 @@ private[spark] object Utils extends Logging { } } - private var customHostname: Option[String] = None + private var customHostname: Option[String] = sys.env.get("SPARK_LOCAL_HOSTNAME") /** * Allow setting a custom host name because when we run on Mesos we need to use the same From aff49a3ee1a91d730590f4a0b9ac485fd52dc8bf Mon Sep 17 00:00:00 2001 From: Sean Owen Date: Mon, 12 Jan 2015 12:15:34 -0800 Subject: [PATCH 235/320] SPARK-5172 [BUILD] spark-examples-***.jar shades a wrong Hadoop distribution In addition to the `hadoop-2.x` profiles in the parent POM, there is actually another set of profiles in `examples` that has to be activated differently to get the right Hadoop 1 vs 2 flavor of HBase. This wasn't actually used in making Hadoop 2 distributions, hence the problem. To reduce complexity, I suggest merging them with the parent POM profiles, which is possible now. You'll see this changes appears to update the HBase version, but actually, the default 0.94 version was not being used. HBase is only used in examples, and the examples POM always chose one profile or the other that updated the version to 0.98.x anyway. Author: Sean Owen Closes #3992 from srowen/SPARK-5172 and squashes the following commits: 17830d9 [Sean Owen] Control hbase hadoop1/2 flavor in the parent POM with existing hadoop-2.x profiles --- examples/pom.xml | 23 ----------------------- pom.xml | 5 ++++- 2 files changed, 4 insertions(+), 24 deletions(-) diff --git a/examples/pom.xml b/examples/pom.xml index 002d4458c4b3e..4b92147725f6b 100644 --- a/examples/pom.xml +++ b/examples/pom.xml @@ -392,29 +392,6 @@ - - hbase-hadoop2 - - - hbase.profile - hadoop2 - - - - 0.98.7-hadoop2 - - - - hbase-hadoop1 - - - !hbase.profile - - - - 0.98.7-hadoop1 - - diff --git a/pom.xml b/pom.xml index 0403c008be4f4..f4466e56c2a53 100644 --- a/pom.xml +++ b/pom.xml @@ -122,7 +122,7 @@ 1.0.4 2.4.1 ${hadoop.version} - 0.94.6 + 0.98.7-hadoop1 hbase 1.4.0 3.4.5 @@ -1466,6 +1466,7 @@ 2.2.0 2.5.0 + 0.98.7-hadoop2 hadoop2 @@ -1476,6 +1477,7 @@ 2.3.0 2.5.0 0.9.0 + 0.98.7-hadoop2 3.1.1 hadoop2 @@ -1487,6 +1489,7 @@ 2.4.0 2.5.0 0.9.0 + 0.98.7-hadoop2 3.1.1 hadoop2 From 3aed3051c0b6cd5f38d7db7d20fa7a1680bfde6f Mon Sep 17 00:00:00 2001 From: jerryshao Date: Mon, 12 Jan 2015 13:14:44 -0800 Subject: [PATCH 236/320] [SPARK-4999][Streaming] Change storeInBlockManager to false by default Currently WAL-backed block is read out from HDFS and put into BlockManger with storage level MEMORY_ONLY_SER by default, since WAL-backed block is already materialized in HDFS with fault-tolerance, no need to put into BlockManger again by default. Author: jerryshao Closes #3906 from jerryshao/SPARK-4999 and squashes the following commits: b95f95e [jerryshao] Change storeInBlockManager to false by default --- .../apache/spark/streaming/dstream/ReceiverInputDStream.scala | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/ReceiverInputDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/ReceiverInputDStream.scala index c834744631e02..afd3c4bc4c4fe 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/ReceiverInputDStream.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/ReceiverInputDStream.scala @@ -86,7 +86,7 @@ abstract class ReceiverInputDStream[T: ClassTag](@transient ssc_ : StreamingCont }.toArray // Since storeInBlockManager = false, the storage level does not matter. new WriteAheadLogBackedBlockRDD[T](ssc.sparkContext, - blockIds, logSegments, storeInBlockManager = true, StorageLevel.MEMORY_ONLY_SER) + blockIds, logSegments, storeInBlockManager = false, StorageLevel.MEMORY_ONLY_SER) } else { new BlockRDD[T](ssc.sc, blockIds) } From 5d9fa550820543ee1b0ce82997917745973a5d65 Mon Sep 17 00:00:00 2001 From: Michael Armbrust Date: Mon, 12 Jan 2015 15:19:09 -0800 Subject: [PATCH 237/320] [SPARK-5049][SQL] Fix ordering of partition columns in ParquetTableScan Followup to #3870. Props to rahulaggarwalguavus for identifying the issue. Author: Michael Armbrust Closes #3990 from marmbrus/SPARK-5049 and squashes the following commits: dd03e4e [Michael Armbrust] Fill in the partition values of parquet scans instead of using JoinedRow --- .../spark/sql/parquet/ParquetRelation.scala | 4 +- .../sql/parquet/ParquetTableOperations.scala | 43 +++++++++++-------- .../spark/sql/parquet/parquetSuites.scala | 12 ++++++ 3 files changed, 41 insertions(+), 18 deletions(-) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetRelation.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetRelation.scala index b237a07c72d07..2835dc3408b96 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetRelation.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetRelation.scala @@ -28,7 +28,7 @@ import parquet.schema.MessageType import org.apache.spark.sql.SQLContext import org.apache.spark.sql.catalyst.analysis.{MultiInstanceRelation, UnresolvedException} -import org.apache.spark.sql.catalyst.expressions.Attribute +import org.apache.spark.sql.catalyst.expressions.{AttributeMap, Attribute} import org.apache.spark.sql.catalyst.plans.logical.{LeafNode, LogicalPlan, Statistics} /** @@ -67,6 +67,8 @@ private[sql] case class ParquetRelation( conf, sqlContext.isParquetBinaryAsString) + lazy val attributeMap = AttributeMap(output.map(o => o -> o)) + override def newInstance() = ParquetRelation(path, conf, sqlContext).asInstanceOf[this.type] // Equals must also take into account the output attributes so that we can distinguish between diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala index 96bace1769f71..f5487740d3af9 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala @@ -64,18 +64,17 @@ case class ParquetTableScan( // The resolution of Parquet attributes is case sensitive, so we resolve the original attributes // by exprId. note: output cannot be transient, see // https://issues.apache.org/jira/browse/SPARK-1367 - val normalOutput = - attributes - .filterNot(a => relation.partitioningAttributes.map(_.exprId).contains(a.exprId)) - .flatMap(a => relation.output.find(o => o.exprId == a.exprId)) + val output = attributes.map(relation.attributeMap) - val partOutput = - attributes.flatMap(a => relation.partitioningAttributes.find(o => o.exprId == a.exprId)) + // A mapping of ordinals partitionRow -> finalOutput. + val requestedPartitionOrdinals = { + val partitionAttributeOrdinals = AttributeMap(relation.partitioningAttributes.zipWithIndex) - def output = partOutput ++ normalOutput - - assert(normalOutput.size + partOutput.size == attributes.size, - s"$normalOutput + $partOutput != $attributes, ${relation.output}") + attributes.zipWithIndex.flatMap { + case (attribute, finalOrdinal) => + partitionAttributeOrdinals.get(attribute).map(_ -> finalOrdinal) + } + }.toArray override def execute(): RDD[Row] = { import parquet.filter2.compat.FilterCompat.FilterPredicateCompat @@ -97,7 +96,7 @@ case class ParquetTableScan( // Store both requested and original schema in `Configuration` conf.set( RowReadSupport.SPARK_ROW_REQUESTED_SCHEMA, - ParquetTypesConverter.convertToString(normalOutput)) + ParquetTypesConverter.convertToString(output)) conf.set( RowWriteSupport.SPARK_ROW_SCHEMA, ParquetTypesConverter.convertToString(relation.output)) @@ -125,7 +124,7 @@ case class ParquetTableScan( classOf[Row], conf) - if (partOutput.nonEmpty) { + if (requestedPartitionOrdinals.nonEmpty) { baseRDD.mapPartitionsWithInputSplit { case (split, iter) => val partValue = "([^=]+)=([^=]+)".r val partValues = @@ -138,15 +137,25 @@ case class ParquetTableScan( case _ => None }.toMap + // Convert the partitioning attributes into the correct types val partitionRowValues = - partOutput.map(a => Cast(Literal(partValues(a.name)), a.dataType).eval(EmptyRow)) + relation.partitioningAttributes + .map(a => Cast(Literal(partValues(a.name)), a.dataType).eval(EmptyRow)) new Iterator[Row] { - private[this] val joinedRow = new JoinedRow5(Row(partitionRowValues:_*), null) - def hasNext = iter.hasNext - - def next() = joinedRow.withRight(iter.next()._2) + def next() = { + val row = iter.next()._2.asInstanceOf[SpecificMutableRow] + + // Parquet will leave partitioning columns empty, so we fill them in here. + var i = 0 + while (i < requestedPartitionOrdinals.size) { + row(requestedPartitionOrdinals(i)._2) = + partitionRowValues(requestedPartitionOrdinals(i)._1) + i += 1 + } + row + } } } } else { diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/parquet/parquetSuites.scala b/sql/hive/src/test/scala/org/apache/spark/sql/parquet/parquetSuites.scala index fc0e42c201d56..8bbb7f2fdbf48 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/parquet/parquetSuites.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/parquet/parquetSuites.scala @@ -174,6 +174,18 @@ abstract class ParquetPartitioningTest extends QueryTest with BeforeAndAfterAll } Seq("partitioned_parquet", "partitioned_parquet_with_key").foreach { table => + test(s"ordering of the partitioning columns $table") { + checkAnswer( + sql(s"SELECT p, stringField FROM $table WHERE p = 1"), + Seq.fill(10)((1, "part-1")) + ) + + checkAnswer( + sql(s"SELECT stringField, p FROM $table WHERE p = 1"), + Seq.fill(10)(("part-1", 1)) + ) + } + test(s"project the partitioning column $table") { checkAnswer( sql(s"SELECT p, count(*) FROM $table group by p"), From 1e42e96ece9e35ceed9ddebef66d589016878b56 Mon Sep 17 00:00:00 2001 From: Gabe Mulley Date: Mon, 12 Jan 2015 21:44:51 -0800 Subject: [PATCH 238/320] [SPARK-5138][SQL] Ensure schema can be inferred from a namedtuple When attempting to infer the schema of an RDD that contains namedtuples, pyspark fails to identify the records as namedtuples, resulting in it raising an error. Example: ```python from pyspark import SparkContext from pyspark.sql import SQLContext from collections import namedtuple import os sc = SparkContext() rdd = sc.textFile(os.path.join(os.getenv('SPARK_HOME'), 'README.md')) TextLine = namedtuple('TextLine', 'line length') tuple_rdd = rdd.map(lambda l: TextLine(line=l, length=len(l))) tuple_rdd.take(5) # This works sqlc = SQLContext(sc) # The following line raises an error schema_rdd = sqlc.inferSchema(tuple_rdd) ``` The error raised is: ``` File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/worker.py", line 107, in main process() File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/worker.py", line 98, in process serializer.dump_stream(func(split_index, iterator), outfile) File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/serializers.py", line 227, in dump_stream vs = list(itertools.islice(iterator, batch)) File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/rdd.py", line 1107, in takeUpToNumLeft yield next(iterator) File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/sql.py", line 816, in convert_struct raise ValueError("unexpected tuple: %s" % obj) TypeError: not all arguments converted during string formatting ``` Author: Gabe Mulley Closes #3978 from mulby/inferschema-namedtuple and squashes the following commits: 98c61cc [Gabe Mulley] Ensure exception message is populated correctly 375d96b [Gabe Mulley] Ensure schema can be inferred from a namedtuple --- python/pyspark/sql.py | 18 ++++++++++++++---- 1 file changed, 14 insertions(+), 4 deletions(-) diff --git a/python/pyspark/sql.py b/python/pyspark/sql.py index 0e8b398fc6b97..014ac1791c849 100644 --- a/python/pyspark/sql.py +++ b/python/pyspark/sql.py @@ -807,14 +807,14 @@ def convert_struct(obj): return if isinstance(obj, tuple): - if hasattr(obj, "fields"): - d = dict(zip(obj.fields, obj)) - if hasattr(obj, "__FIELDS__"): + if hasattr(obj, "_fields"): + d = dict(zip(obj._fields, obj)) + elif hasattr(obj, "__FIELDS__"): d = dict(zip(obj.__FIELDS__, obj)) elif all(isinstance(x, tuple) and len(x) == 2 for x in obj): d = dict(obj) else: - raise ValueError("unexpected tuple: %s" % obj) + raise ValueError("unexpected tuple: %s" % str(obj)) elif isinstance(obj, dict): d = obj @@ -1327,6 +1327,16 @@ def inferSchema(self, rdd, samplingRatio=None): >>> srdd = sqlCtx.inferSchema(nestedRdd2) >>> srdd.collect() [Row(f1=[[1, 2], [2, 3]], f2=[1, 2]), ..., f2=[2, 3])] + + >>> from collections import namedtuple + >>> CustomRow = namedtuple('CustomRow', 'field1 field2') + >>> rdd = sc.parallelize( + ... [CustomRow(field1=1, field2="row1"), + ... CustomRow(field1=2, field2="row2"), + ... CustomRow(field1=3, field2="row3")]) + >>> srdd = sqlCtx.inferSchema(rdd) + >>> srdd.collect()[0] + Row(field1=1, field2=u'row1') """ if isinstance(rdd, SchemaRDD): From f7741a9a72fef23c46f0ad9e1bd16b150967d816 Mon Sep 17 00:00:00 2001 From: WangTaoTheTonic Date: Tue, 13 Jan 2015 09:28:21 -0800 Subject: [PATCH 239/320] [SPARK-5006][Deploy]spark.port.maxRetries doesn't work https://issues.apache.org/jira/browse/SPARK-5006 I think the issue is produced in https://github.com/apache/spark/pull/1777. Not digging mesos's backend yet. Maybe should add same logic either. Author: WangTaoTheTonic Author: WangTao Closes #3841 from WangTaoTheTonic/SPARK-5006 and squashes the following commits: 8cdf96d [WangTao] indent thing 2d86d65 [WangTaoTheTonic] fix line length 7cdfd98 [WangTaoTheTonic] fit for new HttpServer constructor 61a370d [WangTaoTheTonic] some minor fixes bc6e1ec [WangTaoTheTonic] rebase 67bcb46 [WangTaoTheTonic] put conf at 3rd position, modify suite class, add comments f450cd1 [WangTaoTheTonic] startServiceOnPort will use a SparkConf arg 29b751b [WangTaoTheTonic] rebase as ExecutorRunnableUtil changed to ExecutorRunnable 396c226 [WangTaoTheTonic] make the grammar more like scala 191face [WangTaoTheTonic] invalid value name 62ec336 [WangTaoTheTonic] spark.port.maxRetries doesn't work --- .../org/apache/spark/HttpFileServer.scala | 3 ++- .../scala/org/apache/spark/HttpServer.scala | 3 ++- .../scala/org/apache/spark/SparkConf.scala | 6 +++-- .../scala/org/apache/spark/SparkEnv.scala | 2 +- .../spark/broadcast/HttpBroadcast.scala | 3 ++- .../spark/network/nio/ConnectionManager.scala | 2 +- .../org/apache/spark/ui/JettyUtils.scala | 2 +- .../org/apache/spark/util/AkkaUtils.scala | 2 +- .../scala/org/apache/spark/util/Utils.scala | 23 +++++++++---------- .../streaming/flume/FlumeStreamSuite.scala | 2 +- .../streaming/mqtt/MQTTStreamSuite.scala | 3 ++- .../org/apache/spark/repl/SparkIMain.scala | 2 +- .../scala/org/apache/spark/repl/Main.scala | 2 +- .../spark/deploy/yarn/ExecutorRunnable.scala | 9 +++----- 14 files changed, 33 insertions(+), 31 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/HttpFileServer.scala b/core/src/main/scala/org/apache/spark/HttpFileServer.scala index edc3889c9ae51..677c5e0f89d72 100644 --- a/core/src/main/scala/org/apache/spark/HttpFileServer.scala +++ b/core/src/main/scala/org/apache/spark/HttpFileServer.scala @@ -24,6 +24,7 @@ import com.google.common.io.Files import org.apache.spark.util.Utils private[spark] class HttpFileServer( + conf: SparkConf, securityManager: SecurityManager, requestedPort: Int = 0) extends Logging { @@ -41,7 +42,7 @@ private[spark] class HttpFileServer( fileDir.mkdir() jarDir.mkdir() logInfo("HTTP File server directory is " + baseDir) - httpServer = new HttpServer(baseDir, securityManager, requestedPort, "HTTP file server") + httpServer = new HttpServer(conf, baseDir, securityManager, requestedPort, "HTTP file server") httpServer.start() serverUri = httpServer.uri logDebug("HTTP file server started at: " + serverUri) diff --git a/core/src/main/scala/org/apache/spark/HttpServer.scala b/core/src/main/scala/org/apache/spark/HttpServer.scala index 912558d0cab7d..fa22787ce7ea3 100644 --- a/core/src/main/scala/org/apache/spark/HttpServer.scala +++ b/core/src/main/scala/org/apache/spark/HttpServer.scala @@ -42,6 +42,7 @@ private[spark] class ServerStateException(message: String) extends Exception(mes * around a Jetty server. */ private[spark] class HttpServer( + conf: SparkConf, resourceBase: File, securityManager: SecurityManager, requestedPort: Int = 0, @@ -57,7 +58,7 @@ private[spark] class HttpServer( } else { logInfo("Starting HTTP Server") val (actualServer, actualPort) = - Utils.startServiceOnPort[Server](requestedPort, doStart, serverName) + Utils.startServiceOnPort[Server](requestedPort, doStart, conf, serverName) server = actualServer port = actualPort } diff --git a/core/src/main/scala/org/apache/spark/SparkConf.scala b/core/src/main/scala/org/apache/spark/SparkConf.scala index c14764f773982..a0ce107f43b16 100644 --- a/core/src/main/scala/org/apache/spark/SparkConf.scala +++ b/core/src/main/scala/org/apache/spark/SparkConf.scala @@ -370,7 +370,9 @@ private[spark] object SparkConf { } /** - * Return whether the given config is a Spark port config. + * Return true if the given config matches either `spark.*.port` or `spark.port.*`. */ - def isSparkPortConf(name: String): Boolean = name.startsWith("spark.") && name.endsWith(".port") + def isSparkPortConf(name: String): Boolean = { + (name.startsWith("spark.") && name.endsWith(".port")) || name.startsWith("spark.port.") + } } diff --git a/core/src/main/scala/org/apache/spark/SparkEnv.scala b/core/src/main/scala/org/apache/spark/SparkEnv.scala index 43436a1697000..4d418037bd33f 100644 --- a/core/src/main/scala/org/apache/spark/SparkEnv.scala +++ b/core/src/main/scala/org/apache/spark/SparkEnv.scala @@ -312,7 +312,7 @@ object SparkEnv extends Logging { val httpFileServer = if (isDriver) { val fileServerPort = conf.getInt("spark.fileserver.port", 0) - val server = new HttpFileServer(securityManager, fileServerPort) + val server = new HttpFileServer(conf, securityManager, fileServerPort) server.initialize() conf.set("spark.fileserver.uri", server.serverUri) server diff --git a/core/src/main/scala/org/apache/spark/broadcast/HttpBroadcast.scala b/core/src/main/scala/org/apache/spark/broadcast/HttpBroadcast.scala index 31f0a462f84d8..31d6958c403b3 100644 --- a/core/src/main/scala/org/apache/spark/broadcast/HttpBroadcast.scala +++ b/core/src/main/scala/org/apache/spark/broadcast/HttpBroadcast.scala @@ -153,7 +153,8 @@ private[broadcast] object HttpBroadcast extends Logging { private def createServer(conf: SparkConf) { broadcastDir = Utils.createTempDir(Utils.getLocalDir(conf)) val broadcastPort = conf.getInt("spark.broadcast.port", 0) - server = new HttpServer(broadcastDir, securityManager, broadcastPort, "HTTP broadcast server") + server = + new HttpServer(conf, broadcastDir, securityManager, broadcastPort, "HTTP broadcast server") server.start() serverUri = server.uri logInfo("Broadcast server started at " + serverUri) diff --git a/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala b/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala index 3340fca08014e..03c4137ca0a81 100644 --- a/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala +++ b/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala @@ -174,7 +174,7 @@ private[nio] class ConnectionManager( serverChannel.socket.bind(new InetSocketAddress(port)) (serverChannel, serverChannel.socket.getLocalPort) } - Utils.startServiceOnPort[ServerSocketChannel](port, startService, name) + Utils.startServiceOnPort[ServerSocketChannel](port, startService, conf, name) serverChannel.register(selector, SelectionKey.OP_ACCEPT) val id = new ConnectionManagerId(Utils.localHostName, serverChannel.socket.getLocalPort) diff --git a/core/src/main/scala/org/apache/spark/ui/JettyUtils.scala b/core/src/main/scala/org/apache/spark/ui/JettyUtils.scala index 2a27d49d2de05..88fed833f922d 100644 --- a/core/src/main/scala/org/apache/spark/ui/JettyUtils.scala +++ b/core/src/main/scala/org/apache/spark/ui/JettyUtils.scala @@ -201,7 +201,7 @@ private[spark] object JettyUtils extends Logging { } } - val (server, boundPort) = Utils.startServiceOnPort[Server](port, connect, serverName) + val (server, boundPort) = Utils.startServiceOnPort[Server](port, connect, conf, serverName) ServerInfo(server, boundPort, collection) } diff --git a/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala b/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala index db2531dc171f8..4c9b1e3c46f0f 100644 --- a/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala +++ b/core/src/main/scala/org/apache/spark/util/AkkaUtils.scala @@ -53,7 +53,7 @@ private[spark] object AkkaUtils extends Logging { val startService: Int => (ActorSystem, Int) = { actualPort => doCreateActorSystem(name, host, actualPort, conf, securityManager) } - Utils.startServiceOnPort(port, startService, name) + Utils.startServiceOnPort(port, startService, conf, name) } private def doCreateActorSystem( diff --git a/core/src/main/scala/org/apache/spark/util/Utils.scala b/core/src/main/scala/org/apache/spark/util/Utils.scala index 578f1a9cf4868..2c04e4ddfbcb7 100644 --- a/core/src/main/scala/org/apache/spark/util/Utils.scala +++ b/core/src/main/scala/org/apache/spark/util/Utils.scala @@ -1690,17 +1690,15 @@ private[spark] object Utils extends Logging { } /** - * Default maximum number of retries when binding to a port before giving up. + * Maximum number of retries when binding to a port before giving up. */ - val portMaxRetries: Int = { - if (sys.props.contains("spark.testing")) { + def portMaxRetries(conf: SparkConf): Int = { + val maxRetries = conf.getOption("spark.port.maxRetries").map(_.toInt) + if (conf.contains("spark.testing")) { // Set a higher number of retries for tests... - sys.props.get("spark.port.maxRetries").map(_.toInt).getOrElse(100) + maxRetries.getOrElse(100) } else { - Option(SparkEnv.get) - .flatMap(_.conf.getOption("spark.port.maxRetries")) - .map(_.toInt) - .getOrElse(16) + maxRetries.getOrElse(16) } } @@ -1709,17 +1707,18 @@ private[spark] object Utils extends Logging { * Each subsequent attempt uses 1 + the port used in the previous attempt (unless the port is 0). * * @param startPort The initial port to start the service on. - * @param maxRetries Maximum number of retries to attempt. - * A value of 3 means attempting ports n, n+1, n+2, and n+3, for example. * @param startService Function to start service on a given port. * This is expected to throw java.net.BindException on port collision. + * @param conf A SparkConf used to get the maximum number of retries when binding to a port. + * @param serviceName Name of the service. */ def startServiceOnPort[T]( startPort: Int, startService: Int => (T, Int), - serviceName: String = "", - maxRetries: Int = portMaxRetries): (T, Int) = { + conf: SparkConf, + serviceName: String = ""): (T, Int) = { val serviceString = if (serviceName.isEmpty) "" else s" '$serviceName'" + val maxRetries = portMaxRetries(conf) for (offset <- 0 to maxRetries) { // Do not increment port if startPort is 0, which is treated as a special port val tryPort = if (startPort == 0) { diff --git a/external/flume/src/test/scala/org/apache/spark/streaming/flume/FlumeStreamSuite.scala b/external/flume/src/test/scala/org/apache/spark/streaming/flume/FlumeStreamSuite.scala index 13943ed5442b9..f333e3891b5f0 100644 --- a/external/flume/src/test/scala/org/apache/spark/streaming/flume/FlumeStreamSuite.scala +++ b/external/flume/src/test/scala/org/apache/spark/streaming/flume/FlumeStreamSuite.scala @@ -80,7 +80,7 @@ class FlumeStreamSuite extends FunSuite with BeforeAndAfter with Matchers with L val socket = new ServerSocket(trialPort) socket.close() (null, trialPort) - })._2 + }, conf)._2 } /** Setup and start the streaming context */ diff --git a/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala b/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala index 30727dfa64437..fe53a29cba0c9 100644 --- a/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala +++ b/external/mqtt/src/test/scala/org/apache/spark/streaming/mqtt/MQTTStreamSuite.scala @@ -32,6 +32,7 @@ import org.scalatest.concurrent.Eventually import org.apache.spark.streaming.{Milliseconds, StreamingContext} import org.apache.spark.storage.StorageLevel import org.apache.spark.streaming.dstream.ReceiverInputDStream +import org.apache.spark.SparkConf import org.apache.spark.util.Utils class MQTTStreamSuite extends FunSuite with Eventually with BeforeAndAfter { @@ -106,7 +107,7 @@ class MQTTStreamSuite extends FunSuite with Eventually with BeforeAndAfter { val socket = new ServerSocket(trialPort) socket.close() (null, trialPort) - })._2 + }, new SparkConf())._2 } def publishData(data: String): Unit = { diff --git a/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkIMain.scala b/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkIMain.scala index 646c68e60c2e9..b646f0b6f0868 100644 --- a/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkIMain.scala +++ b/repl/scala-2.10/src/main/scala/org/apache/spark/repl/SparkIMain.scala @@ -106,7 +106,7 @@ import org.apache.spark.util.Utils val virtualDirectory = new PlainFile(outputDir) // "directory" for classfiles /** Jetty server that will serve our classes to worker nodes */ val classServerPort = conf.getInt("spark.replClassServer.port", 0) - val classServer = new HttpServer(outputDir, new SecurityManager(conf), classServerPort, "HTTP class server") + val classServer = new HttpServer(conf, outputDir, new SecurityManager(conf), classServerPort, "HTTP class server") private var currentSettings: Settings = initialSettings var printResults = true // whether to print result lines var totalSilence = false // whether to print anything diff --git a/repl/scala-2.11/src/main/scala/org/apache/spark/repl/Main.scala b/repl/scala-2.11/src/main/scala/org/apache/spark/repl/Main.scala index 5e93a71995072..69e44d4f916e1 100644 --- a/repl/scala-2.11/src/main/scala/org/apache/spark/repl/Main.scala +++ b/repl/scala-2.11/src/main/scala/org/apache/spark/repl/Main.scala @@ -32,7 +32,7 @@ object Main extends Logging { val s = new Settings() s.processArguments(List("-Yrepl-class-based", "-Yrepl-outdir", s"${outputDir.getAbsolutePath}", "-Yrepl-sync"), true) - val classServer = new HttpServer(outputDir, new SecurityManager(conf)) + val classServer = new HttpServer(conf, outputDir, new SecurityManager(conf)) var sparkContext: SparkContext = _ var interp = new SparkILoop // this is a public var because tests reset it. diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorRunnable.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorRunnable.scala index ebf5616e8d303..c537da9f67552 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorRunnable.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorRunnable.scala @@ -148,12 +148,9 @@ class ExecutorRunnable( // registers with the Scheduler and transfers the spark configs. Since the Executor backend // uses Akka to connect to the scheduler, the akka settings are needed as well as the // authentication settings. - sparkConf.getAll. - filter { case (k, v) => k.startsWith("spark.auth") || k.startsWith("spark.akka") }. - foreach { case (k, v) => javaOpts += YarnSparkHadoopUtil.escapeForShell(s"-D$k=$v") } - - sparkConf.getAkkaConf. - foreach { case (k, v) => javaOpts += YarnSparkHadoopUtil.escapeForShell(s"-D$k=$v") } + sparkConf.getAll + .filter { case (k, v) => SparkConf.isExecutorStartupConf(k) } + .foreach { case (k, v) => javaOpts += YarnSparkHadoopUtil.escapeForShell(s"-D$k=$v") } // Commenting it out for now - so that people can refer to the properties if required. Remove // it once cpuset version is pushed out. From 9dea64e53ad8df8a3160c0f4010811af1e73dd6f Mon Sep 17 00:00:00 2001 From: WangTaoTheTonic Date: Tue, 13 Jan 2015 09:43:48 -0800 Subject: [PATCH 240/320] [SPARK-4697][YARN]System properties should override environment variables I found some arguments in yarn module take environment variables before system properties while the latter override the former in core module. Author: WangTaoTheTonic Author: WangTao Closes #3557 from WangTaoTheTonic/SPARK4697 and squashes the following commits: 836b9ef [WangTaoTheTonic] fix type mismatch e3e486a [WangTaoTheTonic] remove the comma 1262d57 [WangTaoTheTonic] handle spark.app.name and SPARK_YARN_APP_NAME in SparkSubmitArguments bee9447 [WangTaoTheTonic] wrong brace 81833bb [WangTaoTheTonic] rebase 40934b4 [WangTaoTheTonic] just switch blocks 5f43f45 [WangTao] System property can override environment variable --- .../spark/deploy/SparkSubmitArguments.scala | 5 +++++ .../spark/deploy/yarn/ClientArguments.scala | 4 ++-- .../cluster/YarnClientSchedulerBackend.scala | 19 +++++++++++-------- 3 files changed, 18 insertions(+), 10 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala index f14ef4d299383..47059b08a397f 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala @@ -149,6 +149,11 @@ private[spark] class SparkSubmitArguments(args: Seq[String], env: Map[String, St // Global defaults. These should be keep to minimum to avoid confusing behavior. master = Option(master).getOrElse("local[*]") + // In YARN mode, app name can be set via SPARK_YARN_APP_NAME (see SPARK-5222) + if (master.startsWith("yarn")) { + name = Option(name).orElse(env.get("SPARK_YARN_APP_NAME")).orNull + } + // Set name from main class if not given name = Option(name).orElse(Option(mainClass)).orNull if (name == null && primaryResource != null) { diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala index fdbf9f8eed029..461a9ccd3c216 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala @@ -64,12 +64,12 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf) // For backward compatibility, SPARK_YARN_DIST_{ARCHIVES/FILES} should be resolved to hdfs://, // while spark.yarn.dist.{archives/files} should be resolved to file:// (SPARK-2051). files = Option(files) - .orElse(sys.env.get("SPARK_YARN_DIST_FILES")) .orElse(sparkConf.getOption("spark.yarn.dist.files").map(p => Utils.resolveURIs(p))) + .orElse(sys.env.get("SPARK_YARN_DIST_FILES")) .orNull archives = Option(archives) - .orElse(sys.env.get("SPARK_YARN_DIST_ARCHIVES")) .orElse(sparkConf.getOption("spark.yarn.dist.archives").map(p => Utils.resolveURIs(p))) + .orElse(sys.env.get("SPARK_YARN_DIST_ARCHIVES")) .orNull // If dynamic allocation is enabled, start at the max number of executors if (isDynamicAllocationEnabled) { diff --git a/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala b/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala index f99291553b7b8..690f927e938c3 100644 --- a/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala +++ b/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClientSchedulerBackend.scala @@ -74,8 +74,7 @@ private[spark] class YarnClientSchedulerBackend( ("--executor-memory", "SPARK_EXECUTOR_MEMORY", "spark.executor.memory"), ("--executor-cores", "SPARK_WORKER_CORES", "spark.executor.cores"), ("--executor-cores", "SPARK_EXECUTOR_CORES", "spark.executor.cores"), - ("--queue", "SPARK_YARN_QUEUE", "spark.yarn.queue"), - ("--name", "SPARK_YARN_APP_NAME", "spark.app.name") + ("--queue", "SPARK_YARN_QUEUE", "spark.yarn.queue") ) // Warn against the following deprecated environment variables: env var -> suggestion val deprecatedEnvVars = Map( @@ -86,18 +85,22 @@ private[spark] class YarnClientSchedulerBackend( // Do the same for deprecated properties: property -> suggestion val deprecatedProps = Map("spark.master.memory" -> "--driver-memory through spark-submit") optionTuples.foreach { case (optionName, envVar, sparkProp) => - if (System.getenv(envVar) != null) { - extraArgs += (optionName, System.getenv(envVar)) - if (deprecatedEnvVars.contains(envVar)) { - logWarning(s"NOTE: $envVar is deprecated. Use ${deprecatedEnvVars(envVar)} instead.") - } - } else if (sc.getConf.contains(sparkProp)) { + if (sc.getConf.contains(sparkProp)) { extraArgs += (optionName, sc.getConf.get(sparkProp)) if (deprecatedProps.contains(sparkProp)) { logWarning(s"NOTE: $sparkProp is deprecated. Use ${deprecatedProps(sparkProp)} instead.") } + } else if (System.getenv(envVar) != null) { + extraArgs += (optionName, System.getenv(envVar)) + if (deprecatedEnvVars.contains(envVar)) { + logWarning(s"NOTE: $envVar is deprecated. Use ${deprecatedEnvVars(envVar)} instead.") + } } } + // The app name is a special case because "spark.app.name" is required of all applications. + // As a result, the corresponding "SPARK_YARN_APP_NAME" is already handled preemptively in + // SparkSubmitArguments if "spark.app.name" is not explicitly set by the user. (SPARK-5222) + sc.getConf.getOption("spark.app.name").foreach(v => extraArgs += ("--name", v)) extraArgs } From 39e333ec4350ddafe29ee0958c37eec07bec85df Mon Sep 17 00:00:00 2001 From: uncleGen Date: Tue, 13 Jan 2015 10:07:19 -0800 Subject: [PATCH 241/320] [SPARK-5131][Streaming][DOC]: There is a discrepancy in WAL implementation and configuration doc. There is a discrepancy in WAL implementation and configuration doc. Author: uncleGen Closes #3930 from uncleGen/master-clean-doc and squashes the following commits: 3a4245f [uncleGen] doc typo 8e407d3 [uncleGen] doc typo --- docs/configuration.md | 2 +- docs/streaming-programming-guide.md | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/configuration.md b/docs/configuration.md index f292bfbb7dcd6..673cdb371a512 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -1228,7 +1228,7 @@ Apart from these, the following properties are also available, and may be useful
    spark.streaming.receiver.writeAheadLogs.enablespark.streaming.receiver.writeAheadLog.enable false Enable write ahead logs for receivers. All the input data received through receivers diff --git a/docs/streaming-programming-guide.md b/docs/streaming-programming-guide.md index 01450efe35e55..e37a2bb37b9a4 100644 --- a/docs/streaming-programming-guide.md +++ b/docs/streaming-programming-guide.md @@ -1574,7 +1574,7 @@ To run a Spark Streaming applications, you need to have the following. recovery, thus ensuring zero data loss (discussed in detail in the [Fault-tolerance Semantics](#fault-tolerance-semantics) section). This can be enabled by setting the [configuration parameter](configuration.html#spark-streaming) - `spark.streaming.receiver.writeAheadLogs.enable` to `true`. However, these stronger semantics may + `spark.streaming.receiver.writeAheadLog.enable` to `true`. However, these stronger semantics may come at the cost of the receiving throughput of individual receivers. This can be corrected by running [more receivers in parallel](#level-of-parallelism-in-data-receiving) to increase aggregate throughput. Additionally, it is recommended that the replication of the From 8ead999fd627b12837fb2f082a0e76e9d121d269 Mon Sep 17 00:00:00 2001 From: Davies Liu Date: Tue, 13 Jan 2015 12:50:31 -0800 Subject: [PATCH 242/320] [SPARK-5223] [MLlib] [PySpark] fix MapConverter and ListConverter in MLlib It will introduce problems if the object in dict/list/tuple can not support by py4j, such as Vector. Also, pickle may have better performance for larger object (less RPC). In some cases that the object in dict/list can not be pickled (such as JavaObject), we should still use MapConvert/ListConvert. This PR should be ported into branch-1.2 Author: Davies Liu Closes #4023 from davies/listconvert and squashes the following commits: 55d4ab2 [Davies Liu] fix MapConverter and ListConverter in MLlib --- python/pyspark/mllib/common.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/python/pyspark/mllib/common.py b/python/pyspark/mllib/common.py index 33c49e2399908..3c5ee66cd8b64 100644 --- a/python/pyspark/mllib/common.py +++ b/python/pyspark/mllib/common.py @@ -18,7 +18,7 @@ import py4j.protocol from py4j.protocol import Py4JJavaError from py4j.java_gateway import JavaObject -from py4j.java_collections import MapConverter, ListConverter, JavaArray, JavaList +from py4j.java_collections import ListConverter, JavaArray, JavaList from pyspark import RDD, SparkContext from pyspark.serializers import PickleSerializer, AutoBatchedSerializer @@ -70,9 +70,7 @@ def _py2java(sc, obj): obj = _to_java_object_rdd(obj) elif isinstance(obj, SparkContext): obj = obj._jsc - elif isinstance(obj, dict): - obj = MapConverter().convert(obj, sc._gateway._gateway_client) - elif isinstance(obj, (list, tuple)): + elif isinstance(obj, list) and (obj or isinstance(obj[0], JavaObject)): obj = ListConverter().convert(obj, sc._gateway._gateway_client) elif isinstance(obj, JavaObject): pass From 6463e0b9e8067cce70602c5c9006a2546856a9d6 Mon Sep 17 00:00:00 2001 From: Yin Huai Date: Tue, 13 Jan 2015 13:01:27 -0800 Subject: [PATCH 243/320] [SPARK-4912][SQL] Persistent tables for the Spark SQL data sources api With changes in this PR, users can persist metadata of tables created based on the data source API in metastore through DDLs. Author: Yin Huai Author: Michael Armbrust Closes #3960 from yhuai/persistantTablesWithSchema2 and squashes the following commits: 069c235 [Yin Huai] Make exception messages user friendly. c07cbc6 [Yin Huai] Get the location of test file in a correct way. 4456e98 [Yin Huai] Test data. 5315dfc [Yin Huai] rxin's comments. 7fc4b56 [Yin Huai] Add DDLStrategy and HiveDDLStrategy to plan DDLs based on the data source API. aeaf4b3 [Yin Huai] Add comments. 06f9b0c [Yin Huai] Revert unnecessary changes. feb88aa [Yin Huai] Merge remote-tracking branch 'apache/master' into persistantTablesWithSchema2 172db80 [Yin Huai] Fix unit test. 49bf1ac [Yin Huai] Unit tests. 8f8f1a1 [Yin Huai] [SPARK-4574][SQL] Adding support for defining schema in foreign DDL commands. #3431 f47fda1 [Yin Huai] Unit tests. 2b59723 [Michael Armbrust] Set external when creating tables c00bb1b [Michael Armbrust] Don't use reflection to read options 1ea6e7b [Michael Armbrust] Don't fail when trying to uncache a table that doesn't exist 6edc710 [Michael Armbrust] Add tests. d7da491 [Michael Armbrust] First draft of persistent tables. --- .../org/apache/spark/sql/SQLContext.scala | 1 + .../spark/sql/execution/SparkStrategies.scala | 14 + .../apache/spark/sql/execution/commands.scala | 3 +- .../org/apache/spark/sql/sources/ddl.scala | 53 ++-- .../apache/spark/sql/sources/interfaces.scala | 17 +- .../spark/sql/sources/TableScanSuite.scala | 30 +++ .../apache/spark/sql/hive/HiveContext.scala | 12 + .../spark/sql/hive/HiveMetastoreCatalog.scala | 79 +++++- .../spark/sql/hive/HiveStrategies.scala | 11 + .../org/apache/spark/sql/hive/TestHive.scala | 1 + .../spark/sql/hive/execution/commands.scala | 21 ++ sql/hive/src/test/resources/sample.json | 2 + .../sql/hive/MetastoreDataSourcesSuite.scala | 244 ++++++++++++++++++ .../sql/hive/execution/HiveQuerySuite.scala | 1 - 14 files changed, 461 insertions(+), 28 deletions(-) create mode 100644 sql/hive/src/test/resources/sample.json create mode 100644 sql/hive/src/test/scala/org/apache/spark/sql/hive/MetastoreDataSourcesSuite.scala diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala index 6c575dd727b46..e7021cc3366ca 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala @@ -330,6 +330,7 @@ class SQLContext(@transient val sparkContext: SparkContext) def strategies: Seq[Strategy] = extraStrategies ++ ( DataSourceStrategy :: + DDLStrategy :: TakeOrdered :: HashAggregation :: LeftSemiJoin :: diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala index 99b6611d3bbcf..d91b1fbc69834 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala @@ -17,6 +17,7 @@ package org.apache.spark.sql.execution +import org.apache.spark.sql.sources.{CreateTempTableUsing, CreateTableUsing} import org.apache.spark.sql.{SQLContext, Strategy, execution} import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.planning._ @@ -310,4 +311,17 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { case _ => Nil } } + + object DDLStrategy extends Strategy { + def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match { + case CreateTableUsing(tableName, userSpecifiedSchema, provider, true, options) => + ExecutedCommand( + CreateTempTableUsing(tableName, userSpecifiedSchema, provider, options)) :: Nil + + case CreateTableUsing(tableName, userSpecifiedSchema, provider, false, options) => + sys.error("Tables created with SQLContext must be TEMPORARY. Use a HiveContext instead.") + + case _ => Nil + } + } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala index 0d765c4c92f85..df8e61615104c 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala @@ -177,7 +177,6 @@ case class DescribeCommand( override val output: Seq[Attribute]) extends RunnableCommand { override def run(sqlContext: SQLContext) = { - Row("# Registered as a temporary table", null, null) +: - child.output.map(field => Row(field.name, field.dataType.toString, null)) + child.output.map(field => Row(field.name, field.dataType.toString, null)) } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala index fe2c4d8436b2b..f8741e0082098 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala @@ -92,21 +92,21 @@ private[sql] class DDLParser extends StandardTokenParsers with PackratParsers wi protected lazy val ddl: Parser[LogicalPlan] = createTable /** - * `CREATE TEMPORARY TABLE avroTable + * `CREATE [TEMPORARY] TABLE avroTable * USING org.apache.spark.sql.avro * OPTIONS (path "../hive/src/test/resources/data/files/episodes.avro")` * or - * `CREATE TEMPORARY TABLE avroTable(intField int, stringField string...) + * `CREATE [TEMPORARY] TABLE avroTable(intField int, stringField string...) * USING org.apache.spark.sql.avro * OPTIONS (path "../hive/src/test/resources/data/files/episodes.avro")` */ protected lazy val createTable: Parser[LogicalPlan] = ( - CREATE ~ TEMPORARY ~ TABLE ~> ident + (CREATE ~> TEMPORARY.? <~ TABLE) ~ ident ~ (tableCols).? ~ (USING ~> className) ~ (OPTIONS ~> options) ^^ { - case tableName ~ columns ~ provider ~ opts => + case temp ~ tableName ~ columns ~ provider ~ opts => val userSpecifiedSchema = columns.flatMap(fields => Some(StructType(fields))) - CreateTableUsing(tableName, userSpecifiedSchema, provider, opts) + CreateTableUsing(tableName, userSpecifiedSchema, provider, temp.isDefined, opts) } ) @@ -175,13 +175,12 @@ private[sql] class DDLParser extends StandardTokenParsers with PackratParsers wi primitiveType } -private[sql] case class CreateTableUsing( - tableName: String, - userSpecifiedSchema: Option[StructType], - provider: String, - options: Map[String, String]) extends RunnableCommand { - - def run(sqlContext: SQLContext) = { +object ResolvedDataSource { + def apply( + sqlContext: SQLContext, + userSpecifiedSchema: Option[StructType], + provider: String, + options: Map[String, String]): ResolvedDataSource = { val loader = Utils.getContextOrSparkClassLoader val clazz: Class[_] = try loader.loadClass(provider) catch { case cnf: java.lang.ClassNotFoundException => @@ -199,22 +198,44 @@ private[sql] case class CreateTableUsing( .asInstanceOf[org.apache.spark.sql.sources.SchemaRelationProvider] .createRelation(sqlContext, new CaseInsensitiveMap(options), schema) case _ => - sys.error(s"${clazz.getCanonicalName} should extend SchemaRelationProvider.") + sys.error(s"${clazz.getCanonicalName} does not allow user-specified schemas.") } } case None => { clazz.newInstance match { - case dataSource: org.apache.spark.sql.sources.RelationProvider => + case dataSource: org.apache.spark.sql.sources.RelationProvider => dataSource .asInstanceOf[org.apache.spark.sql.sources.RelationProvider] .createRelation(sqlContext, new CaseInsensitiveMap(options)) case _ => - sys.error(s"${clazz.getCanonicalName} should extend RelationProvider.") + sys.error(s"A schema needs to be specified when using ${clazz.getCanonicalName}.") } } } - sqlContext.baseRelationToSchemaRDD(relation).registerTempTable(tableName) + new ResolvedDataSource(clazz, relation) + } +} + +private[sql] case class ResolvedDataSource(provider: Class[_], relation: BaseRelation) + +private[sql] case class CreateTableUsing( + tableName: String, + userSpecifiedSchema: Option[StructType], + provider: String, + temporary: Boolean, + options: Map[String, String]) extends Command + +private [sql] case class CreateTempTableUsing( + tableName: String, + userSpecifiedSchema: Option[StructType], + provider: String, + options: Map[String, String]) extends RunnableCommand { + + def run(sqlContext: SQLContext) = { + val resolved = ResolvedDataSource(sqlContext, userSpecifiedSchema, provider, options) + + sqlContext.baseRelationToSchemaRDD(resolved.relation).registerTempTable(tableName) Seq.empty } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala index 990f7e0e74bcf..2a7be23e37c74 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala @@ -24,8 +24,8 @@ import org.apache.spark.sql.catalyst.expressions.{Expression, Attribute} /** * ::DeveloperApi:: * Implemented by objects that produce relations for a specific kind of data source. When - * Spark SQL is given a DDL operation with a USING clause specified, this interface is used to - * pass in the parameters specified by a user. + * Spark SQL is given a DDL operation with a USING clause specified (to specify the implemented + * RelationProvider), this interface is used to pass in the parameters specified by a user. * * Users may specify the fully qualified class name of a given data source. When that class is * not found Spark SQL will append the class name `DefaultSource` to the path, allowing for @@ -46,10 +46,10 @@ trait RelationProvider { /** * ::DeveloperApi:: - * Implemented by objects that produce relations for a specific kind of data source. When - * Spark SQL is given a DDL operation with - * 1. USING clause: to specify the implemented SchemaRelationProvider - * 2. User defined schema: users can define schema optionally when create table + * Implemented by objects that produce relations for a specific kind of data source + * with a given schema. When Spark SQL is given a DDL operation with a USING clause specified ( + * to specify the implemented SchemaRelationProvider) and a user defined schema, this interface + * is used to pass in the parameters specified by a user. * * Users may specify the fully qualified class name of a given data source. When that class is * not found Spark SQL will append the class name `DefaultSource` to the path, allowing for @@ -57,6 +57,11 @@ trait RelationProvider { * data source 'org.apache.spark.sql.json.DefaultSource' * * A new instance of this class with be instantiated each time a DDL call is made. + * + * The difference between a [[RelationProvider]] and a [[SchemaRelationProvider]] is that + * users need to provide a schema when using a SchemaRelationProvider. + * A relation provider can inherits both [[RelationProvider]] and [[SchemaRelationProvider]] + * if it can support both schema inference and user-specified schemas. */ @DeveloperApi trait SchemaRelationProvider { diff --git a/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala index 605190f5ae6a2..a1d2468b2573c 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala @@ -314,4 +314,34 @@ class TableScanSuite extends DataSourceTest { sql("SELECT * FROM oneToTenDef"), (1 to 10).map(Row(_)).toSeq) } + + test("exceptions") { + // Make sure we do throw correct exception when users use a relation provider that + // only implements the RelationProvier or the SchemaRelationProvider. + val schemaNotAllowed = intercept[Exception] { + sql( + """ + |CREATE TEMPORARY TABLE relationProvierWithSchema (i int) + |USING org.apache.spark.sql.sources.SimpleScanSource + |OPTIONS ( + | From '1', + | To '10' + |) + """.stripMargin) + } + assert(schemaNotAllowed.getMessage.contains("does not allow user-specified schemas")) + + val schemaNeeded = intercept[Exception] { + sql( + """ + |CREATE TEMPORARY TABLE schemaRelationProvierWithoutSchema + |USING org.apache.spark.sql.sources.AllDataTypesScanSource + |OPTIONS ( + | From '1', + | To '10' + |) + """.stripMargin) + } + assert(schemaNeeded.getMessage.contains("A schema needs to be specified when using")) + } } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala index 02eac43b2103f..09ff4cc5ab437 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala @@ -115,6 +115,16 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { catalog.createTable("default", tableName, ScalaReflection.attributesFor[A], allowExisting) } + def refreshTable(tableName: String): Unit = { + // TODO: Database support... + catalog.refreshTable("default", tableName) + } + + protected[hive] def invalidateTable(tableName: String): Unit = { + // TODO: Database support... + catalog.invalidateTable("default", tableName) + } + /** * Analyzes the given table in the current database to generate statistics, which will be * used in query optimizations. @@ -340,6 +350,8 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { override def strategies: Seq[Strategy] = extraStrategies ++ Seq( DataSourceStrategy, HiveCommandStrategy(self), + HiveDDLStrategy, + DDLStrategy, TakeOrdered, ParquetOperations, InMemoryScans, diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala index c25288e000122..daeabb6c8bab8 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala @@ -20,10 +20,11 @@ package org.apache.spark.sql.hive import java.io.IOException import java.util.{List => JList} +import com.google.common.cache.{LoadingCache, CacheLoader, CacheBuilder} + import org.apache.hadoop.util.ReflectionUtils import org.apache.hadoop.hive.metastore.TableType -import org.apache.hadoop.hive.metastore.api.FieldSchema -import org.apache.hadoop.hive.metastore.api.{Table => TTable, Partition => TPartition} +import org.apache.hadoop.hive.metastore.api.{Table => TTable, Partition => TPartition, FieldSchema} import org.apache.hadoop.hive.ql.metadata.{Hive, Partition, Table, HiveException} import org.apache.hadoop.hive.ql.metadata.InvalidTableException import org.apache.hadoop.hive.ql.plan.CreateTableDesc @@ -39,6 +40,7 @@ import org.apache.spark.sql.catalyst.plans.logical import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.rules._ import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.sources.{LogicalRelation, ResolvedDataSource} import org.apache.spark.util.Utils /* Implicit conversions */ @@ -50,8 +52,76 @@ private[hive] class HiveMetastoreCatalog(hive: HiveContext) extends Catalog with /** Connection to hive metastore. Usages should lock on `this`. */ protected[hive] val client = Hive.get(hive.hiveconf) + // TODO: Use this everywhere instead of tuples or databaseName, tableName,. + /** A fully qualified identifier for a table (i.e., database.tableName) */ + case class QualifiedTableName(database: String, name: String) { + def toLowerCase = QualifiedTableName(database.toLowerCase, name.toLowerCase) + } + + /** A cache of Spark SQL data source tables that have been accessed. */ + protected[hive] val cachedDataSourceTables: LoadingCache[QualifiedTableName, LogicalPlan] = { + val cacheLoader = new CacheLoader[QualifiedTableName, LogicalPlan]() { + override def load(in: QualifiedTableName): LogicalPlan = { + logDebug(s"Creating new cached data source for $in") + val table = client.getTable(in.database, in.name) + val schemaString = table.getProperty("spark.sql.sources.schema") + val userSpecifiedSchema = + if (schemaString == null) { + None + } else { + Some(DataType.fromJson(schemaString).asInstanceOf[StructType]) + } + // It does not appear that the ql client for the metastore has a way to enumerate all the + // SerDe properties directly... + val options = table.getTTable.getSd.getSerdeInfo.getParameters.toMap + + val resolvedRelation = + ResolvedDataSource( + hive, + userSpecifiedSchema, + table.getProperty("spark.sql.sources.provider"), + options) + + LogicalRelation(resolvedRelation.relation) + } + } + + CacheBuilder.newBuilder().maximumSize(1000).build(cacheLoader) + } + + def refreshTable(databaseName: String, tableName: String): Unit = { + cachedDataSourceTables.refresh(QualifiedTableName(databaseName, tableName).toLowerCase) + } + + def invalidateTable(databaseName: String, tableName: String): Unit = { + cachedDataSourceTables.invalidate(QualifiedTableName(databaseName, tableName).toLowerCase) + } + val caseSensitive: Boolean = false + def createDataSourceTable( + tableName: String, + userSpecifiedSchema: Option[StructType], + provider: String, + options: Map[String, String]) = { + val (dbName, tblName) = processDatabaseAndTableName("default", tableName) + val tbl = new Table(dbName, tblName) + + tbl.setProperty("spark.sql.sources.provider", provider) + if (userSpecifiedSchema.isDefined) { + tbl.setProperty("spark.sql.sources.schema", userSpecifiedSchema.get.json) + } + options.foreach { case (key, value) => tbl.setSerdeParam(key, value) } + + tbl.setProperty("EXTERNAL", "TRUE") + tbl.setTableType(TableType.EXTERNAL_TABLE) + + // create the table + synchronized { + client.createTable(tbl, false) + } + } + def tableExists(tableIdentifier: Seq[String]): Boolean = { val tableIdent = processTableIdentifier(tableIdentifier) val databaseName = tableIdent.lift(tableIdent.size - 2).getOrElse( @@ -72,7 +142,10 @@ private[hive] class HiveMetastoreCatalog(hive: HiveContext) extends Catalog with hive.sessionState.getCurrentDatabase) val tblName = tableIdent.last val table = client.getTable(databaseName, tblName) - if (table.isView) { + + if (table.getProperty("spark.sql.sources.provider") != null) { + cachedDataSourceTables(QualifiedTableName(databaseName, tblName).toLowerCase) + } else if (table.isView) { // if the unresolved relation is from hive view // parse the text into logic node. HiveQl.createPlanForView(table, alias) diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala index c439b9ebfe104..cdff82e3d04d2 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala @@ -30,6 +30,7 @@ import org.apache.spark.sql.execution._ import org.apache.spark.sql.hive import org.apache.spark.sql.hive.execution._ import org.apache.spark.sql.parquet.ParquetRelation +import org.apache.spark.sql.sources.CreateTableUsing import org.apache.spark.sql.{SQLContext, SchemaRDD, Strategy} import scala.collection.JavaConversions._ @@ -208,6 +209,16 @@ private[hive] trait HiveStrategies { } } + object HiveDDLStrategy extends Strategy { + def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match { + case CreateTableUsing(tableName, userSpecifiedSchema, provider, false, options) => + ExecutedCommand( + CreateMetastoreDataSource(tableName, userSpecifiedSchema, provider, options)) :: Nil + + case _ => Nil + } + } + case class HiveCommandStrategy(context: HiveContext) extends Strategy { def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match { case describe: DescribeCommand => diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala index 1358a0eccb353..31c7ce96398eb 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala @@ -395,6 +395,7 @@ class TestHiveContext(sc: SparkContext) extends HiveContext(sc) { clearCache() loadedTables.clear() + catalog.cachedDataSourceTables.invalidateAll() catalog.client.getAllTables("default").foreach { t => logDebug(s"Deleting table $t") val table = catalog.client.getTable("default", t) diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala index 6b733a280e6d5..e70cdeaad4c09 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala @@ -19,6 +19,7 @@ package org.apache.spark.sql.hive.execution import org.apache.spark.annotation.DeveloperApi import org.apache.spark.sql.catalyst.expressions.Row +import org.apache.spark.sql.catalyst.types.StructType import org.apache.spark.sql.execution.RunnableCommand import org.apache.spark.sql.hive.HiveContext import org.apache.spark.sql.SQLContext @@ -52,6 +53,12 @@ case class DropTable( override def run(sqlContext: SQLContext) = { val hiveContext = sqlContext.asInstanceOf[HiveContext] val ifExistsClause = if (ifExists) "IF EXISTS " else "" + try { + hiveContext.tryUncacheQuery(hiveContext.table(tableName)) + } catch { + case _: org.apache.hadoop.hive.ql.metadata.InvalidTableException => + } + hiveContext.invalidateTable(tableName) hiveContext.runSqlHive(s"DROP TABLE $ifExistsClause$tableName") hiveContext.catalog.unregisterTable(Seq(tableName)) Seq.empty[Row] @@ -85,3 +92,17 @@ case class AddFile(path: String) extends RunnableCommand { Seq.empty[Row] } } + +case class CreateMetastoreDataSource( + tableName: String, + userSpecifiedSchema: Option[StructType], + provider: String, + options: Map[String, String]) extends RunnableCommand { + + override def run(sqlContext: SQLContext) = { + val hiveContext = sqlContext.asInstanceOf[HiveContext] + hiveContext.catalog.createDataSourceTable(tableName, userSpecifiedSchema, provider, options) + + Seq.empty[Row] + } +} diff --git a/sql/hive/src/test/resources/sample.json b/sql/hive/src/test/resources/sample.json new file mode 100644 index 0000000000000..a2c2ffd5e0330 --- /dev/null +++ b/sql/hive/src/test/resources/sample.json @@ -0,0 +1,2 @@ +{"a" : "2" ,"b" : "blah", "c_!@(3)":1} +{"" : {"d!" : [4, 5], "=" : [{"Dd2": null}, {"Dd2" : true}]}} diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/MetastoreDataSourcesSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/MetastoreDataSourcesSuite.scala new file mode 100644 index 0000000000000..ec9ebb4a775a3 --- /dev/null +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/MetastoreDataSourcesSuite.scala @@ -0,0 +1,244 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.hive + +import java.io.File + +import org.scalatest.BeforeAndAfterEach + +import org.apache.commons.io.FileUtils + +import org.apache.spark.sql._ +import org.apache.spark.util.Utils + +/* Implicits */ +import org.apache.spark.sql.hive.test.TestHive._ + +/** + * Tests for persisting tables created though the data sources API into the metastore. + */ +class MetastoreDataSourcesSuite extends QueryTest with BeforeAndAfterEach { + override def afterEach(): Unit = { + reset() + } + + val filePath = Utils.getSparkClassLoader.getResource("sample.json").getFile + + test ("persistent JSON table") { + sql( + s""" + |CREATE TABLE jsonTable + |USING org.apache.spark.sql.json.DefaultSource + |OPTIONS ( + | path '${filePath}' + |) + """.stripMargin) + + checkAnswer( + sql("SELECT * FROM jsonTable"), + jsonFile(filePath).collect().toSeq) + } + + test ("persistent JSON table with a user specified schema") { + sql( + s""" + |CREATE TABLE jsonTable ( + |a string, + |b String, + |`c_!@(3)` int, + |`` Struct<`d!`:array, `=`:array>>) + |USING org.apache.spark.sql.json.DefaultSource + |OPTIONS ( + | path '${filePath}' + |) + """.stripMargin) + + jsonFile(filePath).registerTempTable("expectedJsonTable") + + checkAnswer( + sql("SELECT a, b, `c_!@(3)`, ``.`d!`, ``.`=` FROM jsonTable"), + sql("SELECT a, b, `c_!@(3)`, ``.`d!`, ``.`=` FROM expectedJsonTable").collect().toSeq) + } + + test ("persistent JSON table with a user specified schema with a subset of fields") { + // This works because JSON objects are self-describing and JSONRelation can get needed + // field values based on field names. + sql( + s""" + |CREATE TABLE jsonTable (`` Struct<`=`:array>>, b String) + |USING org.apache.spark.sql.json.DefaultSource + |OPTIONS ( + | path '${filePath}' + |) + """.stripMargin) + + val innerStruct = StructType( + StructField("=", ArrayType(StructType(StructField("Dd2", BooleanType, true) :: Nil))) :: Nil) + val expectedSchema = StructType( + StructField("", innerStruct, true) :: + StructField("b", StringType, true) :: Nil) + + assert(expectedSchema == table("jsonTable").schema) + + jsonFile(filePath).registerTempTable("expectedJsonTable") + + checkAnswer( + sql("SELECT b, ``.`=` FROM jsonTable"), + sql("SELECT b, ``.`=` FROM expectedJsonTable").collect().toSeq) + } + + test("resolve shortened provider names") { + sql( + s""" + |CREATE TABLE jsonTable + |USING org.apache.spark.sql.json + |OPTIONS ( + | path '${filePath}' + |) + """.stripMargin) + + checkAnswer( + sql("SELECT * FROM jsonTable"), + jsonFile(filePath).collect().toSeq) + } + + test("drop table") { + sql( + s""" + |CREATE TABLE jsonTable + |USING org.apache.spark.sql.json + |OPTIONS ( + | path '${filePath}' + |) + """.stripMargin) + + checkAnswer( + sql("SELECT * FROM jsonTable"), + jsonFile(filePath).collect().toSeq) + + sql("DROP TABLE jsonTable") + + intercept[Exception] { + sql("SELECT * FROM jsonTable").collect() + } + } + + test("check change without refresh") { + val tempDir = File.createTempFile("sparksql", "json") + tempDir.delete() + sparkContext.parallelize(("a", "b") :: Nil).toJSON.saveAsTextFile(tempDir.getCanonicalPath) + + sql( + s""" + |CREATE TABLE jsonTable + |USING org.apache.spark.sql.json + |OPTIONS ( + | path '${tempDir.getCanonicalPath}' + |) + """.stripMargin) + + checkAnswer( + sql("SELECT * FROM jsonTable"), + ("a", "b") :: Nil) + + FileUtils.deleteDirectory(tempDir) + sparkContext.parallelize(("a1", "b1", "c1") :: Nil).toJSON.saveAsTextFile(tempDir.getCanonicalPath) + + // Schema is cached so the new column does not show. The updated values in existing columns + // will show. + checkAnswer( + sql("SELECT * FROM jsonTable"), + ("a1", "b1") :: Nil) + + refreshTable("jsonTable") + + // Check that the refresh worked + checkAnswer( + sql("SELECT * FROM jsonTable"), + ("a1", "b1", "c1") :: Nil) + FileUtils.deleteDirectory(tempDir) + } + + test("drop, change, recreate") { + val tempDir = File.createTempFile("sparksql", "json") + tempDir.delete() + sparkContext.parallelize(("a", "b") :: Nil).toJSON.saveAsTextFile(tempDir.getCanonicalPath) + + sql( + s""" + |CREATE TABLE jsonTable + |USING org.apache.spark.sql.json + |OPTIONS ( + | path '${tempDir.getCanonicalPath}' + |) + """.stripMargin) + + checkAnswer( + sql("SELECT * FROM jsonTable"), + ("a", "b") :: Nil) + + FileUtils.deleteDirectory(tempDir) + sparkContext.parallelize(("a", "b", "c") :: Nil).toJSON.saveAsTextFile(tempDir.getCanonicalPath) + + sql("DROP TABLE jsonTable") + + sql( + s""" + |CREATE TABLE jsonTable + |USING org.apache.spark.sql.json + |OPTIONS ( + | path '${tempDir.getCanonicalPath}' + |) + """.stripMargin) + + // New table should reflect new schema. + checkAnswer( + sql("SELECT * FROM jsonTable"), + ("a", "b", "c") :: Nil) + FileUtils.deleteDirectory(tempDir) + } + + test("invalidate cache and reload") { + sql( + s""" + |CREATE TABLE jsonTable (`c_!@(3)` int) + |USING org.apache.spark.sql.json.DefaultSource + |OPTIONS ( + | path '${filePath}' + |) + """.stripMargin) + + jsonFile(filePath).registerTempTable("expectedJsonTable") + + checkAnswer( + sql("SELECT * FROM jsonTable"), + sql("SELECT `c_!@(3)` FROM expectedJsonTable").collect().toSeq) + + // Discard the cached relation. + invalidateTable("jsonTable") + + checkAnswer( + sql("SELECT * FROM jsonTable"), + sql("SELECT `c_!@(3)` FROM expectedJsonTable").collect().toSeq) + + invalidateTable("jsonTable") + val expectedSchema = StructType(StructField("c_!@(3)", IntegerType, true) :: Nil) + + assert(expectedSchema == table("jsonTable").schema) + } +} diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala index 700a45edb11d6..4decd1548534b 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala @@ -623,7 +623,6 @@ class HiveQuerySuite extends HiveComparisonTest with BeforeAndAfter { assertResult( Array( - Array("# Registered as a temporary table", null, null), Array("a", "IntegerType", null), Array("b", "StringType", null)) ) { From 14e3f114efb906937b2d7b7ac04484b2814a3b48 Mon Sep 17 00:00:00 2001 From: Reynold Xin Date: Tue, 13 Jan 2015 13:30:35 -0800 Subject: [PATCH 244/320] [SPARK-5168] Make SQLConf a field rather than mixin in SQLContext This change should be binary and source backward compatible since we didn't change any user facing APIs. Author: Reynold Xin Closes #3965 from rxin/SPARK-5168-sqlconf and squashes the following commits: 42eec09 [Reynold Xin] Fix default conf value. 0ef86cc [Reynold Xin] Fix constructor ordering. 4d7f910 [Reynold Xin] Properly override config. ccc8e6a [Reynold Xin] [SPARK-5168] Make SQLConf a field rather than mixin in SQLContext --- .../org/apache/spark/sql/CacheManager.scala | 4 +- .../scala/org/apache/spark/sql/SQLConf.scala | 2 +- .../org/apache/spark/sql/SQLContext.scala | 40 +++++++++++++++---- .../spark/sql/api/java/JavaSQLContext.scala | 6 +-- .../columnar/InMemoryColumnarTableScan.scala | 4 +- .../apache/spark/sql/execution/Exchange.scala | 2 +- .../spark/sql/execution/ExistingRDD.scala | 4 +- .../spark/sql/execution/SparkPlan.scala | 2 +- .../spark/sql/execution/SparkStrategies.scala | 18 ++++----- .../apache/spark/sql/execution/commands.scala | 2 +- .../execution/joins/BroadcastHashJoin.scala | 2 +- .../apache/spark/sql/json/JSONRelation.scala | 4 +- .../spark/sql/parquet/ParquetRelation.scala | 7 ++-- .../spark/sql/parquet/ParquetTest.scala | 2 +- .../apache/spark/sql/parquet/newParquet.scala | 4 +- .../apache/spark/sql/sources/interfaces.scala | 2 +- .../spark/sql/test/TestSQLContext.scala | 5 ++- .../org/apache/spark/sql/JoinSuite.scala | 2 +- .../org/apache/spark/sql/SQLConfSuite.scala | 10 ++--- .../org/apache/spark/sql/SQLQuerySuite.scala | 10 ++--- .../columnar/InMemoryColumnarQuerySuite.scala | 3 +- .../columnar/PartitionBatchPruningSuite.scala | 4 +- .../spark/sql/execution/PlannerSuite.scala | 4 +- .../org/apache/spark/sql/json/JsonSuite.scala | 2 +- .../spark/sql/parquet/ParquetIOSuite.scala | 4 +- .../spark/sql/parquet/ParquetQuerySuite.scala | 14 +++---- .../execution/HiveCompatibilitySuite.scala | 4 +- .../apache/spark/sql/hive/HiveContext.scala | 11 ++--- .../spark/sql/hive/HiveMetastoreCatalog.scala | 2 +- .../org/apache/spark/sql/hive/TestHive.scala | 6 ++- .../sql/hive/api/java/JavaHiveContext.scala | 6 +-- .../spark/sql/hive/StatisticsSuite.scala | 20 +++++----- .../sql/hive/execution/HiveQuerySuite.scala | 4 +- 33 files changed, 124 insertions(+), 92 deletions(-) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/CacheManager.scala b/sql/core/src/main/scala/org/apache/spark/sql/CacheManager.scala index 3c9439b2e9a52..e715d9434a2ab 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/CacheManager.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/CacheManager.scala @@ -91,8 +91,8 @@ private[sql] trait CacheManager { CachedData( planToCache, InMemoryRelation( - useCompression, - columnBatchSize, + conf.useCompression, + conf.columnBatchSize, storageLevel, query.queryExecution.executedPlan, tableName)) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala index f5bf935522dad..206d16f5b34f5 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala @@ -61,7 +61,7 @@ private[spark] object SQLConf { * * SQLConf is thread-safe (internally synchronized, so safe to be used in multiple threads). */ -private[sql] trait SQLConf { +private[sql] class SQLConf { import SQLConf._ /** Only low degree of contention is expected for conf, thus NOT using ConcurrentHashMap. */ diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala index e7021cc3366ca..d8efce0cb43eb 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala @@ -17,6 +17,9 @@ package org.apache.spark.sql +import java.util.Properties + +import scala.collection.immutable import scala.language.implicitConversions import scala.reflect.runtime.universe.TypeTag @@ -49,7 +52,6 @@ import org.apache.spark.sql.sources.{DataSourceStrategy, BaseRelation, DDLParser @AlphaComponent class SQLContext(@transient val sparkContext: SparkContext) extends org.apache.spark.Logging - with SQLConf with CacheManager with ExpressionConversions with UDFRegistration @@ -57,6 +59,30 @@ class SQLContext(@transient val sparkContext: SparkContext) self => + // Note that this is a lazy val so we can override the default value in subclasses. + private[sql] lazy val conf: SQLConf = new SQLConf + + /** Set Spark SQL configuration properties. */ + def setConf(props: Properties): Unit = conf.setConf(props) + + /** Set the given Spark SQL configuration property. */ + def setConf(key: String, value: String): Unit = conf.setConf(key, value) + + /** Return the value of Spark SQL configuration property for the given key. */ + def getConf(key: String): String = conf.getConf(key) + + /** + * Return the value of Spark SQL configuration property for the given key. If the key is not set + * yet, return `defaultValue`. + */ + def getConf(key: String, defaultValue: String): String = conf.getConf(key, defaultValue) + + /** + * Return all the configuration properties that have been set (i.e. not the default). + * This creates a new copy of the config properties in the form of a Map. + */ + def getAllConfs: immutable.Map[String, String] = conf.getAllConfs + @transient protected[sql] lazy val catalog: Catalog = new SimpleCatalog(true) @@ -212,7 +238,7 @@ class SQLContext(@transient val sparkContext: SparkContext) */ @Experimental def jsonRDD(json: RDD[String], schema: StructType): SchemaRDD = { - val columnNameOfCorruptJsonRecord = columnNameOfCorruptRecord + val columnNameOfCorruptJsonRecord = conf.columnNameOfCorruptRecord val appliedSchema = Option(schema).getOrElse( JsonRDD.nullTypeToStringType( @@ -226,7 +252,7 @@ class SQLContext(@transient val sparkContext: SparkContext) */ @Experimental def jsonRDD(json: RDD[String], samplingRatio: Double): SchemaRDD = { - val columnNameOfCorruptJsonRecord = columnNameOfCorruptRecord + val columnNameOfCorruptJsonRecord = conf.columnNameOfCorruptRecord val appliedSchema = JsonRDD.nullTypeToStringType( JsonRDD.inferSchema(json, samplingRatio, columnNameOfCorruptJsonRecord)) @@ -299,10 +325,10 @@ class SQLContext(@transient val sparkContext: SparkContext) * @group userf */ def sql(sqlText: String): SchemaRDD = { - if (dialect == "sql") { + if (conf.dialect == "sql") { new SchemaRDD(this, parseSql(sqlText)) } else { - sys.error(s"Unsupported SQL dialect: $dialect") + sys.error(s"Unsupported SQL dialect: ${conf.dialect}") } } @@ -323,9 +349,9 @@ class SQLContext(@transient val sparkContext: SparkContext) val sqlContext: SQLContext = self - def codegenEnabled = self.codegenEnabled + def codegenEnabled = self.conf.codegenEnabled - def numPartitions = self.numShufflePartitions + def numPartitions = self.conf.numShufflePartitions def strategies: Seq[Strategy] = extraStrategies ++ ( diff --git a/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSQLContext.scala index 8884204e5079f..7f868cd4afca4 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSQLContext.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSQLContext.scala @@ -52,7 +52,7 @@ class JavaSQLContext(val sqlContext: SQLContext) extends UDFRegistration { * @group userf */ def sql(sqlText: String): JavaSchemaRDD = { - if (sqlContext.dialect == "sql") { + if (sqlContext.conf.dialect == "sql") { new JavaSchemaRDD(sqlContext, sqlContext.parseSql(sqlText)) } else { sys.error(s"Unsupported SQL dialect: $sqlContext.dialect") @@ -164,7 +164,7 @@ class JavaSQLContext(val sqlContext: SQLContext) extends UDFRegistration { * It goes through the entire dataset once to determine the schema. */ def jsonRDD(json: JavaRDD[String]): JavaSchemaRDD = { - val columnNameOfCorruptJsonRecord = sqlContext.columnNameOfCorruptRecord + val columnNameOfCorruptJsonRecord = sqlContext.conf.columnNameOfCorruptRecord val appliedScalaSchema = JsonRDD.nullTypeToStringType( JsonRDD.inferSchema(json.rdd, 1.0, columnNameOfCorruptJsonRecord)) @@ -182,7 +182,7 @@ class JavaSQLContext(val sqlContext: SQLContext) extends UDFRegistration { */ @Experimental def jsonRDD(json: JavaRDD[String], schema: StructType): JavaSchemaRDD = { - val columnNameOfCorruptJsonRecord = sqlContext.columnNameOfCorruptRecord + val columnNameOfCorruptJsonRecord = sqlContext.conf.columnNameOfCorruptRecord val appliedScalaSchema = Option(asScalaDataType(schema)).getOrElse( JsonRDD.nullTypeToStringType( diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala index 1e432485c4c29..065fae3c83df1 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/InMemoryColumnarTableScan.scala @@ -82,7 +82,7 @@ private[sql] case class InMemoryRelation( if (batchStats.value.isEmpty) { // Underlying columnar RDD hasn't been materialized, no useful statistics information // available, return the default statistics. - Statistics(sizeInBytes = child.sqlContext.defaultSizeInBytes) + Statistics(sizeInBytes = child.sqlContext.conf.defaultSizeInBytes) } else { // Underlying columnar RDD has been materialized, required information has also been collected // via the `batchStats` accumulator, compute the final statistics, and update `_statistics`. @@ -233,7 +233,7 @@ private[sql] case class InMemoryColumnarTableScan( val readPartitions = sparkContext.accumulator(0) val readBatches = sparkContext.accumulator(0) - private val inMemoryPartitionPruningEnabled = sqlContext.inMemoryPartitionPruning + private val inMemoryPartitionPruningEnabled = sqlContext.conf.inMemoryPartitionPruning override def execute() = { readPartitions.setValue(0) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/Exchange.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/Exchange.scala index d7c811ca89022..7c0b72aab448e 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/Exchange.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/Exchange.scala @@ -123,7 +123,7 @@ case class Exchange(newPartitioning: Partitioning, child: SparkPlan) extends Una */ private[sql] case class AddExchange(sqlContext: SQLContext) extends Rule[SparkPlan] { // TODO: Determine the number of partitions. - def numPartitions = sqlContext.numShufflePartitions + def numPartitions = sqlContext.conf.numShufflePartitions def apply(plan: SparkPlan): SparkPlan = plan.transformUp { case operator: SparkPlan => diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala index d2d8cb1c62d40..069e950195302 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala @@ -69,7 +69,7 @@ case class LogicalRDD(output: Seq[Attribute], rdd: RDD[Row])(sqlContext: SQLCont @transient override lazy val statistics = Statistics( // TODO: Instead of returning a default value here, find a way to return a meaningful size // estimate for RDDs. See PR 1238 for more discussions. - sizeInBytes = BigInt(sqlContext.defaultSizeInBytes) + sizeInBytes = BigInt(sqlContext.conf.defaultSizeInBytes) ) } @@ -106,6 +106,6 @@ case class SparkLogicalPlan(alreadyPlanned: SparkPlan)(@transient sqlContext: SQ @transient override lazy val statistics = Statistics( // TODO: Instead of returning a default value here, find a way to return a meaningful size // estimate for RDDs. See PR 1238 for more discussions. - sizeInBytes = BigInt(sqlContext.defaultSizeInBytes) + sizeInBytes = BigInt(sqlContext.conf.defaultSizeInBytes) ) } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala index 017c78d2c66d4..6fecd1ff066c3 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala @@ -51,7 +51,7 @@ abstract class SparkPlan extends QueryPlan[SparkPlan] with Logging with Serializ // sqlContext will be null when we are being deserialized on the slaves. In this instance // the value of codegenEnabled will be set by the desserializer after the constructor has run. val codegenEnabled: Boolean = if (sqlContext != null) { - sqlContext.codegenEnabled + sqlContext.conf.codegenEnabled } else { false } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala index d91b1fbc69834..0652d2ff7c9ab 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala @@ -35,8 +35,8 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { object LeftSemiJoin extends Strategy with PredicateHelper { def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match { case ExtractEquiJoinKeys(LeftSemi, leftKeys, rightKeys, condition, left, right) - if sqlContext.autoBroadcastJoinThreshold > 0 && - right.statistics.sizeInBytes <= sqlContext.autoBroadcastJoinThreshold => + if sqlContext.conf.autoBroadcastJoinThreshold > 0 && + right.statistics.sizeInBytes <= sqlContext.conf.autoBroadcastJoinThreshold => val semiJoin = joins.BroadcastLeftSemiJoinHash( leftKeys, rightKeys, planLater(left), planLater(right)) condition.map(Filter(_, semiJoin)).getOrElse(semiJoin) :: Nil @@ -81,13 +81,13 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match { case ExtractEquiJoinKeys(Inner, leftKeys, rightKeys, condition, left, right) - if sqlContext.autoBroadcastJoinThreshold > 0 && - right.statistics.sizeInBytes <= sqlContext.autoBroadcastJoinThreshold => + if sqlContext.conf.autoBroadcastJoinThreshold > 0 && + right.statistics.sizeInBytes <= sqlContext.conf.autoBroadcastJoinThreshold => makeBroadcastHashJoin(leftKeys, rightKeys, left, right, condition, joins.BuildRight) case ExtractEquiJoinKeys(Inner, leftKeys, rightKeys, condition, left, right) - if sqlContext.autoBroadcastJoinThreshold > 0 && - left.statistics.sizeInBytes <= sqlContext.autoBroadcastJoinThreshold => + if sqlContext.conf.autoBroadcastJoinThreshold > 0 && + left.statistics.sizeInBytes <= sqlContext.conf.autoBroadcastJoinThreshold => makeBroadcastHashJoin(leftKeys, rightKeys, left, right, condition, joins.BuildLeft) case ExtractEquiJoinKeys(Inner, leftKeys, rightKeys, condition, left, right) => @@ -215,7 +215,7 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { InsertIntoParquetTable(table, planLater(child), overwrite) :: Nil case PhysicalOperation(projectList, filters: Seq[Expression], relation: ParquetRelation) => val prunePushedDownFilters = - if (sqlContext.parquetFilterPushDown) { + if (sqlContext.conf.parquetFilterPushDown) { (predicates: Seq[Expression]) => { // Note: filters cannot be pushed down to Parquet if they contain more complex // expressions than simple "Attribute cmp Literal" comparisons. Here we remove all @@ -237,7 +237,7 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { ParquetTableScan( _, relation, - if (sqlContext.parquetFilterPushDown) filters else Nil)) :: Nil + if (sqlContext.conf.parquetFilterPushDown) filters else Nil)) :: Nil case _ => Nil } @@ -270,7 +270,7 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { // This sort only sorts tuples within a partition. Its requiredDistribution will be // an UnspecifiedDistribution. execution.Sort(sortExprs, global = false, planLater(child)) :: Nil - case logical.Sort(sortExprs, global, child) if sqlContext.externalSortEnabled => + case logical.Sort(sortExprs, global, child) if sqlContext.conf.externalSortEnabled => execution.ExternalSort(sortExprs, global, planLater(child)):: Nil case logical.Sort(sortExprs, global, child) => execution.Sort(sortExprs, global, planLater(child)):: Nil diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala index df8e61615104c..af6b07bd6c2f4 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala @@ -94,7 +94,7 @@ case class SetCommand( logWarning( s"Property ${SQLConf.Deprecated.MAPRED_REDUCE_TASKS} is deprecated, " + s"showing ${SQLConf.SHUFFLE_PARTITIONS} instead.") - Seq(Row(s"${SQLConf.SHUFFLE_PARTITIONS}=${sqlContext.numShufflePartitions}")) + Seq(Row(s"${SQLConf.SHUFFLE_PARTITIONS}=${sqlContext.conf.numShufflePartitions}")) // Queries a single property. case Some((key, None)) => diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastHashJoin.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastHashJoin.scala index fbe1d06ed2e82..2dd22c020ef12 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastHashJoin.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastHashJoin.scala @@ -43,7 +43,7 @@ case class BroadcastHashJoin( extends BinaryNode with HashJoin { val timeout = { - val timeoutValue = sqlContext.broadcastTimeout + val timeoutValue = sqlContext.conf.broadcastTimeout if (timeoutValue < 0) { Duration.Inf } else { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/json/JSONRelation.scala b/sql/core/src/main/scala/org/apache/spark/sql/json/JSONRelation.scala index a9a6696cb15e4..f5c02224c82a0 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/json/JSONRelation.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/json/JSONRelation.scala @@ -59,8 +59,8 @@ private[sql] case class JSONRelation( JsonRDD.inferSchema( baseRDD, samplingRatio, - sqlContext.columnNameOfCorruptRecord))) + sqlContext.conf.columnNameOfCorruptRecord))) override def buildScan() = - JsonRDD.jsonStringToRow(baseRDD, schema, sqlContext.columnNameOfCorruptRecord) + JsonRDD.jsonStringToRow(baseRDD, schema, sqlContext.conf.columnNameOfCorruptRecord) } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetRelation.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetRelation.scala index 2835dc3408b96..cde5160149e9c 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetRelation.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetRelation.scala @@ -65,7 +65,7 @@ private[sql] case class ParquetRelation( ParquetTypesConverter.readSchemaFromFile( new Path(path.split(",").head), conf, - sqlContext.isParquetBinaryAsString) + sqlContext.conf.isParquetBinaryAsString) lazy val attributeMap = AttributeMap(output.map(o => o -> o)) @@ -80,7 +80,7 @@ private[sql] case class ParquetRelation( } // TODO: Use data from the footers. - override lazy val statistics = Statistics(sizeInBytes = sqlContext.defaultSizeInBytes) + override lazy val statistics = Statistics(sizeInBytes = sqlContext.conf.defaultSizeInBytes) } private[sql] object ParquetRelation { @@ -163,7 +163,8 @@ private[sql] object ParquetRelation { sqlContext: SQLContext): ParquetRelation = { val path = checkPath(pathString, allowExisting, conf) conf.set(ParquetOutputFormat.COMPRESSION, shortParquetCompressionCodecNames.getOrElse( - sqlContext.parquetCompressionCodec.toUpperCase, CompressionCodecName.UNCOMPRESSED).name()) + sqlContext.conf.parquetCompressionCodec.toUpperCase, CompressionCodecName.UNCOMPRESSED) + .name()) ParquetRelation.enableLogForwarding() ParquetTypesConverter.writeMetaData(attributes, path, conf) new ParquetRelation(path.toString, Some(conf), sqlContext) { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTest.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTest.scala index b4d48902fd2c6..02ce1b3e6d811 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTest.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTest.scala @@ -54,7 +54,7 @@ trait ParquetTest { try f finally { keys.zip(currentValues).foreach { case (key, Some(value)) => setConf(key, value) - case (key, None) => unsetConf(key) + case (key, None) => conf.unsetConf(key) } } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/newParquet.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/newParquet.scala index 2e0c6c51c00e5..55a2728a85cc7 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/newParquet.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/newParquet.scala @@ -137,7 +137,7 @@ case class ParquetRelation2(path: String)(@transient val sqlContext: SQLContext) ParquetTypesConverter.readSchemaFromFile( partitions.head.files.head.getPath, Some(sparkContext.hadoopConfiguration), - sqlContext.isParquetBinaryAsString)) + sqlContext.conf.isParquetBinaryAsString)) val dataIncludesKey = partitionKeys.headOption.map(dataSchema.fieldNames.contains(_)).getOrElse(true) @@ -198,7 +198,7 @@ case class ParquetRelation2(path: String)(@transient val sqlContext: SQLContext) predicates .reduceOption(And) .flatMap(ParquetFilters.createFilter) - .filter(_ => sqlContext.parquetFilterPushDown) + .filter(_ => sqlContext.conf.parquetFilterPushDown) .foreach(ParquetInputFormat.setFilterPredicate(jobConf, _)) def percentRead = selectedPartitions.size.toDouble / partitions.size.toDouble * 100 diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala index 2a7be23e37c74..7f5564baa00f4 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala @@ -99,7 +99,7 @@ abstract class BaseRelation { * large to broadcast. This method will be called multiple times during query planning * and thus should not perform expensive operations for each invocation. */ - def sizeInBytes = sqlContext.defaultSizeInBytes + def sizeInBytes = sqlContext.conf.defaultSizeInBytes } /** diff --git a/sql/core/src/main/scala/org/apache/spark/sql/test/TestSQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/test/TestSQLContext.scala index 6bb81c76ed8bd..8c80be106f3cb 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/test/TestSQLContext.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/test/TestSQLContext.scala @@ -29,6 +29,7 @@ object TestSQLContext new SparkConf().set("spark.sql.testkey", "true"))) { /** Fewer partitions to speed up testing. */ - override private[spark] def numShufflePartitions: Int = - getConf(SQLConf.SHUFFLE_PARTITIONS, "5").toInt + private[sql] override lazy val conf: SQLConf = new SQLConf { + override def numShufflePartitions: Int = this.getConf(SQLConf.SHUFFLE_PARTITIONS, "5").toInt + } } diff --git a/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala index c7e136388fce8..e5ab16f9dd661 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala @@ -387,7 +387,7 @@ class JoinSuite extends QueryTest with BeforeAndAfterEach { test("broadcasted left semi join operator selection") { clearCache() sql("CACHE TABLE testData") - val tmp = autoBroadcastJoinThreshold + val tmp = conf.autoBroadcastJoinThreshold sql(s"SET ${SQLConf.AUTO_BROADCASTJOIN_THRESHOLD}=1000000000") Seq( diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLConfSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLConfSuite.scala index 60701f0e154f8..bf73d0c7074a5 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/SQLConfSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLConfSuite.scala @@ -37,7 +37,7 @@ class SQLConfSuite extends QueryTest with FunSuiteLike { } test("programmatic ways of basic setting and getting") { - clear() + conf.clear() assert(getAllConfs.size === 0) setConf(testKey, testVal) @@ -51,11 +51,11 @@ class SQLConfSuite extends QueryTest with FunSuiteLike { assert(TestSQLContext.getConf(testKey, testVal + "_") == testVal) assert(TestSQLContext.getAllConfs.contains(testKey)) - clear() + conf.clear() } test("parse SQL set commands") { - clear() + conf.clear() sql(s"set $testKey=$testVal") assert(getConf(testKey, testVal + "_") == testVal) assert(TestSQLContext.getConf(testKey, testVal + "_") == testVal) @@ -73,11 +73,11 @@ class SQLConfSuite extends QueryTest with FunSuiteLike { sql(s"set $key=") assert(getConf(key, "0") == "") - clear() + conf.clear() } test("deprecated property") { - clear() + conf.clear() sql(s"set ${SQLConf.Deprecated.MAPRED_REDUCE_TASKS}=10") assert(getConf(SQLConf.SHUFFLE_PARTITIONS) == "10") } diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala index d9de5686dce48..bc72daf0880a1 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala @@ -79,7 +79,7 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll { } test("aggregation with codegen") { - val originalValue = codegenEnabled + val originalValue = conf.codegenEnabled setConf(SQLConf.CODEGEN_ENABLED, "true") sql("SELECT key FROM testData GROUP BY key").collect() setConf(SQLConf.CODEGEN_ENABLED, originalValue.toString) @@ -245,14 +245,14 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll { } test("sorting") { - val before = externalSortEnabled + val before = conf.externalSortEnabled setConf(SQLConf.EXTERNAL_SORT, "false") sortTest() setConf(SQLConf.EXTERNAL_SORT, before.toString) } test("external sorting") { - val before = externalSortEnabled + val before = conf.externalSortEnabled setConf(SQLConf.EXTERNAL_SORT, "true") sortTest() setConf(SQLConf.EXTERNAL_SORT, before.toString) @@ -600,7 +600,7 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll { } test("SET commands semantics using sql()") { - clear() + conf.clear() val testKey = "test.key.0" val testVal = "test.val.0" val nonexistentKey = "nonexistent" @@ -632,7 +632,7 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll { sql(s"SET $nonexistentKey"), Seq(Seq(s"$nonexistentKey=")) ) - clear() + conf.clear() } test("apply schema") { diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/InMemoryColumnarQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/InMemoryColumnarQuerySuite.scala index fc95dccc74e27..d94729ba92360 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/InMemoryColumnarQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/InMemoryColumnarQuerySuite.scala @@ -39,7 +39,8 @@ class InMemoryColumnarQuerySuite extends QueryTest { sparkContext.parallelize(1 to 10).map(i => TestData(i, i.toString)).registerTempTable("sizeTst") cacheTable("sizeTst") assert( - table("sizeTst").queryExecution.logical.statistics.sizeInBytes > autoBroadcastJoinThreshold) + table("sizeTst").queryExecution.logical.statistics.sizeInBytes > + conf.autoBroadcastJoinThreshold) } test("projection") { diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/PartitionBatchPruningSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/PartitionBatchPruningSuite.scala index 1915c25392f1e..592cafbbdc203 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/PartitionBatchPruningSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/PartitionBatchPruningSuite.scala @@ -23,8 +23,8 @@ import org.apache.spark.sql._ import org.apache.spark.sql.test.TestSQLContext._ class PartitionBatchPruningSuite extends FunSuite with BeforeAndAfterAll with BeforeAndAfter { - val originalColumnBatchSize = columnBatchSize - val originalInMemoryPartitionPruning = inMemoryPartitionPruning + val originalColumnBatchSize = conf.columnBatchSize + val originalInMemoryPartitionPruning = conf.inMemoryPartitionPruning override protected def beforeAll(): Unit = { // Make a table with 5 partitions, 2 batches per partition, 10 elements per batch diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala index a5af71acfc79a..c5b6fce5fd297 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala @@ -60,7 +60,7 @@ class PlannerSuite extends FunSuite { } test("sizeInBytes estimation of limit operator for broadcast hash join optimization") { - val origThreshold = autoBroadcastJoinThreshold + val origThreshold = conf.autoBroadcastJoinThreshold setConf(SQLConf.AUTO_BROADCASTJOIN_THRESHOLD, 81920.toString) // Using a threshold that is definitely larger than the small testing table (b) below @@ -78,7 +78,7 @@ class PlannerSuite extends FunSuite { } test("InMemoryRelation statistics propagation") { - val origThreshold = autoBroadcastJoinThreshold + val origThreshold = conf.autoBroadcastJoinThreshold setConf(SQLConf.AUTO_BROADCASTJOIN_THRESHOLD, 81920.toString) testData.limit(3).registerTempTable("tiny") diff --git a/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala index 8dce3372a8db3..b09f1ac49553b 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala @@ -713,7 +713,7 @@ class JsonSuite extends QueryTest { test("Corrupt records") { // Test if we can query corrupt records. - val oldColumnNameOfCorruptRecord = TestSQLContext.columnNameOfCorruptRecord + val oldColumnNameOfCorruptRecord = TestSQLContext.conf.columnNameOfCorruptRecord TestSQLContext.setConf(SQLConf.COLUMN_NAME_OF_CORRUPT_RECORD, "_unparsed") val jsonSchemaRDD = jsonRDD(corruptRecords) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala index 10a01474e95be..6ac67fcafe16b 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala @@ -213,7 +213,7 @@ class ParquetIOSuite extends QueryTest with ParquetTest { def checkCompressionCodec(codec: CompressionCodecName): Unit = { withSQLConf(SQLConf.PARQUET_COMPRESSION -> codec.name()) { withParquetFile(data) { path => - assertResult(parquetCompressionCodec.toUpperCase) { + assertResult(conf.parquetCompressionCodec.toUpperCase) { compressionCodecFor(path) } } @@ -221,7 +221,7 @@ class ParquetIOSuite extends QueryTest with ParquetTest { } // Checks default compression codec - checkCompressionCodec(CompressionCodecName.fromConf(parquetCompressionCodec)) + checkCompressionCodec(CompressionCodecName.fromConf(conf.parquetCompressionCodec)) checkCompressionCodec(CompressionCodecName.UNCOMPRESSED) checkCompressionCodec(CompressionCodecName.GZIP) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala index a5fe2e8da2840..0a92336a3cb39 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala @@ -88,7 +88,7 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA TestData // Load test data tables. private var testRDD: SchemaRDD = null - private val originalParquetFilterPushdownEnabled = TestSQLContext.parquetFilterPushDown + private val originalParquetFilterPushdownEnabled = TestSQLContext.conf.parquetFilterPushDown override def beforeAll() { ParquetTestData.writeFile() @@ -144,7 +144,7 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA } ignore("Treat binary as string") { - val oldIsParquetBinaryAsString = TestSQLContext.isParquetBinaryAsString + val oldIsParquetBinaryAsString = TestSQLContext.conf.isParquetBinaryAsString // Create the test file. val file = getTempFilePath("parquet") @@ -174,7 +174,7 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA } test("Compression options for writing to a Parquetfile") { - val defaultParquetCompressionCodec = TestSQLContext.parquetCompressionCodec + val defaultParquetCompressionCodec = TestSQLContext.conf.parquetCompressionCodec import scala.collection.JavaConversions._ val file = getTempFilePath("parquet") @@ -186,7 +186,7 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA rdd.saveAsParquetFile(path) var actualCodec = ParquetTypesConverter.readMetaData(new Path(path), Some(TestSQLContext.sparkContext.hadoopConfiguration)) .getBlocks.flatMap(block => block.getColumns).map(column => column.getCodec.name()).distinct - assert(actualCodec === TestSQLContext.parquetCompressionCodec.toUpperCase :: Nil) + assert(actualCodec === TestSQLContext.conf.parquetCompressionCodec.toUpperCase :: Nil) parquetFile(path).registerTempTable("tmp") checkAnswer( @@ -202,7 +202,7 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA rdd.saveAsParquetFile(path) actualCodec = ParquetTypesConverter.readMetaData(new Path(path), Some(TestSQLContext.sparkContext.hadoopConfiguration)) .getBlocks.flatMap(block => block.getColumns).map(column => column.getCodec.name()).distinct - assert(actualCodec === TestSQLContext.parquetCompressionCodec.toUpperCase :: Nil) + assert(actualCodec === TestSQLContext.conf.parquetCompressionCodec.toUpperCase :: Nil) parquetFile(path).registerTempTable("tmp") checkAnswer( @@ -234,7 +234,7 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA rdd.saveAsParquetFile(path) actualCodec = ParquetTypesConverter.readMetaData(new Path(path), Some(TestSQLContext.sparkContext.hadoopConfiguration)) .getBlocks.flatMap(block => block.getColumns).map(column => column.getCodec.name()).distinct - assert(actualCodec === TestSQLContext.parquetCompressionCodec.toUpperCase :: Nil) + assert(actualCodec === TestSQLContext.conf.parquetCompressionCodec.toUpperCase :: Nil) parquetFile(path).registerTempTable("tmp") checkAnswer( @@ -250,7 +250,7 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA rdd.saveAsParquetFile(path) actualCodec = ParquetTypesConverter.readMetaData(new Path(path), Some(TestSQLContext.sparkContext.hadoopConfiguration)) .getBlocks.flatMap(block => block.getColumns).map(column => column.getCodec.name()).distinct - assert(actualCodec === TestSQLContext.parquetCompressionCodec.toUpperCase :: Nil) + assert(actualCodec === TestSQLContext.conf.parquetCompressionCodec.toUpperCase :: Nil) parquetFile(path).registerTempTable("tmp") checkAnswer( diff --git a/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala b/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala index 23283fd3fe6b1..0d934620aca09 100644 --- a/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala +++ b/sql/hive/compatibility/src/test/scala/org/apache/spark/sql/hive/execution/HiveCompatibilitySuite.scala @@ -36,8 +36,8 @@ class HiveCompatibilitySuite extends HiveQueryFileTest with BeforeAndAfter { private val originalTimeZone = TimeZone.getDefault private val originalLocale = Locale.getDefault - private val originalColumnBatchSize = TestHive.columnBatchSize - private val originalInMemoryPartitionPruning = TestHive.inMemoryPartitionPruning + private val originalColumnBatchSize = TestHive.conf.columnBatchSize + private val originalInMemoryPartitionPruning = TestHive.conf.inMemoryPartitionPruning def testCases = hiveQueryDir.listFiles.map(f => f.getName.stripSuffix(".q") -> f) diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala index 09ff4cc5ab437..9aeebd7e54366 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala @@ -71,8 +71,9 @@ class LocalHiveContext(sc: SparkContext) extends HiveContext(sc) { class HiveContext(sc: SparkContext) extends SQLContext(sc) { self => - // Change the default SQL dialect to HiveQL - override private[spark] def dialect: String = getConf(SQLConf.DIALECT, "hiveql") + private[sql] override lazy val conf: SQLConf = new SQLConf { + override def dialect: String = getConf(SQLConf.DIALECT, "hiveql") + } /** * When true, enables an experimental feature where metastore tables that use the parquet SerDe @@ -87,12 +88,12 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { override def sql(sqlText: String): SchemaRDD = { // TODO: Create a framework for registering parsers instead of just hardcoding if statements. - if (dialect == "sql") { + if (conf.dialect == "sql") { super.sql(sqlText) - } else if (dialect == "hiveql") { + } else if (conf.dialect == "hiveql") { new SchemaRDD(this, ddlParser(sqlText).getOrElse(HiveQl.parseSql(sqlText))) } else { - sys.error(s"Unsupported SQL dialect: $dialect. Try 'sql' or 'hiveql'") + sys.error(s"Unsupported SQL dialect: ${conf.dialect}. Try 'sql' or 'hiveql'") } } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala index daeabb6c8bab8..785a6a14f49f4 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala @@ -515,7 +515,7 @@ private[hive] case class MetastoreRelation // if the size is still less than zero, we use default size Option(totalSize).map(_.toLong).filter(_ > 0) .getOrElse(Option(rawDataSize).map(_.toLong).filter(_ > 0) - .getOrElse(sqlContext.defaultSizeInBytes))) + .getOrElse(sqlContext.conf.defaultSizeInBytes))) } ) diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala index 31c7ce96398eb..52e1f0d94fbd4 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala @@ -102,8 +102,10 @@ class TestHiveContext(sc: SparkContext) extends HiveContext(sc) { new this.QueryExecution { val logical = plan } /** Fewer partitions to speed up testing. */ - override private[spark] def numShufflePartitions: Int = - getConf(SQLConf.SHUFFLE_PARTITIONS, "5").toInt + private[sql] override lazy val conf: SQLConf = new SQLConf { + override def numShufflePartitions: Int = getConf(SQLConf.SHUFFLE_PARTITIONS, "5").toInt + override def dialect: String = getConf(SQLConf.DIALECT, "hiveql") + } /** * Returns the value of specified environmental variable as a [[java.io.File]] after checking diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/api/java/JavaHiveContext.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/api/java/JavaHiveContext.scala index 1817c7832490e..038f63f6c7441 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/api/java/JavaHiveContext.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/api/java/JavaHiveContext.scala @@ -31,12 +31,12 @@ class JavaHiveContext(sqlContext: SQLContext) extends JavaSQLContext(sqlContext) override def sql(sqlText: String): JavaSchemaRDD = { // TODO: Create a framework for registering parsers instead of just hardcoding if statements. - if (sqlContext.dialect == "sql") { + if (sqlContext.conf.dialect == "sql") { super.sql(sqlText) - } else if (sqlContext.dialect == "hiveql") { + } else if (sqlContext.conf.dialect == "hiveql") { new JavaSchemaRDD(sqlContext, HiveQl.parseSql(sqlText)) } else { - sys.error(s"Unsupported SQL dialect: ${sqlContext.dialect}. Try 'sql' or 'hiveql'") + sys.error(s"Unsupported SQL dialect: ${sqlContext.conf.dialect}. Try 'sql' or 'hiveql'") } } diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala index a758f921e0417..0b4e76c9d3d2f 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/StatisticsSuite.scala @@ -81,7 +81,7 @@ class StatisticsSuite extends QueryTest with BeforeAndAfterAll { // TODO: How does it works? needs to add it back for other hive version. if (HiveShim.version =="0.12.0") { - assert(queryTotalSize("analyzeTable") === defaultSizeInBytes) + assert(queryTotalSize("analyzeTable") === conf.defaultSizeInBytes) } sql("ANALYZE TABLE analyzeTable COMPUTE STATISTICS noscan") @@ -110,7 +110,7 @@ class StatisticsSuite extends QueryTest with BeforeAndAfterAll { |SELECT * FROM src """.stripMargin).collect() - assert(queryTotalSize("analyzeTable_part") === defaultSizeInBytes) + assert(queryTotalSize("analyzeTable_part") === conf.defaultSizeInBytes) sql("ANALYZE TABLE analyzeTable_part COMPUTE STATISTICS noscan") @@ -151,8 +151,8 @@ class StatisticsSuite extends QueryTest with BeforeAndAfterAll { val sizes = rdd.queryExecution.analyzed.collect { case r if ct.runtimeClass.isAssignableFrom(r.getClass) => r.statistics.sizeInBytes } - assert(sizes.size === 2 && sizes(0) <= autoBroadcastJoinThreshold - && sizes(1) <= autoBroadcastJoinThreshold, + assert(sizes.size === 2 && sizes(0) <= conf.autoBroadcastJoinThreshold + && sizes(1) <= conf.autoBroadcastJoinThreshold, s"query should contain two relations, each of which has size smaller than autoConvertSize") // Using `sparkPlan` because for relevant patterns in HashJoin to be @@ -163,8 +163,8 @@ class StatisticsSuite extends QueryTest with BeforeAndAfterAll { checkAnswer(rdd, expectedAnswer) // check correctness of output - TestHive.settings.synchronized { - val tmp = autoBroadcastJoinThreshold + TestHive.conf.settings.synchronized { + val tmp = conf.autoBroadcastJoinThreshold sql(s"""SET ${SQLConf.AUTO_BROADCASTJOIN_THRESHOLD}=-1""") rdd = sql(query) @@ -207,8 +207,8 @@ class StatisticsSuite extends QueryTest with BeforeAndAfterAll { .isAssignableFrom(r.getClass) => r.statistics.sizeInBytes } - assert(sizes.size === 2 && sizes(1) <= autoBroadcastJoinThreshold - && sizes(0) <= autoBroadcastJoinThreshold, + assert(sizes.size === 2 && sizes(1) <= conf.autoBroadcastJoinThreshold + && sizes(0) <= conf.autoBroadcastJoinThreshold, s"query should contain two relations, each of which has size smaller than autoConvertSize") // Using `sparkPlan` because for relevant patterns in HashJoin to be @@ -221,8 +221,8 @@ class StatisticsSuite extends QueryTest with BeforeAndAfterAll { checkAnswer(rdd, answer) // check correctness of output - TestHive.settings.synchronized { - val tmp = autoBroadcastJoinThreshold + TestHive.conf.settings.synchronized { + val tmp = conf.autoBroadcastJoinThreshold sql(s"SET ${SQLConf.AUTO_BROADCASTJOIN_THRESHOLD}=-1") rdd = sql(leftSemiJoinQuery) diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala index 4decd1548534b..c14f0d24e0dc3 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala @@ -847,7 +847,7 @@ class HiveQuerySuite extends HiveComparisonTest with BeforeAndAfter { case Row(key: String, value: String) => key -> value case Row(KV(key, value)) => key -> value }.toSet - clear() + conf.clear() // "SET" itself returns all config variables currently specified in SQLConf. // TODO: Should we be listing the default here always? probably... @@ -879,7 +879,7 @@ class HiveQuerySuite extends HiveComparisonTest with BeforeAndAfter { collectResults(sql(s"SET $nonexistentKey")) } - clear() + conf.clear() } createQueryTest("select from thrift based table", From f9969098c8cb15e36c718b80c6cf5b534a6cf7c3 Mon Sep 17 00:00:00 2001 From: Reynold Xin Date: Tue, 13 Jan 2015 17:16:41 -0800 Subject: [PATCH 245/320] [SPARK-5123][SQL] Reconcile Java/Scala API for data types. Having two versions of the data type APIs (one for Java, one for Scala) requires downstream libraries to also have two versions of the APIs if the library wants to support both Java and Scala. I took a look at the Scala version of the data type APIs - it can actually work out pretty well for Java out of the box. As part of the PR, I created a sql.types package and moved all type definitions there. I then removed the Java specific data type API along with a lot of the conversion code. This subsumes https://github.com/apache/spark/pull/3925 Author: Reynold Xin Closes #3958 from rxin/SPARK-5123-datatype-2 and squashes the following commits: 66505cc [Reynold Xin] [SPARK-5123] Expose only one version of the data type APIs (i.e. remove the Java-specific API). --- .../scala/org/apache/spark/ml/Pipeline.scala | 5 +- .../org/apache/spark/ml/Transformer.scala | 2 +- .../classification/LogisticRegression.scala | 1 + .../BinaryClassificationEvaluator.scala | 3 +- .../apache/spark/ml/feature/HashingTF.scala | 2 +- .../spark/ml/feature/StandardScaler.scala | 1 + .../apache/spark/ml/feature/Tokenizer.scala | 2 +- .../spark/ml/tuning/CrossValidator.scala | 3 +- .../apache/spark/mllib/linalg/Vectors.scala | 3 +- project/MimaExcludes.scala | 12 + project/SparkBuild.scala | 4 +- sql/README.md | 2 +- .../spark/sql/catalyst/ScalaReflection.scala | 5 +- .../apache/spark/sql/catalyst/SqlParser.scala | 2 +- .../sql/catalyst/analysis/Analyzer.scala | 4 +- .../catalyst/analysis/HiveTypeCoercion.scala | 2 +- .../spark/sql/catalyst/dsl/package.scala | 4 +- .../catalyst/expressions/BoundAttribute.scala | 2 +- .../spark/sql/catalyst/expressions/Cast.scala | 4 +- .../sql/catalyst/expressions/Expression.scala | 3 +- .../spark/sql/catalyst/expressions/Rand.scala | 2 +- .../spark/sql/catalyst/expressions/Row.scala | 2 +- .../sql/catalyst/expressions/ScalaUdf.scala | 3 +- .../expressions/SpecificMutableRow.scala | 2 +- .../catalyst/expressions/WrapDynamic.scala | 2 +- .../sql/catalyst/expressions/aggregates.scala | 2 +- .../sql/catalyst/expressions/arithmetic.scala | 2 +- .../expressions/codegen/CodeGenerator.scala | 10 +- .../codegen/GenerateOrdering.scala | 2 +- .../codegen/GenerateProjection.scala | 2 +- .../catalyst/expressions/complexTypes.scala | 2 +- .../expressions/decimalFunctions.scala | 4 +- .../sql/catalyst/expressions/generators.scala | 2 +- .../sql/catalyst/expressions/literals.scala | 4 +- .../expressions/namedExpressions.scala | 3 +- .../sql/catalyst/expressions/predicates.scala | 2 +- .../spark/sql/catalyst/expressions/sets.scala | 2 +- .../expressions/stringOperations.scala | 2 +- .../sql/catalyst/optimizer/Optimizer.scala | 4 +- .../apache/spark/sql/catalyst/package.scala | 2 +- .../spark/sql/catalyst/plans/QueryPlan.scala | 2 +- .../catalyst/plans/logical/LogicalPlan.scala | 17 +- .../plans/logical/basicOperators.scala | 2 +- .../plans/physical/partitioning.scala | 2 +- .../spark/sql/types/DataTypeConversions.scala | 68 ++++ .../apache/spark/sql/types/DataTypes.java} | 50 +-- .../{catalyst/util => types}/Metadata.scala | 16 +- .../SQLUserDefinedType.java | 3 +- .../sql/{catalyst => }/types/dataTypes.scala | 294 +++++++++++++-- .../types/decimal/Decimal.scala | 2 +- .../sql/{catalyst => }/types/package.scala | 3 +- .../sql/catalyst/ScalaReflectionSuite.scala | 2 +- .../sql/catalyst/analysis/AnalysisSuite.scala | 2 +- .../analysis/DecimalPrecisionSuite.scala | 2 +- .../analysis/HiveTypeCoercionSuite.scala | 2 +- .../ExpressionEvaluationSuite.scala | 10 +- .../optimizer/ConstantFoldingSuite.scala | 2 +- .../catalyst/optimizer/OptimizeInSuite.scala | 2 +- .../sql/catalyst/trees/TreeNodeSuite.scala | 2 +- .../sql/catalyst/util/MetadataSuite.scala | 2 + .../spark/sql/types}/DataTypeSuite.scala | 2 +- .../types/decimal/DecimalSuite.scala | 2 +- .../apache/spark/sql/api/java/ArrayType.java | 68 ---- .../apache/spark/sql/api/java/BinaryType.java | 27 -- .../spark/sql/api/java/BooleanType.java | 27 -- .../apache/spark/sql/api/java/ByteType.java | 27 -- .../apache/spark/sql/api/java/DateType.java | 27 -- .../spark/sql/api/java/DecimalType.java | 79 ---- .../apache/spark/sql/api/java/DoubleType.java | 27 -- .../apache/spark/sql/api/java/FloatType.java | 27 -- .../spark/sql/api/java/IntegerType.java | 27 -- .../apache/spark/sql/api/java/LongType.java | 27 -- .../apache/spark/sql/api/java/MapType.java | 78 ---- .../apache/spark/sql/api/java/Metadata.java | 31 -- .../spark/sql/api/java/MetadataBuilder.java | 28 -- .../apache/spark/sql/api/java/NullType.java | 27 -- .../apache/spark/sql/api/java/ShortType.java | 27 -- .../apache/spark/sql/api/java/StringType.java | 27 -- .../spark/sql/api/java/StructField.java | 91 ----- .../apache/spark/sql/api/java/StructType.java | 58 --- .../spark/sql/api/java/TimestampType.java | 27 -- .../spark/sql/api/java/UserDefinedType.java | 54 --- .../org/apache/spark/sql/SQLContext.scala | 9 +- .../org/apache/spark/sql/SchemaRDD.scala | 6 +- .../org/apache/spark/sql/SparkSQLParser.scala | 4 +- .../spark/sql/api/java/JavaSQLContext.scala | 69 ++-- .../spark/sql/api/java/JavaSchemaRDD.scala | 10 +- .../org/apache/spark/sql/api/java/Row.scala | 2 - .../spark/sql/api/java/UDFRegistration.scala | 139 ++++--- .../spark/sql/api/java/UDTWrappers.scala | 75 ---- .../spark/sql/columnar/ColumnAccessor.scala | 4 +- .../spark/sql/columnar/ColumnBuilder.scala | 2 +- .../spark/sql/columnar/ColumnStats.scala | 2 +- .../spark/sql/columnar/ColumnType.scala | 2 +- .../CompressibleColumnAccessor.scala | 2 +- .../CompressibleColumnBuilder.scala | 2 +- .../compression/CompressionScheme.scala | 2 +- .../compression/compressionSchemes.scala | 3 +- .../spark/sql/execution/ExistingRDD.scala | 3 +- .../sql/execution/GeneratedAggregate.scala | 2 +- .../sql/execution/SparkSqlSerializer.scala | 2 +- .../spark/sql/execution/SparkStrategies.scala | 6 +- .../spark/sql/execution/debug/package.scala | 2 +- .../spark/sql/execution/pythonUdfs.scala | 4 +- .../apache/spark/sql/json/JSONRelation.scala | 3 +- .../org/apache/spark/sql/json/JsonRDD.scala | 8 +- .../scala/org/apache/spark/sql/package.scala | 349 ------------------ .../spark/sql/parquet/ParquetConverter.scala | 17 +- .../spark/sql/parquet/ParquetFilters.scala | 2 +- .../sql/parquet/ParquetTableSupport.scala | 4 +- .../spark/sql/parquet/ParquetTypes.scala | 16 +- .../apache/spark/sql/parquet/newParquet.scala | 7 +- .../spark/sql/sources/LogicalRelation.scala | 4 +- .../org/apache/spark/sql/sources/ddl.scala | 10 +- .../apache/spark/sql/sources/interfaces.scala | 3 +- .../spark/sql/test/ExamplePointUDT.scala | 4 +- .../sql/types/util/DataTypeConversions.scala | 175 --------- .../spark/sql/api/java/JavaAPISuite.java | 9 +- .../sql/api/java/JavaApplySchemaSuite.java | 23 +- .../java/JavaSideDataTypeConversionSuite.java | 150 -------- .../org/apache/spark/sql/DslQuerySuite.scala | 1 + .../scala/org/apache/spark/sql/RowSuite.scala | 1 + .../org/apache/spark/sql/SQLQuerySuite.scala | 3 +- .../sql/ScalaReflectionRelationSuite.scala | 1 - .../spark/sql/UserDefinedTypeSuite.scala | 3 +- .../spark/sql/api/java/JavaSQLSuite.scala | 9 +- .../ScalaSideDataTypeConversionSuite.scala | 89 ----- .../spark/sql/columnar/ColumnStatsSuite.scala | 2 +- .../spark/sql/columnar/ColumnTypeSuite.scala | 2 +- .../sql/columnar/ColumnarTestUtils.scala | 2 +- .../NullableColumnAccessorSuite.scala | 2 +- .../columnar/NullableColumnBuilderSuite.scala | 2 +- .../compression/DictionaryEncodingSuite.scala | 2 +- .../compression/IntegralDeltaSuite.scala | 2 +- .../compression/RunLengthEncodingSuite.scala | 2 +- .../TestCompressibleColumnBuilder.scala | 2 +- .../org/apache/spark/sql/json/JsonSuite.scala | 16 +- .../spark/sql/parquet/ParquetIOSuite.scala | 6 +- .../spark/sql/parquet/ParquetQuerySuite.scala | 16 +- .../sql/parquet/ParquetSchemaSuite.scala | 21 +- .../spark/sql/sources/FilteredScanSuite.scala | 2 + .../spark/sql/sources/PrunedScanSuite.scala | 1 + .../spark/sql/sources/TableScanSuite.scala | 2 +- .../spark/sql/hive/thriftserver/Shim12.scala | 4 +- .../spark/sql/hive/thriftserver/Shim13.scala | 4 +- .../apache/spark/sql/hive/HiveContext.scala | 2 +- .../spark/sql/hive/HiveInspectors.scala | 15 +- .../spark/sql/hive/HiveMetastoreCatalog.scala | 2 +- .../org/apache/spark/sql/hive/HiveQl.scala | 5 +- .../spark/sql/hive/HiveStrategies.scala | 7 +- .../hive/execution/HiveNativeCommand.scala | 2 +- .../sql/hive/execution/HiveTableScan.scala | 4 +- .../spark/sql/hive/execution/commands.scala | 4 +- .../org/apache/spark/sql/hive/hiveUdfs.scala | 2 +- .../spark/sql/hive/HiveInspectorSuite.scala | 19 +- .../sql/hive/HiveMetastoreCatalogSuite.scala | 2 +- .../sql/hive/InsertIntoHiveTableSuite.scala | 1 + .../sql/hive/MetastoreDataSourcesSuite.scala | 1 + .../org/apache/spark/sql/hive/Shim12.scala | 20 +- .../org/apache/spark/sql/hive/Shim13.scala | 11 +- 160 files changed, 756 insertions(+), 2096 deletions(-) create mode 100644 sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeConversions.scala rename sql/{core/src/main/java/org/apache/spark/sql/api/java/DataType.java => catalyst/src/main/scala/org/apache/spark/sql/types/DataTypes.java} (81%) rename sql/catalyst/src/main/scala/org/apache/spark/sql/{catalyst/util => types}/Metadata.scala (96%) rename sql/catalyst/src/main/scala/org/apache/spark/sql/{catalyst/annotation => types}/SQLUserDefinedType.java (93%) rename sql/catalyst/src/main/scala/org/apache/spark/sql/{catalyst => }/types/dataTypes.scala (76%) rename sql/catalyst/src/main/scala/org/apache/spark/sql/{catalyst => }/types/decimal/Decimal.scala (99%) rename sql/catalyst/src/main/scala/org/apache/spark/sql/{catalyst => }/types/package.scala (96%) rename sql/{core/src/test/scala/org/apache/spark/sql => catalyst/src/test/scala/org/apache/spark/sql/types}/DataTypeSuite.scala (98%) rename sql/catalyst/src/test/scala/org/apache/spark/sql/{catalyst => }/types/decimal/DecimalSuite.scala (99%) delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/ArrayType.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/BinaryType.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/BooleanType.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/ByteType.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/DateType.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/DecimalType.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/DoubleType.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/FloatType.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/IntegerType.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/LongType.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/MapType.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/Metadata.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/MetadataBuilder.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/NullType.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/ShortType.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/StringType.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/StructField.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/StructType.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/TimestampType.java delete mode 100644 sql/core/src/main/java/org/apache/spark/sql/api/java/UserDefinedType.java delete mode 100644 sql/core/src/main/scala/org/apache/spark/sql/api/java/UDTWrappers.scala delete mode 100644 sql/core/src/main/scala/org/apache/spark/sql/types/util/DataTypeConversions.scala delete mode 100644 sql/core/src/test/java/org/apache/spark/sql/api/java/JavaSideDataTypeConversionSuite.java delete mode 100644 sql/core/src/test/scala/org/apache/spark/sql/api/java/ScalaSideDataTypeConversionSuite.scala diff --git a/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala b/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala index 081a574beea5d..ad6fed178fae9 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala @@ -21,8 +21,9 @@ import scala.collection.mutable.ListBuffer import org.apache.spark.Logging import org.apache.spark.annotation.AlphaComponent -import org.apache.spark.ml.param.{Params, Param, ParamMap} -import org.apache.spark.sql.{SchemaRDD, StructType} +import org.apache.spark.ml.param.{Param, ParamMap} +import org.apache.spark.sql.SchemaRDD +import org.apache.spark.sql.types.StructType /** * :: AlphaComponent :: diff --git a/mllib/src/main/scala/org/apache/spark/ml/Transformer.scala b/mllib/src/main/scala/org/apache/spark/ml/Transformer.scala index 23fbd228d01cb..1331b9124045c 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/Transformer.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/Transformer.scala @@ -26,7 +26,7 @@ import org.apache.spark.sql.SchemaRDD import org.apache.spark.sql.api.java.JavaSchemaRDD import org.apache.spark.sql.catalyst.analysis.Star import org.apache.spark.sql.catalyst.expressions.ScalaUdf -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ /** * :: AlphaComponent :: diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala index 85b8899636ca5..8c570812f8316 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala @@ -26,6 +26,7 @@ import org.apache.spark.mllib.regression.LabeledPoint import org.apache.spark.sql._ import org.apache.spark.sql.catalyst.analysis.Star import org.apache.spark.sql.catalyst.dsl._ +import org.apache.spark.sql.types.{DoubleType, StructField, StructType} import org.apache.spark.storage.StorageLevel /** diff --git a/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala b/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala index 0b0504e036ec9..12473cb2b5719 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala @@ -21,7 +21,8 @@ import org.apache.spark.annotation.AlphaComponent import org.apache.spark.ml._ import org.apache.spark.ml.param._ import org.apache.spark.mllib.evaluation.BinaryClassificationMetrics -import org.apache.spark.sql.{DoubleType, Row, SchemaRDD} +import org.apache.spark.sql.{Row, SchemaRDD} +import org.apache.spark.sql.types.DoubleType /** * :: AlphaComponent :: diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/HashingTF.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/HashingTF.scala index e0bfb1e484a2e..0956062643f23 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/feature/HashingTF.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/feature/HashingTF.scala @@ -22,7 +22,7 @@ import org.apache.spark.ml.UnaryTransformer import org.apache.spark.ml.param.{IntParam, ParamMap} import org.apache.spark.mllib.feature import org.apache.spark.mllib.linalg.{VectorUDT, Vector} -import org.apache.spark.sql.catalyst.types.DataType +import org.apache.spark.sql.types.DataType /** * :: AlphaComponent :: diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala index 896a6b83b67bf..72825f6e02182 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala @@ -25,6 +25,7 @@ import org.apache.spark.mllib.linalg.{Vector, VectorUDT} import org.apache.spark.sql._ import org.apache.spark.sql.catalyst.analysis.Star import org.apache.spark.sql.catalyst.dsl._ +import org.apache.spark.sql.types.{StructField, StructType} /** * Params for [[StandardScaler]] and [[StandardScalerModel]]. diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/Tokenizer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/Tokenizer.scala index 9352f40f372d3..e622a5cf9e6f3 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/feature/Tokenizer.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/feature/Tokenizer.scala @@ -20,7 +20,7 @@ package org.apache.spark.ml.feature import org.apache.spark.annotation.AlphaComponent import org.apache.spark.ml.UnaryTransformer import org.apache.spark.ml.param.ParamMap -import org.apache.spark.sql.{DataType, StringType, ArrayType} +import org.apache.spark.sql.types.{DataType, StringType, ArrayType} /** * :: AlphaComponent :: diff --git a/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala b/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala index 194b9bfd9a9e6..08fe99176424a 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala @@ -24,7 +24,8 @@ import org.apache.spark.annotation.AlphaComponent import org.apache.spark.ml._ import org.apache.spark.ml.param.{IntParam, Param, ParamMap, Params} import org.apache.spark.mllib.util.MLUtils -import org.apache.spark.sql.{SchemaRDD, StructType} +import org.apache.spark.sql.SchemaRDD +import org.apache.spark.sql.types.StructType /** * Params for [[CrossValidator]] and [[CrossValidatorModel]]. diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala index bf1faa25ef0e0..adbd8266ed6fa 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala @@ -27,9 +27,8 @@ import breeze.linalg.{DenseVector => BDV, SparseVector => BSV, Vector => BV} import org.apache.spark.SparkException import org.apache.spark.mllib.util.NumericParser -import org.apache.spark.sql.catalyst.annotation.SQLUserDefinedType import org.apache.spark.sql.catalyst.expressions.{GenericMutableRow, Row} -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ /** * Represents a numeric vector, whose index type is Int and value type is Double. diff --git a/project/MimaExcludes.scala b/project/MimaExcludes.scala index 51e8bd4cf6419..f6f9f491f4ceb 100644 --- a/project/MimaExcludes.scala +++ b/project/MimaExcludes.scala @@ -60,6 +60,18 @@ object MimaExcludes { ProblemFilters.exclude[IncompatibleResultTypeProblem]( "org.apache.spark.streaming.flume.sink.SparkAvroCallbackHandler." + "removeAndGetProcessor") + ) ++ Seq( + // SPARK-5123 (SparkSQL data type change) - alpha component only + ProblemFilters.exclude[IncompatibleResultTypeProblem]( + "org.apache.spark.ml.feature.HashingTF.outputDataType"), + ProblemFilters.exclude[IncompatibleResultTypeProblem]( + "org.apache.spark.ml.feature.Tokenizer.outputDataType"), + ProblemFilters.exclude[IncompatibleMethTypeProblem]( + "org.apache.spark.ml.feature.Tokenizer.validateInputType"), + ProblemFilters.exclude[IncompatibleMethTypeProblem]( + "org.apache.spark.ml.classification.LogisticRegressionModel.validateAndTransformSchema"), + ProblemFilters.exclude[IncompatibleMethTypeProblem]( + "org.apache.spark.ml.classification.LogisticRegression.validateAndTransformSchema") ) case v if v.startsWith("1.2") => diff --git a/project/SparkBuild.scala b/project/SparkBuild.scala index 46a54c6818409..b2c546da21c70 100644 --- a/project/SparkBuild.scala +++ b/project/SparkBuild.scala @@ -254,10 +254,10 @@ object SQL { |import org.apache.spark.sql.catalyst.expressions._ |import org.apache.spark.sql.catalyst.plans.logical._ |import org.apache.spark.sql.catalyst.rules._ - |import org.apache.spark.sql.catalyst.types._ |import org.apache.spark.sql.catalyst.util._ |import org.apache.spark.sql.execution |import org.apache.spark.sql.test.TestSQLContext._ + |import org.apache.spark.sql.types._ |import org.apache.spark.sql.parquet.ParquetTestData""".stripMargin, cleanupCommands in console := "sparkContext.stop()" ) @@ -284,11 +284,11 @@ object Hive { |import org.apache.spark.sql.catalyst.expressions._ |import org.apache.spark.sql.catalyst.plans.logical._ |import org.apache.spark.sql.catalyst.rules._ - |import org.apache.spark.sql.catalyst.types._ |import org.apache.spark.sql.catalyst.util._ |import org.apache.spark.sql.execution |import org.apache.spark.sql.hive._ |import org.apache.spark.sql.hive.test.TestHive._ + |import org.apache.spark.sql.types._ |import org.apache.spark.sql.parquet.ParquetTestData""".stripMargin, cleanupCommands in console := "sparkContext.stop()", // Some of our log4j jars make it impossible to submit jobs from this JVM to Hive Map/Reduce diff --git a/sql/README.md b/sql/README.md index 8d2f3cf4283e0..d058a6b011d37 100644 --- a/sql/README.md +++ b/sql/README.md @@ -34,11 +34,11 @@ import org.apache.spark.sql.catalyst.errors._ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.rules._ -import org.apache.spark.sql.catalyst.types._ import org.apache.spark.sql.catalyst.util._ import org.apache.spark.sql.execution import org.apache.spark.sql.hive._ import org.apache.spark.sql.hive.TestHive._ +import org.apache.spark.sql.types._ Welcome to Scala version 2.10.4 (Java HotSpot(TM) 64-Bit Server VM, Java 1.7.0_45). Type in expressions to have them evaluated. Type :help for more information. diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala index 2cf241de61f7a..d169da691d797 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala @@ -20,11 +20,10 @@ package org.apache.spark.sql.catalyst import java.sql.{Date, Timestamp} import org.apache.spark.util.Utils -import org.apache.spark.sql.catalyst.annotation.SQLUserDefinedType import org.apache.spark.sql.catalyst.expressions.{GenericRow, Attribute, AttributeReference, Row} import org.apache.spark.sql.catalyst.plans.logical.LocalRelation -import org.apache.spark.sql.catalyst.types._ -import org.apache.spark.sql.catalyst.types.decimal.Decimal +import org.apache.spark.sql.types._ +import org.apache.spark.sql.types.decimal.Decimal /** diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala index 5d974df98b699..d19563e95cc73 100755 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala @@ -23,7 +23,7 @@ import org.apache.spark.sql.catalyst.analysis._ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans._ import org.apache.spark.sql.catalyst.plans.logical._ -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ /** * A very simple SQL parser. Based loosely on: diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala index c009cc1e1e85c..bd00ff22ba80a 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala @@ -22,8 +22,8 @@ import org.apache.spark.sql.catalyst.errors.TreeNodeException import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.rules._ -import org.apache.spark.sql.catalyst.types.StructType -import org.apache.spark.sql.catalyst.types.IntegerType +import org.apache.spark.sql.types.StructType +import org.apache.spark.sql.types.IntegerType /** * A trivial [[Analyzer]] with an [[EmptyCatalog]] and [[EmptyFunctionRegistry]]. Used for testing diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala index 242f28f670298..15353361d97cb 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala @@ -20,7 +20,7 @@ package org.apache.spark.sql.catalyst.analysis import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, Project, Union} import org.apache.spark.sql.catalyst.rules.Rule -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ object HiveTypeCoercion { // See https://cwiki.apache.org/confluence/display/Hive/LanguageManual+Types. diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala index b2262e5e6efb6..bdac7504ed027 100755 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala @@ -26,8 +26,8 @@ import org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.plans.{Inner, JoinType} -import org.apache.spark.sql.catalyst.types._ -import org.apache.spark.sql.catalyst.types.decimal.Decimal +import org.apache.spark.sql.types._ +import org.apache.spark.sql.types.decimal.Decimal /** * A collection of implicit conversions that create a DSL for constructing catalyst data structures. diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/BoundAttribute.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/BoundAttribute.scala index fa80b07f8e6be..76a9f08dea85f 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/BoundAttribute.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/BoundAttribute.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.catalyst.expressions import org.apache.spark.Logging import org.apache.spark.sql.catalyst.errors.attachTree -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ import org.apache.spark.sql.catalyst.trees /** diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala index 4ede0b4821fe3..00961f09916b3 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala @@ -22,8 +22,8 @@ import java.text.{DateFormat, SimpleDateFormat} import org.apache.spark.Logging import org.apache.spark.sql.catalyst.errors.TreeNodeException -import org.apache.spark.sql.catalyst.types._ -import org.apache.spark.sql.catalyst.types.decimal.Decimal +import org.apache.spark.sql.types._ +import org.apache.spark.sql.types.decimal.Decimal /** Cast the child expression to the target data type. */ case class Cast(child: Expression, dataType: DataType) extends UnaryExpression with Logging { diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Expression.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Expression.scala index ac5b02c2e6aed..cf14992ef835c 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Expression.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Expression.scala @@ -20,8 +20,7 @@ package org.apache.spark.sql.catalyst.expressions import org.apache.spark.sql.catalyst.errors.TreeNodeException import org.apache.spark.sql.catalyst.trees import org.apache.spark.sql.catalyst.trees.TreeNode -import org.apache.spark.sql.catalyst.types.{DataType, FractionalType, IntegralType, NumericType, NativeType} -import org.apache.spark.sql.catalyst.util.Metadata +import org.apache.spark.sql.types._ abstract class Expression extends TreeNode[Expression] { self: Product => diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Rand.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Rand.scala index 851db95b9177e..b2c6d3029031d 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Rand.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Rand.scala @@ -18,7 +18,7 @@ package org.apache.spark.sql.catalyst.expressions import java.util.Random -import org.apache.spark.sql.catalyst.types.DoubleType +import org.apache.spark.sql.types.DoubleType case object Rand extends LeafExpression { diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Row.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Row.scala index 463f3667fc445..dcda53bb717a9 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Row.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Row.scala @@ -17,7 +17,7 @@ package org.apache.spark.sql.catalyst.expressions -import org.apache.spark.sql.catalyst.types.NativeType +import org.apache.spark.sql.types.NativeType object Row { /** diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUdf.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUdf.scala index 18c96da2f87fb..8a36c6810790d 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUdf.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUdf.scala @@ -18,8 +18,7 @@ package org.apache.spark.sql.catalyst.expressions import org.apache.spark.sql.catalyst.ScalaReflection -import org.apache.spark.sql.catalyst.types.DataType -import org.apache.spark.util.ClosureCleaner +import org.apache.spark.sql.types.DataType /** * User-defined function. diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SpecificMutableRow.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SpecificMutableRow.scala index 570379c533e1f..37d9f0ed5c79e 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SpecificMutableRow.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SpecificMutableRow.scala @@ -17,7 +17,7 @@ package org.apache.spark.sql.catalyst.expressions -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ /** * A parent class for mutable container objects that are reused when the values are changed, diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/WrapDynamic.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/WrapDynamic.scala index 1a4ac06c7a79d..8328278544a1e 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/WrapDynamic.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/WrapDynamic.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.catalyst.expressions import scala.language.dynamics -import org.apache.spark.sql.catalyst.types.DataType +import org.apache.spark.sql.types.DataType /** * The data type representing [[DynamicRow]] values. diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala index 5ea9868e9e846..735b7488fdcbd 100755 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.catalyst.expressions import com.clearspring.analytics.stream.cardinality.HyperLogLog -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ import org.apache.spark.sql.catalyst.trees import org.apache.spark.sql.catalyst.errors.TreeNodeException import org.apache.spark.util.collection.OpenHashSet diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala index 168a963e29c90..574907f566c0f 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala @@ -18,7 +18,7 @@ package org.apache.spark.sql.catalyst.expressions import org.apache.spark.sql.catalyst.analysis.UnresolvedException -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ case class UnaryMinus(child: Expression) extends UnaryExpression { type EvaluatedType = Any diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala index 90c81b2631e59..a5d6423391295 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala @@ -18,14 +18,14 @@ package org.apache.spark.sql.catalyst.expressions.codegen import com.google.common.cache.{CacheLoader, CacheBuilder} -import org.apache.spark.sql.catalyst.types.decimal.Decimal +import org.apache.spark.sql.types.decimal.Decimal import scala.language.existentials import org.apache.spark.Logging import org.apache.spark.sql.catalyst.expressions import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ // These classes are here to avoid issues with serialization and integration with quasiquotes. class IntegerHashSet extends org.apache.spark.util.collection.OpenHashSet[Int] @@ -541,11 +541,11 @@ abstract class CodeGenerator[InType <: AnyRef, OutType <: AnyRef] extends Loggin childEval.code ++ q""" var $nullTerm = ${childEval.nullTerm} - var $primitiveTerm: org.apache.spark.sql.catalyst.types.decimal.Decimal = + var $primitiveTerm: org.apache.spark.sql.types.decimal.Decimal = ${defaultPrimitive(DecimalType())} if (!$nullTerm) { - $primitiveTerm = new org.apache.spark.sql.catalyst.types.decimal.Decimal() + $primitiveTerm = new org.apache.spark.sql.types.decimal.Decimal() $primitiveTerm = $primitiveTerm.setOrNull(${childEval.primitiveTerm}, $precision, $scale) $nullTerm = $primitiveTerm == null } @@ -627,7 +627,7 @@ abstract class CodeGenerator[InType <: AnyRef, OutType <: AnyRef] extends Loggin case LongType => ru.Literal(Constant(1L)) case ByteType => ru.Literal(Constant(-1.toByte)) case DoubleType => ru.Literal(Constant(-1.toDouble)) - case DecimalType() => q"org.apache.spark.sql.catalyst.types.decimal.Decimal(-1)" + case DecimalType() => q"org.apache.spark.sql.types.decimal.Decimal(-1)" case IntegerType => ru.Literal(Constant(-1)) case _ => ru.Literal(Constant(null)) } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateOrdering.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateOrdering.scala index 094ff14552283..0db29eb404bd1 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateOrdering.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateOrdering.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.catalyst.expressions.codegen import org.apache.spark.Logging import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.catalyst.types.{StringType, NumericType} +import org.apache.spark.sql.types.{StringType, NumericType} /** * Generates bytecode for an [[Ordering]] of [[Row Rows]] for a given set of diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateProjection.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateProjection.scala index 2ff61169a17db..cc97cb4f50b69 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateProjection.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateProjection.scala @@ -18,7 +18,7 @@ package org.apache.spark.sql.catalyst.expressions.codegen import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ /** diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala index 9aec601886efc..1bc34f71441fe 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypes.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.catalyst.expressions import scala.collection.Map -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ /** * Returns the item at `ordinal` in the Array `child` or the Key `ordinal` in Map `child`. diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/decimalFunctions.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/decimalFunctions.scala index d1eab2eb4ed56..e54cfa144a173 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/decimalFunctions.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/decimalFunctions.scala @@ -17,8 +17,8 @@ package org.apache.spark.sql.catalyst.expressions -import org.apache.spark.sql.catalyst.types.decimal.Decimal -import org.apache.spark.sql.catalyst.types.{DecimalType, LongType, DoubleType, DataType} +import org.apache.spark.sql.types.decimal.Decimal +import org.apache.spark.sql.types.{DecimalType, LongType, DoubleType, DataType} /** Return the unscaled Long value of a Decimal, assuming it fits in a Long */ case class UnscaledValue(child: Expression) extends UnaryExpression { diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/generators.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/generators.scala index ab0701fd9a80b..43b6482c0171c 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/generators.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/generators.scala @@ -20,7 +20,7 @@ package org.apache.spark.sql.catalyst.expressions import scala.collection.Map import org.apache.spark.sql.catalyst.trees -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ /** * An expression that produces zero or more rows given a single input row. diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala index 94e1d37c1c3ab..8ee4bbd8caa62 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala @@ -19,8 +19,8 @@ package org.apache.spark.sql.catalyst.expressions import java.sql.{Date, Timestamp} -import org.apache.spark.sql.catalyst.types._ -import org.apache.spark.sql.catalyst.types.decimal.Decimal +import org.apache.spark.sql.types._ +import org.apache.spark.sql.types.decimal.Decimal object Literal { def apply(v: Any): Literal = v match { diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/namedExpressions.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/namedExpressions.scala index a3c300b5d90e9..3035d934ff9f8 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/namedExpressions.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/namedExpressions.scala @@ -20,8 +20,7 @@ package org.apache.spark.sql.catalyst.expressions import org.apache.spark.sql.catalyst.trees import org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute import org.apache.spark.sql.catalyst.errors.TreeNodeException -import org.apache.spark.sql.catalyst.types._ -import org.apache.spark.sql.catalyst.util.Metadata +import org.apache.spark.sql.types._ object NamedExpression { private val curId = new java.util.concurrent.atomic.AtomicLong() diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala index cb5ff67959868..c84cc95520a19 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/predicates.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.catalyst.expressions import org.apache.spark.sql.catalyst.analysis.UnresolvedException import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan -import org.apache.spark.sql.catalyst.types.BooleanType +import org.apache.spark.sql.types.BooleanType object InterpretedPredicate { def apply(expression: Expression, inputSchema: Seq[Attribute]): (Row => Boolean) = diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/sets.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/sets.scala index 3d4c4a8853c12..3a5bdca1f07c3 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/sets.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/sets.scala @@ -17,7 +17,7 @@ package org.apache.spark.sql.catalyst.expressions -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ import org.apache.spark.util.collection.OpenHashSet /** diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringOperations.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringOperations.scala index f6349767764a3..f85ee0a9bb6d8 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringOperations.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringOperations.scala @@ -23,7 +23,7 @@ import scala.collection.IndexedSeqOptimized import org.apache.spark.sql.catalyst.analysis.UnresolvedException -import org.apache.spark.sql.catalyst.types.{BinaryType, BooleanType, DataType, StringType} +import org.apache.spark.sql.types.{BinaryType, BooleanType, DataType, StringType} trait StringRegexExpression { self: BinaryExpression => diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala index cd3137980ca43..17b4f9c23a978 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala @@ -26,8 +26,8 @@ import org.apache.spark.sql.catalyst.plans.RightOuter import org.apache.spark.sql.catalyst.plans.LeftSemi import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.rules._ -import org.apache.spark.sql.catalyst.types._ -import org.apache.spark.sql.catalyst.types.decimal.Decimal +import org.apache.spark.sql.types._ +import org.apache.spark.sql.types.decimal.Decimal abstract class Optimizer extends RuleExecutor[LogicalPlan] diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/package.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/package.scala index a38079ced34b2..105cdf52500c6 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/package.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/package.scala @@ -27,6 +27,6 @@ package object catalyst { * scala.reflect.*. Note that Scala Reflection API is made thread-safe in 2.11, but not yet for * 2.10.* builds. See SI-6240 for more details. */ - protected[catalyst] object ScalaReflectionLock + protected[sql] object ScalaReflectionLock } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala index dcbbb62c0aca4..619f42859cbb8 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.catalyst.plans import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeSet, Expression} import org.apache.spark.sql.catalyst.trees.TreeNode -import org.apache.spark.sql.catalyst.types.{ArrayType, DataType, StructField, StructType} +import org.apache.spark.sql.types.{ArrayType, DataType, StructField, StructType} abstract class QueryPlan[PlanType <: TreeNode[PlanType]] extends TreeNode[PlanType] { self: PlanType with Product => diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LogicalPlan.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LogicalPlan.scala index ed578e081be73..65ae066e4b4b5 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LogicalPlan.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/LogicalPlan.scala @@ -23,7 +23,7 @@ import org.apache.spark.sql.catalyst.errors.TreeNodeException import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.QueryPlan import org.apache.spark.sql.catalyst.trees.TreeNode -import org.apache.spark.sql.catalyst.types.StructType +import org.apache.spark.sql.types.StructType import org.apache.spark.sql.catalyst.trees /** @@ -191,14 +191,13 @@ abstract class LogicalPlan extends QueryPlan[LogicalPlan] with Logging { case (Nil, _) => expression case (requestedField :: rest, StructType(fields)) => val actualField = fields.filter(f => resolver(f.name, requestedField)) - actualField match { - case Seq() => - sys.error( - s"No such struct field $requestedField in ${fields.map(_.name).mkString(", ")}") - case Seq(singleMatch) => - resolveNesting(rest, GetField(expression, singleMatch.name), resolver) - case multipleMatches => - sys.error(s"Ambiguous reference to fields ${multipleMatches.mkString(", ")}") + if (actualField.length == 0) { + sys.error( + s"No such struct field $requestedField in ${fields.map(_.name).mkString(", ")}") + } else if (actualField.length == 1) { + resolveNesting(rest, GetField(expression, actualField(0).name), resolver) + } else { + sys.error(s"Ambiguous reference to fields ${actualField.mkString(", ")}") } case (_, dt) => sys.error(s"Can't access nested field in type $dt") } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala index 0b9f01cbae9ea..1483beacc9088 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.catalyst.plans.logical import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans._ -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ case class Project(projectList: Seq[NamedExpression], child: LogicalPlan) extends UnaryNode { def output = projectList.map(_.toAttribute) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/physical/partitioning.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/physical/partitioning.scala index ccb0df113c063..3c3d7a3119064 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/physical/partitioning.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/physical/partitioning.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.catalyst.plans.physical import org.apache.spark.sql.catalyst.errors.TreeNodeException import org.apache.spark.sql.catalyst.expressions.{Expression, Row, SortOrder} -import org.apache.spark.sql.catalyst.types.IntegerType +import org.apache.spark.sql.types.IntegerType /** * Specifies how tuples that share common expressions will be distributed when a query is executed diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeConversions.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeConversions.scala new file mode 100644 index 0000000000000..2a8914cde248c --- /dev/null +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeConversions.scala @@ -0,0 +1,68 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.types + +import java.text.SimpleDateFormat + +import org.apache.spark.sql.catalyst.ScalaReflection +import org.apache.spark.sql.types.decimal.Decimal + + +protected[sql] object DataTypeConversions { + + def stringToTime(s: String): java.util.Date = { + if (!s.contains('T')) { + // JDBC escape string + if (s.contains(' ')) { + java.sql.Timestamp.valueOf(s) + } else { + java.sql.Date.valueOf(s) + } + } else if (s.endsWith("Z")) { + // this is zero timezone of ISO8601 + stringToTime(s.substring(0, s.length - 1) + "GMT-00:00") + } else if (s.indexOf("GMT") == -1) { + // timezone with ISO8601 + val inset = "+00.00".length + val s0 = s.substring(0, s.length - inset) + val s1 = s.substring(s.length - inset, s.length) + if (s0.substring(s0.lastIndexOf(':')).contains('.')) { + stringToTime(s0 + "GMT" + s1) + } else { + stringToTime(s0 + ".0GMT" + s1) + } + } else { + // ISO8601 with GMT insert + val ISO8601GMT: SimpleDateFormat = new SimpleDateFormat( "yyyy-MM-dd'T'HH:mm:ss.SSSz" ) + ISO8601GMT.parse(s) + } + } + + /** Converts Java objects to catalyst rows / types */ + def convertJavaToCatalyst(a: Any, dataType: DataType): Any = (a, dataType) match { + case (obj, udt: UserDefinedType[_]) => ScalaReflection.convertToCatalyst(obj, udt) // Scala type + case (d: java.math.BigDecimal, _) => Decimal(BigDecimal(d)) + case (other, _) => other + } + + /** Converts Java objects to catalyst rows / types */ + def convertCatalystToJava(a: Any): Any = a match { + case d: scala.math.BigDecimal => d.underlying() + case other => other + } +} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/DataType.java b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypes.java similarity index 81% rename from sql/core/src/main/java/org/apache/spark/sql/api/java/DataType.java rename to sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypes.java index c69bbd5736a5b..e457542c647e7 100644 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/DataType.java +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypes.java @@ -15,77 +15,74 @@ * limitations under the License. */ -package org.apache.spark.sql.api.java; +package org.apache.spark.sql.types; import java.util.*; /** - * The base type of all Spark SQL data types. - * * To get/create specific data type, users should use singleton objects and factory methods * provided by this class. */ -public abstract class DataType { - +public class DataTypes { /** * Gets the StringType object. */ - public static final StringType StringType = new StringType(); + public static final DataType StringType = StringType$.MODULE$; /** * Gets the BinaryType object. */ - public static final BinaryType BinaryType = new BinaryType(); + public static final DataType BinaryType = BinaryType$.MODULE$; /** * Gets the BooleanType object. */ - public static final BooleanType BooleanType = new BooleanType(); + public static final DataType BooleanType = BooleanType$.MODULE$; /** * Gets the DateType object. */ - public static final DateType DateType = new DateType(); + public static final DataType DateType = DateType$.MODULE$; /** * Gets the TimestampType object. */ - public static final TimestampType TimestampType = new TimestampType(); + public static final DataType TimestampType = TimestampType$.MODULE$; /** * Gets the DoubleType object. */ - public static final DoubleType DoubleType = new DoubleType(); + public static final DataType DoubleType = DoubleType$.MODULE$; /** * Gets the FloatType object. */ - public static final FloatType FloatType = new FloatType(); + public static final DataType FloatType = FloatType$.MODULE$; /** * Gets the ByteType object. */ - public static final ByteType ByteType = new ByteType(); + public static final DataType ByteType = ByteType$.MODULE$; /** * Gets the IntegerType object. */ - public static final IntegerType IntegerType = new IntegerType(); + public static final DataType IntegerType = IntegerType$.MODULE$; /** * Gets the LongType object. */ - public static final LongType LongType = new LongType(); + public static final DataType LongType = LongType$.MODULE$; /** * Gets the ShortType object. */ - public static final ShortType ShortType = new ShortType(); + public static final DataType ShortType = ShortType$.MODULE$; /** * Gets the NullType object. */ - public static final NullType NullType = new NullType(); + public static final DataType NullType = NullType$.MODULE$; /** * Creates an ArrayType by specifying the data type of elements ({@code elementType}). @@ -95,7 +92,6 @@ public static ArrayType createArrayType(DataType elementType) { if (elementType == null) { throw new IllegalArgumentException("elementType should not be null."); } - return new ArrayType(elementType, true); } @@ -107,10 +103,17 @@ public static ArrayType createArrayType(DataType elementType, boolean containsNu if (elementType == null) { throw new IllegalArgumentException("elementType should not be null."); } - return new ArrayType(elementType, containsNull); } + public static DecimalType createDecimalType(int precision, int scale) { + return DecimalType$.MODULE$.apply(precision, scale); + } + + public static DecimalType createDecimalType() { + return DecimalType$.MODULE$.Unlimited(); + } + /** * Creates a MapType by specifying the data type of keys ({@code keyType}) and values * ({@code keyType}). The field of {@code valueContainsNull} is set to {@code true}. @@ -122,7 +125,6 @@ public static MapType createMapType(DataType keyType, DataType valueType) { if (valueType == null) { throw new IllegalArgumentException("valueType should not be null."); } - return new MapType(keyType, valueType, true); } @@ -141,7 +143,6 @@ public static MapType createMapType( if (valueType == null) { throw new IllegalArgumentException("valueType should not be null."); } - return new MapType(keyType, valueType, valueContainsNull); } @@ -163,7 +164,6 @@ public static StructField createStructField( if (metadata == null) { throw new IllegalArgumentException("metadata should not be null."); } - return new StructField(name, dataType, nullable, metadata); } @@ -191,18 +191,18 @@ public static StructType createStructType(StructField[] fields) { throw new IllegalArgumentException("fields should not be null."); } Set distinctNames = new HashSet(); - for (StructField field: fields) { + for (StructField field : fields) { if (field == null) { throw new IllegalArgumentException( "fields should not contain any null."); } - distinctNames.add(field.getName()); + distinctNames.add(field.name()); } if (distinctNames.size() != fields.length) { throw new IllegalArgumentException("fields should have distinct names."); } - return new StructType(fields); + return StructType$.MODULE$.apply(fields); } } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/Metadata.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/Metadata.scala similarity index 96% rename from sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/Metadata.scala rename to sql/catalyst/src/main/scala/org/apache/spark/sql/types/Metadata.scala index 8172733e94dd5..e50e9761431f5 100755 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/Metadata.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/Metadata.scala @@ -15,24 +15,31 @@ * limitations under the License. */ -package org.apache.spark.sql.catalyst.util +package org.apache.spark.sql.types import scala.collection.mutable import org.json4s._ import org.json4s.jackson.JsonMethods._ +import org.apache.spark.annotation.DeveloperApi + + /** + * :: DeveloperApi :: + * * Metadata is a wrapper over Map[String, Any] that limits the value type to simple ones: Boolean, * Long, Double, String, Metadata, Array[Boolean], Array[Long], Array[Double], Array[String], and * Array[Metadata]. JSON is used for serialization. * * The default constructor is private. User should use either [[MetadataBuilder]] or - * [[Metadata$#fromJson]] to create Metadata instances. + * [[Metadata.fromJson()]] to create Metadata instances. * * @param map an immutable map that stores the data */ -sealed class Metadata private[util] (private[util] val map: Map[String, Any]) extends Serializable { +@DeveloperApi +sealed class Metadata private[types] (private[types] val map: Map[String, Any]) + extends Serializable { /** Tests whether this Metadata contains a binding for a key. */ def contains(key: String): Boolean = map.contains(key) @@ -201,8 +208,11 @@ object Metadata { } /** + * :: DeveloperApi :: + * * Builder for [[Metadata]]. If there is a key collision, the latter will overwrite the former. */ +@DeveloperApi class MetadataBuilder { private val map: mutable.Map[String, Any] = mutable.Map.empty diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/annotation/SQLUserDefinedType.java b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/SQLUserDefinedType.java similarity index 93% rename from sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/annotation/SQLUserDefinedType.java rename to sql/catalyst/src/main/scala/org/apache/spark/sql/types/SQLUserDefinedType.java index e966aeea1cb23..a64d2bb7cde37 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/annotation/SQLUserDefinedType.java +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/SQLUserDefinedType.java @@ -15,12 +15,11 @@ * limitations under the License. */ -package org.apache.spark.sql.catalyst.annotation; +package org.apache.spark.sql.types; import java.lang.annotation.*; import org.apache.spark.annotation.DeveloperApi; -import org.apache.spark.sql.catalyst.types.UserDefinedType; /** * ::DeveloperApi:: diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/dataTypes.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/dataTypes.scala similarity index 76% rename from sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/dataTypes.scala rename to sql/catalyst/src/main/scala/org/apache/spark/sql/types/dataTypes.scala index 892b7e1a97c8b..fa0a355ebc9b0 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/dataTypes.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/dataTypes.scala @@ -15,11 +15,11 @@ * limitations under the License. */ -package org.apache.spark.sql.catalyst.types +package org.apache.spark.sql.types import java.sql.{Date, Timestamp} -import scala.math.Numeric.{FloatAsIfIntegral, BigDecimalAsIfIntegral, DoubleAsIfIntegral} +import scala.math.Numeric.{FloatAsIfIntegral, DoubleAsIfIntegral} import scala.reflect.ClassTag import scala.reflect.runtime.universe.{TypeTag, runtimeMirror, typeTag} import scala.util.parsing.combinator.RegexParsers @@ -31,11 +31,11 @@ import org.json4s.jackson.JsonMethods._ import org.apache.spark.annotation.DeveloperApi import org.apache.spark.sql.catalyst.ScalaReflectionLock -import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeReference, Expression, Row} -import org.apache.spark.sql.catalyst.types.decimal._ -import org.apache.spark.sql.catalyst.util.Metadata +import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeReference, Expression} +import org.apache.spark.sql.types.decimal._ import org.apache.spark.util.Utils + object DataType { def fromJson(json: String): DataType = parseDataType(parse(json)) @@ -140,7 +140,7 @@ object DataType { protected lazy val structType: Parser[DataType] = "StructType\\([A-zA-z]*\\(".r ~> repsep(structField, ",") <~ "))" ^^ { - case fields => new StructType(fields) + case fields => StructType(fields) } protected lazy val dataType: Parser[DataType] = @@ -181,7 +181,7 @@ object DataType { /** * Compares two types, ignoring nullability of ArrayType, MapType, StructType. */ - def equalsIgnoreNullability(left: DataType, right: DataType): Boolean = { + private[sql] def equalsIgnoreNullability(left: DataType, right: DataType): Boolean = { (left, right) match { case (ArrayType(leftElementType, _), ArrayType(rightElementType, _)) => equalsIgnoreNullability(leftElementType, rightElementType) @@ -200,6 +200,15 @@ object DataType { } } + +/** + * :: DeveloperApi :: + * + * The base type of all Spark SQL data types. + * + * @group dataType + */ +@DeveloperApi abstract class DataType { /** Matches any expression that evaluates to this DataType */ def unapply(a: Expression): Boolean = a match { @@ -218,8 +227,18 @@ abstract class DataType { def prettyJson: String = pretty(render(jsonValue)) } + +/** + * :: DeveloperApi :: + * + * The data type representing `NULL` values. Please use the singleton [[DataTypes.NullType]]. + * + * @group dataType + */ +@DeveloperApi case object NullType extends DataType + object NativeType { val all = Seq( IntegerType, BooleanType, LongType, DoubleType, FloatType, ShortType, ByteType, StringType) @@ -237,10 +256,12 @@ object NativeType { StringType -> 4096) } + trait PrimitiveType extends DataType { override def isPrimitive = true } + object PrimitiveType { private val nonDecimals = Seq(NullType, DateType, TimestampType, BinaryType) ++ NativeType.all private val nonDecimalNameToType = nonDecimals.map(t => t.typeName -> t).toMap @@ -267,12 +288,31 @@ abstract class NativeType extends DataType { } } + +/** + * :: DeveloperApi :: + * + * The data type representing `String` values. Please use the singleton [[DataTypes.StringType]]. + * + * @group dataType + */ +@DeveloperApi case object StringType extends NativeType with PrimitiveType { private[sql] type JvmType = String @transient private[sql] lazy val tag = ScalaReflectionLock.synchronized { typeTag[JvmType] } private[sql] val ordering = implicitly[Ordering[JvmType]] } + +/** + * :: DeveloperApi :: + * + * The data type representing `Array[Byte]` values. + * Please use the singleton [[DataTypes.BinaryType]]. + * + * @group dataType + */ +@DeveloperApi case object BinaryType extends NativeType with PrimitiveType { private[sql] type JvmType = Array[Byte] @transient private[sql] lazy val tag = ScalaReflectionLock.synchronized { typeTag[JvmType] } @@ -287,12 +327,31 @@ case object BinaryType extends NativeType with PrimitiveType { } } + +/** + * :: DeveloperApi :: + * + * The data type representing `Boolean` values. Please use the singleton [[DataTypes.BooleanType]]. + * + *@group dataType + */ +@DeveloperApi case object BooleanType extends NativeType with PrimitiveType { private[sql] type JvmType = Boolean @transient private[sql] lazy val tag = ScalaReflectionLock.synchronized { typeTag[JvmType] } private[sql] val ordering = implicitly[Ordering[JvmType]] } + +/** + * :: DeveloperApi :: + * + * The data type representing `java.sql.Timestamp` values. + * Please use the singleton [[DataTypes.TimestampType]]. + * + * @group dataType + */ +@DeveloperApi case object TimestampType extends NativeType { private[sql] type JvmType = Timestamp @@ -303,6 +362,16 @@ case object TimestampType extends NativeType { } } + +/** + * :: DeveloperApi :: + * + * The data type representing `java.sql.Date` values. + * Please use the singleton [[DataTypes.DateType]]. + * + * @group dataType + */ +@DeveloperApi case object DateType extends NativeType { private[sql] type JvmType = Date @@ -313,6 +382,7 @@ case object DateType extends NativeType { } } + abstract class NumericType extends NativeType with PrimitiveType { // Unfortunately we can't get this implicitly as that breaks Spark Serialization. In order for // implicitly[Numeric[JvmType]] to be valid, we have to change JvmType from a type variable to a @@ -322,10 +392,12 @@ abstract class NumericType extends NativeType with PrimitiveType { private[sql] val numeric: Numeric[JvmType] } + object NumericType { def unapply(e: Expression): Boolean = e.dataType.isInstanceOf[NumericType] } + /** Matcher for any expressions that evaluate to [[IntegralType]]s */ object IntegralType { def unapply(a: Expression): Boolean = a match { @@ -334,10 +406,20 @@ object IntegralType { } } -abstract class IntegralType extends NumericType { + +sealed abstract class IntegralType extends NumericType { private[sql] val integral: Integral[JvmType] } + +/** + * :: DeveloperApi :: + * + * The data type representing `Long` values. Please use the singleton [[DataTypes.LongType]]. + * + * @group dataType + */ +@DeveloperApi case object LongType extends IntegralType { private[sql] type JvmType = Long @transient private[sql] lazy val tag = ScalaReflectionLock.synchronized { typeTag[JvmType] } @@ -346,6 +428,15 @@ case object LongType extends IntegralType { private[sql] val ordering = implicitly[Ordering[JvmType]] } + +/** + * :: DeveloperApi :: + * + * The data type representing `Int` values. Please use the singleton [[DataTypes.IntegerType]]. + * + * @group dataType + */ +@DeveloperApi case object IntegerType extends IntegralType { private[sql] type JvmType = Int @transient private[sql] lazy val tag = ScalaReflectionLock.synchronized { typeTag[JvmType] } @@ -354,6 +445,15 @@ case object IntegerType extends IntegralType { private[sql] val ordering = implicitly[Ordering[JvmType]] } + +/** + * :: DeveloperApi :: + * + * The data type representing `Short` values. Please use the singleton [[DataTypes.ShortType]]. + * + * @group dataType + */ +@DeveloperApi case object ShortType extends IntegralType { private[sql] type JvmType = Short @transient private[sql] lazy val tag = ScalaReflectionLock.synchronized { typeTag[JvmType] } @@ -362,6 +462,15 @@ case object ShortType extends IntegralType { private[sql] val ordering = implicitly[Ordering[JvmType]] } + +/** + * :: DeveloperApi :: + * + * The data type representing `Byte` values. Please use the singleton [[DataTypes.ByteType]]. + * + * @group dataType + */ +@DeveloperApi case object ByteType extends IntegralType { private[sql] type JvmType = Byte @transient private[sql] lazy val tag = ScalaReflectionLock.synchronized { typeTag[JvmType] } @@ -370,6 +479,7 @@ case object ByteType extends IntegralType { private[sql] val ordering = implicitly[Ordering[JvmType]] } + /** Matcher for any expressions that evaluate to [[FractionalType]]s */ object FractionalType { def unapply(a: Expression): Boolean = a match { @@ -378,15 +488,28 @@ object FractionalType { } } -abstract class FractionalType extends NumericType { + +sealed abstract class FractionalType extends NumericType { private[sql] val fractional: Fractional[JvmType] private[sql] val asIntegral: Integral[JvmType] } + /** Precision parameters for a Decimal */ case class PrecisionInfo(precision: Int, scale: Int) -/** A Decimal that might have fixed precision and scale, or unlimited values for these */ + +/** + * :: DeveloperApi :: + * + * The data type representing `scala.math.BigDecimal` values. + * A Decimal that might have fixed precision and scale, or unlimited values for these. + * + * Please use [[DataTypes.createDecimalType()]] to create a specific instance. + * + * @group dataType + */ +@DeveloperApi case class DecimalType(precisionInfo: Option[PrecisionInfo]) extends FractionalType { private[sql] type JvmType = Decimal @transient private[sql] lazy val tag = ScalaReflectionLock.synchronized { typeTag[JvmType] } @@ -395,6 +518,10 @@ case class DecimalType(precisionInfo: Option[PrecisionInfo]) extends FractionalT private[sql] val ordering = Decimal.DecimalIsFractional private[sql] val asIntegral = Decimal.DecimalAsIfIntegral + def precision: Int = precisionInfo.map(_.precision).getOrElse(-1) + + def scale: Int = precisionInfo.map(_.scale).getOrElse(-1) + override def typeName: String = precisionInfo match { case Some(PrecisionInfo(precision, scale)) => s"decimal($precision,$scale)" case None => "decimal" @@ -406,6 +533,7 @@ case class DecimalType(precisionInfo: Option[PrecisionInfo]) extends FractionalT } } + /** Extra factory methods and pattern matchers for Decimals */ object DecimalType { val Unlimited: DecimalType = DecimalType(None) @@ -437,6 +565,15 @@ object DecimalType { } } + +/** + * :: DeveloperApi :: + * + * The data type representing `Double` values. Please use the singleton [[DataTypes.DoubleType]]. + * + * @group dataType + */ +@DeveloperApi case object DoubleType extends FractionalType { private[sql] type JvmType = Double @transient private[sql] lazy val tag = ScalaReflectionLock.synchronized { typeTag[JvmType] } @@ -446,6 +583,15 @@ case object DoubleType extends FractionalType { private[sql] val asIntegral = DoubleAsIfIntegral } + +/** + * :: DeveloperApi :: + * + * The data type representing `Float` values. Please use the singleton [[DataTypes.FloatType]]. + * + * @group dataType + */ +@DeveloperApi case object FloatType extends FractionalType { private[sql] type JvmType = Float @transient private[sql] lazy val tag = ScalaReflectionLock.synchronized { typeTag[JvmType] } @@ -455,18 +601,31 @@ case object FloatType extends FractionalType { private[sql] val asIntegral = FloatAsIfIntegral } + object ArrayType { /** Construct a [[ArrayType]] object with the given element type. The `containsNull` is true. */ def apply(elementType: DataType): ArrayType = ArrayType(elementType, true) } + /** + * :: DeveloperApi :: + * * The data type for collections of multiple values. * Internally these are represented as columns that contain a ``scala.collection.Seq``. * + * Please use [[DataTypes.createArrayType()]] to create a specific instance. + * + * An [[ArrayType]] object comprises two fields, `elementType: [[DataType]]` and + * `containsNull: Boolean`. The field of `elementType` is used to specify the type of + * array elements. The field of `containsNull` is used to specify if the array has `null` values. + * * @param elementType The data type of values. * @param containsNull Indicates if values have `null` values + * + * @group dataType */ +@DeveloperApi case class ArrayType(elementType: DataType, containsNull: Boolean) extends DataType { private[sql] def buildFormattedString(prefix: String, builder: StringBuilder): Unit = { builder.append( @@ -480,8 +639,10 @@ case class ArrayType(elementType: DataType, containsNull: Boolean) extends DataT ("containsNull" -> containsNull) } + /** * A field inside a StructType. + * * @param name The name of this field. * @param dataType The data type of this field. * @param nullable Indicates if values of this field can be `null` values. @@ -510,19 +671,92 @@ case class StructField( } } + object StructType { protected[sql] def fromAttributes(attributes: Seq[Attribute]): StructType = StructType(attributes.map(a => StructField(a.name, a.dataType, a.nullable, a.metadata))) + + def apply(fields: Seq[StructField]): StructType = StructType(fields.toArray) + + def apply(fields: java.util.List[StructField]): StructType = { + StructType(fields.toArray.asInstanceOf[Array[StructField]]) + } } -case class StructType(fields: Seq[StructField]) extends DataType { - /** - * Returns all field names in a [[Seq]]. - */ - lazy val fieldNames: Seq[String] = fields.map(_.name) +/** + * :: DeveloperApi :: + * + * A [[StructType]] object can be constructed by + * {{{ + * StructType(fields: Seq[StructField]) + * }}} + * For a [[StructType]] object, one or multiple [[StructField]]s can be extracted by names. + * If multiple [[StructField]]s are extracted, a [[StructType]] object will be returned. + * If a provided name does not have a matching field, it will be ignored. For the case + * of extracting a single StructField, a `null` will be returned. + * Example: + * {{{ + * import org.apache.spark.sql._ + * + * val struct = + * StructType( + * StructField("a", IntegerType, true) :: + * StructField("b", LongType, false) :: + * StructField("c", BooleanType, false) :: Nil) + * + * // Extract a single StructField. + * val singleField = struct("b") + * // singleField: StructField = StructField(b,LongType,false) + * + * // This struct does not have a field called "d". null will be returned. + * val nonExisting = struct("d") + * // nonExisting: StructField = null + * + * // Extract multiple StructFields. Field names are provided in a set. + * // A StructType object will be returned. + * val twoFields = struct(Set("b", "c")) + * // twoFields: StructType = + * // StructType(List(StructField(b,LongType,false), StructField(c,BooleanType,false))) + * + * // Any names without matching fields will be ignored. + * // For the case shown below, "d" will be ignored and + * // it is treated as struct(Set("b", "c")). + * val ignoreNonExisting = struct(Set("b", "c", "d")) + * // ignoreNonExisting: StructType = + * // StructType(List(StructField(b,LongType,false), StructField(c,BooleanType,false))) + * }}} + * + * A [[org.apache.spark.sql.catalyst.expressions.Row]] object is used as a value of the StructType. + * Example: + * {{{ + * import org.apache.spark.sql._ + * + * val innerStruct = + * StructType( + * StructField("f1", IntegerType, true) :: + * StructField("f2", LongType, false) :: + * StructField("f3", BooleanType, false) :: Nil) + * + * val struct = StructType( + * StructField("a", innerStruct, true) :: Nil) + * + * // Create a Row with the schema defined by struct + * val row = Row(Row(1, 2, true)) + * // row: Row = [[1,2,true]] + * }}} + * + * @group dataType + */ +@DeveloperApi +case class StructType(fields: Array[StructField]) extends DataType with Seq[StructField] { + + /** Returns all field names in an array. */ + def fieldNames: Array[String] = fields.map(_.name) + private lazy val fieldNamesSet: Set[String] = fieldNames.toSet private lazy val nameToField: Map[String, StructField] = fields.map(f => f.name -> f).toMap + /** * Extracts a [[StructField]] of the given name. If the [[StructType]] object does not * have a name matching the given name, `null` will be returned. @@ -532,8 +766,8 @@ case class StructType(fields: Seq[StructField]) extends DataType { } /** - * Returns a [[StructType]] containing [[StructField]]s of the given names. - * Those names which do not have matching fields will be ignored. + * Returns a [[StructType]] containing [[StructField]]s of the given names, preserving the + * original order of fields. Those names which do not have matching fields will be ignored. */ def apply(names: Set[String]): StructType = { val nonExistFields = names -- fieldNamesSet @@ -545,8 +779,8 @@ case class StructType(fields: Seq[StructField]) extends DataType { StructType(fields.filter(f => names.contains(f.name))) } - protected[sql] def toAttributes = - fields.map(f => AttributeReference(f.name, f.dataType, f.nullable, f.metadata)()) + protected[sql] def toAttributes: Seq[AttributeReference] = + map(f => AttributeReference(f.name, f.dataType, f.nullable, f.metadata)()) def treeString: String = { val builder = new StringBuilder @@ -565,23 +799,38 @@ case class StructType(fields: Seq[StructField]) extends DataType { override private[sql] def jsonValue = ("type" -> typeName) ~ - ("fields" -> fields.map(_.jsonValue)) + ("fields" -> map(_.jsonValue)) + + override def apply(fieldIndex: Int): StructField = fields(fieldIndex) + + override def length: Int = fields.length + + override def iterator: Iterator[StructField] = fields.iterator } + object MapType { /** * Construct a [[MapType]] object with the given key type and value type. * The `valueContainsNull` is true. */ def apply(keyType: DataType, valueType: DataType): MapType = - MapType(keyType: DataType, valueType: DataType, true) + MapType(keyType: DataType, valueType: DataType, valueContainsNull = true) } + /** + * :: DeveloperApi :: + * * The data type for Maps. Keys in a map are not allowed to have `null` values. + * + * Please use [[DataTypes.createMapType()]] to create a specific instance. + * * @param keyType The data type of map keys. * @param valueType The data type of map values. * @param valueContainsNull Indicates if map values have `null` values. + * + * @group dataType */ case class MapType( keyType: DataType, @@ -602,6 +851,7 @@ case class MapType( ("valueContainsNull" -> valueContainsNull) } + /** * ::DeveloperApi:: * The data type for User Defined Types (UDTs). @@ -611,7 +861,7 @@ case class MapType( * a SchemaRDD which has class X in the schema. * * For SparkSQL to recognize UDTs, the UDT must be annotated with - * [[org.apache.spark.sql.catalyst.annotation.SQLUserDefinedType]]. + * [[SQLUserDefinedType]]. * * The conversion via `serialize` occurs when instantiating a `SchemaRDD` from another RDD. * The conversion via `deserialize` occurs when reading from a `SchemaRDD`. diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/decimal/Decimal.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/decimal/Decimal.scala similarity index 99% rename from sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/decimal/Decimal.scala rename to sql/catalyst/src/main/scala/org/apache/spark/sql/types/decimal/Decimal.scala index 708362acf32dc..c7864d1ae9e74 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/decimal/Decimal.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/decimal/Decimal.scala @@ -15,7 +15,7 @@ * limitations under the License. */ -package org.apache.spark.sql.catalyst.types.decimal +package org.apache.spark.sql.types.decimal import org.apache.spark.annotation.DeveloperApi diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/package.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/package.scala similarity index 96% rename from sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/package.scala rename to sql/catalyst/src/main/scala/org/apache/spark/sql/types/package.scala index de24449590f9a..346a51ea10c82 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/package.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/package.scala @@ -15,7 +15,8 @@ * limitations under the License. */ -package org.apache.spark.sql.catalyst +package org.apache.spark.sql + /** * Contains a type system for attributes produced by relations, including complex types like * structs, arrays and maps. diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/ScalaReflectionSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/ScalaReflectionSuite.scala index 7be24bea7d5a6..117725df32e19 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/ScalaReflectionSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/ScalaReflectionSuite.scala @@ -23,7 +23,7 @@ import java.sql.{Date, Timestamp} import org.scalatest.FunSuite import org.apache.spark.sql.catalyst.expressions.Row -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ case class PrimitiveData( intField: Int, diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala index f430057ef7191..3aea337460d42 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala @@ -22,7 +22,7 @@ import org.scalatest.{BeforeAndAfter, FunSuite} import org.apache.spark.sql.catalyst.expressions.{Alias, AttributeReference} import org.apache.spark.sql.catalyst.errors.TreeNodeException import org.apache.spark.sql.catalyst.plans.logical._ -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ import org.apache.spark.sql.catalyst.dsl.expressions._ import org.apache.spark.sql.catalyst.dsl.plans._ diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/DecimalPrecisionSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/DecimalPrecisionSuite.scala index bbbeb4f2e4fe3..bc2ec754d5865 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/DecimalPrecisionSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/DecimalPrecisionSuite.scala @@ -19,7 +19,7 @@ package org.apache.spark.sql.catalyst.analysis import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.logical.{Project, LocalRelation} -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ import org.scalatest.{BeforeAndAfter, FunSuite} class DecimalPrecisionSuite extends FunSuite with BeforeAndAfter { diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercionSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercionSuite.scala index dfa2d958c0faf..f5a502b43f80b 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercionSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercionSuite.scala @@ -21,7 +21,7 @@ import org.scalatest.FunSuite import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.logical.{LocalRelation, Project} -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ class HiveTypeCoercionSuite extends FunSuite { diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala index 4ba7d87ba8c5a..8552448b8d108 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala @@ -21,16 +21,14 @@ import java.sql.{Date, Timestamp} import scala.collection.immutable.HashSet -import org.apache.spark.sql.catalyst.types.decimal.Decimal +import org.scalactic.TripleEqualsSupport.Spread import org.scalatest.FunSuite import org.scalatest.Matchers._ -import org.scalactic.TripleEqualsSupport.Spread - -import org.apache.spark.sql.catalyst.types._ - -/* Implicit conversions */ import org.apache.spark.sql.catalyst.dsl.expressions._ +import org.apache.spark.sql.types._ +import org.apache.spark.sql.types.decimal.Decimal + class ExpressionEvaluationSuite extends FunSuite { diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ConstantFoldingSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ConstantFoldingSuite.scala index 0a27cce337482..9fdf3efa02bb6 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ConstantFoldingSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ConstantFoldingSuite.scala @@ -22,7 +22,7 @@ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.logical.{LocalRelation, LogicalPlan} import org.apache.spark.sql.catalyst.plans.PlanTest import org.apache.spark.sql.catalyst.rules.RuleExecutor -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ // For implicit conversions import org.apache.spark.sql.catalyst.dsl.plans._ diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/OptimizeInSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/OptimizeInSuite.scala index 017b180c574b4..da912ab382179 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/OptimizeInSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/OptimizeInSuite.scala @@ -23,7 +23,7 @@ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.logical.{LocalRelation, LogicalPlan} import org.apache.spark.sql.catalyst.plans.PlanTest import org.apache.spark.sql.catalyst.rules.RuleExecutor -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ // For implicit conversions import org.apache.spark.sql.catalyst.dsl.plans._ diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/trees/TreeNodeSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/trees/TreeNodeSuite.scala index 036fd3fa1d6a1..cdb843f959704 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/trees/TreeNodeSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/trees/TreeNodeSuite.scala @@ -22,7 +22,7 @@ import scala.collection.mutable.ArrayBuffer import org.scalatest.FunSuite import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.catalyst.types.{StringType, NullType} +import org.apache.spark.sql.types.{StringType, NullType} case class Dummy(optKey: Option[Expression]) extends Expression { def children = optKey.toSeq diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/MetadataSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/MetadataSuite.scala index f005b7df21043..d7d60efee50fa 100755 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/MetadataSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/MetadataSuite.scala @@ -20,6 +20,8 @@ package org.apache.spark.sql.catalyst.util import org.json4s.jackson.JsonMethods.parse import org.scalatest.FunSuite +import org.apache.spark.sql.types.{MetadataBuilder, Metadata} + class MetadataSuite extends FunSuite { val baseMetadata = new MetadataBuilder() diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataTypeSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/types/DataTypeSuite.scala similarity index 98% rename from sql/core/src/test/scala/org/apache/spark/sql/DataTypeSuite.scala rename to sql/catalyst/src/test/scala/org/apache/spark/sql/types/DataTypeSuite.scala index e9740d913cf57..892195f46ea24 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/DataTypeSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/types/DataTypeSuite.scala @@ -15,7 +15,7 @@ * limitations under the License. */ -package org.apache.spark.sql +package org.apache.spark.sql.types import org.scalatest.FunSuite diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/types/decimal/DecimalSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/types/decimal/DecimalSuite.scala similarity index 99% rename from sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/types/decimal/DecimalSuite.scala rename to sql/catalyst/src/test/scala/org/apache/spark/sql/types/decimal/DecimalSuite.scala index e32f1ac382130..813377df00132 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/types/decimal/DecimalSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/types/decimal/DecimalSuite.scala @@ -15,7 +15,7 @@ * limitations under the License. */ -package org.apache.spark.sql.catalyst.types.decimal +package org.apache.spark.sql.types.decimal import org.scalatest.{PrivateMethodTester, FunSuite} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/ArrayType.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/ArrayType.java deleted file mode 100644 index b73a371e93001..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/ArrayType.java +++ /dev/null @@ -1,68 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -/** - * The data type representing Lists. - * An ArrayType object comprises two fields, {@code DataType elementType} and - * {@code boolean containsNull}. The field of {@code elementType} is used to specify the type of - * array elements. The field of {@code containsNull} is used to specify if the array has - * {@code null} values. - * - * To create an {@link ArrayType}, - * {@link DataType#createArrayType(DataType)} or - * {@link DataType#createArrayType(DataType, boolean)} - * should be used. - */ -public class ArrayType extends DataType { - private DataType elementType; - private boolean containsNull; - - protected ArrayType(DataType elementType, boolean containsNull) { - this.elementType = elementType; - this.containsNull = containsNull; - } - - public DataType getElementType() { - return elementType; - } - - public boolean isContainsNull() { - return containsNull; - } - - @Override - public boolean equals(Object o) { - if (this == o) return true; - if (o == null || getClass() != o.getClass()) return false; - - ArrayType arrayType = (ArrayType) o; - - if (containsNull != arrayType.containsNull) return false; - if (!elementType.equals(arrayType.elementType)) return false; - - return true; - } - - @Override - public int hashCode() { - int result = elementType.hashCode(); - result = 31 * result + (containsNull ? 1 : 0); - return result; - } -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/BinaryType.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/BinaryType.java deleted file mode 100644 index 7daad60f62a0b..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/BinaryType.java +++ /dev/null @@ -1,27 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -/** - * The data type representing byte[] values. - * - * {@code BinaryType} is represented by the singleton object {@link DataType#BinaryType}. - */ -public class BinaryType extends DataType { - protected BinaryType() {} -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/BooleanType.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/BooleanType.java deleted file mode 100644 index 5a1f52725631b..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/BooleanType.java +++ /dev/null @@ -1,27 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -/** - * The data type representing boolean and Boolean values. - * - * {@code BooleanType} is represented by the singleton object {@link DataType#BooleanType}. - */ -public class BooleanType extends DataType { - protected BooleanType() {} -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/ByteType.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/ByteType.java deleted file mode 100644 index e5cdf06b21bbe..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/ByteType.java +++ /dev/null @@ -1,27 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -/** - * The data type representing byte and Byte values. - * - * {@code ByteType} is represented by the singleton object {@link DataType#ByteType}. - */ -public class ByteType extends DataType { - protected ByteType() {} -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/DateType.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/DateType.java deleted file mode 100644 index 6677793baa365..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/DateType.java +++ /dev/null @@ -1,27 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -/** - * The data type representing java.sql.Date values. - * - * {@code DateType} is represented by the singleton object {@link DataType#DateType}. - */ -public class DateType extends DataType { - protected DateType() {} -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/DecimalType.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/DecimalType.java deleted file mode 100644 index 60752451ecfc7..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/DecimalType.java +++ /dev/null @@ -1,79 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -/** - * The data type representing java.math.BigDecimal values. - */ -public class DecimalType extends DataType { - private boolean hasPrecisionInfo; - private int precision; - private int scale; - - public DecimalType(int precision, int scale) { - this.hasPrecisionInfo = true; - this.precision = precision; - this.scale = scale; - } - - public DecimalType() { - this.hasPrecisionInfo = false; - this.precision = -1; - this.scale = -1; - } - - public boolean isUnlimited() { - return !hasPrecisionInfo; - } - - public boolean isFixed() { - return hasPrecisionInfo; - } - - /** Return the precision, or -1 if no precision is set */ - public int getPrecision() { - return precision; - } - - /** Return the scale, or -1 if no precision is set */ - public int getScale() { - return scale; - } - - @Override - public boolean equals(Object o) { - if (this == o) return true; - if (o == null || getClass() != o.getClass()) return false; - - DecimalType that = (DecimalType) o; - - if (hasPrecisionInfo != that.hasPrecisionInfo) return false; - if (precision != that.precision) return false; - if (scale != that.scale) return false; - - return true; - } - - @Override - public int hashCode() { - int result = (hasPrecisionInfo ? 1 : 0); - result = 31 * result + precision; - result = 31 * result + scale; - return result; - } -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/DoubleType.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/DoubleType.java deleted file mode 100644 index f0060d0bcf9f5..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/DoubleType.java +++ /dev/null @@ -1,27 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -/** - * The data type representing double and Double values. - * - * {@code DoubleType} is represented by the singleton object {@link DataType#DoubleType}. - */ -public class DoubleType extends DataType { - protected DoubleType() {} -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/FloatType.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/FloatType.java deleted file mode 100644 index 4a6a37f69176a..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/FloatType.java +++ /dev/null @@ -1,27 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -/** - * The data type representing float and Float values. - * - * {@code FloatType} is represented by the singleton object {@link DataType#FloatType}. - */ -public class FloatType extends DataType { - protected FloatType() {} -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/IntegerType.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/IntegerType.java deleted file mode 100644 index bfd70490bbbbb..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/IntegerType.java +++ /dev/null @@ -1,27 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -/** - * The data type representing int and Integer values. - * - * {@code IntegerType} is represented by the singleton object {@link DataType#IntegerType}. - */ -public class IntegerType extends DataType { - protected IntegerType() {} -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/LongType.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/LongType.java deleted file mode 100644 index af13a46eb165c..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/LongType.java +++ /dev/null @@ -1,27 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -/** - * The data type representing long and Long values. - * - * {@code LongType} is represented by the singleton object {@link DataType#LongType}. - */ -public class LongType extends DataType { - protected LongType() {} -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/MapType.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/MapType.java deleted file mode 100644 index 063e6b34abc48..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/MapType.java +++ /dev/null @@ -1,78 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -/** - * The data type representing Maps. A MapType object comprises two fields, - * {@code DataType keyType}, {@code DataType valueType}, and {@code boolean valueContainsNull}. - * The field of {@code keyType} is used to specify the type of keys in the map. - * The field of {@code valueType} is used to specify the type of values in the map. - * The field of {@code valueContainsNull} is used to specify if map values have - * {@code null} values. - * For values of a MapType column, keys are not allowed to have {@code null} values. - * - * To create a {@link MapType}, - * {@link DataType#createMapType(DataType, DataType)} or - * {@link DataType#createMapType(DataType, DataType, boolean)} - * should be used. - */ -public class MapType extends DataType { - private DataType keyType; - private DataType valueType; - private boolean valueContainsNull; - - protected MapType(DataType keyType, DataType valueType, boolean valueContainsNull) { - this.keyType = keyType; - this.valueType = valueType; - this.valueContainsNull = valueContainsNull; - } - - public DataType getKeyType() { - return keyType; - } - - public DataType getValueType() { - return valueType; - } - - public boolean isValueContainsNull() { - return valueContainsNull; - } - - @Override - public boolean equals(Object o) { - if (this == o) return true; - if (o == null || getClass() != o.getClass()) return false; - - MapType mapType = (MapType) o; - - if (valueContainsNull != mapType.valueContainsNull) return false; - if (!keyType.equals(mapType.keyType)) return false; - if (!valueType.equals(mapType.valueType)) return false; - - return true; - } - - @Override - public int hashCode() { - int result = keyType.hashCode(); - result = 31 * result + valueType.hashCode(); - result = 31 * result + (valueContainsNull ? 1 : 0); - return result; - } -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/Metadata.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/Metadata.java deleted file mode 100644 index 0f819fb01a76a..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/Metadata.java +++ /dev/null @@ -1,31 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -/** - * Metadata is a wrapper over Map[String, Any] that limits the value type to simple ones: Boolean, - * Long, Double, String, Metadata, Array[Boolean], Array[Long], Array[Double], Array[String], and - * Array[Metadata]. JSON is used for serialization. - * - * The default constructor is private. User should use [[MetadataBuilder]]. - */ -class Metadata extends org.apache.spark.sql.catalyst.util.Metadata { - Metadata(scala.collection.immutable.Map map) { - super(map); - } -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/MetadataBuilder.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/MetadataBuilder.java deleted file mode 100644 index 6e6b12f0722c5..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/MetadataBuilder.java +++ /dev/null @@ -1,28 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -/** - * Builder for [[Metadata]]. If there is a key collision, the latter will overwrite the former. - */ -public class MetadataBuilder extends org.apache.spark.sql.catalyst.util.MetadataBuilder { - @Override - public Metadata build() { - return new Metadata(getMap()); - } -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/NullType.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/NullType.java deleted file mode 100644 index 6d5ecdf46e551..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/NullType.java +++ /dev/null @@ -1,27 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -/** - * The data type representing null and NULL values. - * - * {@code NullType} is represented by the singleton object {@link DataType#NullType}. - */ -public class NullType extends DataType { - protected NullType() {} -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/ShortType.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/ShortType.java deleted file mode 100644 index 7d7604b4e3d2d..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/ShortType.java +++ /dev/null @@ -1,27 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -/** - * The data type representing short and Short values. - * - * {@code ShortType} is represented by the singleton object {@link DataType#ShortType}. - */ -public class ShortType extends DataType { - protected ShortType() {} -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/StringType.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/StringType.java deleted file mode 100644 index f4ba0c07c9c6e..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/StringType.java +++ /dev/null @@ -1,27 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -/** - * The data type representing String values. - * - * {@code StringType} is represented by the singleton object {@link DataType#StringType}. - */ -public class StringType extends DataType { - protected StringType() {} -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/StructField.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/StructField.java deleted file mode 100644 index 7c60d492bcdf0..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/StructField.java +++ /dev/null @@ -1,91 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -import java.util.Map; - -/** - * A StructField object represents a field in a StructType object. - * A StructField object comprises three fields, {@code String name}, {@code DataType dataType}, - * and {@code boolean nullable}. The field of {@code name} is the name of a StructField. - * The field of {@code dataType} specifies the data type of a StructField. - * The field of {@code nullable} specifies if values of a StructField can contain {@code null} - * values. - * The field of {@code metadata} provides extra information of the StructField. - * - * To create a {@link StructField}, - * {@link DataType#createStructField(String, DataType, boolean, Metadata)} - * should be used. - */ -public class StructField { - private String name; - private DataType dataType; - private boolean nullable; - private Metadata metadata; - - protected StructField( - String name, - DataType dataType, - boolean nullable, - Metadata metadata) { - this.name = name; - this.dataType = dataType; - this.nullable = nullable; - this.metadata = metadata; - } - - public String getName() { - return name; - } - - public DataType getDataType() { - return dataType; - } - - public boolean isNullable() { - return nullable; - } - - public Metadata getMetadata() { - return metadata; - } - - @Override - public boolean equals(Object o) { - if (this == o) return true; - if (o == null || getClass() != o.getClass()) return false; - - StructField that = (StructField) o; - - if (nullable != that.nullable) return false; - if (!dataType.equals(that.dataType)) return false; - if (!name.equals(that.name)) return false; - if (!metadata.equals(that.metadata)) return false; - - return true; - } - - @Override - public int hashCode() { - int result = name.hashCode(); - result = 31 * result + dataType.hashCode(); - result = 31 * result + (nullable ? 1 : 0); - result = 31 * result + metadata.hashCode(); - return result; - } -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/StructType.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/StructType.java deleted file mode 100644 index a4b501efd9a10..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/StructType.java +++ /dev/null @@ -1,58 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -import java.util.Arrays; - -/** - * The data type representing Rows. - * A StructType object comprises an array of StructFields. - * - * To create an {@link StructType}, - * {@link DataType#createStructType(java.util.List)} or - * {@link DataType#createStructType(StructField[])} - * should be used. - */ -public class StructType extends DataType { - private StructField[] fields; - - protected StructType(StructField[] fields) { - this.fields = fields; - } - - public StructField[] getFields() { - return fields; - } - - @Override - public boolean equals(Object o) { - if (this == o) return true; - if (o == null || getClass() != o.getClass()) return false; - - StructType that = (StructType) o; - - if (!Arrays.equals(fields, that.fields)) return false; - - return true; - } - - @Override - public int hashCode() { - return Arrays.hashCode(fields); - } -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/TimestampType.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/TimestampType.java deleted file mode 100644 index 06d44c731cdfe..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/TimestampType.java +++ /dev/null @@ -1,27 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -/** - * The data type representing java.sql.Timestamp values. - * - * {@code TimestampType} is represented by the singleton object {@link DataType#TimestampType}. - */ -public class TimestampType extends DataType { - protected TimestampType() {} -} diff --git a/sql/core/src/main/java/org/apache/spark/sql/api/java/UserDefinedType.java b/sql/core/src/main/java/org/apache/spark/sql/api/java/UserDefinedType.java deleted file mode 100644 index f0d079d25b5d4..0000000000000 --- a/sql/core/src/main/java/org/apache/spark/sql/api/java/UserDefinedType.java +++ /dev/null @@ -1,54 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -import java.io.Serializable; - -import org.apache.spark.annotation.DeveloperApi; - -/** - * ::DeveloperApi:: - * The data type representing User-Defined Types (UDTs). - * UDTs may use any other DataType for an underlying representation. - */ -@DeveloperApi -public abstract class UserDefinedType extends DataType implements Serializable { - - protected UserDefinedType() { } - - @Override - public boolean equals(Object o) { - if (this == o) return true; - if (o == null || getClass() != o.getClass()) return false; - @SuppressWarnings("unchecked") - UserDefinedType that = (UserDefinedType) o; - return this.sqlType().equals(that.sqlType()); - } - - /** Underlying storage type for this UDT */ - public abstract DataType sqlType(); - - /** Convert the user type to a SQL datum */ - public abstract Object serialize(Object obj); - - /** Convert a SQL datum to the user type */ - public abstract UserType deserialize(Object datum); - - /** Class object for the UserType */ - public abstract Class userClass(); -} diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala index d8efce0cb43eb..d9f3b3a53f582 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala @@ -24,7 +24,6 @@ import scala.language.implicitConversions import scala.reflect.runtime.universe.TypeTag import org.apache.hadoop.conf.Configuration - import org.apache.spark.SparkContext import org.apache.spark.annotation.{AlphaComponent, DeveloperApi, Experimental} import org.apache.spark.rdd.RDD @@ -32,14 +31,14 @@ import org.apache.spark.sql.catalyst.ScalaReflection import org.apache.spark.sql.catalyst.analysis._ import org.apache.spark.sql.catalyst.dsl.ExpressionConversions import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.catalyst.optimizer.{Optimizer, DefaultOptimizer} +import org.apache.spark.sql.catalyst.optimizer.{DefaultOptimizer, Optimizer} import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan import org.apache.spark.sql.catalyst.rules.RuleExecutor -import org.apache.spark.sql.catalyst.types.UserDefinedType -import org.apache.spark.sql.execution.{SparkStrategies, _} +import org.apache.spark.sql.execution._ import org.apache.spark.sql.json._ import org.apache.spark.sql.parquet.ParquetRelation -import org.apache.spark.sql.sources.{DataSourceStrategy, BaseRelation, DDLParser, LogicalRelation} +import org.apache.spark.sql.sources.{BaseRelation, DDLParser, DataSourceStrategy, LogicalRelation} +import org.apache.spark.sql.types._ /** * :: AlphaComponent :: diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala index 80787b61ce1bf..686bcdfbb4ff1 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala @@ -17,8 +17,7 @@ package org.apache.spark.sql -import java.util.{Map => JMap, List => JList} - +import java.util.{List => JList} import scala.collection.JavaConversions._ @@ -37,8 +36,9 @@ import org.apache.spark.sql.catalyst.analysis._ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.{Inner, JoinType} import org.apache.spark.sql.catalyst.plans.logical._ -import org.apache.spark.sql.json.JsonRDD import org.apache.spark.sql.execution.{LogicalRDD, EvaluatePython} +import org.apache.spark.sql.json.JsonRDD +import org.apache.spark.sql.types.{BooleanType, StructType} import org.apache.spark.storage.StorageLevel /** diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SparkSQLParser.scala b/sql/core/src/main/scala/org/apache/spark/sql/SparkSQLParser.scala index 65358b7d4ea8e..f10ee7b66feb7 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SparkSQLParser.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SparkSQLParser.scala @@ -17,12 +17,14 @@ package org.apache.spark.sql +import scala.util.parsing.combinator.RegexParsers + import org.apache.spark.sql.catalyst.{SqlLexical, AbstractSparkSQLParser} import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeReference} import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan import org.apache.spark.sql.execution.{UncacheTableCommand, CacheTableCommand, SetCommand} +import org.apache.spark.sql.types.StringType -import scala.util.parsing.combinator.RegexParsers /** * The top level Spark SQL parser. This parser recognizes syntaxes that are available for all SQL diff --git a/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSQLContext.scala index 7f868cd4afca4..a75f55992826a 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSQLContext.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSQLContext.scala @@ -23,15 +23,13 @@ import org.apache.hadoop.conf.Configuration import org.apache.spark.annotation.{DeveloperApi, Experimental} import org.apache.spark.api.java.{JavaRDD, JavaSparkContext} -import org.apache.spark.sql.{SQLContext, StructType => SStructType} -import org.apache.spark.sql.catalyst.annotation.SQLUserDefinedType +import org.apache.spark.sql.SQLContext import org.apache.spark.sql.catalyst.expressions.{AttributeReference, GenericRow, Row => ScalaRow} import org.apache.spark.sql.execution.LogicalRDD import org.apache.spark.sql.json.JsonRDD import org.apache.spark.sql.parquet.ParquetRelation import org.apache.spark.sql.sources.{LogicalRelation, BaseRelation} -import org.apache.spark.sql.types.util.DataTypeConversions -import org.apache.spark.sql.types.util.DataTypeConversions.asScalaDataType +import org.apache.spark.sql.types._ import org.apache.spark.util.Utils /** @@ -126,9 +124,8 @@ class JavaSQLContext(val sqlContext: SQLContext) extends UDFRegistration { @DeveloperApi def applySchema(rowRDD: JavaRDD[Row], schema: StructType): JavaSchemaRDD = { val scalaRowRDD = rowRDD.rdd.map(r => r.row) - val scalaSchema = asScalaDataType(schema).asInstanceOf[SStructType] val logicalPlan = - LogicalRDD(scalaSchema.toAttributes, scalaRowRDD)(sqlContext) + LogicalRDD(schema.toAttributes, scalaRowRDD)(sqlContext) new JavaSchemaRDD(sqlContext, logicalPlan) } @@ -184,10 +181,10 @@ class JavaSQLContext(val sqlContext: SQLContext) extends UDFRegistration { def jsonRDD(json: JavaRDD[String], schema: StructType): JavaSchemaRDD = { val columnNameOfCorruptJsonRecord = sqlContext.conf.columnNameOfCorruptRecord val appliedScalaSchema = - Option(asScalaDataType(schema)).getOrElse( + Option(schema).getOrElse( JsonRDD.nullTypeToStringType( JsonRDD.inferSchema( - json.rdd, 1.0, columnNameOfCorruptJsonRecord))).asInstanceOf[SStructType] + json.rdd, 1.0, columnNameOfCorruptJsonRecord))) val scalaRowRDD = JsonRDD.jsonStringToRow( json.rdd, appliedScalaSchema, columnNameOfCorruptJsonRecord) val logicalPlan = @@ -218,43 +215,25 @@ class JavaSQLContext(val sqlContext: SQLContext) extends UDFRegistration { val (dataType, nullable) = property.getPropertyType match { case c: Class[_] if c.isAnnotationPresent(classOf[SQLUserDefinedType]) => (c.getAnnotation(classOf[SQLUserDefinedType]).udt().newInstance(), true) - case c: Class[_] if c == classOf[java.lang.String] => - (org.apache.spark.sql.StringType, true) - case c: Class[_] if c == java.lang.Short.TYPE => - (org.apache.spark.sql.ShortType, false) - case c: Class[_] if c == java.lang.Integer.TYPE => - (org.apache.spark.sql.IntegerType, false) - case c: Class[_] if c == java.lang.Long.TYPE => - (org.apache.spark.sql.LongType, false) - case c: Class[_] if c == java.lang.Double.TYPE => - (org.apache.spark.sql.DoubleType, false) - case c: Class[_] if c == java.lang.Byte.TYPE => - (org.apache.spark.sql.ByteType, false) - case c: Class[_] if c == java.lang.Float.TYPE => - (org.apache.spark.sql.FloatType, false) - case c: Class[_] if c == java.lang.Boolean.TYPE => - (org.apache.spark.sql.BooleanType, false) - - case c: Class[_] if c == classOf[java.lang.Short] => - (org.apache.spark.sql.ShortType, true) - case c: Class[_] if c == classOf[java.lang.Integer] => - (org.apache.spark.sql.IntegerType, true) - case c: Class[_] if c == classOf[java.lang.Long] => - (org.apache.spark.sql.LongType, true) - case c: Class[_] if c == classOf[java.lang.Double] => - (org.apache.spark.sql.DoubleType, true) - case c: Class[_] if c == classOf[java.lang.Byte] => - (org.apache.spark.sql.ByteType, true) - case c: Class[_] if c == classOf[java.lang.Float] => - (org.apache.spark.sql.FloatType, true) - case c: Class[_] if c == classOf[java.lang.Boolean] => - (org.apache.spark.sql.BooleanType, true) - case c: Class[_] if c == classOf[java.math.BigDecimal] => - (org.apache.spark.sql.DecimalType(), true) - case c: Class[_] if c == classOf[java.sql.Date] => - (org.apache.spark.sql.DateType, true) - case c: Class[_] if c == classOf[java.sql.Timestamp] => - (org.apache.spark.sql.TimestampType, true) + case c: Class[_] if c == classOf[java.lang.String] => (StringType, true) + case c: Class[_] if c == java.lang.Short.TYPE => (ShortType, false) + case c: Class[_] if c == java.lang.Integer.TYPE => (IntegerType, false) + case c: Class[_] if c == java.lang.Long.TYPE => (LongType, false) + case c: Class[_] if c == java.lang.Double.TYPE => (DoubleType, false) + case c: Class[_] if c == java.lang.Byte.TYPE => (ByteType, false) + case c: Class[_] if c == java.lang.Float.TYPE => (FloatType, false) + case c: Class[_] if c == java.lang.Boolean.TYPE => (BooleanType, false) + + case c: Class[_] if c == classOf[java.lang.Short] => (ShortType, true) + case c: Class[_] if c == classOf[java.lang.Integer] => (IntegerType, true) + case c: Class[_] if c == classOf[java.lang.Long] => (LongType, true) + case c: Class[_] if c == classOf[java.lang.Double] => (DoubleType, true) + case c: Class[_] if c == classOf[java.lang.Byte] => (ByteType, true) + case c: Class[_] if c == classOf[java.lang.Float] => (FloatType, true) + case c: Class[_] if c == classOf[java.lang.Boolean] => (BooleanType, true) + case c: Class[_] if c == classOf[java.math.BigDecimal] => (DecimalType(), true) + case c: Class[_] if c == classOf[java.sql.Date] => (DateType, true) + case c: Class[_] if c == classOf[java.sql.Timestamp] => (TimestampType, true) } AttributeReference(property.getName, dataType, nullable)() } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSchemaRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSchemaRDD.scala index 5b9c612487ace..9e10e532fb011 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSchemaRDD.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/api/java/JavaSchemaRDD.scala @@ -20,13 +20,12 @@ package org.apache.spark.sql.api.java import java.util.{List => JList} import org.apache.spark.Partitioner -import org.apache.spark.api.java.{JavaRDDLike, JavaRDD} +import org.apache.spark.api.java.{JavaRDD, JavaRDDLike} import org.apache.spark.api.java.function.{Function => JFunction} -import org.apache.spark.sql.types.util.DataTypeConversions +import org.apache.spark.rdd.RDD import org.apache.spark.sql.{SQLContext, SchemaRDD, SchemaRDDLike} import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan -import DataTypeConversions._ -import org.apache.spark.rdd.RDD +import org.apache.spark.sql.types.StructType import org.apache.spark.storage.StorageLevel /** @@ -59,8 +58,7 @@ class JavaSchemaRDD( override def toString: String = baseSchemaRDD.toString /** Returns the schema of this JavaSchemaRDD (represented by a StructType). */ - def schema: StructType = - asJavaDataType(baseSchemaRDD.schema).asInstanceOf[StructType] + def schema: StructType = baseSchemaRDD.schema.asInstanceOf[StructType] // ======================================================================= // Base RDD functions that do NOT change schema diff --git a/sql/core/src/main/scala/org/apache/spark/sql/api/java/Row.scala b/sql/core/src/main/scala/org/apache/spark/sql/api/java/Row.scala index 401798e317e96..207e2805fffe3 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/api/java/Row.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/api/java/Row.scala @@ -17,8 +17,6 @@ package org.apache.spark.sql.api.java -import org.apache.spark.sql.catalyst.types.decimal.Decimal - import scala.annotation.varargs import scala.collection.convert.Wrappers.{JListWrapper, JMapWrapper} import scala.collection.JavaConversions diff --git a/sql/core/src/main/scala/org/apache/spark/sql/api/java/UDFRegistration.scala b/sql/core/src/main/scala/org/apache/spark/sql/api/java/UDFRegistration.scala index 158f26e3d445f..4186c274515ab 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/api/java/UDFRegistration.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/api/java/UDFRegistration.scala @@ -18,7 +18,7 @@ package org.apache.spark.sql.api.java import org.apache.spark.sql.catalyst.expressions.{Expression, ScalaUdf} -import org.apache.spark.sql.types.util.DataTypeConversions._ +import org.apache.spark.sql.types.DataType /** * A collection of functions that allow Java users to register UDFs. In order to handle functions @@ -38,10 +38,9 @@ private[java] trait UDFRegistration { println(s""" |def registerFunction( | name: String, f: UDF$i[$extTypeArgs, _], @transient dataType: DataType) = { - | val scalaType = asScalaDataType(dataType) | sqlContext.functionRegistry.registerFunction( | name, - | (e: Seq[Expression]) => ScalaUdf(f$anyCast.call($anyParams), scalaType, e)) + | (e: Seq[Expression]) => ScalaUdf(f$anyCast.call($anyParams), dataType, e)) |} """.stripMargin) } @@ -94,159 +93,159 @@ private[java] trait UDFRegistration { */ // scalastyle:off - def registerFunction(name: String, f: UDF1[_, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF1[_, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF1[Any, Any]].call(_: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF1[Any, Any]].call(_: Any), dataType, e)) } - def registerFunction(name: String, f: UDF2[_, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF2[_, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF2[Any, Any, Any]].call(_: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF2[Any, Any, Any]].call(_: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF3[_, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF3[_, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF3[Any, Any, Any, Any]].call(_: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF3[Any, Any, Any, Any]].call(_: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF4[_, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF4[_, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF4[Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF4[Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF5[_, _, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF5[_, _, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF5[Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF5[Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF6[_, _, _, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF6[_, _, _, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF6[Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF6[Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF7[_, _, _, _, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF7[_, _, _, _, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF7[Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF7[Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF8[_, _, _, _, _, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF8[_, _, _, _, _, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF8[Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF8[Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF9[_, _, _, _, _, _, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF9[_, _, _, _, _, _, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF9[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF9[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF10[_, _, _, _, _, _, _, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF10[_, _, _, _, _, _, _, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF10[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF10[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF11[_, _, _, _, _, _, _, _, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + + def registerFunction( + name: String, f: UDF11[_, _, _, _, _, _, _, _, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF11[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF11[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF12[_, _, _, _, _, _, _, _, _, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF12[_, _, _, _, _, _, _, _, _, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF12[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF12[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF13[_, _, _, _, _, _, _, _, _, _, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF13[_, _, _, _, _, _, _, _, _, _, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF13[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF13[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF14[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF14[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF14[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF14[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF15[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF15[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF15[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF15[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF16[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF16[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF16[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF16[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF17[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF17[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF17[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF17[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF18[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF18[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF18[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF18[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF19[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF19[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF19[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF19[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF20[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF20[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF20[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF20[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF21[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF21[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF21[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF21[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), dataType, e)) } - def registerFunction(name: String, f: UDF22[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], dataType: DataType) = { - val scalaType = asScalaDataType(dataType) + def registerFunction( + name: String, f: UDF22[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], @transient dataType: DataType) = { sqlContext.functionRegistry.registerFunction( name, - (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF22[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), scalaType, e)) + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF22[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), dataType, e)) } - // scalastyle:on } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/api/java/UDTWrappers.scala b/sql/core/src/main/scala/org/apache/spark/sql/api/java/UDTWrappers.scala deleted file mode 100644 index a7d0f4f127ecc..0000000000000 --- a/sql/core/src/main/scala/org/apache/spark/sql/api/java/UDTWrappers.scala +++ /dev/null @@ -1,75 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java - -import org.apache.spark.sql.catalyst.types.{UserDefinedType => ScalaUserDefinedType} -import org.apache.spark.sql.{DataType => ScalaDataType} -import org.apache.spark.sql.types.util.DataTypeConversions - -/** - * Scala wrapper for a Java UserDefinedType - */ -private[sql] class JavaToScalaUDTWrapper[UserType](val javaUDT: UserDefinedType[UserType]) - extends ScalaUserDefinedType[UserType] with Serializable { - - /** Underlying storage type for this UDT */ - val sqlType: ScalaDataType = DataTypeConversions.asScalaDataType(javaUDT.sqlType()) - - /** Convert the user type to a SQL datum */ - def serialize(obj: Any): Any = javaUDT.serialize(obj) - - /** Convert a SQL datum to the user type */ - def deserialize(datum: Any): UserType = javaUDT.deserialize(datum) - - val userClass: java.lang.Class[UserType] = javaUDT.userClass() -} - -/** - * Java wrapper for a Scala UserDefinedType - */ -private[sql] class ScalaToJavaUDTWrapper[UserType](val scalaUDT: ScalaUserDefinedType[UserType]) - extends UserDefinedType[UserType] with Serializable { - - /** Underlying storage type for this UDT */ - val sqlType: DataType = DataTypeConversions.asJavaDataType(scalaUDT.sqlType) - - /** Convert the user type to a SQL datum */ - def serialize(obj: Any): java.lang.Object = scalaUDT.serialize(obj).asInstanceOf[java.lang.Object] - - /** Convert a SQL datum to the user type */ - def deserialize(datum: Any): UserType = scalaUDT.deserialize(datum) - - val userClass: java.lang.Class[UserType] = scalaUDT.userClass -} - -private[sql] object UDTWrappers { - - def wrapAsScala(udtType: UserDefinedType[_]): ScalaUserDefinedType[_] = { - udtType match { - case t: ScalaToJavaUDTWrapper[_] => t.scalaUDT - case _ => new JavaToScalaUDTWrapper(udtType) - } - } - - def wrapAsJava(udtType: ScalaUserDefinedType[_]): UserDefinedType[_] = { - udtType match { - case t: JavaToScalaUDTWrapper[_] => t.javaUDT - case _ => new ScalaToJavaUDTWrapper(udtType) - } - } -} diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnAccessor.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnAccessor.scala index 538dd5b734664..91c4c105b14e6 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnAccessor.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnAccessor.scala @@ -17,11 +17,11 @@ package org.apache.spark.sql.columnar -import java.nio.{ByteOrder, ByteBuffer} +import java.nio.{ByteBuffer, ByteOrder} -import org.apache.spark.sql.catalyst.types.{BinaryType, NativeType, DataType} import org.apache.spark.sql.catalyst.expressions.MutableRow import org.apache.spark.sql.columnar.compression.CompressibleColumnAccessor +import org.apache.spark.sql.types.{BinaryType, DataType, NativeType} /** * An `Iterator` like trait used to extract values from columnar byte buffer. When a value is diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnBuilder.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnBuilder.scala index c68dceef3b142..3a4977b836af7 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnBuilder.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnBuilder.scala @@ -20,9 +20,9 @@ package org.apache.spark.sql.columnar import java.nio.{ByteBuffer, ByteOrder} import org.apache.spark.sql.Row -import org.apache.spark.sql.catalyst.types._ import org.apache.spark.sql.columnar.ColumnBuilder._ import org.apache.spark.sql.columnar.compression.{AllCompressionSchemes, CompressibleColumnBuilder} +import org.apache.spark.sql.types._ private[sql] trait ColumnBuilder { /** diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnStats.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnStats.scala index 668efe4a3b2a8..391b3dae5c8ce 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnStats.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnStats.scala @@ -21,7 +21,7 @@ import java.sql.{Date, Timestamp} import org.apache.spark.sql.Row import org.apache.spark.sql.catalyst.expressions.{AttributeMap, Attribute, AttributeReference} -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ private[sql] class ColumnStatisticsSchema(a: Attribute) extends Serializable { val upperBound = AttributeReference(a.name + ".upperBound", a.dataType, nullable = true)() diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnType.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnType.scala index ab66c85c4f242..fcf2faa0914c0 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnType.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/ColumnType.scala @@ -24,8 +24,8 @@ import scala.reflect.runtime.universe.TypeTag import org.apache.spark.sql.Row import org.apache.spark.sql.catalyst.expressions.MutableRow -import org.apache.spark.sql.catalyst.types._ import org.apache.spark.sql.execution.SparkSqlSerializer +import org.apache.spark.sql.types._ /** * An abstract class that represents type of a column. Used to append/extract Java objects into/from diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnAccessor.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnAccessor.scala index 27ac5f4dbdbbc..7dff9deac8dc0 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnAccessor.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnAccessor.scala @@ -18,8 +18,8 @@ package org.apache.spark.sql.columnar.compression import org.apache.spark.sql.catalyst.expressions.MutableRow -import org.apache.spark.sql.catalyst.types.NativeType import org.apache.spark.sql.columnar.{ColumnAccessor, NativeColumnAccessor} +import org.apache.spark.sql.types.NativeType private[sql] trait CompressibleColumnAccessor[T <: NativeType] extends ColumnAccessor { this: NativeColumnAccessor[T] => diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnBuilder.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnBuilder.scala index 628d9cec41d6b..aead768ecdf0a 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnBuilder.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressibleColumnBuilder.scala @@ -21,8 +21,8 @@ import java.nio.{ByteBuffer, ByteOrder} import org.apache.spark.Logging import org.apache.spark.sql.Row -import org.apache.spark.sql.catalyst.types.NativeType import org.apache.spark.sql.columnar.{ColumnBuilder, NativeColumnBuilder} +import org.apache.spark.sql.types.NativeType /** * A stackable trait that builds optionally compressed byte buffer for a column. Memory layout of diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressionScheme.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressionScheme.scala index acb06cb5376b4..879d29bcfa6f6 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressionScheme.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/CompressionScheme.scala @@ -21,8 +21,8 @@ import java.nio.{ByteBuffer, ByteOrder} import org.apache.spark.sql.Row import org.apache.spark.sql.catalyst.expressions.MutableRow -import org.apache.spark.sql.catalyst.types.NativeType import org.apache.spark.sql.columnar.{ColumnType, NativeColumnType} +import org.apache.spark.sql.types.NativeType private[sql] trait Encoder[T <: NativeType] { def gatherCompressibilityStats(row: Row, ordinal: Int): Unit = {} diff --git a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/compressionSchemes.scala b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/compressionSchemes.scala index 29edcf17242c5..64673248394c6 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/compressionSchemes.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/columnar/compression/compressionSchemes.scala @@ -25,10 +25,11 @@ import scala.reflect.runtime.universe.runtimeMirror import org.apache.spark.sql.Row import org.apache.spark.sql.catalyst.expressions.{MutableRow, SpecificMutableRow} -import org.apache.spark.sql.catalyst.types._ import org.apache.spark.sql.columnar._ +import org.apache.spark.sql.types._ import org.apache.spark.util.Utils + private[sql] case object PassThrough extends CompressionScheme { override val typeId = 0 diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala index 069e950195302..20b14834bb0d5 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala @@ -19,11 +19,12 @@ package org.apache.spark.sql.execution import org.apache.spark.annotation.DeveloperApi import org.apache.spark.rdd.RDD -import org.apache.spark.sql.{StructType, Row, SQLContext} +import org.apache.spark.sql.{Row, SQLContext} import org.apache.spark.sql.catalyst.ScalaReflection import org.apache.spark.sql.catalyst.analysis.MultiInstanceRelation import org.apache.spark.sql.catalyst.expressions.{Attribute, GenericMutableRow} import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, Statistics} +import org.apache.spark.sql.types.StructType /** * :: DeveloperApi :: diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala index 7c3bf947e743d..4abe26fe4afc6 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala @@ -21,7 +21,7 @@ import org.apache.spark.annotation.DeveloperApi import org.apache.spark.sql.catalyst.trees._ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.physical._ -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ case class AggregateEvaluation( schema: Seq[Attribute], diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer.scala index 84d96e612f0dc..131146012ecac 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer.scala @@ -29,7 +29,7 @@ import com.twitter.chill.{AllScalaRegistrar, ResourcePool} import org.apache.spark.{SparkEnv, SparkConf} import org.apache.spark.serializer.{SerializerInstance, KryoSerializer} import org.apache.spark.sql.catalyst.expressions.GenericRow -import org.apache.spark.sql.catalyst.types.decimal.Decimal +import org.apache.spark.sql.types.decimal.Decimal import org.apache.spark.util.collection.OpenHashSet import org.apache.spark.util.MutablePair import org.apache.spark.util.Utils diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala index 0652d2ff7c9ab..0cc9d049c9640 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala @@ -17,16 +17,16 @@ package org.apache.spark.sql.execution -import org.apache.spark.sql.sources.{CreateTempTableUsing, CreateTableUsing} import org.apache.spark.sql.{SQLContext, Strategy, execution} import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.planning._ import org.apache.spark.sql.catalyst.plans._ import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan import org.apache.spark.sql.catalyst.plans.physical._ -import org.apache.spark.sql.catalyst.types._ -import org.apache.spark.sql.columnar.{InMemoryRelation, InMemoryColumnarTableScan} +import org.apache.spark.sql.columnar.{InMemoryColumnarTableScan, InMemoryRelation} import org.apache.spark.sql.parquet._ +import org.apache.spark.sql.types._ +import org.apache.spark.sql.sources.{CreateTempTableUsing, CreateTableUsing} private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/debug/package.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/debug/package.scala index 61be5ed2db65c..46245cd5a1869 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/debug/package.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/debug/package.scala @@ -24,7 +24,7 @@ import org.apache.spark.annotation.DeveloperApi import org.apache.spark.SparkContext._ import org.apache.spark.sql.{SchemaRDD, Row} import org.apache.spark.sql.catalyst.trees.TreeNodeRef -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ /** * :: DeveloperApi :: diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/pythonUdfs.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/pythonUdfs.scala index 5a41399971dda..741ccb8fb8fa7 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/pythonUdfs.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/pythonUdfs.scala @@ -19,8 +19,6 @@ package org.apache.spark.sql.execution import java.util.{List => JList, Map => JMap} -import org.apache.spark.sql.catalyst.types.decimal.Decimal - import scala.collection.JavaConversions._ import scala.collection.JavaConverters._ @@ -33,7 +31,7 @@ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.logical import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan import org.apache.spark.sql.catalyst.rules.Rule -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ import org.apache.spark.{Accumulator, Logging => SparkLogging} /** diff --git a/sql/core/src/main/scala/org/apache/spark/sql/json/JSONRelation.scala b/sql/core/src/main/scala/org/apache/spark/sql/json/JSONRelation.scala index f5c02224c82a0..1af96c28d5fdf 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/json/JSONRelation.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/json/JSONRelation.scala @@ -18,8 +18,9 @@ package org.apache.spark.sql.json import org.apache.spark.sql.SQLContext -import org.apache.spark.sql.catalyst.types.StructType import org.apache.spark.sql.sources._ +import org.apache.spark.sql.types.StructType + private[sql] class DefaultSource extends RelationProvider with SchemaRelationProvider { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala index 00449c200704a..c92ec543e2936 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala @@ -17,9 +17,6 @@ package org.apache.spark.sql.json -import org.apache.spark.sql.catalyst.types.decimal.Decimal -import org.apache.spark.sql.types.util.DataTypeConversions - import java.io.StringWriter import scala.collection.Map @@ -34,8 +31,9 @@ import com.fasterxml.jackson.databind.ObjectMapper import org.apache.spark.rdd.RDD import org.apache.spark.sql.catalyst.analysis.HiveTypeCoercion import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.catalyst.types._ import org.apache.spark.sql.catalyst.ScalaReflection +import org.apache.spark.sql.types._ +import org.apache.spark.sql.types.decimal.Decimal import org.apache.spark.Logging private[sql] object JsonRDD extends Logging { @@ -246,7 +244,7 @@ private[sql] object JsonRDD extends Logging { // The value associated with the key is an array. // Handle inner structs of an array. def buildKeyPathForInnerStructs(v: Any, t: DataType): Seq[(String, DataType)] = t match { - case ArrayType(StructType(Nil), containsNull) => { + case ArrayType(e: StructType, containsNull) => { // The elements of this arrays are structs. v.asInstanceOf[Seq[Map[String, Any]]].flatMap(Option(_)).flatMap { element => allKeysWithValueTypes(element) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/package.scala b/sql/core/src/main/scala/org/apache/spark/sql/package.scala index 1fd8e6220f83b..b75266d5aa409 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/package.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/package.scala @@ -116,358 +116,9 @@ package object sql { @DeveloperApi val Row = catalyst.expressions.Row - /** - * :: DeveloperApi :: - * - * The base type of all Spark SQL data types. - * - * @group dataType - */ - @DeveloperApi - type DataType = catalyst.types.DataType - - @DeveloperApi - val DataType = catalyst.types.DataType - - /** - * :: DeveloperApi :: - * - * The data type representing `String` values - * - * @group dataType - */ - @DeveloperApi - val StringType = catalyst.types.StringType - - /** - * :: DeveloperApi :: - * - * The data type representing `Array[Byte]` values. - * - * @group dataType - */ - @DeveloperApi - val BinaryType = catalyst.types.BinaryType - - /** - * :: DeveloperApi :: - * - * The data type representing `Boolean` values. - * - *@group dataType - */ - @DeveloperApi - val BooleanType = catalyst.types.BooleanType - - /** - * :: DeveloperApi :: - * - * The data type representing `java.sql.Timestamp` values. - * - * @group dataType - */ - @DeveloperApi - val TimestampType = catalyst.types.TimestampType - - /** - * :: DeveloperApi :: - * - * The data type representing `java.sql.Date` values. - * - * @group dataType - */ - @DeveloperApi - val DateType = catalyst.types.DateType - - /** - * :: DeveloperApi :: - * - * The data type representing `scala.math.BigDecimal` values. - * - * TODO(matei): explain precision and scale - * - * @group dataType - */ - @DeveloperApi - type DecimalType = catalyst.types.DecimalType - - /** - * :: DeveloperApi :: - * - * The data type representing `scala.math.BigDecimal` values. - * - * TODO(matei): explain precision and scale - * - * @group dataType - */ - @DeveloperApi - val DecimalType = catalyst.types.DecimalType - - /** - * :: DeveloperApi :: - * - * The data type representing `Double` values. - * - * @group dataType - */ - @DeveloperApi - val DoubleType = catalyst.types.DoubleType - - /** - * :: DeveloperApi :: - * - * The data type representing `Float` values. - * - * @group dataType - */ - @DeveloperApi - val FloatType = catalyst.types.FloatType - - /** - * :: DeveloperApi :: - * - * The data type representing `Byte` values. - * - * @group dataType - */ - @DeveloperApi - val ByteType = catalyst.types.ByteType - - /** - * :: DeveloperApi :: - * - * The data type representing `Int` values. - * - * @group dataType - */ - @DeveloperApi - val IntegerType = catalyst.types.IntegerType - - /** - * :: DeveloperApi :: - * - * The data type representing `Long` values. - * - * @group dataType - */ - @DeveloperApi - val LongType = catalyst.types.LongType - - /** - * :: DeveloperApi :: - * - * The data type representing `Short` values. - * - * @group dataType - */ - @DeveloperApi - val ShortType = catalyst.types.ShortType - - /** - * :: DeveloperApi :: - * - * The data type representing `NULL` values. - * - * @group dataType - */ - @DeveloperApi - val NullType = catalyst.types.NullType - - /** - * :: DeveloperApi :: - * - * The data type for collections of multiple values. - * Internally these are represented as columns that contain a ``scala.collection.Seq``. - * - * An [[ArrayType]] object comprises two fields, `elementType: [[DataType]]` and - * `containsNull: Boolean`. The field of `elementType` is used to specify the type of - * array elements. The field of `containsNull` is used to specify if the array has `null` values. - * - * @group dataType - */ - @DeveloperApi - type ArrayType = catalyst.types.ArrayType - - /** - * :: DeveloperApi :: - * - * An [[ArrayType]] object can be constructed with two ways, - * {{{ - * ArrayType(elementType: DataType, containsNull: Boolean) - * }}} and - * {{{ - * ArrayType(elementType: DataType) - * }}} - * For `ArrayType(elementType)`, the field of `containsNull` is set to `false`. - * - * @group dataType - */ - @DeveloperApi - val ArrayType = catalyst.types.ArrayType - - /** - * :: DeveloperApi :: - * - * The data type representing `Map`s. A [[MapType]] object comprises three fields, - * `keyType: [[DataType]]`, `valueType: [[DataType]]` and `valueContainsNull: Boolean`. - * The field of `keyType` is used to specify the type of keys in the map. - * The field of `valueType` is used to specify the type of values in the map. - * The field of `valueContainsNull` is used to specify if values of this map has `null` values. - * For values of a MapType column, keys are not allowed to have `null` values. - * - * @group dataType - */ - @DeveloperApi - type MapType = catalyst.types.MapType - - /** - * :: DeveloperApi :: - * - * A [[MapType]] object can be constructed with two ways, - * {{{ - * MapType(keyType: DataType, valueType: DataType, valueContainsNull: Boolean) - * }}} and - * {{{ - * MapType(keyType: DataType, valueType: DataType) - * }}} - * For `MapType(keyType: DataType, valueType: DataType)`, - * the field of `valueContainsNull` is set to `true`. - * - * @group dataType - */ - @DeveloperApi - val MapType = catalyst.types.MapType - - /** - * :: DeveloperApi :: - * - * The data type representing [[Row]]s. - * A [[StructType]] object comprises a [[Seq]] of [[StructField]]s. - * - * @group dataType - */ - @DeveloperApi - type StructType = catalyst.types.StructType - - /** - * :: DeveloperApi :: - * - * A [[StructType]] object can be constructed by - * {{{ - * StructType(fields: Seq[StructField]) - * }}} - * For a [[StructType]] object, one or multiple [[StructField]]s can be extracted by names. - * If multiple [[StructField]]s are extracted, a [[StructType]] object will be returned. - * If a provided name does not have a matching field, it will be ignored. For the case - * of extracting a single StructField, a `null` will be returned. - * Example: - * {{{ - * import org.apache.spark.sql._ - * - * val struct = - * StructType( - * StructField("a", IntegerType, true) :: - * StructField("b", LongType, false) :: - * StructField("c", BooleanType, false) :: Nil) - * - * // Extract a single StructField. - * val singleField = struct("b") - * // singleField: StructField = StructField(b,LongType,false) - * - * // This struct does not have a field called "d". null will be returned. - * val nonExisting = struct("d") - * // nonExisting: StructField = null - * - * // Extract multiple StructFields. Field names are provided in a set. - * // A StructType object will be returned. - * val twoFields = struct(Set("b", "c")) - * // twoFields: StructType = - * // StructType(List(StructField(b,LongType,false), StructField(c,BooleanType,false))) - * - * // Those names do not have matching fields will be ignored. - * // For the case shown below, "d" will be ignored and - * // it is treated as struct(Set("b", "c")). - * val ignoreNonExisting = struct(Set("b", "c", "d")) - * // ignoreNonExisting: StructType = - * // StructType(List(StructField(b,LongType,false), StructField(c,BooleanType,false))) - * }}} - * - * A [[Row]] object is used as a value of the StructType. - * Example: - * {{{ - * import org.apache.spark.sql._ - * - * val innerStruct = - * StructType( - * StructField("f1", IntegerType, true) :: - * StructField("f2", LongType, false) :: - * StructField("f3", BooleanType, false) :: Nil) - * - * val struct = StructType( - * StructField("a", innerStruct, true) :: Nil) - * - * // Create a Row with the schema defined by struct - * val row = Row(Row(1, 2, true)) - * // row: Row = [[1,2,true]] - * }}} - * - * @group dataType - */ - @DeveloperApi - val StructType = catalyst.types.StructType - - /** - * :: DeveloperApi :: - * - * A [[StructField]] object represents a field in a [[StructType]] object. - * A [[StructField]] object comprises three fields, `name: [[String]]`, `dataType: [[DataType]]`, - * and `nullable: Boolean`. The field of `name` is the name of a `StructField`. The field of - * `dataType` specifies the data type of a `StructField`. - * The field of `nullable` specifies if values of a `StructField` can contain `null` values. - * - * @group field - */ - @DeveloperApi - type StructField = catalyst.types.StructField - - /** - * :: DeveloperApi :: - * - * A [[StructField]] object can be constructed by - * {{{ - * StructField(name: String, dataType: DataType, nullable: Boolean) - * }}} - * - * @group dataType - */ - @DeveloperApi - val StructField = catalyst.types.StructField - /** * Converts a logical plan into zero or more SparkPlans. */ @DeveloperApi type Strategy = org.apache.spark.sql.catalyst.planning.GenericStrategy[SparkPlan] - - /** - * :: DeveloperApi :: - * - * Metadata is a wrapper over Map[String, Any] that limits the value type to simple ones: Boolean, - * Long, Double, String, Metadata, Array[Boolean], Array[Long], Array[Double], Array[String], and - * Array[Metadata]. JSON is used for serialization. - * - * The default constructor is private. User should use either [[MetadataBuilder]] or - * [[Metadata$#fromJson]] to create Metadata instances. - * - * @param map an immutable map that stores the data - */ - @DeveloperApi - type Metadata = catalyst.util.Metadata - - /** - * :: DeveloperApi :: - * Builder for [[Metadata]]. If there is a key collision, the latter will overwrite the former. - */ - @DeveloperApi - type MetadataBuilder = catalyst.util.MetadataBuilder } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetConverter.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetConverter.scala index 1bbb66aaa19a3..7f437c40777f2 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetConverter.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetConverter.scala @@ -17,16 +17,15 @@ package org.apache.spark.sql.parquet -import org.apache.spark.sql.catalyst.types.decimal.Decimal - import scala.collection.mutable.{Buffer, ArrayBuffer, HashMap} import parquet.io.api.{PrimitiveConverter, GroupConverter, Binary, Converter} import parquet.schema.MessageType -import org.apache.spark.sql.catalyst.types._ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.parquet.CatalystConverter.FieldType +import org.apache.spark.sql.types._ +import org.apache.spark.sql.types.decimal.Decimal /** * Collection of converters of Parquet types (group and primitive types) that @@ -91,8 +90,8 @@ private[sql] object CatalystConverter { case ArrayType(elementType: DataType, true) => { new CatalystArrayContainsNullConverter(elementType, fieldIndex, parent) } - case StructType(fields: Seq[StructField]) => { - new CatalystStructConverter(fields.toArray, fieldIndex, parent) + case StructType(fields: Array[StructField]) => { + new CatalystStructConverter(fields, fieldIndex, parent) } case MapType(keyType: DataType, valueType: DataType, valueContainsNull: Boolean) => { new CatalystMapConverter( @@ -436,7 +435,7 @@ private[parquet] object CatalystArrayConverter { * A `parquet.io.api.GroupConverter` that converts a single-element groups that * match the characteristics of an array (see * [[org.apache.spark.sql.parquet.ParquetTypesConverter]]) into an - * [[org.apache.spark.sql.catalyst.types.ArrayType]]. + * [[org.apache.spark.sql.types.ArrayType]]. * * @param elementType The type of the array elements (complex or primitive) * @param index The position of this (array) field inside its parent converter @@ -500,7 +499,7 @@ private[parquet] class CatalystArrayConverter( * A `parquet.io.api.GroupConverter` that converts a single-element groups that * match the characteristics of an array (see * [[org.apache.spark.sql.parquet.ParquetTypesConverter]]) into an - * [[org.apache.spark.sql.catalyst.types.ArrayType]]. + * [[org.apache.spark.sql.types.ArrayType]]. * * @param elementType The type of the array elements (native) * @param index The position of this (array) field inside its parent converter @@ -621,7 +620,7 @@ private[parquet] class CatalystNativeArrayConverter( * A `parquet.io.api.GroupConverter` that converts a single-element groups that * match the characteristics of an array contains null (see * [[org.apache.spark.sql.parquet.ParquetTypesConverter]]) into an - * [[org.apache.spark.sql.catalyst.types.ArrayType]]. + * [[org.apache.spark.sql.types.ArrayType]]. * * @param elementType The type of the array elements (complex or primitive) * @param index The position of this (array) field inside its parent converter @@ -727,7 +726,7 @@ private[parquet] class CatalystStructConverter( * A `parquet.io.api.GroupConverter` that converts two-element groups that * match the characteristics of a map (see * [[org.apache.spark.sql.parquet.ParquetTypesConverter]]) into an - * [[org.apache.spark.sql.catalyst.types.MapType]]. + * [[org.apache.spark.sql.types.MapType]]. * * @param schema * @param index diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetFilters.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetFilters.scala index 56e7d11b2feea..f08350878f239 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetFilters.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetFilters.scala @@ -29,7 +29,7 @@ import parquet.io.api.Binary import org.apache.spark.SparkEnv import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ private[sql] object ParquetFilters { val PARQUET_FILTER_DATA = "org.apache.spark.sql.parquet.row.filter" diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableSupport.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableSupport.scala index 9049eb5932b79..af7248fdf451d 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableSupport.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableSupport.scala @@ -29,8 +29,8 @@ import parquet.schema.MessageType import org.apache.spark.Logging import org.apache.spark.sql.catalyst.expressions.{Attribute, Row} -import org.apache.spark.sql.catalyst.types._ -import org.apache.spark.sql.catalyst.types.decimal.Decimal +import org.apache.spark.sql.types._ +import org.apache.spark.sql.types.decimal.Decimal /** * A `parquet.io.api.RecordMaterializer` for Rows. diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTypes.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTypes.scala index 97447871a11ee..6d8c682ccced8 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTypes.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTypes.scala @@ -36,7 +36,7 @@ import parquet.schema.Type.Repetition import org.apache.spark.Logging import org.apache.spark.sql.catalyst.expressions.{AttributeReference, Attribute} -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ // Implicits import scala.collection.JavaConversions._ @@ -80,7 +80,7 @@ private[parquet] object ParquetTypesConverter extends Logging { /** * Converts a given Parquet `Type` into the corresponding - * [[org.apache.spark.sql.catalyst.types.DataType]]. + * [[org.apache.spark.sql.types.DataType]]. * * We apply the following conversion rules: *
      @@ -191,7 +191,7 @@ private[parquet] object ParquetTypesConverter extends Logging { } /** - * For a given Catalyst [[org.apache.spark.sql.catalyst.types.DataType]] return + * For a given Catalyst [[org.apache.spark.sql.types.DataType]] return * the name of the corresponding Parquet primitive type or None if the given type * is not primitive. * @@ -231,21 +231,21 @@ private[parquet] object ParquetTypesConverter extends Logging { } /** - * Converts a given Catalyst [[org.apache.spark.sql.catalyst.types.DataType]] into + * Converts a given Catalyst [[org.apache.spark.sql.types.DataType]] into * the corresponding Parquet `Type`. * * The conversion follows the rules below: *
        *
      • Primitive types are converted into Parquet's primitive types.
        • - *
      • [[org.apache.spark.sql.catalyst.types.StructType]]s are converted + *
      • [[org.apache.spark.sql.types.StructType]]s are converted * into Parquet's `GroupType` with the corresponding field types.
        • - *
      • [[org.apache.spark.sql.catalyst.types.ArrayType]]s are converted + *
      • [[org.apache.spark.sql.types.ArrayType]]s are converted * into a 2-level nested group, where the outer group has the inner * group as sole field. The inner group has name `values` and * repetition level `REPEATED` and has the element type of * the array as schema. We use Parquet's `ConversionPatterns` for this * purpose.
        • - *
      • [[org.apache.spark.sql.catalyst.types.MapType]]s are converted + *
      • [[org.apache.spark.sql.types.MapType]]s are converted * into a nested (2-level) Parquet `GroupType` with two fields: a key * type and a value type. The nested group has repetition level * `REPEATED` and name `map`. We use Parquet's `ConversionPatterns` @@ -319,7 +319,7 @@ private[parquet] object ParquetTypesConverter extends Logging { val fields = structFields.map { field => fromDataType(field.dataType, field.name, field.nullable, inArray = false) } - new ParquetGroupType(repetition, name, fields) + new ParquetGroupType(repetition, name, fields.toSeq) } case MapType(keyType, valueType, valueContainsNull) => { val parquetKeyType = diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/newParquet.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/newParquet.scala index 55a2728a85cc7..1b50afbbabcb0 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/newParquet.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/newParquet.scala @@ -18,11 +18,12 @@ package org.apache.spark.sql.parquet import java.util.{List => JList} +import scala.collection.JavaConversions._ + import org.apache.hadoop.fs.{FileStatus, FileSystem, Path} import org.apache.hadoop.conf.{Configurable, Configuration} import org.apache.hadoop.io.Writable import org.apache.hadoop.mapreduce.{JobContext, InputSplit, Job} -import org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate import parquet.hadoop.ParquetInputFormat import parquet.hadoop.util.ContextUtil @@ -30,13 +31,11 @@ import parquet.hadoop.util.ContextUtil import org.apache.spark.annotation.DeveloperApi import org.apache.spark.{Partition => SparkPartition, Logging} import org.apache.spark.rdd.{NewHadoopPartition, RDD} - import org.apache.spark.sql.{SQLConf, Row, SQLContext} import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.catalyst.types.{StringType, IntegerType, StructField, StructType} import org.apache.spark.sql.sources._ +import org.apache.spark.sql.types.{IntegerType, StructField, StructType} -import scala.collection.JavaConversions._ /** * Allows creation of parquet based tables using the syntax diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/LogicalRelation.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/LogicalRelation.scala index 4d87f6817dcb9..12b59ba20bb10 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/LogicalRelation.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/LogicalRelation.scala @@ -17,7 +17,7 @@ package org.apache.spark.sql.sources import org.apache.spark.sql.catalyst.analysis.MultiInstanceRelation -import org.apache.spark.sql.catalyst.expressions.AttributeMap +import org.apache.spark.sql.catalyst.expressions.{AttributeReference, AttributeMap} import org.apache.spark.sql.catalyst.plans.logical.{Statistics, LeafNode, LogicalPlan} /** @@ -27,7 +27,7 @@ private[sql] case class LogicalRelation(relation: BaseRelation) extends LeafNode with MultiInstanceRelation { - override val output = relation.schema.toAttributes + override val output: Seq[AttributeReference] = relation.schema.toAttributes // Logical Relations are distinct if they have different output for the sake of transformations. override def equals(other: Any) = other match { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala index f8741e0082098..4cc9641c4d9e0 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala @@ -23,11 +23,11 @@ import scala.util.parsing.combinator.PackratParsers import org.apache.spark.Logging import org.apache.spark.sql.SQLContext -import org.apache.spark.sql.catalyst.types._ -import org.apache.spark.sql.execution.RunnableCommand -import org.apache.spark.util.Utils import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.SqlLexical +import org.apache.spark.sql.execution.RunnableCommand +import org.apache.spark.sql.types._ +import org.apache.spark.util.Utils /** * A parser for foreign DDL commands. @@ -162,10 +162,10 @@ private[sql] class DDLParser extends StandardTokenParsers with PackratParsers wi protected lazy val structType: Parser[DataType] = (STRUCT ~> "<" ~> repsep(structField, ",") <~ ">" ^^ { - case fields => new StructType(fields) + case fields => StructType(fields) }) | (STRUCT ~> "<>" ^^ { - case fields => new StructType(Nil) + case fields => StructType(Nil) }) private[sql] lazy val dataType: Parser[DataType] = diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala index 7f5564baa00f4..cd82cc6ecb61b 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/interfaces.scala @@ -18,8 +18,9 @@ package org.apache.spark.sql.sources import org.apache.spark.annotation.{Experimental, DeveloperApi} import org.apache.spark.rdd.RDD -import org.apache.spark.sql.{Row, SQLContext, StructType} +import org.apache.spark.sql.{Row, SQLContext} import org.apache.spark.sql.catalyst.expressions.{Expression, Attribute} +import org.apache.spark.sql.types.StructType /** * ::DeveloperApi:: diff --git a/sql/core/src/main/scala/org/apache/spark/sql/test/ExamplePointUDT.scala b/sql/core/src/main/scala/org/apache/spark/sql/test/ExamplePointUDT.scala index b9569e96c0312..006b16fbe07bd 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/test/ExamplePointUDT.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/test/ExamplePointUDT.scala @@ -20,9 +20,7 @@ package org.apache.spark.sql.test import java.util import scala.collection.JavaConverters._ - -import org.apache.spark.sql.catalyst.annotation.SQLUserDefinedType -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ /** * An example class to demonstrate UDT in Scala, Java, and Python. diff --git a/sql/core/src/main/scala/org/apache/spark/sql/types/util/DataTypeConversions.scala b/sql/core/src/main/scala/org/apache/spark/sql/types/util/DataTypeConversions.scala deleted file mode 100644 index d4ef517981699..0000000000000 --- a/sql/core/src/main/scala/org/apache/spark/sql/types/util/DataTypeConversions.scala +++ /dev/null @@ -1,175 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.types.util - -import java.text.SimpleDateFormat - -import scala.collection.JavaConverters._ - -import org.apache.spark.sql._ -import org.apache.spark.sql.api.java.{DataType => JDataType, StructField => JStructField, - MetadataBuilder => JMetaDataBuilder, UDTWrappers} -import org.apache.spark.sql.api.java.{DecimalType => JDecimalType} -import org.apache.spark.sql.catalyst.types.decimal.Decimal -import org.apache.spark.sql.catalyst.ScalaReflection -import org.apache.spark.sql.catalyst.types.UserDefinedType - -protected[sql] object DataTypeConversions { - - /** - * Returns the equivalent StructField in Scala for the given StructField in Java. - */ - def asJavaStructField(scalaStructField: StructField): JStructField = { - JDataType.createStructField( - scalaStructField.name, - asJavaDataType(scalaStructField.dataType), - scalaStructField.nullable, - (new JMetaDataBuilder).withMetadata(scalaStructField.metadata).build()) - } - - /** - * Returns the equivalent DataType in Java for the given DataType in Scala. - */ - def asJavaDataType(scalaDataType: DataType): JDataType = scalaDataType match { - case udtType: UserDefinedType[_] => - UDTWrappers.wrapAsJava(udtType) - - case StringType => JDataType.StringType - case BinaryType => JDataType.BinaryType - case BooleanType => JDataType.BooleanType - case DateType => JDataType.DateType - case TimestampType => JDataType.TimestampType - case DecimalType.Fixed(precision, scale) => new JDecimalType(precision, scale) - case DecimalType.Unlimited => new JDecimalType() - case DoubleType => JDataType.DoubleType - case FloatType => JDataType.FloatType - case ByteType => JDataType.ByteType - case IntegerType => JDataType.IntegerType - case LongType => JDataType.LongType - case ShortType => JDataType.ShortType - case NullType => JDataType.NullType - - case arrayType: ArrayType => JDataType.createArrayType( - asJavaDataType(arrayType.elementType), arrayType.containsNull) - case mapType: MapType => JDataType.createMapType( - asJavaDataType(mapType.keyType), - asJavaDataType(mapType.valueType), - mapType.valueContainsNull) - case structType: StructType => JDataType.createStructType( - structType.fields.map(asJavaStructField).asJava) - } - - /** - * Returns the equivalent StructField in Scala for the given StructField in Java. - */ - def asScalaStructField(javaStructField: JStructField): StructField = { - StructField( - javaStructField.getName, - asScalaDataType(javaStructField.getDataType), - javaStructField.isNullable, - javaStructField.getMetadata) - } - - /** - * Returns the equivalent DataType in Scala for the given DataType in Java. - */ - def asScalaDataType(javaDataType: JDataType): DataType = javaDataType match { - case udtType: org.apache.spark.sql.api.java.UserDefinedType[_] => - UDTWrappers.wrapAsScala(udtType) - - case stringType: org.apache.spark.sql.api.java.StringType => - StringType - case binaryType: org.apache.spark.sql.api.java.BinaryType => - BinaryType - case booleanType: org.apache.spark.sql.api.java.BooleanType => - BooleanType - case dateType: org.apache.spark.sql.api.java.DateType => - DateType - case timestampType: org.apache.spark.sql.api.java.TimestampType => - TimestampType - case decimalType: org.apache.spark.sql.api.java.DecimalType => - if (decimalType.isFixed) { - DecimalType(decimalType.getPrecision, decimalType.getScale) - } else { - DecimalType.Unlimited - } - case doubleType: org.apache.spark.sql.api.java.DoubleType => - DoubleType - case floatType: org.apache.spark.sql.api.java.FloatType => - FloatType - case byteType: org.apache.spark.sql.api.java.ByteType => - ByteType - case integerType: org.apache.spark.sql.api.java.IntegerType => - IntegerType - case longType: org.apache.spark.sql.api.java.LongType => - LongType - case shortType: org.apache.spark.sql.api.java.ShortType => - ShortType - - case arrayType: org.apache.spark.sql.api.java.ArrayType => - ArrayType(asScalaDataType(arrayType.getElementType), arrayType.isContainsNull) - case mapType: org.apache.spark.sql.api.java.MapType => - MapType( - asScalaDataType(mapType.getKeyType), - asScalaDataType(mapType.getValueType), - mapType.isValueContainsNull) - case structType: org.apache.spark.sql.api.java.StructType => - StructType(structType.getFields.map(asScalaStructField)) - } - - def stringToTime(s: String): java.util.Date = { - if (!s.contains('T')) { - // JDBC escape string - if (s.contains(' ')) { - java.sql.Timestamp.valueOf(s) - } else { - java.sql.Date.valueOf(s) - } - } else if (s.endsWith("Z")) { - // this is zero timezone of ISO8601 - stringToTime(s.substring(0, s.length - 1) + "GMT-00:00") - } else if (s.indexOf("GMT") == -1) { - // timezone with ISO8601 - val inset = "+00.00".length - val s0 = s.substring(0, s.length - inset) - val s1 = s.substring(s.length - inset, s.length) - if (s0.substring(s0.lastIndexOf(':')).contains('.')) { - stringToTime(s0 + "GMT" + s1) - } else { - stringToTime(s0 + ".0GMT" + s1) - } - } else { - // ISO8601 with GMT insert - val ISO8601GMT: SimpleDateFormat = new SimpleDateFormat( "yyyy-MM-dd'T'HH:mm:ss.SSSz" ) - ISO8601GMT.parse(s) - } - } - - /** Converts Java objects to catalyst rows / types */ - def convertJavaToCatalyst(a: Any, dataType: DataType): Any = (a, dataType) match { - case (obj, udt: UserDefinedType[_]) => ScalaReflection.convertToCatalyst(obj, udt) // Scala type - case (d: java.math.BigDecimal, _) => Decimal(BigDecimal(d)) - case (other, _) => other - } - - /** Converts Java objects to catalyst rows / types */ - def convertCatalystToJava(a: Any): Any = a match { - case d: scala.math.BigDecimal => d.underlying() - case other => other - } -} diff --git a/sql/core/src/test/java/org/apache/spark/sql/api/java/JavaAPISuite.java b/sql/core/src/test/java/org/apache/spark/sql/api/java/JavaAPISuite.java index a9a11285def54..88017eb47d908 100644 --- a/sql/core/src/test/java/org/apache/spark/sql/api/java/JavaAPISuite.java +++ b/sql/core/src/test/java/org/apache/spark/sql/api/java/JavaAPISuite.java @@ -19,15 +19,12 @@ import java.io.Serializable; -import org.apache.spark.sql.api.java.UDF1; import org.junit.After; -import org.junit.Assert; import org.junit.Before; import org.junit.Test; -import org.junit.runners.Suite; -import org.junit.runner.RunWith; import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.sql.types.DataTypes; // The test suite itself is Serializable so that anonymous Function implementations can be // serialized, as an alternative to converting these anonymous classes to static inner classes; @@ -60,7 +57,7 @@ public void udf1Test() { public Integer call(String str) throws Exception { return str.length(); } - }, DataType.IntegerType); + }, DataTypes.IntegerType); // TODO: Why do we need this cast? Row result = (Row) sqlContext.sql("SELECT stringLengthTest('test')").first(); @@ -81,7 +78,7 @@ public void udf2Test() { public Integer call(String str1, String str2) throws Exception { return str1.length() + str2.length(); } - }, DataType.IntegerType); + }, DataTypes.IntegerType); // TODO: Why do we need this cast? Row result = (Row) sqlContext.sql("SELECT stringLengthTest('test', 'test2')").first(); diff --git a/sql/core/src/test/java/org/apache/spark/sql/api/java/JavaApplySchemaSuite.java b/sql/core/src/test/java/org/apache/spark/sql/api/java/JavaApplySchemaSuite.java index a04b8060cd658..de586ba635913 100644 --- a/sql/core/src/test/java/org/apache/spark/sql/api/java/JavaApplySchemaSuite.java +++ b/sql/core/src/test/java/org/apache/spark/sql/api/java/JavaApplySchemaSuite.java @@ -31,6 +31,7 @@ import org.apache.spark.api.java.JavaRDD; import org.apache.spark.api.java.JavaSparkContext; import org.apache.spark.api.java.function.Function; +import org.apache.spark.sql.types.*; // The test suite itself is Serializable so that anonymous Function implementations can be // serialized, as an alternative to converting these anonymous classes to static inner classes; @@ -93,9 +94,9 @@ public Row call(Person person) throws Exception { }); List fields = new ArrayList(2); - fields.add(DataType.createStructField("name", DataType.StringType, false)); - fields.add(DataType.createStructField("age", DataType.IntegerType, false)); - StructType schema = DataType.createStructType(fields); + fields.add(DataTypes.createStructField("name", DataTypes.StringType, false)); + fields.add(DataTypes.createStructField("age", DataTypes.IntegerType, false)); + StructType schema = DataTypes.createStructType(fields); JavaSchemaRDD schemaRDD = javaSqlCtx.applySchema(rowRDD, schema); schemaRDD.registerTempTable("people"); @@ -118,14 +119,14 @@ public void applySchemaToJSON() { "\"bigInteger\":92233720368547758069, \"double\":1.7976931348623157E305, " + "\"boolean\":false, \"null\":null}")); List fields = new ArrayList(7); - fields.add(DataType.createStructField("bigInteger", new DecimalType(), true)); - fields.add(DataType.createStructField("boolean", DataType.BooleanType, true)); - fields.add(DataType.createStructField("double", DataType.DoubleType, true)); - fields.add(DataType.createStructField("integer", DataType.IntegerType, true)); - fields.add(DataType.createStructField("long", DataType.LongType, true)); - fields.add(DataType.createStructField("null", DataType.StringType, true)); - fields.add(DataType.createStructField("string", DataType.StringType, true)); - StructType expectedSchema = DataType.createStructType(fields); + fields.add(DataTypes.createStructField("bigInteger", DataTypes.createDecimalType(), true)); + fields.add(DataTypes.createStructField("boolean", DataTypes.BooleanType, true)); + fields.add(DataTypes.createStructField("double", DataTypes.DoubleType, true)); + fields.add(DataTypes.createStructField("integer", DataTypes.IntegerType, true)); + fields.add(DataTypes.createStructField("long", DataTypes.LongType, true)); + fields.add(DataTypes.createStructField("null", DataTypes.StringType, true)); + fields.add(DataTypes.createStructField("string", DataTypes.StringType, true)); + StructType expectedSchema = DataTypes.createStructType(fields); List expectedResult = new ArrayList(2); expectedResult.add( Row.create( diff --git a/sql/core/src/test/java/org/apache/spark/sql/api/java/JavaSideDataTypeConversionSuite.java b/sql/core/src/test/java/org/apache/spark/sql/api/java/JavaSideDataTypeConversionSuite.java deleted file mode 100644 index 8396a29c61c4c..0000000000000 --- a/sql/core/src/test/java/org/apache/spark/sql/api/java/JavaSideDataTypeConversionSuite.java +++ /dev/null @@ -1,150 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java; - -import java.util.List; -import java.util.ArrayList; - -import org.junit.Assert; -import org.junit.Test; - -import org.apache.spark.sql.types.util.DataTypeConversions; - -public class JavaSideDataTypeConversionSuite { - public void checkDataType(DataType javaDataType) { - org.apache.spark.sql.catalyst.types.DataType scalaDataType = - DataTypeConversions.asScalaDataType(javaDataType); - DataType actual = DataTypeConversions.asJavaDataType(scalaDataType); - Assert.assertEquals(javaDataType, actual); - } - - @Test - public void createDataTypes() { - // Simple DataTypes. - checkDataType(DataType.StringType); - checkDataType(DataType.BinaryType); - checkDataType(DataType.BooleanType); - checkDataType(DataType.DateType); - checkDataType(DataType.TimestampType); - checkDataType(new DecimalType()); - checkDataType(new DecimalType(10, 4)); - checkDataType(DataType.DoubleType); - checkDataType(DataType.FloatType); - checkDataType(DataType.ByteType); - checkDataType(DataType.IntegerType); - checkDataType(DataType.LongType); - checkDataType(DataType.ShortType); - - // Simple ArrayType. - DataType simpleJavaArrayType = DataType.createArrayType(DataType.StringType, true); - checkDataType(simpleJavaArrayType); - - // Simple MapType. - DataType simpleJavaMapType = DataType.createMapType(DataType.StringType, DataType.LongType); - checkDataType(simpleJavaMapType); - - // Simple StructType. - List simpleFields = new ArrayList(); - simpleFields.add(DataType.createStructField("a", new DecimalType(), false)); - simpleFields.add(DataType.createStructField("b", DataType.BooleanType, true)); - simpleFields.add(DataType.createStructField("c", DataType.LongType, true)); - simpleFields.add(DataType.createStructField("d", DataType.BinaryType, false)); - DataType simpleJavaStructType = DataType.createStructType(simpleFields); - checkDataType(simpleJavaStructType); - - // Complex StructType. - List complexFields = new ArrayList(); - complexFields.add(DataType.createStructField("simpleArray", simpleJavaArrayType, true)); - complexFields.add(DataType.createStructField("simpleMap", simpleJavaMapType, true)); - complexFields.add(DataType.createStructField("simpleStruct", simpleJavaStructType, true)); - complexFields.add(DataType.createStructField("boolean", DataType.BooleanType, false)); - DataType complexJavaStructType = DataType.createStructType(complexFields); - checkDataType(complexJavaStructType); - - // Complex ArrayType. - DataType complexJavaArrayType = DataType.createArrayType(complexJavaStructType, true); - checkDataType(complexJavaArrayType); - - // Complex MapType. - DataType complexJavaMapType = - DataType.createMapType(complexJavaStructType, complexJavaArrayType, false); - checkDataType(complexJavaMapType); - } - - @Test - public void illegalArgument() { - // ArrayType - try { - DataType.createArrayType(null, true); - Assert.fail(); - } catch (IllegalArgumentException expectedException) { - } - - // MapType - try { - DataType.createMapType(null, DataType.StringType); - Assert.fail(); - } catch (IllegalArgumentException expectedException) { - } - try { - DataType.createMapType(DataType.StringType, null); - Assert.fail(); - } catch (IllegalArgumentException expectedException) { - } - try { - DataType.createMapType(null, null); - Assert.fail(); - } catch (IllegalArgumentException expectedException) { - } - - // StructField - try { - DataType.createStructField(null, DataType.StringType, true); - } catch (IllegalArgumentException expectedException) { - } - try { - DataType.createStructField("name", null, true); - } catch (IllegalArgumentException expectedException) { - } - try { - DataType.createStructField(null, null, true); - } catch (IllegalArgumentException expectedException) { - } - - // StructType - try { - List simpleFields = new ArrayList(); - simpleFields.add(DataType.createStructField("a", new DecimalType(), false)); - simpleFields.add(DataType.createStructField("b", DataType.BooleanType, true)); - simpleFields.add(DataType.createStructField("c", DataType.LongType, true)); - simpleFields.add(null); - DataType.createStructType(simpleFields); - Assert.fail(); - } catch (IllegalArgumentException expectedException) { - } - try { - List simpleFields = new ArrayList(); - simpleFields.add(DataType.createStructField("a", new DecimalType(), false)); - simpleFields.add(DataType.createStructField("a", DataType.BooleanType, true)); - simpleFields.add(DataType.createStructField("c", DataType.LongType, true)); - DataType.createStructType(simpleFields); - Assert.fail(); - } catch (IllegalArgumentException expectedException) { - } - } -} diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala index ab88f3ad10d66..efe622f8bcb27 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala @@ -19,6 +19,7 @@ package org.apache.spark.sql import org.apache.spark.sql.catalyst.analysis._ import org.apache.spark.sql.catalyst.expressions._ +import org.apache.spark.sql.types._ /* Implicits */ import org.apache.spark.sql.catalyst.dsl._ diff --git a/sql/core/src/test/scala/org/apache/spark/sql/RowSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/RowSuite.scala index 811319e0a6601..f5b945f468dad 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/RowSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/RowSuite.scala @@ -20,6 +20,7 @@ package org.apache.spark.sql import org.scalatest.FunSuite import org.apache.spark.sql.catalyst.expressions.{GenericMutableRow, SpecificMutableRow} +import org.apache.spark.sql.types._ class RowSuite extends FunSuite { diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala index bc72daf0880a1..cbdb3e64bb66b 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala @@ -23,6 +23,7 @@ import org.scalatest.BeforeAndAfterAll import org.apache.spark.sql.catalyst.errors.TreeNodeException import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan +import org.apache.spark.sql.types._ /* Implicits */ import org.apache.spark.sql.TestData._ @@ -748,7 +749,7 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll { val metadata = new MetadataBuilder() .putString(docKey, docValue) .build() - val schemaWithMeta = new StructType(Seq( + val schemaWithMeta = new StructType(Array( schema("id"), schema("name").copy(metadata = metadata), schema("age"))) val personWithMeta = applySchema(person, schemaWithMeta) def validateMetadata(rdd: SchemaRDD): Unit = { diff --git a/sql/core/src/test/scala/org/apache/spark/sql/ScalaReflectionRelationSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/ScalaReflectionRelationSuite.scala index cf3a59e545905..40fb8d5779fdf 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/ScalaReflectionRelationSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/ScalaReflectionRelationSuite.scala @@ -19,7 +19,6 @@ package org.apache.spark.sql import java.sql.{Date, Timestamp} -import org.apache.spark.sql.catalyst.types.decimal.Decimal import org.scalatest.FunSuite import org.apache.spark.sql.catalyst.expressions._ diff --git a/sql/core/src/test/scala/org/apache/spark/sql/UserDefinedTypeSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/UserDefinedTypeSuite.scala index 1806a1dd82023..a0d54d17f5f13 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/UserDefinedTypeSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/UserDefinedTypeSuite.scala @@ -20,9 +20,8 @@ package org.apache.spark.sql import scala.beans.{BeanInfo, BeanProperty} import org.apache.spark.rdd.RDD -import org.apache.spark.sql.catalyst.annotation.SQLUserDefinedType -import org.apache.spark.sql.catalyst.types.UserDefinedType import org.apache.spark.sql.test.TestSQLContext._ +import org.apache.spark.sql.types._ @SQLUserDefinedType(udt = classOf[MyDenseVectorUDT]) private[sql] class MyDenseVector(val data: Array[Double]) extends Serializable { diff --git a/sql/core/src/test/scala/org/apache/spark/sql/api/java/JavaSQLSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/api/java/JavaSQLSuite.scala index 8afc3a9fb2187..fdbb4282baf48 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/api/java/JavaSQLSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/api/java/JavaSQLSuite.scala @@ -17,8 +17,6 @@ package org.apache.spark.sql.api.java -import org.apache.spark.sql.catalyst.types.decimal.Decimal - import scala.beans.BeanProperty import org.scalatest.FunSuite @@ -26,6 +24,7 @@ import org.scalatest.FunSuite import org.apache.spark.api.java.JavaSparkContext import org.apache.spark.sql.catalyst.util._ import org.apache.spark.sql.test.TestSQLContext +import org.apache.spark.sql.types.NullType // Implicits import scala.collection.JavaConversions._ @@ -78,10 +77,10 @@ class JavaSQLSuite extends FunSuite { schemaRDD.registerTempTable("people") val nullRDD = javaSqlCtx.sql("SELECT null FROM people") - val structFields = nullRDD.schema.getFields() + val structFields = nullRDD.schema.fields assert(structFields.size == 1) - assert(structFields(0).getDataType().isInstanceOf[NullType]) - assert(nullRDD.collect.head.row === Seq(null)) + assert(structFields(0).dataType === NullType) + assert(nullRDD.collect().head.row === Seq(null)) } test("all types in JavaBeans") { diff --git a/sql/core/src/test/scala/org/apache/spark/sql/api/java/ScalaSideDataTypeConversionSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/api/java/ScalaSideDataTypeConversionSuite.scala deleted file mode 100644 index 62fe59dd345d7..0000000000000 --- a/sql/core/src/test/scala/org/apache/spark/sql/api/java/ScalaSideDataTypeConversionSuite.scala +++ /dev/null @@ -1,89 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql.api.java - -import org.scalatest.FunSuite - -import org.apache.spark.sql.{DataType => SDataType, StructField => SStructField, StructType => SStructType} -import org.apache.spark.sql.types.util.DataTypeConversions._ - -class ScalaSideDataTypeConversionSuite extends FunSuite { - - def checkDataType(scalaDataType: SDataType) { - val javaDataType = asJavaDataType(scalaDataType) - val actual = asScalaDataType(javaDataType) - assert(scalaDataType === actual, s"Converted data type ${actual} " + - s"does not equal the expected data type ${scalaDataType}") - } - - test("convert data types") { - // Simple DataTypes. - checkDataType(org.apache.spark.sql.StringType) - checkDataType(org.apache.spark.sql.BinaryType) - checkDataType(org.apache.spark.sql.BooleanType) - checkDataType(org.apache.spark.sql.DateType) - checkDataType(org.apache.spark.sql.TimestampType) - checkDataType(org.apache.spark.sql.DecimalType.Unlimited) - checkDataType(org.apache.spark.sql.DoubleType) - checkDataType(org.apache.spark.sql.FloatType) - checkDataType(org.apache.spark.sql.ByteType) - checkDataType(org.apache.spark.sql.IntegerType) - checkDataType(org.apache.spark.sql.LongType) - checkDataType(org.apache.spark.sql.ShortType) - - // Simple ArrayType. - val simpleScalaArrayType = - org.apache.spark.sql.ArrayType(org.apache.spark.sql.StringType, true) - checkDataType(simpleScalaArrayType) - - // Simple MapType. - val simpleScalaMapType = - org.apache.spark.sql.MapType(org.apache.spark.sql.StringType, org.apache.spark.sql.LongType) - checkDataType(simpleScalaMapType) - - // Simple StructType. - val simpleScalaStructType = SStructType( - SStructField("a", org.apache.spark.sql.DecimalType.Unlimited, false) :: - SStructField("b", org.apache.spark.sql.BooleanType, true) :: - SStructField("c", org.apache.spark.sql.LongType, true) :: - SStructField("d", org.apache.spark.sql.BinaryType, false) :: Nil) - checkDataType(simpleScalaStructType) - - // Complex StructType. - val metadata = new MetadataBuilder() - .putString("name", "age") - .build() - val complexScalaStructType = SStructType( - SStructField("simpleArray", simpleScalaArrayType, true) :: - SStructField("simpleMap", simpleScalaMapType, true) :: - SStructField("simpleStruct", simpleScalaStructType, true) :: - SStructField("boolean", org.apache.spark.sql.BooleanType, false) :: - SStructField("withMeta", org.apache.spark.sql.DoubleType, false, metadata) :: Nil) - checkDataType(complexScalaStructType) - - // Complex ArrayType. - val complexScalaArrayType = - org.apache.spark.sql.ArrayType(complexScalaStructType, true) - checkDataType(complexScalaArrayType) - - // Complex MapType. - val complexScalaMapType = - org.apache.spark.sql.MapType(complexScalaStructType, complexScalaArrayType, false) - checkDataType(complexScalaMapType) - } -} diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnStatsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnStatsSuite.scala index a9f0851f8826c..9be0b38e689ff 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnStatsSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnStatsSuite.scala @@ -20,7 +20,7 @@ package org.apache.spark.sql.columnar import org.scalatest.FunSuite import org.apache.spark.sql.catalyst.expressions.Row -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ class ColumnStatsSuite extends FunSuite { testColumnStats(classOf[ByteColumnStats], BYTE, Row(Byte.MaxValue, Byte.MinValue, 0)) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnTypeSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnTypeSuite.scala index 3f3f35d50188b..87e608a8853dc 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnTypeSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnTypeSuite.scala @@ -24,9 +24,9 @@ import org.scalatest.FunSuite import org.apache.spark.Logging import org.apache.spark.sql.catalyst.expressions.GenericMutableRow -import org.apache.spark.sql.catalyst.types._ import org.apache.spark.sql.columnar.ColumnarTestUtils._ import org.apache.spark.sql.execution.SparkSqlSerializer +import org.apache.spark.sql.types._ class ColumnTypeSuite extends FunSuite with Logging { val DEFAULT_BUFFER_SIZE = 512 diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnarTestUtils.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnarTestUtils.scala index a1f21219eaf2f..f941465fa3e35 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnarTestUtils.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/ColumnarTestUtils.scala @@ -24,7 +24,7 @@ import java.sql.{Date, Timestamp} import org.apache.spark.sql.Row import org.apache.spark.sql.catalyst.expressions.GenericMutableRow -import org.apache.spark.sql.catalyst.types.{DataType, NativeType} +import org.apache.spark.sql.types.{DataType, NativeType} object ColumnarTestUtils { def makeNullRow(length: Int) = { diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnAccessorSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnAccessorSuite.scala index 21906e3fdcc6f..f95c895587f3f 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnAccessorSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnAccessorSuite.scala @@ -22,7 +22,7 @@ import java.nio.ByteBuffer import org.scalatest.FunSuite import org.apache.spark.sql.catalyst.expressions.GenericMutableRow -import org.apache.spark.sql.catalyst.types.DataType +import org.apache.spark.sql.types.DataType class TestNullableColumnAccessor[T <: DataType, JvmType]( buffer: ByteBuffer, diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnBuilderSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnBuilderSuite.scala index cb73f3da81e24..80bd5c94570cb 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnBuilderSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/NullableColumnBuilderSuite.scala @@ -19,8 +19,8 @@ package org.apache.spark.sql.columnar import org.scalatest.FunSuite -import org.apache.spark.sql.catalyst.types._ import org.apache.spark.sql.execution.SparkSqlSerializer +import org.apache.spark.sql.types._ class TestNullableColumnBuilder[T <: DataType, JvmType](columnType: ColumnType[T, JvmType]) extends BasicColumnBuilder[T, JvmType](new NoopColumnStats, columnType) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/DictionaryEncodingSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/DictionaryEncodingSuite.scala index 1cdb909146d57..c82d9799359c7 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/DictionaryEncodingSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/DictionaryEncodingSuite.scala @@ -22,9 +22,9 @@ import java.nio.ByteBuffer import org.scalatest.FunSuite import org.apache.spark.sql.catalyst.expressions.GenericMutableRow -import org.apache.spark.sql.catalyst.types.NativeType import org.apache.spark.sql.columnar._ import org.apache.spark.sql.columnar.ColumnarTestUtils._ +import org.apache.spark.sql.types.NativeType class DictionaryEncodingSuite extends FunSuite { testDictionaryEncoding(new IntColumnStats, INT) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/IntegralDeltaSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/IntegralDeltaSuite.scala index 73f31c0233343..88011631ee4e3 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/IntegralDeltaSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/IntegralDeltaSuite.scala @@ -20,9 +20,9 @@ package org.apache.spark.sql.columnar.compression import org.scalatest.FunSuite import org.apache.spark.sql.catalyst.expressions.GenericMutableRow -import org.apache.spark.sql.catalyst.types.IntegralType import org.apache.spark.sql.columnar._ import org.apache.spark.sql.columnar.ColumnarTestUtils._ +import org.apache.spark.sql.types.IntegralType class IntegralDeltaSuite extends FunSuite { testIntegralDelta(new IntColumnStats, INT, IntDelta) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/RunLengthEncodingSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/RunLengthEncodingSuite.scala index 4ce2552112c92..08df1db375097 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/RunLengthEncodingSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/RunLengthEncodingSuite.scala @@ -20,9 +20,9 @@ package org.apache.spark.sql.columnar.compression import org.scalatest.FunSuite import org.apache.spark.sql.catalyst.expressions.GenericMutableRow -import org.apache.spark.sql.catalyst.types.NativeType import org.apache.spark.sql.columnar._ import org.apache.spark.sql.columnar.ColumnarTestUtils._ +import org.apache.spark.sql.types.NativeType class RunLengthEncodingSuite extends FunSuite { testRunLengthEncoding(new NoopColumnStats, BOOLEAN) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/TestCompressibleColumnBuilder.scala b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/TestCompressibleColumnBuilder.scala index 7db723d648d80..0b18b4119268f 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/TestCompressibleColumnBuilder.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/columnar/compression/TestCompressibleColumnBuilder.scala @@ -17,8 +17,8 @@ package org.apache.spark.sql.columnar.compression -import org.apache.spark.sql.catalyst.types.NativeType import org.apache.spark.sql.columnar._ +import org.apache.spark.sql.types.NativeType class TestCompressibleColumnBuilder[T <: NativeType]( override val columnStats: ColumnStats, diff --git a/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala index b09f1ac49553b..01c1ce2a61023 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala @@ -17,19 +17,19 @@ package org.apache.spark.sql.json -import org.apache.spark.sql.catalyst.types._ -import org.apache.spark.sql.catalyst.types.decimal.Decimal -import org.apache.spark.sql.catalyst.util._ -import org.apache.spark.sql.json.JsonRDD.{enforceCorrectType, compatibleType} -import org.apache.spark.sql.{Row, SQLConf, QueryTest} +import java.sql.{Date, Timestamp} + import org.apache.spark.sql.TestData._ +import org.apache.spark.sql.catalyst.util._ +import org.apache.spark.sql.json.JsonRDD.{compatibleType, enforceCorrectType} import org.apache.spark.sql.test.TestSQLContext import org.apache.spark.sql.test.TestSQLContext._ - -import java.sql.{Date, Timestamp} +import org.apache.spark.sql.types._ +import org.apache.spark.sql.types.decimal.Decimal +import org.apache.spark.sql.{QueryTest, Row, SQLConf} class JsonSuite extends QueryTest { - import TestJsonData._ + import org.apache.spark.sql.json.TestJsonData._ TestJsonData test("Type promotion") { diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala index 6ac67fcafe16b..973819aaa4d77 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetIOSuite.scala @@ -21,8 +21,6 @@ import scala.collection.JavaConversions._ import scala.reflect.ClassTag import scala.reflect.runtime.universe.TypeTag -import org.apache.hadoop.conf.Configuration -import org.apache.hadoop.fs.{FileSystem, Path} import parquet.example.data.simple.SimpleGroup import parquet.example.data.{Group, GroupWriter} import parquet.hadoop.api.WriteSupport @@ -32,11 +30,13 @@ import parquet.hadoop.{ParquetFileWriter, ParquetWriter} import parquet.io.api.RecordConsumer import parquet.schema.{MessageType, MessageTypeParser} +import org.apache.hadoop.conf.Configuration +import org.apache.hadoop.fs.{FileSystem, Path} import org.apache.spark.sql.catalyst.ScalaReflection import org.apache.spark.sql.catalyst.expressions.Row -import org.apache.spark.sql.catalyst.types.DecimalType import org.apache.spark.sql.test.TestSQLContext import org.apache.spark.sql.test.TestSQLContext._ +import org.apache.spark.sql.types.DecimalType import org.apache.spark.sql.{QueryTest, SQLConf, SchemaRDD} // Write support class for nested groups: ParquetWriter initializes GroupWriteSupport diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala index 0a92336a3cb39..fe781ec05fb6f 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala @@ -29,10 +29,10 @@ import parquet.io.api.Binary import org.apache.spark.sql._ import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.catalyst.types.IntegerType import org.apache.spark.sql.catalyst.util.getTempFilePath import org.apache.spark.sql.test.TestSQLContext import org.apache.spark.sql.test.TestSQLContext._ +import org.apache.spark.sql.types._ import org.apache.spark.util.Utils case class TestRDDEntry(key: Int, value: String) @@ -911,20 +911,6 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA Utils.deleteRecursively(tmpdir) } - test("DataType string parser compatibility") { - val schema = StructType(List( - StructField("c1", IntegerType, false), - StructField("c2", BinaryType, false))) - - val fromCaseClassString = ParquetTypesConverter.convertFromString(schema.toString) - val fromJson = ParquetTypesConverter.convertFromString(schema.json) - - (fromCaseClassString, fromJson).zipped.foreach { (a, b) => - assert(a.name == b.name) - assert(a.dataType === b.dataType) - } - } - test("read/write fixed-length decimals") { for ((precision, scale) <- Seq((5, 2), (1, 0), (1, 1), (18, 10), (18, 17))) { val tempDir = getTempFilePath("parquetTest").getCanonicalPath diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetSchemaSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetSchemaSuite.scala index 34d61bf908483..64274950b868e 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetSchemaSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetSchemaSuite.scala @@ -24,7 +24,6 @@ import org.scalatest.FunSuite import parquet.schema.MessageTypeParser import org.apache.spark.sql.catalyst.ScalaReflection -import org.apache.spark.sql.catalyst.types.{BinaryType, IntegerType, StructField, StructType} import org.apache.spark.sql.test.TestSQLContext class ParquetSchemaSuite extends FunSuite with ParquetTest { @@ -148,12 +147,20 @@ class ParquetSchemaSuite extends FunSuite with ParquetTest { """.stripMargin) test("DataType string parser compatibility") { - val schema = StructType(List( - StructField("c1", IntegerType, false), - StructField("c2", BinaryType, true))) - - val fromCaseClassString = ParquetTypesConverter.convertFromString(schema.toString) - val fromJson = ParquetTypesConverter.convertFromString(schema.json) + // This is the generated string from previous versions of the Spark SQL, using the following: + // val schema = StructType(List( + // StructField("c1", IntegerType, false), + // StructField("c2", BinaryType, true))) + val caseClassString = + "StructType(List(StructField(c1,IntegerType,false), StructField(c2,BinaryType,true)))" + + val jsonString = + """ + |{"type":"struct","fields":[{"name":"c1","type":"integer","nullable":false,"metadata":{}},{"name":"c2","type":"binary","nullable":true,"metadata":{}}]} + """.stripMargin + + val fromCaseClassString = ParquetTypesConverter.convertFromString(caseClassString) + val fromJson = ParquetTypesConverter.convertFromString(jsonString) (fromCaseClassString, fromJson).zipped.foreach { (a, b) => assert(a.name == b.name) diff --git a/sql/core/src/test/scala/org/apache/spark/sql/sources/FilteredScanSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/sources/FilteredScanSuite.scala index 939b3c0c66de7..390538d35a348 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/sources/FilteredScanSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/sources/FilteredScanSuite.scala @@ -20,6 +20,8 @@ package org.apache.spark.sql.sources import scala.language.existentials import org.apache.spark.sql._ +import org.apache.spark.sql.types._ + class FilteredScanSource extends RelationProvider { override def createRelation( diff --git a/sql/core/src/test/scala/org/apache/spark/sql/sources/PrunedScanSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/sources/PrunedScanSuite.scala index fee2e22611cdc..7900b3e8948d9 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/sources/PrunedScanSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/sources/PrunedScanSuite.scala @@ -18,6 +18,7 @@ package org.apache.spark.sql.sources import org.apache.spark.sql._ +import org.apache.spark.sql.types._ class PrunedScanSource extends RelationProvider { override def createRelation( diff --git a/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala index a1d2468b2573c..382dddcdeac38 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/sources/TableScanSuite.scala @@ -20,7 +20,7 @@ package org.apache.spark.sql.sources import java.sql.{Timestamp, Date} import org.apache.spark.sql._ -import org.apache.spark.sql.catalyst.types.DecimalType +import org.apache.spark.sql.types._ class DefaultSource extends SimpleScanSource diff --git a/sql/hive-thriftserver/v0.12.0/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim12.scala b/sql/hive-thriftserver/v0.12.0/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim12.scala index 742acba58d776..171d707b138b6 100644 --- a/sql/hive-thriftserver/v0.12.0/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim12.scala +++ b/sql/hive-thriftserver/v0.12.0/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim12.scala @@ -32,11 +32,11 @@ import org.apache.hive.service.cli.operation.ExecuteStatementOperation import org.apache.hive.service.cli.session.HiveSession import org.apache.spark.Logging -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.{SQLConf, SchemaRDD, Row => SparkRow} import org.apache.spark.sql.execution.SetCommand import org.apache.spark.sql.hive.thriftserver.ReflectionUtils._ import org.apache.spark.sql.hive.{HiveContext, HiveMetastoreTypes} -import org.apache.spark.sql.{SQLConf, SchemaRDD, Row => SparkRow} +import org.apache.spark.sql.types._ /** * A compatibility layer for interacting with Hive version 0.12.0. diff --git a/sql/hive-thriftserver/v0.13.1/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim13.scala b/sql/hive-thriftserver/v0.13.1/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim13.scala index b82156427a88c..bec9d9aca30cf 100644 --- a/sql/hive-thriftserver/v0.13.1/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim13.scala +++ b/sql/hive-thriftserver/v0.13.1/src/main/scala/org/apache/spark/sql/hive/thriftserver/Shim13.scala @@ -30,11 +30,11 @@ import org.apache.hive.service.cli.operation.ExecuteStatementOperation import org.apache.hive.service.cli.session.HiveSession import org.apache.spark.Logging +import org.apache.spark.sql.{Row => SparkRow, SQLConf, SchemaRDD} import org.apache.spark.sql.execution.SetCommand -import org.apache.spark.sql.catalyst.types._ import org.apache.spark.sql.hive.thriftserver.ReflectionUtils._ import org.apache.spark.sql.hive.{HiveContext, HiveMetastoreTypes} -import org.apache.spark.sql.{Row => SparkRow, SQLConf, SchemaRDD} +import org.apache.spark.sql.types._ /** * A compatibility layer for interacting with Hive version 0.13.1. diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala index 9aeebd7e54366..bf56e60cf995f 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala @@ -37,10 +37,10 @@ import org.apache.spark.sql._ import org.apache.spark.sql.catalyst.ScalaReflection import org.apache.spark.sql.catalyst.analysis.{Analyzer, EliminateAnalysisOperators, OverrideCatalog, OverrideFunctionRegistry} import org.apache.spark.sql.catalyst.plans.logical._ -import org.apache.spark.sql.catalyst.types.DecimalType import org.apache.spark.sql.execution.{ExecutedCommand, ExtractPythonUdfs, SetCommand, QueryExecutionException} import org.apache.spark.sql.hive.execution.{HiveNativeCommand, DescribeHiveTableCommand} import org.apache.spark.sql.sources.DataSourceStrategy +import org.apache.spark.sql.types._ /** * DEPRECATED: Use HiveContext instead. diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala index a156d6f7e285d..245b847cf4cd4 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala @@ -24,9 +24,9 @@ import org.apache.hadoop.hive.serde2.{io => hiveIo} import org.apache.hadoop.{io => hadoopIo} import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.catalyst.types -import org.apache.spark.sql.catalyst.types._ -import org.apache.spark.sql.catalyst.types.decimal.Decimal +import org.apache.spark.sql.types +import org.apache.spark.sql.types._ +import org.apache.spark.sql.types.decimal.Decimal /* Implicit conversions */ import scala.collection.JavaConversions._ @@ -43,7 +43,7 @@ import scala.collection.JavaConversions._ * long / scala.Long * short / scala.Short * byte / scala.Byte - * org.apache.spark.sql.catalyst.types.decimal.Decimal + * org.apache.spark.sql.types.decimal.Decimal * Array[Byte] * java.sql.Date * java.sql.Timestamp @@ -504,7 +504,8 @@ private[hive] trait HiveInspectors { case DecimalType() => PrimitiveObjectInspectorFactory.javaHiveDecimalObjectInspector case StructType(fields) => ObjectInspectorFactory.getStandardStructObjectInspector( - fields.map(f => f.name), fields.map(f => toInspector(f.dataType))) + java.util.Arrays.asList(fields.map(f => f.name) :_*), + java.util.Arrays.asList(fields.map(f => toInspector(f.dataType)) :_*)) } /** @@ -618,7 +619,9 @@ private[hive] trait HiveInspectors { case ArrayType(elemType, _) => getListTypeInfo(elemType.toTypeInfo) case StructType(fields) => - getStructTypeInfo(fields.map(_.name), fields.map(_.dataType.toTypeInfo)) + getStructTypeInfo( + java.util.Arrays.asList(fields.map(_.name) :_*), + java.util.Arrays.asList(fields.map(_.dataType.toTypeInfo) :_*)) case MapType(keyType, valueType, _) => getMapTypeInfo(keyType.toTypeInfo, valueType.toTypeInfo) case BinaryType => binaryTypeInfo diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala index 785a6a14f49f4..d40f9936fd3b5 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala @@ -39,8 +39,8 @@ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.logical import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.rules._ -import org.apache.spark.sql.catalyst.types._ import org.apache.spark.sql.sources.{LogicalRelation, ResolvedDataSource} +import org.apache.spark.sql.types._ import org.apache.spark.util.Utils /* Implicit conversions */ diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala index 34622b5f57873..b13ef7276bf3c 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala @@ -18,6 +18,7 @@ package org.apache.spark.sql.hive import java.sql.Date + import org.apache.hadoop.hive.conf.HiveConf import org.apache.hadoop.hive.ql.Context import org.apache.hadoop.hive.ql.lib.Node @@ -31,10 +32,10 @@ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans._ import org.apache.spark.sql.catalyst.plans.logical import org.apache.spark.sql.catalyst.plans.logical._ -import org.apache.spark.sql.catalyst.types._ -import org.apache.spark.sql.catalyst.types.decimal.Decimal import org.apache.spark.sql.execution.ExplainCommand import org.apache.spark.sql.hive.execution.{HiveNativeCommand, DropTable, AnalyzeTable} +import org.apache.spark.sql.types._ +import org.apache.spark.sql.types.decimal.Decimal /* Implicit conversions */ import scala.collection.JavaConversions._ diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala index cdff82e3d04d2..6952b126cf894 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveStrategies.scala @@ -17,23 +17,24 @@ package org.apache.spark.sql.hive +import scala.collection.JavaConversions._ + import org.apache.spark.annotation.Experimental +import org.apache.spark.sql.{SQLContext, SchemaRDD, Strategy} import org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate import org.apache.spark.sql.catalyst.planning._ import org.apache.spark.sql.catalyst.plans._ import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan -import org.apache.spark.sql.catalyst.types.StringType import org.apache.spark.sql.execution.{DescribeCommand => RunnableDescribeCommand} import org.apache.spark.sql.execution._ import org.apache.spark.sql.hive import org.apache.spark.sql.hive.execution._ import org.apache.spark.sql.parquet.ParquetRelation import org.apache.spark.sql.sources.CreateTableUsing -import org.apache.spark.sql.{SQLContext, SchemaRDD, Strategy} +import org.apache.spark.sql.types.StringType -import scala.collection.JavaConversions._ private[hive] trait HiveStrategies { // Possibly being too clever with types here... or not clever enough. diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveNativeCommand.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveNativeCommand.scala index 8ba818af5f9d0..781a2e9164c82 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveNativeCommand.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveNativeCommand.scala @@ -22,7 +22,7 @@ import org.apache.spark.sql.catalyst.expressions.{AttributeReference, Row} import org.apache.spark.sql.execution.RunnableCommand import org.apache.spark.sql.hive.HiveContext import org.apache.spark.sql.SQLContext -import org.apache.spark.sql.catalyst.types.StringType +import org.apache.spark.sql.types.StringType /** * :: DeveloperApi :: diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScan.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScan.scala index 8bbcd6fec1f3b..b56175fe76376 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScan.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScan.scala @@ -19,20 +19,18 @@ package org.apache.spark.sql.hive.execution import scala.collection.JavaConversions._ -import org.apache.hadoop.hive.common.`type`.{HiveDecimal, HiveVarchar} import org.apache.hadoop.hive.conf.HiveConf import org.apache.hadoop.hive.ql.metadata.{Partition => HivePartition} import org.apache.hadoop.hive.serde.serdeConstants import org.apache.hadoop.hive.serde2.objectinspector._ import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorUtils.ObjectInspectorCopyOption -import org.apache.hadoop.hive.serde2.objectinspector.primitive._ import org.apache.hadoop.hive.serde2.typeinfo.TypeInfoUtils import org.apache.spark.annotation.DeveloperApi import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.catalyst.types.{BooleanType, DataType} import org.apache.spark.sql.execution._ import org.apache.spark.sql.hive._ +import org.apache.spark.sql.types.{BooleanType, DataType} /** * :: DeveloperApi :: diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala index e70cdeaad4c09..cf72345efa63f 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/commands.scala @@ -18,11 +18,11 @@ package org.apache.spark.sql.hive.execution import org.apache.spark.annotation.DeveloperApi +import org.apache.spark.sql.SQLContext import org.apache.spark.sql.catalyst.expressions.Row -import org.apache.spark.sql.catalyst.types.StructType import org.apache.spark.sql.execution.RunnableCommand import org.apache.spark.sql.hive.HiveContext -import org.apache.spark.sql.SQLContext +import org.apache.spark.sql.types.StructType /** * :: DeveloperApi :: diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala index 7d863f9d89dae..d898b876c39f8 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala @@ -33,7 +33,7 @@ import org.apache.hadoop.hive.ql.udf.generic.GenericUDF._ import org.apache.spark.Logging import org.apache.spark.sql.catalyst.analysis import org.apache.spark.sql.catalyst.expressions._ -import org.apache.spark.sql.catalyst.types._ +import org.apache.spark.sql.types._ import org.apache.spark.util.Utils.getContextOrSparkClassLoader /* Implicit conversions */ diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala index f90d3607915ae..dc23d9a101d17 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala @@ -17,22 +17,21 @@ package org.apache.spark.sql.hive -import java.sql.Date import java.util +import java.sql.Date import java.util.{Locale, TimeZone} -import org.apache.hadoop.hive.serde2.io.DoubleWritable -import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory -import org.apache.spark.sql.catalyst.types._ -import org.apache.spark.sql.catalyst.types.decimal.Decimal -import org.scalatest.FunSuite - import org.apache.hadoop.hive.ql.udf.UDAFPercentile -import org.apache.hadoop.hive.serde2.objectinspector.{ObjectInspector, StructObjectInspector, ObjectInspectorFactory} +import org.apache.hadoop.hive.serde2.io.DoubleWritable +import org.apache.hadoop.hive.serde2.objectinspector.{ObjectInspector, ObjectInspectorFactory, StructObjectInspector} import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory.ObjectInspectorOptions +import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory import org.apache.hadoop.io.LongWritable +import org.scalatest.FunSuite import org.apache.spark.sql.catalyst.expressions.{Literal, Row} +import org.apache.spark.sql.types._ +import org.apache.spark.sql.types.decimal.Decimal class HiveInspectorSuite extends FunSuite with HiveInspectors { test("Test wrap SettableStructObjectInspector") { @@ -93,7 +92,6 @@ class HiveInspectorSuite extends FunSuite with HiveInspectors { val row = data.map(_.eval(null)) val dataTypes = data.map(_.dataType) - import scala.collection.JavaConversions._ def toWritableInspector(dataType: DataType): ObjectInspector = dataType match { case ArrayType(tpe, _) => ObjectInspectorFactory.getStandardListObjectInspector(toWritableInspector(tpe)) @@ -115,7 +113,8 @@ class HiveInspectorSuite extends FunSuite with HiveInspectors { case DecimalType() => PrimitiveObjectInspectorFactory.writableHiveDecimalObjectInspector case StructType(fields) => ObjectInspectorFactory.getStandardStructObjectInspector( - fields.map(f => f.name), fields.map(f => toWritableInspector(f.dataType))) + java.util.Arrays.asList(fields.map(f => f.name) :_*), + java.util.Arrays.asList(fields.map(f => toWritableInspector(f.dataType)) :_*)) } def checkDataType(dt1: Seq[DataType], dt2: Seq[DataType]): Unit = { diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveMetastoreCatalogSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveMetastoreCatalogSuite.scala index 041a36f1295ef..fa6905f31f81e 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveMetastoreCatalogSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveMetastoreCatalogSuite.scala @@ -19,9 +19,9 @@ package org.apache.spark.sql.hive import org.scalatest.FunSuite -import org.apache.spark.sql.catalyst.types.StructType import org.apache.spark.sql.sources.DDLParser import org.apache.spark.sql.test.ExamplePointUDT +import org.apache.spark.sql.types.StructType class HiveMetastoreCatalogSuite extends FunSuite { diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/InsertIntoHiveTableSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/InsertIntoHiveTableSuite.scala index fb481edc853b7..7cfb875e05db3 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/InsertIntoHiveTableSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/InsertIntoHiveTableSuite.scala @@ -22,6 +22,7 @@ import java.io.File import com.google.common.io.Files import org.apache.spark.sql.{QueryTest, _} import org.apache.spark.sql.hive.test.TestHive +import org.apache.spark.sql.types._ /* Implicits */ import org.apache.spark.sql.hive.test.TestHive._ diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/MetastoreDataSourcesSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/MetastoreDataSourcesSuite.scala index ec9ebb4a775a3..8ff833e0d60d1 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/MetastoreDataSourcesSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/MetastoreDataSourcesSuite.scala @@ -25,6 +25,7 @@ import org.apache.commons.io.FileUtils import org.apache.spark.sql._ import org.apache.spark.util.Utils +import org.apache.spark.sql.types._ /* Implicits */ import org.apache.spark.sql.hive.test.TestHive._ diff --git a/sql/hive/v0.12.0/src/main/scala/org/apache/spark/sql/hive/Shim12.scala b/sql/hive/v0.12.0/src/main/scala/org/apache/spark/sql/hive/Shim12.scala index 25fdf5c5f3da6..a5587460fd696 100644 --- a/sql/hive/v0.12.0/src/main/scala/org/apache/spark/sql/hive/Shim12.scala +++ b/sql/hive/v0.12.0/src/main/scala/org/apache/spark/sql/hive/Shim12.scala @@ -18,8 +18,12 @@ package org.apache.spark.sql.hive import java.net.URI -import java.util.{ArrayList => JArrayList} -import java.util.Properties +import java.util.{ArrayList => JArrayList, Properties} + +import scala.collection.JavaConversions._ +import scala.language.implicitConversions + +import org.apache.hadoop.{io => hadoopIo} import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.Path import org.apache.hadoop.hive.common.`type`.HiveDecimal @@ -29,20 +33,16 @@ import org.apache.hadoop.hive.ql.metadata.{Hive, Partition, Table} import org.apache.hadoop.hive.ql.plan.{CreateTableDesc, FileSinkDesc, TableDesc} import org.apache.hadoop.hive.ql.processors._ import org.apache.hadoop.hive.ql.stats.StatsSetupConst +import org.apache.hadoop.hive.serde2.{ColumnProjectionUtils, Deserializer, io => hiveIo} +import org.apache.hadoop.hive.serde2.objectinspector.{ObjectInspector, PrimitiveObjectInspector} import org.apache.hadoop.hive.serde2.objectinspector.PrimitiveObjectInspector.PrimitiveCategory import org.apache.hadoop.hive.serde2.objectinspector.primitive.{HiveDecimalObjectInspector, PrimitiveObjectInspectorFactory} -import org.apache.hadoop.hive.serde2.objectinspector.{PrimitiveObjectInspector, ObjectInspector} import org.apache.hadoop.hive.serde2.typeinfo.{TypeInfo, TypeInfoFactory} -import org.apache.hadoop.hive.serde2.{Deserializer, ColumnProjectionUtils} -import org.apache.hadoop.hive.serde2.{io => hiveIo} import org.apache.hadoop.io.NullWritable -import org.apache.hadoop.{io => hadoopIo} import org.apache.hadoop.mapred.InputFormat -import org.apache.spark.sql.catalyst.types.decimal.Decimal -import scala.collection.JavaConversions._ -import scala.language.implicitConversions -import org.apache.spark.sql.catalyst.types.DecimalType +import org.apache.spark.sql.types.DecimalType +import org.apache.spark.sql.types.decimal.Decimal case class HiveFunctionWrapper(functionClassName: String) extends java.io.Serializable { // for Serialization diff --git a/sql/hive/v0.13.1/src/main/scala/org/apache/spark/sql/hive/Shim13.scala b/sql/hive/v0.13.1/src/main/scala/org/apache/spark/sql/hive/Shim13.scala index e47002cb0b8c8..a7121360dd350 100644 --- a/sql/hive/v0.13.1/src/main/scala/org/apache/spark/sql/hive/Shim13.scala +++ b/sql/hive/v0.13.1/src/main/scala/org/apache/spark/sql/hive/Shim13.scala @@ -20,6 +20,9 @@ package org.apache.spark.sql.hive import java.util.{ArrayList => JArrayList} import java.util.Properties +import scala.collection.JavaConversions._ +import scala.language.implicitConversions + import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.Path import org.apache.hadoop.io.NullWritable @@ -37,12 +40,10 @@ import org.apache.hadoop.hive.serde2.objectinspector.{PrimitiveObjectInspector, import org.apache.hadoop.hive.serde2.{Deserializer, ColumnProjectionUtils} import org.apache.hadoop.hive.serde2.{io => hiveIo} import org.apache.hadoop.{io => hadoopIo} -import org.apache.spark.Logging -import org.apache.spark.sql.catalyst.types.DecimalType -import org.apache.spark.sql.catalyst.types.decimal.Decimal -import scala.collection.JavaConversions._ -import scala.language.implicitConversions +import org.apache.spark.Logging +import org.apache.spark.sql.types.DecimalType +import org.apache.spark.sql.types.decimal.Decimal /** From d5eeb35167e1ab72fab7778757163ff0aacaef2c Mon Sep 17 00:00:00 2001 From: Reynold Xin Date: Wed, 14 Jan 2015 00:38:55 -0800 Subject: [PATCH 246/320] [SPARK-5167][SQL] Move Row into sql package and make it usable for Java. Mostly just moving stuff around. This should still be source compatible since we type aliased Row previously in org.apache.spark.sql.Row. Added the following APIs to Row: ```scala def getMap[K, V](i: Int): scala.collection.Map[K, V] def getJavaMap[K, V](i: Int): java.util.Map[K, V] def getSeq[T](i: Int): Seq[T] def getList[T](i: Int): java.util.List[T] def getStruct(i: Int): StructType ``` Author: Reynold Xin Closes #4030 from rxin/sql-row and squashes the following commits: 6c85c29 [Reynold Xin] Fixed style violation by adding a new line to Row.scala. 82b064a [Reynold Xin] [SPARK-5167][SQL] Move Row into sql package and make it usable for Java. --- .../java/org/apache/spark/sql/RowFactory.java | 34 +++ .../main/scala/org/apache/spark/sql/Row.scala | 240 ++++++++++++++++++ .../sql/catalyst/expressions/package.scala | 4 + .../expressions/{Row.scala => rows.scala} | 113 ++------- .../apache/spark/sql/types/dataTypes.scala | 2 +- .../org/apache/spark/sql/api/java/Row.scala | 2 +- .../scala/org/apache/spark/sql/package.scala | 83 ------ 7 files changed, 304 insertions(+), 174 deletions(-) create mode 100644 sql/catalyst/src/main/java/org/apache/spark/sql/RowFactory.java create mode 100644 sql/catalyst/src/main/scala/org/apache/spark/sql/Row.scala rename sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/{Row.scala => rows.scala} (68%) diff --git a/sql/catalyst/src/main/java/org/apache/spark/sql/RowFactory.java b/sql/catalyst/src/main/java/org/apache/spark/sql/RowFactory.java new file mode 100644 index 0000000000000..62fcec824d09a --- /dev/null +++ b/sql/catalyst/src/main/java/org/apache/spark/sql/RowFactory.java @@ -0,0 +1,34 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql; + +import org.apache.spark.sql.catalyst.expressions.GenericRow; + +/** + * A factory class used to construct {@link Row} objects. + */ +public class RowFactory { + + /** + * Create a {@link Row} from an array of values. Position i in the array becomes position i + * in the created {@link Row} object. + */ + public static Row create(Object[] values) { + return new GenericRow(values); + } +} diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/Row.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/Row.scala new file mode 100644 index 0000000000000..d7a4e014ce6a6 --- /dev/null +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/Row.scala @@ -0,0 +1,240 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql + +import org.apache.spark.sql.catalyst.expressions.GenericRow + + +object Row { + /** + * This method can be used to extract fields from a [[Row]] object in a pattern match. Example: + * {{{ + * import org.apache.spark.sql._ + * + * val pairs = sql("SELECT key, value FROM src").rdd.map { + * case Row(key: Int, value: String) => + * key -> value + * } + * }}} + */ + def unapplySeq(row: Row): Some[Seq[Any]] = Some(row) + + /** + * This method can be used to construct a [[Row]] with the given values. + */ + def apply(values: Any*): Row = new GenericRow(values.toArray) + + /** + * This method can be used to construct a [[Row]] from a [[Seq]] of values. + */ + def fromSeq(values: Seq[Any]): Row = new GenericRow(values.toArray) +} + + +/** + * Represents one row of output from a relational operator. Allows both generic access by ordinal, + * which will incur boxing overhead for primitives, as well as native primitive access. + * + * It is invalid to use the native primitive interface to retrieve a value that is null, instead a + * user must check `isNullAt` before attempting to retrieve a value that might be null. + * + * To create a new Row, use [[RowFactory.create()]] in Java or [[Row.apply()]] in Scala. + * + * A [[Row]] object can be constructed by providing field values. Example: + * {{{ + * import org.apache.spark.sql._ + * + * // Create a Row from values. + * Row(value1, value2, value3, ...) + * // Create a Row from a Seq of values. + * Row.fromSeq(Seq(value1, value2, ...)) + * }}} + * + * A value of a row can be accessed through both generic access by ordinal, + * which will incur boxing overhead for primitives, as well as native primitive access. + * An example of generic access by ordinal: + * {{{ + * import org.apache.spark.sql._ + * + * val row = Row(1, true, "a string", null) + * // row: Row = [1,true,a string,null] + * val firstValue = row(0) + * // firstValue: Any = 1 + * val fourthValue = row(3) + * // fourthValue: Any = null + * }}} + * + * For native primitive access, it is invalid to use the native primitive interface to retrieve + * a value that is null, instead a user must check `isNullAt` before attempting to retrieve a + * value that might be null. + * An example of native primitive access: + * {{{ + * // using the row from the previous example. + * val firstValue = row.getInt(0) + * // firstValue: Int = 1 + * val isNull = row.isNullAt(3) + * // isNull: Boolean = true + * }}} + * + * Interfaces related to native primitive access are: + * + * `isNullAt(i: Int): Boolean` + * + * `getInt(i: Int): Int` + * + * `getLong(i: Int): Long` + * + * `getDouble(i: Int): Double` + * + * `getFloat(i: Int): Float` + * + * `getBoolean(i: Int): Boolean` + * + * `getShort(i: Int): Short` + * + * `getByte(i: Int): Byte` + * + * `getString(i: Int): String` + * + * In Scala, fields in a [[Row]] object can be extracted in a pattern match. Example: + * {{{ + * import org.apache.spark.sql._ + * + * val pairs = sql("SELECT key, value FROM src").rdd.map { + * case Row(key: Int, value: String) => + * key -> value + * } + * }}} + * + * @group row + */ +trait Row extends Seq[Any] with Serializable { + def apply(i: Int): Any + + /** Returns the value at position i. If the value is null, null is returned. */ + def get(i: Int): Any = apply(i) + + /** Checks whether the value at position i is null. */ + def isNullAt(i: Int): Boolean + + /** + * Returns the value at position i as a primitive int. + * Throws an exception if the type mismatches or if the value is null. + */ + def getInt(i: Int): Int + + /** + * Returns the value at position i as a primitive long. + * Throws an exception if the type mismatches or if the value is null. + */ + def getLong(i: Int): Long + + /** + * Returns the value at position i as a primitive double. + * Throws an exception if the type mismatches or if the value is null. + */ + def getDouble(i: Int): Double + + /** + * Returns the value at position i as a primitive float. + * Throws an exception if the type mismatches or if the value is null. + */ + def getFloat(i: Int): Float + + /** + * Returns the value at position i as a primitive boolean. + * Throws an exception if the type mismatches or if the value is null. + */ + def getBoolean(i: Int): Boolean + + /** + * Returns the value at position i as a primitive short. + * Throws an exception if the type mismatches or if the value is null. + */ + def getShort(i: Int): Short + + /** + * Returns the value at position i as a primitive byte. + * Throws an exception if the type mismatches or if the value is null. + */ + def getByte(i: Int): Byte + + /** + * Returns the value at position i as a String object. + * Throws an exception if the type mismatches or if the value is null. + */ + def getString(i: Int): String + + /** + * Return the value at position i of array type as a Scala Seq. + * Throws an exception if the type mismatches. + */ + def getSeq[T](i: Int): Seq[T] = apply(i).asInstanceOf[Seq[T]] + + /** + * Return the value at position i of array type as [[java.util.List]]. + * Throws an exception if the type mismatches. + */ + def getList[T](i: Int): java.util.List[T] = { + scala.collection.JavaConversions.seqAsJavaList(getSeq[T](i)) + } + + /** + * Return the value at position i of map type as a Scala Map. + * Throws an exception if the type mismatches. + */ + def getMap[K, V](i: Int): scala.collection.Map[K, V] = apply(i).asInstanceOf[Map[K, V]] + + /** + * Return the value at position i of array type as a [[java.util.Map]]. + * Throws an exception if the type mismatches. + */ + def getJavaMap[K, V](i: Int): java.util.Map[K, V] = { + scala.collection.JavaConversions.mapAsJavaMap(getMap[K, V](i)) + } + + /** + * Return the value at position i of struct type as an [[Row]] object. + * Throws an exception if the type mismatches. + */ + def getStruct(i: Int): Row = getAs[Row](i) + + /** + * Returns the value at position i. + * Throws an exception if the type mismatches. + */ + def getAs[T](i: Int): T = apply(i).asInstanceOf[T] + + override def toString(): String = s"[${this.mkString(",")}]" + + /** + * Make a copy of the current [[Row]] object. + */ + def copy(): Row + + /** Returns true if there are any NULL values in this row. */ + def anyNull: Boolean = { + val l = length + var i = 0 + while (i < l) { + if (isNullAt(i)) { return true } + i += 1 + } + false + } +} diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/package.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/package.scala index 55d95991c5f11..fbc97b2e75312 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/package.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/package.scala @@ -49,6 +49,10 @@ package org.apache.spark.sql.catalyst */ package object expressions { + type Row = org.apache.spark.sql.Row + + val Row = org.apache.spark.sql.Row + /** * Converts a [[Row]] to another Row given a sequence of expression that define each column of the * new row. If the schema of the input row is specified, then the given expression will be bound diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Row.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/rows.scala similarity index 68% rename from sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Row.scala rename to sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/rows.scala index dcda53bb717a9..c22b8426841da 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Row.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/rows.scala @@ -19,68 +19,6 @@ package org.apache.spark.sql.catalyst.expressions import org.apache.spark.sql.types.NativeType -object Row { - /** - * This method can be used to extract fields from a [[Row]] object in a pattern match. Example: - * {{{ - * import org.apache.spark.sql._ - * - * val pairs = sql("SELECT key, value FROM src").rdd.map { - * case Row(key: Int, value: String) => - * key -> value - * } - * }}} - */ - def unapplySeq(row: Row): Some[Seq[Any]] = Some(row) - - /** - * This method can be used to construct a [[Row]] with the given values. - */ - def apply(values: Any*): Row = new GenericRow(values.toArray) - - /** - * This method can be used to construct a [[Row]] from a [[Seq]] of values. - */ - def fromSeq(values: Seq[Any]): Row = new GenericRow(values.toArray) -} - -/** - * Represents one row of output from a relational operator. Allows both generic access by ordinal, - * which will incur boxing overhead for primitives, as well as native primitive access. - * - * It is invalid to use the native primitive interface to retrieve a value that is null, instead a - * user must check [[isNullAt]] before attempting to retrieve a value that might be null. - */ -trait Row extends Seq[Any] with Serializable { - def apply(i: Int): Any - - def isNullAt(i: Int): Boolean - - def getInt(i: Int): Int - def getLong(i: Int): Long - def getDouble(i: Int): Double - def getFloat(i: Int): Float - def getBoolean(i: Int): Boolean - def getShort(i: Int): Short - def getByte(i: Int): Byte - def getString(i: Int): String - def getAs[T](i: Int): T = apply(i).asInstanceOf[T] - - override def toString() = - s"[${this.mkString(",")}]" - - def copy(): Row - - /** Returns true if there are any NULL values in this row. */ - def anyNull: Boolean = { - var i = 0 - while (i < length) { - if (isNullAt(i)) { return true } - i += 1 - } - false - } -} /** * An extended interface to [[Row]] that allows the values for each column to be updated. Setting @@ -105,22 +43,19 @@ trait MutableRow extends Row { * A row with no data. Calling any methods will result in an error. Can be used as a placeholder. */ object EmptyRow extends Row { - def apply(i: Int): Any = throw new UnsupportedOperationException - - def iterator = Iterator.empty - def length = 0 - def isNullAt(i: Int): Boolean = throw new UnsupportedOperationException - - def getInt(i: Int): Int = throw new UnsupportedOperationException - def getLong(i: Int): Long = throw new UnsupportedOperationException - def getDouble(i: Int): Double = throw new UnsupportedOperationException - def getFloat(i: Int): Float = throw new UnsupportedOperationException - def getBoolean(i: Int): Boolean = throw new UnsupportedOperationException - def getShort(i: Int): Short = throw new UnsupportedOperationException - def getByte(i: Int): Byte = throw new UnsupportedOperationException - def getString(i: Int): String = throw new UnsupportedOperationException + override def apply(i: Int): Any = throw new UnsupportedOperationException + override def iterator = Iterator.empty + override def length = 0 + override def isNullAt(i: Int): Boolean = throw new UnsupportedOperationException + override def getInt(i: Int): Int = throw new UnsupportedOperationException + override def getLong(i: Int): Long = throw new UnsupportedOperationException + override def getDouble(i: Int): Double = throw new UnsupportedOperationException + override def getFloat(i: Int): Float = throw new UnsupportedOperationException + override def getBoolean(i: Int): Boolean = throw new UnsupportedOperationException + override def getShort(i: Int): Short = throw new UnsupportedOperationException + override def getByte(i: Int): Byte = throw new UnsupportedOperationException + override def getString(i: Int): String = throw new UnsupportedOperationException override def getAs[T](i: Int): T = throw new UnsupportedOperationException - def copy() = this } @@ -135,50 +70,50 @@ class GenericRow(protected[sql] val values: Array[Any]) extends Row { def this(size: Int) = this(new Array[Any](size)) - def iterator = values.iterator + override def iterator = values.iterator - def length = values.length + override def length = values.length - def apply(i: Int) = values(i) + override def apply(i: Int) = values(i) - def isNullAt(i: Int) = values(i) == null + override def isNullAt(i: Int) = values(i) == null - def getInt(i: Int): Int = { + override def getInt(i: Int): Int = { if (values(i) == null) sys.error("Failed to check null bit for primitive int value.") values(i).asInstanceOf[Int] } - def getLong(i: Int): Long = { + override def getLong(i: Int): Long = { if (values(i) == null) sys.error("Failed to check null bit for primitive long value.") values(i).asInstanceOf[Long] } - def getDouble(i: Int): Double = { + override def getDouble(i: Int): Double = { if (values(i) == null) sys.error("Failed to check null bit for primitive double value.") values(i).asInstanceOf[Double] } - def getFloat(i: Int): Float = { + override def getFloat(i: Int): Float = { if (values(i) == null) sys.error("Failed to check null bit for primitive float value.") values(i).asInstanceOf[Float] } - def getBoolean(i: Int): Boolean = { + override def getBoolean(i: Int): Boolean = { if (values(i) == null) sys.error("Failed to check null bit for primitive boolean value.") values(i).asInstanceOf[Boolean] } - def getShort(i: Int): Short = { + override def getShort(i: Int): Short = { if (values(i) == null) sys.error("Failed to check null bit for primitive short value.") values(i).asInstanceOf[Short] } - def getByte(i: Int): Byte = { + override def getByte(i: Int): Byte = { if (values(i) == null) sys.error("Failed to check null bit for primitive byte value.") values(i).asInstanceOf[Byte] } - def getString(i: Int): String = { + override def getString(i: Int): String = { if (values(i) == null) sys.error("Failed to check null bit for primitive String value.") values(i).asInstanceOf[String] } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/dataTypes.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/dataTypes.scala index fa0a355ebc9b0..e38ad63f2e2c3 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/dataTypes.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/dataTypes.scala @@ -727,7 +727,7 @@ object StructType { * // StructType(List(StructField(b,LongType,false), StructField(c,BooleanType,false))) * }}} * - * A [[org.apache.spark.sql.catalyst.expressions.Row]] object is used as a value of the StructType. + * A [[org.apache.spark.sql.Row]] object is used as a value of the StructType. * Example: * {{{ * import org.apache.spark.sql._ diff --git a/sql/core/src/main/scala/org/apache/spark/sql/api/java/Row.scala b/sql/core/src/main/scala/org/apache/spark/sql/api/java/Row.scala index 207e2805fffe3..4faa79af2568a 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/api/java/Row.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/api/java/Row.scala @@ -23,7 +23,7 @@ import scala.collection.JavaConversions import scala.math.BigDecimal import org.apache.spark.api.java.JavaUtils.mapAsSerializableJavaMap -import org.apache.spark.sql.catalyst.expressions.{Row => ScalaRow} +import org.apache.spark.sql.{Row => ScalaRow} /** * A result row from a Spark SQL query. diff --git a/sql/core/src/main/scala/org/apache/spark/sql/package.scala b/sql/core/src/main/scala/org/apache/spark/sql/package.scala index b75266d5aa409..6dd39be807037 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/package.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/package.scala @@ -33,89 +33,6 @@ import org.apache.spark.sql.execution.SparkPlan */ package object sql { - /** - * :: DeveloperApi :: - * - * Represents one row of output from a relational operator. - * @group row - */ - @DeveloperApi - type Row = catalyst.expressions.Row - - /** - * :: DeveloperApi :: - * - * A [[Row]] object can be constructed by providing field values. Example: - * {{{ - * import org.apache.spark.sql._ - * - * // Create a Row from values. - * Row(value1, value2, value3, ...) - * // Create a Row from a Seq of values. - * Row.fromSeq(Seq(value1, value2, ...)) - * }}} - * - * A value of a row can be accessed through both generic access by ordinal, - * which will incur boxing overhead for primitives, as well as native primitive access. - * An example of generic access by ordinal: - * {{{ - * import org.apache.spark.sql._ - * - * val row = Row(1, true, "a string", null) - * // row: Row = [1,true,a string,null] - * val firstValue = row(0) - * // firstValue: Any = 1 - * val fourthValue = row(3) - * // fourthValue: Any = null - * }}} - * - * For native primitive access, it is invalid to use the native primitive interface to retrieve - * a value that is null, instead a user must check `isNullAt` before attempting to retrieve a - * value that might be null. - * An example of native primitive access: - * {{{ - * // using the row from the previous example. - * val firstValue = row.getInt(0) - * // firstValue: Int = 1 - * val isNull = row.isNullAt(3) - * // isNull: Boolean = true - * }}} - * - * Interfaces related to native primitive access are: - * - * `isNullAt(i: Int): Boolean` - * - * `getInt(i: Int): Int` - * - * `getLong(i: Int): Long` - * - * `getDouble(i: Int): Double` - * - * `getFloat(i: Int): Float` - * - * `getBoolean(i: Int): Boolean` - * - * `getShort(i: Int): Short` - * - * `getByte(i: Int): Byte` - * - * `getString(i: Int): String` - * - * Fields in a [[Row]] object can be extracted in a pattern match. Example: - * {{{ - * import org.apache.spark.sql._ - * - * val pairs = sql("SELECT key, value FROM src").rdd.map { - * case Row(key: Int, value: String) => - * key -> value - * } - * }}} - * - * @group row - */ - @DeveloperApi - val Row = catalyst.expressions.Row - /** * Converts a logical plan into zero or more SparkPlans. */ From a3f7421b42f45e39f3e53679188e4eae2ed1f208 Mon Sep 17 00:00:00 2001 From: Daoyuan Wang Date: Wed, 14 Jan 2015 09:36:59 -0800 Subject: [PATCH 247/320] [SPARK-5248] [SQL] move sql.types.decimal.Decimal to sql.types.Decimal rxin follow up of #3732 Author: Daoyuan Wang Closes #4041 from adrian-wang/decimal and squashes the following commits: aa3d738 [Daoyuan Wang] fix auto refactor 7777a58 [Daoyuan Wang] move sql.types.decimal.Decimal to sql.types.Decimal --- .../org/apache/spark/sql/catalyst/ScalaReflection.scala | 1 - .../scala/org/apache/spark/sql/catalyst/dsl/package.scala | 1 - .../org/apache/spark/sql/catalyst/expressions/Cast.scala | 1 - .../sql/catalyst/expressions/codegen/CodeGenerator.scala | 7 +++---- .../spark/sql/catalyst/expressions/decimalFunctions.scala | 3 +-- .../apache/spark/sql/catalyst/expressions/literals.scala | 1 - .../apache/spark/sql/catalyst/optimizer/Optimizer.scala | 1 - .../org/apache/spark/sql/types/DataTypeConversions.scala | 2 +- .../org/apache/spark/sql/types/{decimal => }/Decimal.scala | 4 ++-- .../main/scala/org/apache/spark/sql/types/dataTypes.scala | 1 - .../catalyst/expressions/ExpressionEvaluationSuite.scala | 1 - .../org/apache/spark/sql/types/decimal/DecimalSuite.scala | 1 + .../apache/spark/sql/execution/SparkSqlSerializer.scala | 3 ++- .../src/main/scala/org/apache/spark/sql/json/JsonRDD.scala | 1 - .../org/apache/spark/sql/parquet/ParquetConverter.scala | 1 - .../org/apache/spark/sql/parquet/ParquetTableSupport.scala | 1 - .../test/scala/org/apache/spark/sql/json/JsonSuite.scala | 1 - .../scala/org/apache/spark/sql/hive/HiveInspectors.scala | 3 +-- .../src/main/scala/org/apache/spark/sql/hive/HiveQl.scala | 1 - .../org/apache/spark/sql/hive/HiveInspectorSuite.scala | 1 - .../src/main/scala/org/apache/spark/sql/hive/Shim12.scala | 3 +-- .../src/main/scala/org/apache/spark/sql/hive/Shim13.scala | 3 +-- 22 files changed, 13 insertions(+), 29 deletions(-) rename sql/catalyst/src/main/scala/org/apache/spark/sql/types/{decimal => }/Decimal.scala (98%) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala index d169da691d797..697bacfedc624 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala @@ -23,7 +23,6 @@ import org.apache.spark.util.Utils import org.apache.spark.sql.catalyst.expressions.{GenericRow, Attribute, AttributeReference, Row} import org.apache.spark.sql.catalyst.plans.logical.LocalRelation import org.apache.spark.sql.types._ -import org.apache.spark.sql.types.decimal.Decimal /** diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala index bdac7504ed027..8bc36a238dbbb 100755 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala @@ -27,7 +27,6 @@ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.plans.{Inner, JoinType} import org.apache.spark.sql.types._ -import org.apache.spark.sql.types.decimal.Decimal /** * A collection of implicit conversions that create a DSL for constructing catalyst data structures. diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala index 00961f09916b3..1a2133bbbcec7 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala @@ -23,7 +23,6 @@ import java.text.{DateFormat, SimpleDateFormat} import org.apache.spark.Logging import org.apache.spark.sql.catalyst.errors.TreeNodeException import org.apache.spark.sql.types._ -import org.apache.spark.sql.types.decimal.Decimal /** Cast the child expression to the target data type. */ case class Cast(child: Expression, dataType: DataType) extends UnaryExpression with Logging { diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala index a5d6423391295..4cae5c4718683 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala @@ -18,7 +18,6 @@ package org.apache.spark.sql.catalyst.expressions.codegen import com.google.common.cache.{CacheLoader, CacheBuilder} -import org.apache.spark.sql.types.decimal.Decimal import scala.language.existentials @@ -541,11 +540,11 @@ abstract class CodeGenerator[InType <: AnyRef, OutType <: AnyRef] extends Loggin childEval.code ++ q""" var $nullTerm = ${childEval.nullTerm} - var $primitiveTerm: org.apache.spark.sql.types.decimal.Decimal = + var $primitiveTerm: org.apache.spark.sql.types.Decimal = ${defaultPrimitive(DecimalType())} if (!$nullTerm) { - $primitiveTerm = new org.apache.spark.sql.types.decimal.Decimal() + $primitiveTerm = new org.apache.spark.sql.types.Decimal() $primitiveTerm = $primitiveTerm.setOrNull(${childEval.primitiveTerm}, $precision, $scale) $nullTerm = $primitiveTerm == null } @@ -627,7 +626,7 @@ abstract class CodeGenerator[InType <: AnyRef, OutType <: AnyRef] extends Loggin case LongType => ru.Literal(Constant(1L)) case ByteType => ru.Literal(Constant(-1.toByte)) case DoubleType => ru.Literal(Constant(-1.toDouble)) - case DecimalType() => q"org.apache.spark.sql.types.decimal.Decimal(-1)" + case DecimalType() => q"org.apache.spark.sql.types.Decimal(-1)" case IntegerType => ru.Literal(Constant(-1)) case _ => ru.Literal(Constant(null)) } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/decimalFunctions.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/decimalFunctions.scala index e54cfa144a173..83d8c1d42bca4 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/decimalFunctions.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/decimalFunctions.scala @@ -17,8 +17,7 @@ package org.apache.spark.sql.catalyst.expressions -import org.apache.spark.sql.types.decimal.Decimal -import org.apache.spark.sql.types.{DecimalType, LongType, DoubleType, DataType} +import org.apache.spark.sql.types._ /** Return the unscaled Long value of a Decimal, assuming it fits in a Long */ case class UnscaledValue(child: Expression) extends UnaryExpression { diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala index 8ee4bbd8caa62..c94a947fb275c 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/literals.scala @@ -20,7 +20,6 @@ package org.apache.spark.sql.catalyst.expressions import java.sql.{Date, Timestamp} import org.apache.spark.sql.types._ -import org.apache.spark.sql.types.decimal.Decimal object Literal { def apply(v: Any): Literal = v match { diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala index 17b4f9c23a978..d4a4c35691bcf 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala @@ -27,7 +27,6 @@ import org.apache.spark.sql.catalyst.plans.LeftSemi import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.rules._ import org.apache.spark.sql.types._ -import org.apache.spark.sql.types.decimal.Decimal abstract class Optimizer extends RuleExecutor[LogicalPlan] diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeConversions.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeConversions.scala index 2a8914cde248c..08bb933a2b33e 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeConversions.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/DataTypeConversions.scala @@ -20,7 +20,7 @@ package org.apache.spark.sql.types import java.text.SimpleDateFormat import org.apache.spark.sql.catalyst.ScalaReflection -import org.apache.spark.sql.types.decimal.Decimal +import org.apache.spark.sql.types.Decimal protected[sql] object DataTypeConversions { diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/decimal/Decimal.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/Decimal.scala similarity index 98% rename from sql/catalyst/src/main/scala/org/apache/spark/sql/types/decimal/Decimal.scala rename to sql/catalyst/src/main/scala/org/apache/spark/sql/types/Decimal.scala index c7864d1ae9e74..3744d77c0736e 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/decimal/Decimal.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/Decimal.scala @@ -15,7 +15,7 @@ * limitations under the License. */ -package org.apache.spark.sql.types.decimal +package org.apache.spark.sql.types import org.apache.spark.annotation.DeveloperApi @@ -28,7 +28,7 @@ import org.apache.spark.annotation.DeveloperApi * - Otherwise, the decimal value is longVal / (10 ** _scale) */ final class Decimal extends Ordered[Decimal] with Serializable { - import Decimal.{MAX_LONG_DIGITS, POW_10, ROUNDING_MODE, BIG_DEC_ZERO} + import org.apache.spark.sql.types.Decimal.{BIG_DEC_ZERO, MAX_LONG_DIGITS, POW_10, ROUNDING_MODE} private var decimalVal: BigDecimal = null private var longVal: Long = 0L diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/dataTypes.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/dataTypes.scala index e38ad63f2e2c3..e1cbe6650aaaf 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/dataTypes.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/dataTypes.scala @@ -32,7 +32,6 @@ import org.json4s.jackson.JsonMethods._ import org.apache.spark.annotation.DeveloperApi import org.apache.spark.sql.catalyst.ScalaReflectionLock import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeReference, Expression} -import org.apache.spark.sql.types.decimal._ import org.apache.spark.util.Utils diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala index 8552448b8d108..37e64adeea853 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala @@ -27,7 +27,6 @@ import org.scalatest.Matchers._ import org.apache.spark.sql.catalyst.dsl.expressions._ import org.apache.spark.sql.types._ -import org.apache.spark.sql.types.decimal.Decimal class ExpressionEvaluationSuite extends FunSuite { diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/types/decimal/DecimalSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/types/decimal/DecimalSuite.scala index 813377df00132..de6a2cd448c47 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/types/decimal/DecimalSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/types/decimal/DecimalSuite.scala @@ -17,6 +17,7 @@ package org.apache.spark.sql.types.decimal +import org.apache.spark.sql.types.Decimal import org.scalatest.{PrivateMethodTester, FunSuite} import scala.language.postfixOps diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer.scala index 131146012ecac..7a0249137a207 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer.scala @@ -19,6 +19,8 @@ package org.apache.spark.sql.execution import java.nio.ByteBuffer +import org.apache.spark.sql.types.Decimal + import scala.reflect.ClassTag import com.clearspring.analytics.stream.cardinality.HyperLogLog @@ -29,7 +31,6 @@ import com.twitter.chill.{AllScalaRegistrar, ResourcePool} import org.apache.spark.{SparkEnv, SparkConf} import org.apache.spark.serializer.{SerializerInstance, KryoSerializer} import org.apache.spark.sql.catalyst.expressions.GenericRow -import org.apache.spark.sql.types.decimal.Decimal import org.apache.spark.util.collection.OpenHashSet import org.apache.spark.util.MutablePair import org.apache.spark.util.Utils diff --git a/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala index c92ec543e2936..453b560ff8716 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala @@ -33,7 +33,6 @@ import org.apache.spark.sql.catalyst.analysis.HiveTypeCoercion import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.ScalaReflection import org.apache.spark.sql.types._ -import org.apache.spark.sql.types.decimal.Decimal import org.apache.spark.Logging private[sql] object JsonRDD extends Logging { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetConverter.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetConverter.scala index 7f437c40777f2..b4aed04199129 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetConverter.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetConverter.scala @@ -25,7 +25,6 @@ import parquet.schema.MessageType import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.parquet.CatalystConverter.FieldType import org.apache.spark.sql.types._ -import org.apache.spark.sql.types.decimal.Decimal /** * Collection of converters of Parquet types (group and primitive types) that diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableSupport.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableSupport.scala index af7248fdf451d..fd63ad8144064 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableSupport.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableSupport.scala @@ -30,7 +30,6 @@ import parquet.schema.MessageType import org.apache.spark.Logging import org.apache.spark.sql.catalyst.expressions.{Attribute, Row} import org.apache.spark.sql.types._ -import org.apache.spark.sql.types.decimal.Decimal /** * A `parquet.io.api.RecordMaterializer` for Rows. diff --git a/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala index 01c1ce2a61023..1dd85a3bb43a5 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/json/JsonSuite.scala @@ -25,7 +25,6 @@ import org.apache.spark.sql.json.JsonRDD.{compatibleType, enforceCorrectType} import org.apache.spark.sql.test.TestSQLContext import org.apache.spark.sql.test.TestSQLContext._ import org.apache.spark.sql.types._ -import org.apache.spark.sql.types.decimal.Decimal import org.apache.spark.sql.{QueryTest, Row, SQLConf} class JsonSuite extends QueryTest { diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala index 245b847cf4cd4..5140d2064c5fb 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala @@ -26,7 +26,6 @@ import org.apache.hadoop.{io => hadoopIo} import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.types import org.apache.spark.sql.types._ -import org.apache.spark.sql.types.decimal.Decimal /* Implicit conversions */ import scala.collection.JavaConversions._ @@ -43,7 +42,7 @@ import scala.collection.JavaConversions._ * long / scala.Long * short / scala.Short * byte / scala.Byte - * org.apache.spark.sql.types.decimal.Decimal + * org.apache.spark.sql.types.Decimal * Array[Byte] * java.sql.Date * java.sql.Timestamp diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala index b13ef7276bf3c..5e29e57d93585 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala @@ -35,7 +35,6 @@ import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.execution.ExplainCommand import org.apache.spark.sql.hive.execution.{HiveNativeCommand, DropTable, AnalyzeTable} import org.apache.spark.sql.types._ -import org.apache.spark.sql.types.decimal.Decimal /* Implicit conversions */ import scala.collection.JavaConversions._ diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala index dc23d9a101d17..4864607252034 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveInspectorSuite.scala @@ -31,7 +31,6 @@ import org.scalatest.FunSuite import org.apache.spark.sql.catalyst.expressions.{Literal, Row} import org.apache.spark.sql.types._ -import org.apache.spark.sql.types.decimal.Decimal class HiveInspectorSuite extends FunSuite with HiveInspectors { test("Test wrap SettableStructObjectInspector") { diff --git a/sql/hive/v0.12.0/src/main/scala/org/apache/spark/sql/hive/Shim12.scala b/sql/hive/v0.12.0/src/main/scala/org/apache/spark/sql/hive/Shim12.scala index a5587460fd696..58417a15bbedc 100644 --- a/sql/hive/v0.12.0/src/main/scala/org/apache/spark/sql/hive/Shim12.scala +++ b/sql/hive/v0.12.0/src/main/scala/org/apache/spark/sql/hive/Shim12.scala @@ -41,8 +41,7 @@ import org.apache.hadoop.hive.serde2.typeinfo.{TypeInfo, TypeInfoFactory} import org.apache.hadoop.io.NullWritable import org.apache.hadoop.mapred.InputFormat -import org.apache.spark.sql.types.DecimalType -import org.apache.spark.sql.types.decimal.Decimal +import org.apache.spark.sql.types.{Decimal, DecimalType} case class HiveFunctionWrapper(functionClassName: String) extends java.io.Serializable { // for Serialization diff --git a/sql/hive/v0.13.1/src/main/scala/org/apache/spark/sql/hive/Shim13.scala b/sql/hive/v0.13.1/src/main/scala/org/apache/spark/sql/hive/Shim13.scala index a7121360dd350..1f768ca971249 100644 --- a/sql/hive/v0.13.1/src/main/scala/org/apache/spark/sql/hive/Shim13.scala +++ b/sql/hive/v0.13.1/src/main/scala/org/apache/spark/sql/hive/Shim13.scala @@ -42,8 +42,7 @@ import org.apache.hadoop.hive.serde2.{io => hiveIo} import org.apache.hadoop.{io => hadoopIo} import org.apache.spark.Logging -import org.apache.spark.sql.types.DecimalType -import org.apache.spark.sql.types.decimal.Decimal +import org.apache.spark.sql.types.{Decimal, DecimalType} /** From 81f72a0df2250debe8a6a0773d809d8c42eeabb9 Mon Sep 17 00:00:00 2001 From: Yin Huai Date: Wed, 14 Jan 2015 09:47:30 -0800 Subject: [PATCH 248/320] [SPARK-5211][SQL]Restore HiveMetastoreTypes.toDataType jira: https://issues.apache.org/jira/browse/SPARK-5211 Author: Yin Huai Closes #4026 from yhuai/SPARK-5211 and squashes the following commits: 15ee32b [Yin Huai] Remove extra line. c6c1651 [Yin Huai] Get back HiveMetastoreTypes.toDataType. --- .../org/apache/spark/sql/hive/HiveMetastoreCatalog.scala | 8 +++++++- .../apache/spark/sql/hive/HiveMetastoreCatalogSuite.scala | 5 +---- 2 files changed, 8 insertions(+), 5 deletions(-) diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala index d40f9936fd3b5..1a49f09bd9988 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala @@ -39,7 +39,7 @@ import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.catalyst.plans.logical import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.rules._ -import org.apache.spark.sql.sources.{LogicalRelation, ResolvedDataSource} +import org.apache.spark.sql.sources.{DDLParser, LogicalRelation, ResolvedDataSource} import org.apache.spark.sql.types._ import org.apache.spark.util.Utils @@ -558,6 +558,12 @@ private[hive] case class MetastoreRelation } object HiveMetastoreTypes { + protected val ddlParser = new DDLParser + + def toDataType(metastoreType: String): DataType = synchronized { + ddlParser.parseType(metastoreType) + } + def toMetastoreType(dt: DataType): String = dt match { case ArrayType(elementType, _) => s"array<${toMetastoreType(elementType)}>" case StructType(fields) => diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveMetastoreCatalogSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveMetastoreCatalogSuite.scala index fa6905f31f81e..aad48ada52642 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveMetastoreCatalogSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveMetastoreCatalogSuite.scala @@ -19,7 +19,6 @@ package org.apache.spark.sql.hive import org.scalatest.FunSuite -import org.apache.spark.sql.sources.DDLParser import org.apache.spark.sql.test.ExamplePointUDT import org.apache.spark.sql.types.StructType @@ -28,9 +27,7 @@ class HiveMetastoreCatalogSuite extends FunSuite { test("struct field should accept underscore in sub-column name") { val metastr = "struct" - val ddlParser = new DDLParser - - val datatype = ddlParser.parseType(metastr) + val datatype = HiveMetastoreTypes.toDataType(metastr) assert(datatype.isInstanceOf[StructType]) } From 38bdc992a1a0485ac630af500da54f0a77e133bf Mon Sep 17 00:00:00 2001 From: Daoyuan Wang Date: Wed, 14 Jan 2015 09:50:01 -0800 Subject: [PATCH 249/320] [SQL] some comments fix for GROUPING SETS Author: Daoyuan Wang Closes #4000 from adrian-wang/comment and squashes the following commits: 9c24fc4 [Daoyuan Wang] some comments --- .../spark/sql/catalyst/analysis/Analyzer.scala | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala index bd00ff22ba80a..7f4cc234dc9cd 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala @@ -126,10 +126,10 @@ class Analyzer(catalog: Catalog, } /* - * GROUP BY a, b, c, WITH ROLLUP + * GROUP BY a, b, c WITH ROLLUP * is equivalent to - * GROUP BY a, b, c GROUPING SETS ( (a, b, c), (a, b), (a), ( )). - * Group Count: N + 1 (N is the number of group expression) + * GROUP BY a, b, c GROUPING SETS ( (a, b, c), (a, b), (a), ( ) ). + * Group Count: N + 1 (N is the number of group expressions) * * We need to get all of its subsets for the rule described above, the subset is * represented as the bit masks. @@ -139,12 +139,12 @@ class Analyzer(catalog: Catalog, } /* - * GROUP BY a, b, c, WITH CUBE + * GROUP BY a, b, c WITH CUBE * is equivalent to * GROUP BY a, b, c GROUPING SETS ( (a, b, c), (a, b), (b, c), (a, c), (a), (b), (c), ( ) ). - * Group Count: 2^N (N is the number of group expression) + * Group Count: 2 ^ N (N is the number of group expressions) * - * We need to get all of its sub sets for a given GROUPBY expressions, the subset is + * We need to get all of its subsets for a given GROUPBY expression, the subsets are * represented as the bit masks. */ def bitmasks(c: Cube): Seq[Int] = { From 5840f5464bad8431810d459c97d6e4635eea175c Mon Sep 17 00:00:00 2001 From: MechCoder Date: Wed, 14 Jan 2015 11:03:11 -0800 Subject: [PATCH 250/320] [SPARK-2909] [MLlib] [PySpark] SparseVector in pyspark now supports indexing Slightly different than the scala code which converts the sparsevector into a densevector and then checks the index. I also hope I've added tests in the right place. Author: MechCoder Closes #4025 from MechCoder/spark-2909 and squashes the following commits: 07d0f26 [MechCoder] STY: Rename item to index f02148b [MechCoder] [SPARK-2909] [Mlib] SparseVector in pyspark now supports indexing --- python/pyspark/mllib/linalg.py | 17 +++++++++++++++++ python/pyspark/mllib/tests.py | 12 ++++++++++++ 2 files changed, 29 insertions(+) diff --git a/python/pyspark/mllib/linalg.py b/python/pyspark/mllib/linalg.py index 4f8491f43e457..7f21190ed8c25 100644 --- a/python/pyspark/mllib/linalg.py +++ b/python/pyspark/mllib/linalg.py @@ -510,6 +510,23 @@ def __eq__(self, other): and np.array_equal(other.indices, self.indices) and np.array_equal(other.values, self.values)) + def __getitem__(self, index): + inds = self.indices + vals = self.values + if not isinstance(index, int): + raise ValueError( + "Indices must be of type integer, got type %s" % type(index)) + if index < 0: + index += self.size + if index >= self.size or index < 0: + raise ValueError("Index %d out of bounds." % index) + + insert_index = np.searchsorted(inds, index) + row_ind = inds[insert_index] + if row_ind == index: + return vals[insert_index] + return 0. + def __ne__(self, other): return not self.__eq__(other) diff --git a/python/pyspark/mllib/tests.py b/python/pyspark/mllib/tests.py index 1f48bc1219dba..140c22b5fd4e8 100644 --- a/python/pyspark/mllib/tests.py +++ b/python/pyspark/mllib/tests.py @@ -120,6 +120,18 @@ def test_conversion(self): dv = DenseVector(v) self.assertTrue(dv.array.dtype == 'float64') + def test_sparse_vector_indexing(self): + sv = SparseVector(4, {1: 1, 3: 2}) + self.assertEquals(sv[0], 0.) + self.assertEquals(sv[3], 2.) + self.assertEquals(sv[1], 1.) + self.assertEquals(sv[2], 0.) + self.assertEquals(sv[-1], 2) + self.assertEquals(sv[-2], 0) + self.assertEquals(sv[-4], 0) + for ind in [4, -5, 7.8]: + self.assertRaises(ValueError, sv.__getitem__, ind) + class ListTests(PySparkTestCase): From 9d4449c4b3d0f5e60e71fef3a9b2e1c58a80b9e8 Mon Sep 17 00:00:00 2001 From: Kousuke Saruta Date: Wed, 14 Jan 2015 11:10:29 -0800 Subject: [PATCH 251/320] [SPARK-5228][WebUI] Hide tables for "Active Jobs/Completed Jobs/Failed Jobs" when they are empty In current WebUI, tables for Active Stages, Completed Stages, Skipped Stages and Failed Stages are hidden when they are empty while tables for Active Jobs, Completed Jobs and Failed Jobs are not hidden though they are empty. This is before my patch is applied. ![2015-01-13 14 13 03](https://cloud.githubusercontent.com/assets/4736016/5730793/2b73d6f4-9b32-11e4-9a24-1784d758c644.png) And this is after my patch is applied. ![2015-01-13 14 38 13](https://cloud.githubusercontent.com/assets/4736016/5730797/359ea2da-9b32-11e4-97b0-544739ddbf4c.png) Author: Kousuke Saruta Closes #4028 from sarutak/SPARK-5228 and squashes the following commits: b1e6e8b [Kousuke Saruta] Fixed a small typo daab563 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-5228 9493a1d [Kousuke Saruta] Modified AllJobPage.scala so that hide Active Jobs/Completed Jobs/Failed Jobs when they are empty --- .../apache/spark/ui/jobs/AllJobsPage.scala | 62 +++++++++++++------ 1 file changed, 43 insertions(+), 19 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/AllJobsPage.scala b/core/src/main/scala/org/apache/spark/ui/jobs/AllJobsPage.scala index ea2d187a0e8e4..1d1c701878447 100644 --- a/core/src/main/scala/org/apache/spark/ui/jobs/AllJobsPage.scala +++ b/core/src/main/scala/org/apache/spark/ui/jobs/AllJobsPage.scala @@ -47,7 +47,7 @@ private[ui] class AllJobsPage(parent: JobsTab) extends WebUIPage("") { val lastStageData = lastStageInfo.flatMap { s => listener.stageIdToData.get((s.stageId, s.attemptId)) } - val isComplete = job.status == JobExecutionStatus.SUCCEEDED + val lastStageName = lastStageInfo.map(_.name).getOrElse("(Unknown Stage Name)") val lastStageDescription = lastStageData.flatMap(_.description).getOrElse("") val duration: Option[Long] = { @@ -107,6 +107,10 @@ private[ui] class AllJobsPage(parent: JobsTab) extends WebUIPage("") { val failedJobsTable = jobsTable(failedJobs.sortBy(_.endTime.getOrElse(-1L)).reverse) + val shouldShowActiveJobs = activeJobs.nonEmpty + val shouldShowCompletedJobs = completedJobs.nonEmpty + val shouldShowFailedJobs = failedJobs.nonEmpty + val summary: NodeSeq =
          @@ -121,27 +125,47 @@ private[ui] class AllJobsPage(parent: JobsTab) extends WebUIPage("") { Scheduling Mode: {listener.schedulingMode.map(_.toString).getOrElse("Unknown")} -
        • - Active Jobs: - {activeJobs.size} -
          • -
        • - Completed Jobs: - {completedJobs.size} -
          • -
        • - Failed Jobs: - {failedJobs.size} -
          • + { + if (shouldShowActiveJobs) { +
        • + Active Jobs: + {activeJobs.size} +
          • + } + } + { + if (shouldShowCompletedJobs) { +
        • + Completed Jobs: + {completedJobs.size} +
          • + } + } + { + if (shouldShowFailedJobs) { +
        • + Failed Jobs: + {failedJobs.size} +
          • + } + }
        - val content = summary ++ -

        Active Jobs ({activeJobs.size})

        ++ activeJobsTable ++ -

        Completed Jobs ({completedJobs.size})

        ++ completedJobsTable ++ -

        Failed Jobs ({failedJobs.size})

        ++ failedJobsTable - - val helpText = """A job is triggered by a action, like "count()" or "saveAsTextFile()".""" + + var content = summary + if (shouldShowActiveJobs) { + content ++=

        Active Jobs ({activeJobs.size})

        ++ + activeJobsTable + } + if (shouldShowCompletedJobs) { + content ++=

        Completed Jobs ({completedJobs.size})

        ++ + completedJobsTable + } + if (shouldShowFailedJobs) { + content ++=

        Failed Jobs ({failedJobs.size})

        ++ + failedJobsTable + } + val helpText = """A job is triggered by an action, like "count()" or "saveAsTextFile()".""" + " Click on a job's title to see information about the stages of tasks associated with" + " the job." From 259936be710f367e1d1e019ee7b93fb68dfc33d0 Mon Sep 17 00:00:00 2001 From: Josh Rosen Date: Wed, 14 Jan 2015 11:45:40 -0800 Subject: [PATCH 252/320] [SPARK-4014] Add TaskContext.attemptNumber and deprecate TaskContext.attemptId `TaskContext.attemptId` is misleadingly-named, since it currently returns a taskId, which uniquely identifies a particular task attempt within a particular SparkContext, instead of an attempt number, which conveys how many times a task has been attempted. This patch deprecates `TaskContext.attemptId` and add `TaskContext.taskId` and `TaskContext.attemptNumber` fields. Prior to this change, it was impossible to determine whether a task was being re-attempted (or was a speculative copy), which made it difficult to write unit tests for tasks that fail on early attempts or speculative tasks that complete faster than original tasks. Earlier versions of the TaskContext docs suggest that `attemptId` behaves like `attemptNumber`, so there's an argument to be made in favor of changing this method's implementation. Since we've decided against making that change in maintenance branches, I think it's simpler to add better-named methods and retain the old behavior for `attemptId`; if `attemptId` behaved differently in different branches, then this would cause confusing build-breaks when backporting regression tests that rely on the new `attemptId` behavior. Most of this patch is fairly straightforward, but there is a bit of trickiness related to Mesos tasks: since there's no field in MesosTaskInfo to encode the attemptId, I packed it into the `data` field alongside the task binary. Author: Josh Rosen Closes #3849 from JoshRosen/SPARK-4014 and squashes the following commits: 89d03e0 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4014 5cfff05 [Josh Rosen] Introduce wrapper for serializing Mesos task launch data. 38574d4 [Josh Rosen] attemptId -> taskAttemptId in PairRDDFunctions a180b88 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4014 1d43aa6 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4014 eee6a45 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4014 0b10526 [Josh Rosen] Use putInt instead of putLong (silly mistake) 8c387ce [Josh Rosen] Use local with maxRetries instead of local-cluster. cbe4d76 [Josh Rosen] Preserve attemptId behavior and deprecate it: b2dffa3 [Josh Rosen] Address some of Reynold's minor comments 9d8d4d1 [Josh Rosen] Doc typo 1e7a933 [Josh Rosen] [SPARK-4014] Change TaskContext.attemptId to return attempt number instead of task ID. fd515a5 [Josh Rosen] Add failing test for SPARK-4014 --- .../java/org/apache/spark/TaskContext.java | 24 +++++++++- .../org/apache/spark/TaskContextImpl.scala | 9 +++- .../CoarseGrainedExecutorBackend.scala | 3 +- .../org/apache/spark/executor/Executor.scala | 17 +++++-- .../spark/executor/MesosExecutorBackend.scala | 5 +- .../org/apache/spark/rdd/CheckpointRDD.scala | 5 +- .../org/apache/spark/rdd/HadoopRDD.scala | 2 +- .../apache/spark/rdd/PairRDDFunctions.scala | 9 ++-- .../apache/spark/scheduler/DAGScheduler.scala | 4 +- .../org/apache/spark/scheduler/Task.scala | 12 ++++- .../spark/scheduler/TaskDescription.scala | 1 + .../spark/scheduler/TaskSetManager.scala | 3 +- .../cluster/mesos/MesosSchedulerBackend.scala | 4 +- .../cluster/mesos/MesosTaskLaunchData.scala | 46 +++++++++++++++++++ .../spark/scheduler/local/LocalBackend.scala | 3 +- .../java/org/apache/spark/JavaAPISuite.java | 2 +- .../org/apache/spark/CacheManagerSuite.scala | 8 ++-- .../org/apache/spark/rdd/PipedRDDSuite.scala | 2 +- .../spark/scheduler/TaskContextSuite.scala | 31 ++++++++++++- .../mesos/MesosSchedulerBackendSuite.scala | 2 +- .../ShuffleBlockFetcherIteratorSuite.scala | 6 +-- .../org/apache/spark/ui/UISeleniumSuite.scala | 2 +- project/MimaExcludes.scala | 6 +++ .../sql/parquet/ParquetTableOperations.scala | 5 +- .../hive/execution/InsertIntoHiveTable.scala | 5 +- 25 files changed, 168 insertions(+), 48 deletions(-) create mode 100644 core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosTaskLaunchData.scala diff --git a/core/src/main/java/org/apache/spark/TaskContext.java b/core/src/main/java/org/apache/spark/TaskContext.java index 0d6973203eba1..095f9fb94fdf0 100644 --- a/core/src/main/java/org/apache/spark/TaskContext.java +++ b/core/src/main/java/org/apache/spark/TaskContext.java @@ -62,7 +62,7 @@ static void unset() { */ public abstract boolean isInterrupted(); - /** @deprecated: use isRunningLocally() */ + /** @deprecated use {@link #isRunningLocally()} */ @Deprecated public abstract boolean runningLocally(); @@ -87,19 +87,39 @@ static void unset() { * is for HadoopRDD to register a callback to close the input stream. * Will be called in any situation - success, failure, or cancellation. * - * @deprecated: use addTaskCompletionListener + * @deprecated use {@link #addTaskCompletionListener(scala.Function1)} * * @param f Callback function. */ @Deprecated public abstract void addOnCompleteCallback(final Function0 f); + /** + * The ID of the stage that this task belong to. + */ public abstract int stageId(); + /** + * The ID of the RDD partition that is computed by this task. + */ public abstract int partitionId(); + /** + * How many times this task has been attempted. The first task attempt will be assigned + * attemptNumber = 0, and subsequent attempts will have increasing attempt numbers. + */ + public abstract int attemptNumber(); + + /** @deprecated use {@link #taskAttemptId()}; it was renamed to avoid ambiguity. */ + @Deprecated public abstract long attemptId(); + /** + * An ID that is unique to this task attempt (within the same SparkContext, no two task attempts + * will share the same attempt ID). This is roughly equivalent to Hadoop's TaskAttemptID. + */ + public abstract long taskAttemptId(); + /** ::DeveloperApi:: */ @DeveloperApi public abstract TaskMetrics taskMetrics(); diff --git a/core/src/main/scala/org/apache/spark/TaskContextImpl.scala b/core/src/main/scala/org/apache/spark/TaskContextImpl.scala index afd2b85d33a77..9bb0c61e441f8 100644 --- a/core/src/main/scala/org/apache/spark/TaskContextImpl.scala +++ b/core/src/main/scala/org/apache/spark/TaskContextImpl.scala @@ -22,14 +22,19 @@ import org.apache.spark.util.{TaskCompletionListener, TaskCompletionListenerExce import scala.collection.mutable.ArrayBuffer -private[spark] class TaskContextImpl(val stageId: Int, +private[spark] class TaskContextImpl( + val stageId: Int, val partitionId: Int, - val attemptId: Long, + override val taskAttemptId: Long, + override val attemptNumber: Int, val runningLocally: Boolean = false, val taskMetrics: TaskMetrics = TaskMetrics.empty) extends TaskContext with Logging { + // For backwards-compatibility; this method is now deprecated as of 1.3.0. + override def attemptId: Long = taskAttemptId + // List of callback functions to execute when the task completes. @transient private val onCompleteCallbacks = new ArrayBuffer[TaskCompletionListener] diff --git a/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala b/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala index c794a7bc3599e..9a4adfbbb3d71 100644 --- a/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala +++ b/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala @@ -71,7 +71,8 @@ private[spark] class CoarseGrainedExecutorBackend( val ser = env.closureSerializer.newInstance() val taskDesc = ser.deserialize[TaskDescription](data.value) logInfo("Got assigned task " + taskDesc.taskId) - executor.launchTask(this, taskDesc.taskId, taskDesc.name, taskDesc.serializedTask) + executor.launchTask(this, taskId = taskDesc.taskId, attemptNumber = taskDesc.attemptNumber, + taskDesc.name, taskDesc.serializedTask) } case KillTask(taskId, _, interruptThread) => diff --git a/core/src/main/scala/org/apache/spark/executor/Executor.scala b/core/src/main/scala/org/apache/spark/executor/Executor.scala index 0f99cd9f3b08a..b75c77b5b4457 100644 --- a/core/src/main/scala/org/apache/spark/executor/Executor.scala +++ b/core/src/main/scala/org/apache/spark/executor/Executor.scala @@ -108,8 +108,13 @@ private[spark] class Executor( startDriverHeartbeater() def launchTask( - context: ExecutorBackend, taskId: Long, taskName: String, serializedTask: ByteBuffer) { - val tr = new TaskRunner(context, taskId, taskName, serializedTask) + context: ExecutorBackend, + taskId: Long, + attemptNumber: Int, + taskName: String, + serializedTask: ByteBuffer) { + val tr = new TaskRunner(context, taskId = taskId, attemptNumber = attemptNumber, taskName, + serializedTask) runningTasks.put(taskId, tr) threadPool.execute(tr) } @@ -134,7 +139,11 @@ private[spark] class Executor( private def gcTime = ManagementFactory.getGarbageCollectorMXBeans.map(_.getCollectionTime).sum class TaskRunner( - execBackend: ExecutorBackend, val taskId: Long, taskName: String, serializedTask: ByteBuffer) + execBackend: ExecutorBackend, + val taskId: Long, + val attemptNumber: Int, + taskName: String, + serializedTask: ByteBuffer) extends Runnable { @volatile private var killed = false @@ -180,7 +189,7 @@ private[spark] class Executor( // Run the actual task and measure its runtime. taskStart = System.currentTimeMillis() - val value = task.run(taskId.toInt) + val value = task.run(taskAttemptId = taskId, attemptNumber = attemptNumber) val taskFinish = System.currentTimeMillis() // If the task has been killed, let's fail it. diff --git a/core/src/main/scala/org/apache/spark/executor/MesosExecutorBackend.scala b/core/src/main/scala/org/apache/spark/executor/MesosExecutorBackend.scala index 2e23ae0a4f831..cfd672e1d8a97 100644 --- a/core/src/main/scala/org/apache/spark/executor/MesosExecutorBackend.scala +++ b/core/src/main/scala/org/apache/spark/executor/MesosExecutorBackend.scala @@ -28,6 +28,7 @@ import org.apache.mesos.Protos.{TaskStatus => MesosTaskStatus, _} import org.apache.spark.{Logging, TaskState, SparkConf, SparkEnv} import org.apache.spark.TaskState.TaskState import org.apache.spark.deploy.SparkHadoopUtil +import org.apache.spark.scheduler.cluster.mesos.{MesosTaskLaunchData} import org.apache.spark.util.{SignalLogger, Utils} private[spark] class MesosExecutorBackend @@ -77,11 +78,13 @@ private[spark] class MesosExecutorBackend override def launchTask(d: ExecutorDriver, taskInfo: TaskInfo) { val taskId = taskInfo.getTaskId.getValue.toLong + val taskData = MesosTaskLaunchData.fromByteString(taskInfo.getData) if (executor == null) { logError("Received launchTask but executor was null") } else { SparkHadoopUtil.get.runAsSparkUser { () => - executor.launchTask(this, taskId, taskInfo.getName, taskInfo.getData.asReadOnlyByteBuffer) + executor.launchTask(this, taskId = taskId, attemptNumber = taskData.attemptNumber, + taskInfo.getName, taskData.serializedTask) } } } diff --git a/core/src/main/scala/org/apache/spark/rdd/CheckpointRDD.scala b/core/src/main/scala/org/apache/spark/rdd/CheckpointRDD.scala index 7ba1182f0ed27..1c13e2c372845 100644 --- a/core/src/main/scala/org/apache/spark/rdd/CheckpointRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/CheckpointRDD.scala @@ -95,7 +95,8 @@ private[spark] object CheckpointRDD extends Logging { val finalOutputName = splitIdToFile(ctx.partitionId) val finalOutputPath = new Path(outputDir, finalOutputName) - val tempOutputPath = new Path(outputDir, "." + finalOutputName + "-attempt-" + ctx.attemptId) + val tempOutputPath = + new Path(outputDir, "." + finalOutputName + "-attempt-" + ctx.attemptNumber) if (fs.exists(tempOutputPath)) { throw new IOException("Checkpoint failed: temporary path " + @@ -119,7 +120,7 @@ private[spark] object CheckpointRDD extends Logging { logInfo("Deleting tempOutputPath " + tempOutputPath) fs.delete(tempOutputPath, false) throw new IOException("Checkpoint failed: failed to save output of task: " - + ctx.attemptId + " and final output path does not exist") + + ctx.attemptNumber + " and final output path does not exist") } else { // Some other copy of this task must've finished before us and renamed it logInfo("Final output path " + finalOutputPath + " already exists; not overwriting it") diff --git a/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala b/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala index 0001c2329c83a..37e0c13029d8b 100644 --- a/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala @@ -229,7 +229,7 @@ class HadoopRDD[K, V]( var reader: RecordReader[K, V] = null val inputFormat = getInputFormat(jobConf) HadoopRDD.addLocalConfiguration(new SimpleDateFormat("yyyyMMddHHmm").format(createTime), - context.stageId, theSplit.index, context.attemptId.toInt, jobConf) + context.stageId, theSplit.index, context.attemptNumber, jobConf) reader = inputFormat.getRecordReader(split.inputSplit.value, jobConf, Reporter.NULL) // Register an on-task-completion callback to close the input stream. diff --git a/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala b/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala index 38f8f36a4a4db..e43e5066655b9 100644 --- a/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala +++ b/core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala @@ -978,12 +978,9 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)]) val writeShard = (context: TaskContext, iter: Iterator[(K,V)]) => { val config = wrappedConf.value - // Hadoop wants a 32-bit task attempt ID, so if ours is bigger than Int.MaxValue, roll it - // around by taking a mod. We expect that no task will be attempted 2 billion times. - val attemptNumber = (context.attemptId % Int.MaxValue).toInt /* "reduce task" */ val attemptId = newTaskAttemptID(jobtrackerID, stageId, isMap = false, context.partitionId, - attemptNumber) + context.attemptNumber) val hadoopContext = newTaskAttemptContext(config, attemptId) val format = outfmt.newInstance format match { @@ -1062,11 +1059,11 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)]) val config = wrappedConf.value // Hadoop wants a 32-bit task attempt ID, so if ours is bigger than Int.MaxValue, roll it // around by taking a mod. We expect that no task will be attempted 2 billion times. - val attemptNumber = (context.attemptId % Int.MaxValue).toInt + val taskAttemptId = (context.taskAttemptId % Int.MaxValue).toInt val (outputMetrics, bytesWrittenCallback) = initHadoopOutputMetrics(context, config) - writer.setup(context.stageId, context.partitionId, attemptNumber) + writer.setup(context.stageId, context.partitionId, taskAttemptId) writer.open() try { var recordsWritten = 0L diff --git a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala index 61d09d73e17cb..8cb15918baa8c 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala @@ -635,8 +635,8 @@ class DAGScheduler( try { val rdd = job.finalStage.rdd val split = rdd.partitions(job.partitions(0)) - val taskContext = - new TaskContextImpl(job.finalStage.id, job.partitions(0), 0, true) + val taskContext = new TaskContextImpl(job.finalStage.id, job.partitions(0), taskAttemptId = 0, + attemptNumber = 0, runningLocally = true) TaskContextHelper.setTaskContext(taskContext) try { val result = job.func(taskContext, rdd.iterator(split, taskContext)) diff --git a/core/src/main/scala/org/apache/spark/scheduler/Task.scala b/core/src/main/scala/org/apache/spark/scheduler/Task.scala index d7dde4fe38436..2367f7e2cf67e 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/Task.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/Task.scala @@ -44,8 +44,16 @@ import org.apache.spark.util.Utils */ private[spark] abstract class Task[T](val stageId: Int, var partitionId: Int) extends Serializable { - final def run(attemptId: Long): T = { - context = new TaskContextImpl(stageId, partitionId, attemptId, runningLocally = false) + /** + * Called by Executor to run this task. + * + * @param taskAttemptId an identifier for this task attempt that is unique within a SparkContext. + * @param attemptNumber how many times this task has been attempted (0 for the first attempt) + * @return the result of the task + */ + final def run(taskAttemptId: Long, attemptNumber: Int): T = { + context = new TaskContextImpl(stageId = stageId, partitionId = partitionId, + taskAttemptId = taskAttemptId, attemptNumber = attemptNumber, runningLocally = false) TaskContextHelper.setTaskContext(context) context.taskMetrics.hostname = Utils.localHostName() taskThread = Thread.currentThread() diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskDescription.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskDescription.scala index 4c96b9e5fef60..1c7c81c488c3a 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/TaskDescription.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/TaskDescription.scala @@ -27,6 +27,7 @@ import org.apache.spark.util.SerializableBuffer */ private[spark] class TaskDescription( val taskId: Long, + val attemptNumber: Int, val executorId: String, val name: String, val index: Int, // Index within this task's TaskSet diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala index 4667850917151..5c94c6bbcb37b 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala @@ -487,7 +487,8 @@ private[spark] class TaskSetManager( taskName, taskId, host, taskLocality, serializedTask.limit)) sched.dagScheduler.taskStarted(task, info) - return Some(new TaskDescription(taskId, execId, taskName, index, serializedTask)) + return Some(new TaskDescription(taskId = taskId, attemptNumber = attemptNum, execId, + taskName, index, serializedTask)) } case _ => } diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackend.scala index 10e6886c16a4f..75d8ddf375e27 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackend.scala @@ -22,7 +22,7 @@ import java.util.{ArrayList => JArrayList, List => JList} import java.util.Collections import scala.collection.JavaConversions._ -import scala.collection.mutable.{ArrayBuffer, HashMap, HashSet} +import scala.collection.mutable.{HashMap, HashSet} import org.apache.mesos.protobuf.ByteString import org.apache.mesos.{Scheduler => MScheduler} @@ -296,7 +296,7 @@ private[spark] class MesosSchedulerBackend( .setExecutor(createExecutorInfo(slaveId)) .setName(task.name) .addResources(cpuResource) - .setData(ByteString.copyFrom(task.serializedTask)) + .setData(MesosTaskLaunchData(task.serializedTask, task.attemptNumber).toByteString) .build() } diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosTaskLaunchData.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosTaskLaunchData.scala new file mode 100644 index 0000000000000..4416ce92ade25 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosTaskLaunchData.scala @@ -0,0 +1,46 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster.mesos + +import java.nio.ByteBuffer + +import org.apache.mesos.protobuf.ByteString + +/** + * Wrapper for serializing the data sent when launching Mesos tasks. + */ +private[spark] case class MesosTaskLaunchData( + serializedTask: ByteBuffer, + attemptNumber: Int) { + + def toByteString: ByteString = { + val dataBuffer = ByteBuffer.allocate(4 + serializedTask.limit) + dataBuffer.putInt(attemptNumber) + dataBuffer.put(serializedTask) + ByteString.copyFrom(dataBuffer) + } +} + +private[spark] object MesosTaskLaunchData { + def fromByteString(byteString: ByteString): MesosTaskLaunchData = { + val byteBuffer = byteString.asReadOnlyByteBuffer() + val attemptNumber = byteBuffer.getInt // updates the position by 4 bytes + val serializedTask = byteBuffer.slice() // subsequence starting at the current position + MesosTaskLaunchData(serializedTask, attemptNumber) + } +} diff --git a/core/src/main/scala/org/apache/spark/scheduler/local/LocalBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/local/LocalBackend.scala index b3bd3110ac809..05b6fa54564b7 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/local/LocalBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/local/LocalBackend.scala @@ -76,7 +76,8 @@ private[spark] class LocalActor( val offers = Seq(new WorkerOffer(localExecutorId, localExecutorHostname, freeCores)) for (task <- scheduler.resourceOffers(offers).flatten) { freeCores -= scheduler.CPUS_PER_TASK - executor.launchTask(executorBackend, task.taskId, task.name, task.serializedTask) + executor.launchTask(executorBackend, taskId = task.taskId, attemptNumber = task.attemptNumber, + task.name, task.serializedTask) } } } diff --git a/core/src/test/java/org/apache/spark/JavaAPISuite.java b/core/src/test/java/org/apache/spark/JavaAPISuite.java index 5ce299d05824b..07b1e44d04be6 100644 --- a/core/src/test/java/org/apache/spark/JavaAPISuite.java +++ b/core/src/test/java/org/apache/spark/JavaAPISuite.java @@ -820,7 +820,7 @@ public void persist() { @Test public void iterator() { JavaRDD rdd = sc.parallelize(Arrays.asList(1, 2, 3, 4, 5), 2); - TaskContext context = new TaskContextImpl(0, 0, 0L, false, new TaskMetrics()); + TaskContext context = new TaskContextImpl(0, 0, 0L, 0, false, new TaskMetrics()); Assert.assertEquals(1, rdd.iterator(rdd.partitions().get(0), context).next().intValue()); } diff --git a/core/src/test/scala/org/apache/spark/CacheManagerSuite.scala b/core/src/test/scala/org/apache/spark/CacheManagerSuite.scala index c0735f448d193..d7d9dc7b50f30 100644 --- a/core/src/test/scala/org/apache/spark/CacheManagerSuite.scala +++ b/core/src/test/scala/org/apache/spark/CacheManagerSuite.scala @@ -66,7 +66,7 @@ class CacheManagerSuite extends FunSuite with BeforeAndAfter with EasyMockSugar // in blockManager.put is a losing battle. You have been warned. blockManager = sc.env.blockManager cacheManager = sc.env.cacheManager - val context = new TaskContextImpl(0, 0, 0) + val context = new TaskContextImpl(0, 0, 0, 0) val computeValue = cacheManager.getOrCompute(rdd, split, context, StorageLevel.MEMORY_ONLY) val getValue = blockManager.get(RDDBlockId(rdd.id, split.index)) assert(computeValue.toList === List(1, 2, 3, 4)) @@ -81,7 +81,7 @@ class CacheManagerSuite extends FunSuite with BeforeAndAfter with EasyMockSugar } whenExecuting(blockManager) { - val context = new TaskContextImpl(0, 0, 0) + val context = new TaskContextImpl(0, 0, 0, 0) val value = cacheManager.getOrCompute(rdd, split, context, StorageLevel.MEMORY_ONLY) assert(value.toList === List(5, 6, 7)) } @@ -94,7 +94,7 @@ class CacheManagerSuite extends FunSuite with BeforeAndAfter with EasyMockSugar } whenExecuting(blockManager) { - val context = new TaskContextImpl(0, 0, 0, true) + val context = new TaskContextImpl(0, 0, 0, 0, true) val value = cacheManager.getOrCompute(rdd, split, context, StorageLevel.MEMORY_ONLY) assert(value.toList === List(1, 2, 3, 4)) } @@ -102,7 +102,7 @@ class CacheManagerSuite extends FunSuite with BeforeAndAfter with EasyMockSugar test("verify task metrics updated correctly") { cacheManager = sc.env.cacheManager - val context = new TaskContextImpl(0, 0, 0) + val context = new TaskContextImpl(0, 0, 0, 0) cacheManager.getOrCompute(rdd3, split, context, StorageLevel.MEMORY_ONLY) assert(context.taskMetrics.updatedBlocks.getOrElse(Seq()).size === 2) } diff --git a/core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala b/core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala index 271a90c6646bb..1a9a0e857e546 100644 --- a/core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala +++ b/core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala @@ -174,7 +174,7 @@ class PipedRDDSuite extends FunSuite with SharedSparkContext { } val hadoopPart1 = generateFakeHadoopPartition() val pipedRdd = new PipedRDD(nums, "printenv " + varName) - val tContext = new TaskContextImpl(0, 0, 0) + val tContext = new TaskContextImpl(0, 0, 0, 0) val rddIter = pipedRdd.compute(hadoopPart1, tContext) val arr = rddIter.toArray assert(arr(0) == "/some/path") diff --git a/core/src/test/scala/org/apache/spark/scheduler/TaskContextSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/TaskContextSuite.scala index 561a5e9cd90c4..057e226916027 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/TaskContextSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/TaskContextSuite.scala @@ -45,13 +45,13 @@ class TaskContextSuite extends FunSuite with BeforeAndAfter with LocalSparkConte val task = new ResultTask[String, String]( 0, sc.broadcast(closureSerializer.serialize((rdd, func)).array), rdd.partitions(0), Seq(), 0) intercept[RuntimeException] { - task.run(0) + task.run(0, 0) } assert(TaskContextSuite.completed === true) } test("all TaskCompletionListeners should be called even if some fail") { - val context = new TaskContextImpl(0, 0, 0) + val context = new TaskContextImpl(0, 0, 0, 0) val listener = mock(classOf[TaskCompletionListener]) context.addTaskCompletionListener(_ => throw new Exception("blah")) context.addTaskCompletionListener(listener) @@ -63,6 +63,33 @@ class TaskContextSuite extends FunSuite with BeforeAndAfter with LocalSparkConte verify(listener, times(1)).onTaskCompletion(any()) } + + test("TaskContext.attemptNumber should return attempt number, not task id (SPARK-4014)") { + sc = new SparkContext("local[1,2]", "test") // use maxRetries = 2 because we test failed tasks + // Check that attemptIds are 0 for all tasks' initial attempts + val attemptIds = sc.parallelize(Seq(1, 2), 2).mapPartitions { iter => + Seq(TaskContext.get().attemptNumber).iterator + }.collect() + assert(attemptIds.toSet === Set(0)) + + // Test a job with failed tasks + val attemptIdsWithFailedTask = sc.parallelize(Seq(1, 2), 2).mapPartitions { iter => + val attemptId = TaskContext.get().attemptNumber + if (iter.next() == 1 && attemptId == 0) { + throw new Exception("First execution of task failed") + } + Seq(attemptId).iterator + }.collect() + assert(attemptIdsWithFailedTask.toSet === Set(0, 1)) + } + + test("TaskContext.attemptId returns taskAttemptId for backwards-compatibility (SPARK-4014)") { + sc = new SparkContext("local", "test") + val attemptIds = sc.parallelize(Seq(1, 2, 3, 4), 4).mapPartitions { iter => + Seq(TaskContext.get().attemptId).iterator + }.collect() + assert(attemptIds.toSet === Set(0, 1, 2, 3)) + } } private object TaskContextSuite { diff --git a/core/src/test/scala/org/apache/spark/scheduler/mesos/MesosSchedulerBackendSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/mesos/MesosSchedulerBackendSuite.scala index e60e70afd3218..48f5e40f506d9 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/mesos/MesosSchedulerBackendSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/mesos/MesosSchedulerBackendSuite.scala @@ -80,7 +80,7 @@ class MesosSchedulerBackendSuite extends FunSuite with LocalSparkContext with Ea mesosOffers.get(2).getHostname, 2 )) - val taskDesc = new TaskDescription(1L, "s1", "n1", 0, ByteBuffer.wrap(new Array[Byte](0))) + val taskDesc = new TaskDescription(1L, 0, "s1", "n1", 0, ByteBuffer.wrap(new Array[Byte](0))) EasyMock.expect(taskScheduler.resourceOffers(EasyMock.eq(expectedWorkerOffers))).andReturn(Seq(Seq(taskDesc))) EasyMock.expect(taskScheduler.CPUS_PER_TASK).andReturn(2).anyTimes() EasyMock.replay(taskScheduler) diff --git a/core/src/test/scala/org/apache/spark/storage/ShuffleBlockFetcherIteratorSuite.scala b/core/src/test/scala/org/apache/spark/storage/ShuffleBlockFetcherIteratorSuite.scala index 1eaabb93adbed..37b593b2c5f79 100644 --- a/core/src/test/scala/org/apache/spark/storage/ShuffleBlockFetcherIteratorSuite.scala +++ b/core/src/test/scala/org/apache/spark/storage/ShuffleBlockFetcherIteratorSuite.scala @@ -89,7 +89,7 @@ class ShuffleBlockFetcherIteratorSuite extends FunSuite { ) val iterator = new ShuffleBlockFetcherIterator( - new TaskContextImpl(0, 0, 0), + new TaskContextImpl(0, 0, 0, 0), transfer, blockManager, blocksByAddress, @@ -154,7 +154,7 @@ class ShuffleBlockFetcherIteratorSuite extends FunSuite { val blocksByAddress = Seq[(BlockManagerId, Seq[(BlockId, Long)])]( (remoteBmId, blocks.keys.map(blockId => (blockId, 1.asInstanceOf[Long])).toSeq)) - val taskContext = new TaskContextImpl(0, 0, 0) + val taskContext = new TaskContextImpl(0, 0, 0, 0) val iterator = new ShuffleBlockFetcherIterator( taskContext, transfer, @@ -217,7 +217,7 @@ class ShuffleBlockFetcherIteratorSuite extends FunSuite { val blocksByAddress = Seq[(BlockManagerId, Seq[(BlockId, Long)])]( (remoteBmId, blocks.keys.map(blockId => (blockId, 1.asInstanceOf[Long])).toSeq)) - val taskContext = new TaskContextImpl(0, 0, 0) + val taskContext = new TaskContextImpl(0, 0, 0, 0) val iterator = new ShuffleBlockFetcherIterator( taskContext, transfer, diff --git a/core/src/test/scala/org/apache/spark/ui/UISeleniumSuite.scala b/core/src/test/scala/org/apache/spark/ui/UISeleniumSuite.scala index 787f4c2b5a8b2..e85a436cdba17 100644 --- a/core/src/test/scala/org/apache/spark/ui/UISeleniumSuite.scala +++ b/core/src/test/scala/org/apache/spark/ui/UISeleniumSuite.scala @@ -173,7 +173,7 @@ class UISeleniumSuite extends FunSuite with WebBrowser with Matchers { // Simulate fetch failures: val mappedData = data.map { x => val taskContext = TaskContext.get - if (taskContext.attemptId() == 1) { // Cause this stage to fail on its first attempt. + if (taskContext.attemptNumber == 0) { // Cause this stage to fail on its first attempt. val env = SparkEnv.get val bmAddress = env.blockManager.blockManagerId val shuffleId = shuffleHandle.shuffleId diff --git a/project/MimaExcludes.scala b/project/MimaExcludes.scala index f6f9f491f4ceb..d3ea594245722 100644 --- a/project/MimaExcludes.scala +++ b/project/MimaExcludes.scala @@ -72,6 +72,12 @@ object MimaExcludes { "org.apache.spark.ml.classification.LogisticRegressionModel.validateAndTransformSchema"), ProblemFilters.exclude[IncompatibleMethTypeProblem]( "org.apache.spark.ml.classification.LogisticRegression.validateAndTransformSchema") + ) ++ Seq( + // SPARK-4014 + ProblemFilters.exclude[MissingMethodProblem]( + "org.apache.spark.TaskContext.taskAttemptId"), + ProblemFilters.exclude[MissingMethodProblem]( + "org.apache.spark.TaskContext.attemptNumber") ) case v if v.startsWith("1.2") => diff --git a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala index f5487740d3af9..28cd17fde46ab 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetTableOperations.scala @@ -301,12 +301,9 @@ case class InsertIntoParquetTable( } def writeShard(context: TaskContext, iter: Iterator[Row]): Int = { - // Hadoop wants a 32-bit task attempt ID, so if ours is bigger than Int.MaxValue, roll it - // around by taking a mod. We expect that no task will be attempted 2 billion times. - val attemptNumber = (context.attemptId % Int.MaxValue).toInt /* "reduce task" */ val attemptId = newTaskAttemptID(jobtrackerID, stageId, isMap = false, context.partitionId, - attemptNumber) + context.attemptNumber) val hadoopContext = newTaskAttemptContext(wrappedConf.value, attemptId) val format = new AppendingParquetOutputFormat(taskIdOffset) val committer = format.getOutputCommitter(hadoopContext) diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala index ca0ec1513917f..42bc8a0b67933 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala @@ -100,10 +100,7 @@ case class InsertIntoHiveTable( val wrappers = fieldOIs.map(wrapperFor) val outputData = new Array[Any](fieldOIs.length) - // Hadoop wants a 32-bit task attempt ID, so if ours is bigger than Int.MaxValue, roll it - // around by taking a mod. We expect that no task will be attempted 2 billion times. - val attemptNumber = (context.attemptId % Int.MaxValue).toInt - writerContainer.executorSideSetup(context.stageId, context.partitionId, attemptNumber) + writerContainer.executorSideSetup(context.stageId, context.partitionId, context.attemptNumber) iterator.foreach { row => var i = 0 From 2fd7f72b6b0b24bec12331c7bbbcf6bfc265d2ec Mon Sep 17 00:00:00 2001 From: Alex Baretta Date: Wed, 14 Jan 2015 11:51:55 -0800 Subject: [PATCH 253/320] [SPARK-5235] Make SQLConf Serializable Declare SQLConf to be serializable to fix "Task not serializable" exceptions in SparkSQL Author: Alex Baretta Closes #4031 from alexbaretta/SPARK-5235-SQLConf and squashes the following commits: c2103f5 [Alex Baretta] [SPARK-5235] Make SQLConf Serializable --- sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala index 206d16f5b34f5..3bc201a2425b6 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala @@ -61,7 +61,7 @@ private[spark] object SQLConf { * * SQLConf is thread-safe (internally synchronized, so safe to be used in multiple threads). */ -private[sql] class SQLConf { +private[sql] class SQLConf extends Serializable { import SQLConf._ /** Only low degree of contention is expected for conf, thus NOT using ConcurrentHashMap. */ From 76389c5b99183e456ff85fd92ea68d95c4c13e82 Mon Sep 17 00:00:00 2001 From: Yuhao Yang Date: Wed, 14 Jan 2015 11:53:43 -0800 Subject: [PATCH 254/320] [SPARK-5234][ml]examples for ml don't have sparkContext.stop JIRA issue: https://issues.apache.org/jira/browse/SPARK-5234 simply add the call. Author: Yuhao Yang Closes #4044 from hhbyyh/addscStop and squashes the following commits: c1f75ac [Yuhao Yang] add SparkContext.stop to 3 ml examples --- .../org/apache/spark/examples/ml/CrossValidatorExample.scala | 2 ++ .../org/apache/spark/examples/ml/SimpleParamsExample.scala | 2 ++ .../spark/examples/ml/SimpleTextClassificationPipeline.scala | 2 ++ 3 files changed, 6 insertions(+) diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/CrossValidatorExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/CrossValidatorExample.scala index ce6bc066bd70d..d8c7ef38ee46d 100644 --- a/examples/src/main/scala/org/apache/spark/examples/ml/CrossValidatorExample.scala +++ b/examples/src/main/scala/org/apache/spark/examples/ml/CrossValidatorExample.scala @@ -106,5 +106,7 @@ object CrossValidatorExample { .foreach { case Row(id: Long, text: String, score: Double, prediction: Double) => println("(" + id + ", " + text + ") --> score=" + score + ", prediction=" + prediction) } + + sc.stop() } } diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/SimpleParamsExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/SimpleParamsExample.scala index 44d5b084c269a..e8a2adff929cb 100644 --- a/examples/src/main/scala/org/apache/spark/examples/ml/SimpleParamsExample.scala +++ b/examples/src/main/scala/org/apache/spark/examples/ml/SimpleParamsExample.scala @@ -97,5 +97,7 @@ object SimpleParamsExample { .foreach { case Row(features: Vector, label: Double, prob: Double, prediction: Double) => println("(" + features + ", " + label + ") -> prob=" + prob + ", prediction=" + prediction) } + + sc.stop() } } diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/SimpleTextClassificationPipeline.scala b/examples/src/main/scala/org/apache/spark/examples/ml/SimpleTextClassificationPipeline.scala index 92895a05e479a..b9a6ef0229def 100644 --- a/examples/src/main/scala/org/apache/spark/examples/ml/SimpleTextClassificationPipeline.scala +++ b/examples/src/main/scala/org/apache/spark/examples/ml/SimpleTextClassificationPipeline.scala @@ -85,5 +85,7 @@ object SimpleTextClassificationPipeline { .foreach { case Row(id: Long, text: String, score: Double, prediction: Double) => println("(" + id + ", " + text + ") --> score=" + score + ", prediction=" + prediction) } + + sc.stop() } } From 13d2406781714daea2bbf3bfb7fec0dead10760c Mon Sep 17 00:00:00 2001 From: Xiangrui Meng Date: Wed, 14 Jan 2015 17:50:33 -0800 Subject: [PATCH 255/320] [SPARK-5254][MLLIB] Update the user guide to position spark.ml better The current statement in the user guide may deliver confusing messages to users. spark.ml contains high-level APIs for building ML pipelines. But it doesn't mean that spark.mllib is being deprecated. First of all, the pipeline API is in its alpha stage and we need to see more use cases from the community to stabilizes it, which may take several releases. Secondly, the components in spark.ml are simple wrappers over spark.mllib implementations. Neither the APIs or the implementations from spark.mllib are being deprecated. We expect users use spark.ml pipeline APIs to build their ML pipelines, but we will keep supporting and adding features to spark.mllib. For example, there are many features in review at https://spark-prs.appspot.com/#mllib. So users should be comfortable with using spark.mllib features and expect more coming. The user guide needs to be updated to make the message clear. Author: Xiangrui Meng Closes #4052 from mengxr/SPARK-5254 and squashes the following commits: 6d5f1d3 [Xiangrui Meng] typo 0cc935b [Xiangrui Meng] update user guide to position spark.ml better --- docs/ml-guide.md | 17 ++++++++++------- docs/mllib-guide.md | 18 +++++++++++------- 2 files changed, 21 insertions(+), 14 deletions(-) diff --git a/docs/ml-guide.md b/docs/ml-guide.md index 1c2e27341473b..88158fd77edae 100644 --- a/docs/ml-guide.md +++ b/docs/ml-guide.md @@ -3,13 +3,16 @@ layout: global title: Spark ML Programming Guide --- -Spark ML is Spark's new machine learning package. It is currently an alpha component but is potentially a successor to [MLlib](mllib-guide.html). The `spark.ml` package aims to replace the old APIs with a cleaner, more uniform set of APIs which will help users create full machine learning pipelines. - -MLlib vs. Spark ML: - -* Users can use algorithms from either of the two packages, but APIs may differ. Currently, `spark.ml` offers a subset of the algorithms from `spark.mllib`. Since Spark ML is an alpha component, its API may change in future releases. -* Developers should contribute new algorithms to `spark.mllib` and can optionally contribute to `spark.ml`. See below for more details. -* Spark ML only has Scala and Java APIs, whereas MLlib also has a Python API. +`spark.ml` is a new package introduced in Spark 1.2, which aims to provide a uniform set of +high-level APIs that help users create and tune practical machine learning pipelines. +It is currently an alpha component, and we would like to hear back from the community about +how it fits real-world use cases and how it could be improved. + +Note that we will keep supporting and adding features to `spark.mllib` along with the +development of `spark.ml`. +Users should be comfortable using `spark.mllib` features and expect more features coming. +Developers should contribute new algorithms to `spark.mllib` and can optionally contribute +to `spark.ml`. **Table of Contents** diff --git a/docs/mllib-guide.md b/docs/mllib-guide.md index efd7dda310712..39c64d06926bf 100644 --- a/docs/mllib-guide.md +++ b/docs/mllib-guide.md @@ -35,16 +35,20 @@ MLlib is under active development. The APIs marked `Experimental`/`DeveloperApi` may change in future releases, and the migration guide below will explain all changes between releases. -# spark.ml: The New ML Package +# spark.ml: high-level APIs for ML pipelines -Spark 1.2 includes a new machine learning package called `spark.ml`, currently an alpha component but potentially a successor to `spark.mllib`. The `spark.ml` package aims to replace the old APIs with a cleaner, more uniform set of APIs which will help users create full machine learning pipelines. +Spark 1.2 includes a new package called `spark.ml`, which aims to provide a uniform set of +high-level APIs that help users create and tune practical machine learning pipelines. +It is currently an alpha component, and we would like to hear back from the community about +how it fits real-world use cases and how it could be improved. -See the **[spark.ml programming guide](ml-guide.html)** for more information on this package. - -Users can use algorithms from either of the two packages, but APIs may differ. Currently, `spark.ml` offers a subset of the algorithms from `spark.mllib`. +Note that we will keep supporting and adding features to `spark.mllib` along with the +development of `spark.ml`. +Users should be comfortable using `spark.mllib` features and expect more features coming. +Developers should contribute new algorithms to `spark.mllib` and can optionally contribute +to `spark.ml`. -Developers should contribute new algorithms to `spark.mllib` and can optionally contribute to `spark.ml`. -See the `spark.ml` programming guide linked above for more details. +See the **[spark.ml programming guide](ml-guide.html)** for more information on this package. # Dependencies From cfa397c126c857bfc9843d9e598a14b7c1e0457f Mon Sep 17 00:00:00 2001 From: Reynold Xin Date: Wed, 14 Jan 2015 18:36:15 -0800 Subject: [PATCH 256/320] [SPARK-5193][SQL] Tighten up SQLContext API 1. Removed 2 implicits (logicalPlanToSparkQuery and baseRelationToSchemaRDD) 2. Moved extraStrategies into ExperimentalMethods. 3. Made private methods protected[sql] so they don't show up in javadocs. 4. Removed createParquetFile. 5. Added Java version of applySchema to SQLContext. Author: Reynold Xin Closes #4049 from rxin/sqlContext-refactor and squashes the following commits: a326a1a [Reynold Xin] Remove createParquetFile and add applySchema for Java to SQLContext. ecd6685 [Reynold Xin] Added baseRelationToSchemaRDD back. 4a38c9b [Reynold Xin] [SPARK-5193][SQL] Tighten up SQLContext API --- .../spark/sql/ExperimentalMethods.scala | 36 ++++ .../org/apache/spark/sql/SQLContext.scala | 152 ++++++++++------- .../apache/spark/sql/execution/commands.scala | 10 +- .../org/apache/spark/sql/sources/ddl.scala | 5 +- .../spark/sql/test/TestSQLContext.scala | 16 +- .../apache/spark/sql/InsertIntoSuite.scala | 160 ------------------ .../spark/sql/parquet/ParquetQuerySuite.scala | 26 --- .../sql/parquet/ParquetQuerySuite2.scala | 22 --- .../apache/spark/sql/hive/HiveContext.scala | 4 +- .../org/apache/spark/sql/hive/TestHive.scala | 2 +- 10 files changed, 152 insertions(+), 281 deletions(-) create mode 100644 sql/core/src/main/scala/org/apache/spark/sql/ExperimentalMethods.scala delete mode 100644 sql/core/src/test/scala/org/apache/spark/sql/InsertIntoSuite.scala diff --git a/sql/core/src/main/scala/org/apache/spark/sql/ExperimentalMethods.scala b/sql/core/src/main/scala/org/apache/spark/sql/ExperimentalMethods.scala new file mode 100644 index 0000000000000..f0e6a8f332188 --- /dev/null +++ b/sql/core/src/main/scala/org/apache/spark/sql/ExperimentalMethods.scala @@ -0,0 +1,36 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql + +import org.apache.spark.annotation.Experimental + +/** + * Holder for experimental methods for the bravest. We make NO guarantee about the stability + * regarding binary compatibility and source compatibility of methods here. + */ +@Experimental +class ExperimentalMethods protected[sql](sqlContext: SQLContext) { + + /** + * Allows extra strategies to be injected into the query planner at runtime. Note this API + * should be consider experimental and is not intended to be stable across releases. + */ + @Experimental + var extraStrategies: Seq[Strategy] = Nil + +} diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala index d9f3b3a53f582..279671ced0a17 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala @@ -17,15 +17,16 @@ package org.apache.spark.sql +import java.beans.Introspector import java.util.Properties import scala.collection.immutable import scala.language.implicitConversions import scala.reflect.runtime.universe.TypeTag -import org.apache.hadoop.conf.Configuration import org.apache.spark.SparkContext import org.apache.spark.annotation.{AlphaComponent, DeveloperApi, Experimental} +import org.apache.spark.api.java.JavaRDD import org.apache.spark.rdd.RDD import org.apache.spark.sql.catalyst.ScalaReflection import org.apache.spark.sql.catalyst.analysis._ @@ -36,9 +37,9 @@ import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan import org.apache.spark.sql.catalyst.rules.RuleExecutor import org.apache.spark.sql.execution._ import org.apache.spark.sql.json._ -import org.apache.spark.sql.parquet.ParquetRelation -import org.apache.spark.sql.sources.{BaseRelation, DDLParser, DataSourceStrategy, LogicalRelation} +import org.apache.spark.sql.sources.{LogicalRelation, BaseRelation, DDLParser, DataSourceStrategy} import org.apache.spark.sql.types._ +import org.apache.spark.util.Utils /** * :: AlphaComponent :: @@ -59,7 +60,7 @@ class SQLContext(@transient val sparkContext: SparkContext) self => // Note that this is a lazy val so we can override the default value in subclasses. - private[sql] lazy val conf: SQLConf = new SQLConf + protected[sql] lazy val conf: SQLConf = new SQLConf /** Set Spark SQL configuration properties. */ def setConf(props: Properties): Unit = conf.setConf(props) @@ -117,15 +118,6 @@ class SQLContext(@transient val sparkContext: SparkContext) case _ => } - /** - * :: DeveloperApi :: - * Allows catalyst LogicalPlans to be executed as a SchemaRDD. Note that the LogicalPlan - * interface is considered internal, and thus not guaranteed to be stable. As a result, using - * them directly is not recommended. - */ - @DeveloperApi - implicit def logicalPlanToSparkQuery(plan: LogicalPlan): SchemaRDD = new SchemaRDD(this, plan) - /** * Creates a SchemaRDD from an RDD of case classes. * @@ -139,8 +131,11 @@ class SQLContext(@transient val sparkContext: SparkContext) new SchemaRDD(this, LogicalRDD(attributeSeq, rowRDD)(self)) } - implicit def baseRelationToSchemaRDD(baseRelation: BaseRelation): SchemaRDD = { - logicalPlanToSparkQuery(LogicalRelation(baseRelation)) + /** + * Convert a [[BaseRelation]] created for external data sources into a [[SchemaRDD]]. + */ + def baseRelationToSchemaRDD(baseRelation: BaseRelation): SchemaRDD = { + new SchemaRDD(this, LogicalRelation(baseRelation)) } /** @@ -181,6 +176,43 @@ class SQLContext(@transient val sparkContext: SparkContext) new SchemaRDD(this, logicalPlan) } + /** + * Applies a schema to an RDD of Java Beans. + * + * WARNING: Since there is no guaranteed ordering for fields in a Java Bean, + * SELECT * queries will return the columns in an undefined order. + */ + def applySchema(rdd: RDD[_], beanClass: Class[_]): SchemaRDD = { + val attributeSeq = getSchema(beanClass) + val className = beanClass.getName + val rowRdd = rdd.mapPartitions { iter => + // BeanInfo is not serializable so we must rediscover it remotely for each partition. + val localBeanInfo = Introspector.getBeanInfo( + Class.forName(className, true, Utils.getContextOrSparkClassLoader)) + val extractors = + localBeanInfo.getPropertyDescriptors.filterNot(_.getName == "class").map(_.getReadMethod) + + iter.map { row => + new GenericRow( + extractors.zip(attributeSeq).map { case (e, attr) => + DataTypeConversions.convertJavaToCatalyst(e.invoke(row), attr.dataType) + }.toArray[Any] + ) : Row + } + } + new SchemaRDD(this, LogicalRDD(attributeSeq, rowRdd)(this)) + } + + /** + * Applies a schema to an RDD of Java Beans. + * + * WARNING: Since there is no guaranteed ordering for fields in a Java Bean, + * SELECT * queries will return the columns in an undefined order. + */ + def applySchema(rdd: JavaRDD[_], beanClass: Class[_]): SchemaRDD = { + applySchema(rdd.rdd, beanClass) + } + /** * Loads a Parquet file, returning the result as a [[SchemaRDD]]. * @@ -259,41 +291,6 @@ class SQLContext(@transient val sparkContext: SparkContext) applySchema(rowRDD, appliedSchema) } - /** - * :: Experimental :: - * Creates an empty parquet file with the schema of class `A`, which can be registered as a table. - * This registered table can be used as the target of future `insertInto` operations. - * - * {{{ - * val sqlContext = new SQLContext(...) - * import sqlContext._ - * - * case class Person(name: String, age: Int) - * createParquetFile[Person]("path/to/file.parquet").registerTempTable("people") - * sql("INSERT INTO people SELECT 'michael', 29") - * }}} - * - * @tparam A A case class type that describes the desired schema of the parquet file to be - * created. - * @param path The path where the directory containing parquet metadata should be created. - * Data inserted into this table will also be stored at this location. - * @param allowExisting When false, an exception will be thrown if this directory already exists. - * @param conf A Hadoop configuration object that can be used to specify options to the parquet - * output format. - * - * @group userf - */ - @Experimental - def createParquetFile[A <: Product : TypeTag]( - path: String, - allowExisting: Boolean = true, - conf: Configuration = new Configuration()): SchemaRDD = { - new SchemaRDD( - this, - ParquetRelation.createEmpty( - path, ScalaReflection.attributesFor[A], allowExisting, conf, this)) - } - /** * Registers the given RDD as a temporary table in the catalog. Temporary tables exist only * during the lifetime of this instance of SQLContext. @@ -336,12 +333,10 @@ class SQLContext(@transient val sparkContext: SparkContext) new SchemaRDD(this, catalog.lookupRelation(Seq(tableName))) /** - * :: DeveloperApi :: - * Allows extra strategies to be injected into the query planner at runtime. Note this API - * should be consider experimental and is not intended to be stable across releases. + * A collection of methods that are considered experimental, but can be used to hook into + * the query planner for advanced functionalities. */ - @DeveloperApi - var extraStrategies: Seq[Strategy] = Nil + val experimental: ExperimentalMethods = new ExperimentalMethods(this) protected[sql] class SparkPlanner extends SparkStrategies { val sparkContext: SparkContext = self.sparkContext @@ -353,7 +348,7 @@ class SQLContext(@transient val sparkContext: SparkContext) def numPartitions = self.conf.numShufflePartitions def strategies: Seq[Strategy] = - extraStrategies ++ ( + experimental.extraStrategies ++ ( DataSourceStrategy :: DDLStrategy :: TakeOrdered :: @@ -479,14 +474,14 @@ class SQLContext(@transient val sparkContext: SparkContext) * have the same format as the one generated by `toString` in scala. * It is only used by PySpark. */ - private[sql] def parseDataType(dataTypeString: String): DataType = { + protected[sql] def parseDataType(dataTypeString: String): DataType = { DataType.fromJson(dataTypeString) } /** * Apply a schema defined by the schemaString to an RDD. It is only used by PySpark. */ - private[sql] def applySchemaToPythonRDD( + protected[sql] def applySchemaToPythonRDD( rdd: RDD[Array[Any]], schemaString: String): SchemaRDD = { val schema = parseDataType(schemaString).asInstanceOf[StructType] @@ -496,7 +491,7 @@ class SQLContext(@transient val sparkContext: SparkContext) /** * Apply a schema defined by the schema to an RDD. It is only used by PySpark. */ - private[sql] def applySchemaToPythonRDD( + protected[sql] def applySchemaToPythonRDD( rdd: RDD[Array[Any]], schema: StructType): SchemaRDD = { @@ -527,4 +522,43 @@ class SQLContext(@transient val sparkContext: SparkContext) new SchemaRDD(this, LogicalRDD(schema.toAttributes, rowRdd)(self)) } + + /** + * Returns a Catalyst Schema for the given java bean class. + */ + protected def getSchema(beanClass: Class[_]): Seq[AttributeReference] = { + // TODO: All of this could probably be moved to Catalyst as it is mostly not Spark specific. + val beanInfo = Introspector.getBeanInfo(beanClass) + + // Note: The ordering of elements may differ from when the schema is inferred in Scala. + // This is because beanInfo.getPropertyDescriptors gives no guarantees about + // element ordering. + val fields = beanInfo.getPropertyDescriptors.filterNot(_.getName == "class") + fields.map { property => + val (dataType, nullable) = property.getPropertyType match { + case c: Class[_] if c.isAnnotationPresent(classOf[SQLUserDefinedType]) => + (c.getAnnotation(classOf[SQLUserDefinedType]).udt().newInstance(), true) + case c: Class[_] if c == classOf[java.lang.String] => (StringType, true) + case c: Class[_] if c == java.lang.Short.TYPE => (ShortType, false) + case c: Class[_] if c == java.lang.Integer.TYPE => (IntegerType, false) + case c: Class[_] if c == java.lang.Long.TYPE => (LongType, false) + case c: Class[_] if c == java.lang.Double.TYPE => (DoubleType, false) + case c: Class[_] if c == java.lang.Byte.TYPE => (ByteType, false) + case c: Class[_] if c == java.lang.Float.TYPE => (FloatType, false) + case c: Class[_] if c == java.lang.Boolean.TYPE => (BooleanType, false) + + case c: Class[_] if c == classOf[java.lang.Short] => (ShortType, true) + case c: Class[_] if c == classOf[java.lang.Integer] => (IntegerType, true) + case c: Class[_] if c == classOf[java.lang.Long] => (LongType, true) + case c: Class[_] if c == classOf[java.lang.Double] => (DoubleType, true) + case c: Class[_] if c == classOf[java.lang.Byte] => (ByteType, true) + case c: Class[_] if c == classOf[java.lang.Float] => (FloatType, true) + case c: Class[_] if c == classOf[java.lang.Boolean] => (BooleanType, true) + case c: Class[_] if c == classOf[java.math.BigDecimal] => (DecimalType(), true) + case c: Class[_] if c == classOf[java.sql.Date] => (DateType, true) + case c: Class[_] if c == classOf[java.sql.Timestamp] => (TimestampType, true) + } + AttributeReference(property.getName, dataType, nullable)() + } + } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala index af6b07bd6c2f4..52a31f01a4358 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala @@ -20,11 +20,11 @@ package org.apache.spark.sql.execution import org.apache.spark.Logging import org.apache.spark.annotation.DeveloperApi import org.apache.spark.rdd.RDD +import org.apache.spark.sql.{SchemaRDD, SQLConf, SQLContext} import org.apache.spark.sql.catalyst.errors.TreeNodeException import org.apache.spark.sql.catalyst.expressions.{Row, Attribute} import org.apache.spark.sql.catalyst.plans.logical import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan -import org.apache.spark.sql.{SQLConf, SQLContext} /** * A logical command that is executed for its side-effects. `RunnableCommand`s are @@ -137,14 +137,12 @@ case class CacheTableCommand( isLazy: Boolean) extends RunnableCommand { override def run(sqlContext: SQLContext) = { - import sqlContext._ - - plan.foreach(_.registerTempTable(tableName)) - cacheTable(tableName) + plan.foreach(p => new SchemaRDD(sqlContext, p).registerTempTable(tableName)) + sqlContext.cacheTable(tableName) if (!isLazy) { // Performs eager caching - table(tableName).count() + sqlContext.table(tableName).count() } Seq.empty[Row] diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala index 4cc9641c4d9e0..381298caba6f2 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala @@ -22,7 +22,7 @@ import scala.util.parsing.combinator.syntactical.StandardTokenParsers import scala.util.parsing.combinator.PackratParsers import org.apache.spark.Logging -import org.apache.spark.sql.SQLContext +import org.apache.spark.sql.{SchemaRDD, SQLContext} import org.apache.spark.sql.catalyst.plans.logical._ import org.apache.spark.sql.catalyst.SqlLexical import org.apache.spark.sql.execution.RunnableCommand @@ -234,8 +234,7 @@ private [sql] case class CreateTempTableUsing( def run(sqlContext: SQLContext) = { val resolved = ResolvedDataSource(sqlContext, userSpecifiedSchema, provider, options) - - sqlContext.baseRelationToSchemaRDD(resolved.relation).registerTempTable(tableName) + new SchemaRDD(sqlContext, LogicalRelation(resolved.relation)).registerTempTable(tableName) Seq.empty } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/test/TestSQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/test/TestSQLContext.scala index 8c80be106f3cb..f9c082216085d 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/test/TestSQLContext.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/test/TestSQLContext.scala @@ -17,8 +17,11 @@ package org.apache.spark.sql.test +import scala.language.implicitConversions + import org.apache.spark.{SparkConf, SparkContext} -import org.apache.spark.sql.{SQLConf, SQLContext} +import org.apache.spark.sql.{SchemaRDD, SQLConf, SQLContext} +import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan /** A SQLContext that can be used for local testing. */ object TestSQLContext @@ -29,7 +32,16 @@ object TestSQLContext new SparkConf().set("spark.sql.testkey", "true"))) { /** Fewer partitions to speed up testing. */ - private[sql] override lazy val conf: SQLConf = new SQLConf { + protected[sql] override lazy val conf: SQLConf = new SQLConf { override def numShufflePartitions: Int = this.getConf(SQLConf.SHUFFLE_PARTITIONS, "5").toInt } + + /** + * Turn a logical plan into a SchemaRDD. This should be removed once we have an easier way to + * construct SchemaRDD directly out of local data without relying on implicits. + */ + protected[sql] implicit def logicalPlanToSparkQuery(plan: LogicalPlan): SchemaRDD = { + new SchemaRDD(this, plan) + } + } diff --git a/sql/core/src/test/scala/org/apache/spark/sql/InsertIntoSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/InsertIntoSuite.scala deleted file mode 100644 index c87d762751e6d..0000000000000 --- a/sql/core/src/test/scala/org/apache/spark/sql/InsertIntoSuite.scala +++ /dev/null @@ -1,160 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.sql - -import _root_.java.io.File - -/* Implicits */ -import org.apache.spark.sql.test.TestSQLContext._ - -class InsertIntoSuite extends QueryTest { - TestData // Initialize TestData - import TestData._ - - test("insertInto() created parquet file") { - val testFilePath = File.createTempFile("sparkSql", "pqt") - testFilePath.delete() - testFilePath.deleteOnExit() - val testFile = createParquetFile[TestData](testFilePath.getCanonicalPath) - testFile.registerTempTable("createAndInsertTest") - - // Add some data. - testData.insertInto("createAndInsertTest") - - // Make sure its there for a new instance of parquet file. - checkAnswer( - parquetFile(testFilePath.getCanonicalPath), - testData.collect().toSeq - ) - - // Make sure the registered table has also been updated. - checkAnswer( - sql("SELECT * FROM createAndInsertTest"), - testData.collect().toSeq - ) - - // Add more data. - testData.insertInto("createAndInsertTest") - - // Make sure all data is there for a new instance of parquet file. - checkAnswer( - parquetFile(testFilePath.getCanonicalPath), - testData.collect().toSeq ++ testData.collect().toSeq - ) - - // Make sure the registered table has also been updated. - checkAnswer( - sql("SELECT * FROM createAndInsertTest"), - testData.collect().toSeq ++ testData.collect().toSeq - ) - - // Now overwrite. - testData.insertInto("createAndInsertTest", overwrite = true) - - // Make sure its there for a new instance of parquet file. - checkAnswer( - parquetFile(testFilePath.getCanonicalPath), - testData.collect().toSeq - ) - - // Make sure the registered table has also been updated. - checkAnswer( - sql("SELECT * FROM createAndInsertTest"), - testData.collect().toSeq - ) - - testFilePath.delete() - } - - test("INSERT INTO parquet table") { - val testFilePath = File.createTempFile("sparkSql", "pqt") - testFilePath.delete() - testFilePath.deleteOnExit() - val testFile = createParquetFile[TestData](testFilePath.getCanonicalPath) - testFile.registerTempTable("createAndInsertSQLTest") - - sql("INSERT INTO createAndInsertSQLTest SELECT * FROM testData") - - // Make sure its there for a new instance of parquet file. - checkAnswer( - parquetFile(testFilePath.getCanonicalPath), - testData.collect().toSeq - ) - - // Make sure the registered table has also been updated. - checkAnswer( - sql("SELECT * FROM createAndInsertSQLTest"), - testData.collect().toSeq - ) - - // Append more data. - sql("INSERT INTO createAndInsertSQLTest SELECT * FROM testData") - - // Make sure all data is there for a new instance of parquet file. - checkAnswer( - parquetFile(testFilePath.getCanonicalPath), - testData.collect().toSeq ++ testData.collect().toSeq - ) - - // Make sure the registered table has also been updated. - checkAnswer( - sql("SELECT * FROM createAndInsertSQLTest"), - testData.collect().toSeq ++ testData.collect().toSeq - ) - - sql("INSERT OVERWRITE INTO createAndInsertSQLTest SELECT * FROM testData") - - // Make sure its there for a new instance of parquet file. - checkAnswer( - parquetFile(testFilePath.getCanonicalPath), - testData.collect().toSeq - ) - - // Make sure the registered table has also been updated. - checkAnswer( - sql("SELECT * FROM createAndInsertSQLTest"), - testData.collect().toSeq - ) - - testFilePath.delete() - } - - test("Double create fails when allowExisting = false") { - val testFilePath = File.createTempFile("sparkSql", "pqt") - testFilePath.delete() - testFilePath.deleteOnExit() - val testFile = createParquetFile[TestData](testFilePath.getCanonicalPath) - - intercept[RuntimeException] { - createParquetFile[TestData](testFilePath.getCanonicalPath, allowExisting = false) - } - - testFilePath.delete() - } - - test("Double create does not fail when allowExisting = true") { - val testFilePath = File.createTempFile("sparkSql", "pqt") - testFilePath.delete() - testFilePath.deleteOnExit() - val testFile = createParquetFile[TestData](testFilePath.getCanonicalPath) - - createParquetFile[TestData](testFilePath.getCanonicalPath, allowExisting = true) - - testFilePath.delete() - } -} diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala index fe781ec05fb6f..3a073a6b7057e 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite.scala @@ -402,23 +402,6 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA Utils.deleteRecursively(file) } - test("Insert (overwrite) via Scala API") { - val dirname = Utils.createTempDir() - val source_rdd = TestSQLContext.sparkContext.parallelize((1 to 100)) - .map(i => TestRDDEntry(i, s"val_$i")) - source_rdd.registerTempTable("source") - val dest_rdd = createParquetFile[TestRDDEntry](dirname.toString) - dest_rdd.registerTempTable("dest") - sql("INSERT OVERWRITE INTO dest SELECT * FROM source").collect() - val rdd_copy1 = sql("SELECT * FROM dest").collect() - assert(rdd_copy1.size === 100) - - sql("INSERT INTO dest SELECT * FROM source") - val rdd_copy2 = sql("SELECT * FROM dest").collect().sortBy(_.getInt(0)) - assert(rdd_copy2.size === 200) - Utils.deleteRecursively(dirname) - } - test("Insert (appending) to same table via Scala API") { sql("INSERT INTO testsource SELECT * FROM testsource") val double_rdd = sql("SELECT * FROM testsource").collect() @@ -902,15 +885,6 @@ class ParquetQuerySuite extends QueryTest with FunSuiteLike with BeforeAndAfterA Utils.deleteRecursively(tmpdir) } - test("Querying on empty parquet throws exception (SPARK-3536)") { - val tmpdir = Utils.createTempDir() - Utils.deleteRecursively(tmpdir) - createParquetFile[TestRDDEntry](tmpdir.toString()).registerTempTable("tmpemptytable") - val result1 = sql("SELECT * FROM tmpemptytable").collect() - assert(result1.size === 0) - Utils.deleteRecursively(tmpdir) - } - test("read/write fixed-length decimals") { for ((precision, scale) <- Seq((5, 2), (1, 0), (1, 1), (18, 10), (18, 17))) { val tempDir = getTempFilePath("parquetTest").getCanonicalPath diff --git a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite2.scala b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite2.scala index daa7ca65cd993..4c081fb4510b2 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite2.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/parquet/ParquetQuerySuite2.scala @@ -34,19 +34,6 @@ class ParquetQuerySuite2 extends QueryTest with ParquetTest { } } - test("insertion") { - withTempDir { dir => - val data = (0 until 10).map(i => (i, i.toString)) - withParquetTable(data, "t") { - createParquetFile[(Int, String)](dir.toString).registerTempTable("dest") - withTempTable("dest") { - sql("INSERT OVERWRITE INTO dest SELECT * FROM t") - checkAnswer(table("dest"), data) - } - } - } - } - test("appending") { val data = (0 until 10).map(i => (i, i.toString)) withParquetTable(data, "t") { @@ -98,13 +85,4 @@ class ParquetQuerySuite2 extends QueryTest with ParquetTest { checkAnswer(sql(s"SELECT _1 FROM t WHERE _1 < 10"), (1 to 9).map(Row.apply(_))) } } - - test("SPARK-3536 regression: query empty Parquet file shouldn't throw") { - withTempDir { dir => - createParquetFile[(Int, String)](dir.toString).registerTempTable("t") - withTempTable("t") { - checkAnswer(sql("SELECT * FROM t"), Seq.empty[Row]) - } - } - } } diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala index bf56e60cf995f..a9a20a54bebe8 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala @@ -71,7 +71,7 @@ class LocalHiveContext(sc: SparkContext) extends HiveContext(sc) { class HiveContext(sc: SparkContext) extends SQLContext(sc) { self => - private[sql] override lazy val conf: SQLConf = new SQLConf { + protected[sql] override lazy val conf: SQLConf = new SQLConf { override def dialect: String = getConf(SQLConf.DIALECT, "hiveql") } @@ -348,7 +348,7 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { val hivePlanner = new SparkPlanner with HiveStrategies { val hiveContext = self - override def strategies: Seq[Strategy] = extraStrategies ++ Seq( + override def strategies: Seq[Strategy] = experimental.extraStrategies ++ Seq( DataSourceStrategy, HiveCommandStrategy(self), HiveDDLStrategy, diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala index 52e1f0d94fbd4..47431cef03e13 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TestHive.scala @@ -102,7 +102,7 @@ class TestHiveContext(sc: SparkContext) extends HiveContext(sc) { new this.QueryExecution { val logical = plan } /** Fewer partitions to speed up testing. */ - private[sql] override lazy val conf: SQLConf = new SQLConf { + protected[sql] override lazy val conf: SQLConf = new SQLConf { override def numShufflePartitions: Int = getConf(SQLConf.SHUFFLE_PARTITIONS, "5").toInt override def dialect: String = getConf(SQLConf.DIALECT, "hiveql") } From 6abc45e340d3be5f07236adc104db5f8dda0d514 Mon Sep 17 00:00:00 2001 From: Xiangrui Meng Date: Wed, 14 Jan 2015 18:54:17 -0800 Subject: [PATCH 257/320] [SPARK-5254][MLLIB] remove developers section from spark.ml guide Forgot to remove this section in #4052. Author: Xiangrui Meng Closes #4053 from mengxr/SPARK-5254-update and squashes the following commits: f295bde [Xiangrui Meng] remove developers section from spark.ml guide --- docs/ml-guide.md | 14 -------------- 1 file changed, 14 deletions(-) diff --git a/docs/ml-guide.md b/docs/ml-guide.md index 88158fd77edae..be178d7689fdd 100644 --- a/docs/ml-guide.md +++ b/docs/ml-guide.md @@ -689,17 +689,3 @@ Spark ML currently depends on MLlib and has the same dependencies. Please see the [MLlib Dependencies guide](mllib-guide.html#Dependencies) for more info. Spark ML also depends upon Spark SQL, but the relevant parts of Spark SQL do not bring additional dependencies. - -# Developers - -**Development plan** - -If all goes well, `spark.ml` will become the primary ML package at the time of the Spark 1.3 release. Initially, simple wrappers will be used to port algorithms to `spark.ml`, but eventually, code will be moved to `spark.ml` and `spark.mllib` will be deprecated. - -**Advice to developers** - -During the next development cycle, new algorithms should be contributed to `spark.mllib`, but we welcome patches sent to either package. If an algorithm is best expressed using the new API (e.g., feature transformers), we may ask for developers to use the new `spark.ml` API. -Wrappers for old and new algorithms can be contributed to `spark.ml`. - -Users will be able to use algorithms from either of the two packages. The main difficulty will be the differences in APIs between the two packages. - From 4b325c77a270ec32d6858d204313d4f161774fae Mon Sep 17 00:00:00 2001 From: Reynold Xin Date: Wed, 14 Jan 2015 20:31:02 -0800 Subject: [PATCH 258/320] [SPARK-5193][SQL] Tighten up HiveContext API 1. Removed the deprecated LocalHiveContext 2. Made private[sql] fields protected[sql] so they don't show up in javadoc. 3. Added javadoc to refreshTable. 4. Added Experimental tag to analyze command. Author: Reynold Xin Closes #4054 from rxin/hivecontext-api and squashes the following commits: 25cc00a [Reynold Xin] Add implicit conversion back. cbca886 [Reynold Xin] [SPARK-5193][SQL] Tighten up HiveContext API --- .../apache/spark/sql/hive/HiveContext.scala | 48 +++++-------------- 1 file changed, 13 insertions(+), 35 deletions(-) diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala index a9a20a54bebe8..4246b8b0918fd 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala @@ -17,7 +17,7 @@ package org.apache.spark.sql.hive -import java.io.{BufferedReader, File, InputStreamReader, PrintStream} +import java.io.{BufferedReader, InputStreamReader, PrintStream} import java.sql.{Date, Timestamp} import scala.collection.JavaConversions._ @@ -33,6 +33,7 @@ import org.apache.hadoop.hive.ql.session.SessionState import org.apache.hadoop.hive.serde2.io.{DateWritable, TimestampWritable} import org.apache.spark.SparkContext +import org.apache.spark.annotation.Experimental import org.apache.spark.sql._ import org.apache.spark.sql.catalyst.ScalaReflection import org.apache.spark.sql.catalyst.analysis.{Analyzer, EliminateAnalysisOperators, OverrideCatalog, OverrideFunctionRegistry} @@ -42,28 +43,6 @@ import org.apache.spark.sql.hive.execution.{HiveNativeCommand, DescribeHiveTable import org.apache.spark.sql.sources.DataSourceStrategy import org.apache.spark.sql.types._ -/** - * DEPRECATED: Use HiveContext instead. - */ -@deprecated(""" - Use HiveContext instead. It will still create a local metastore if one is not specified. - However, note that the default directory is ./metastore_db, not ./metastore - """, "1.1") -class LocalHiveContext(sc: SparkContext) extends HiveContext(sc) { - - lazy val metastorePath = new File("metastore").getCanonicalPath - lazy val warehousePath: String = new File("warehouse").getCanonicalPath - - /** Sets up the system initially or after a RESET command */ - protected def configure() { - setConf("javax.jdo.option.ConnectionURL", - s"jdbc:derby:;databaseName=$metastorePath;create=true") - setConf("hive.metastore.warehouse.dir", warehousePath) - } - - configure() // Must be called before initializing the catalog below. -} - /** * An instance of the Spark SQL execution engine that integrates with data stored in Hive. * Configuration for Hive is read from hive-site.xml on the classpath. @@ -80,7 +59,7 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { * are automatically converted to use the Spark SQL parquet table scan, instead of the Hive * SerDe. */ - private[spark] def convertMetastoreParquet: Boolean = + protected[sql] def convertMetastoreParquet: Boolean = getConf("spark.sql.hive.convertMetastoreParquet", "true") == "true" override protected[sql] def executePlan(plan: LogicalPlan): this.QueryExecution = @@ -97,14 +76,6 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { } } - @deprecated("hiveql() is deprecated as the sql function now parses using HiveQL by default. " + - s"The SQL dialect for parsing can be set using ${SQLConf.DIALECT}", "1.1") - def hiveql(hqlQuery: String): SchemaRDD = new SchemaRDD(this, HiveQl.parseSql(hqlQuery)) - - @deprecated("hql() is deprecated as the sql function now parses using HiveQL by default. " + - s"The SQL dialect for parsing can be set using ${SQLConf.DIALECT}", "1.1") - def hql(hqlQuery: String): SchemaRDD = hiveql(hqlQuery) - /** * Creates a table using the schema of the given class. * @@ -116,6 +87,12 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { catalog.createTable("default", tableName, ScalaReflection.attributesFor[A], allowExisting) } + /** + * Invalidate and refresh all the cached the metadata of the given table. For performance reasons, + * Spark SQL or the external data source library it uses might cache certain metadata about a + * table, such as the location of blocks. When those change outside of Spark SQL, users should + * call this function to invalidate the cache. + */ def refreshTable(tableName: String): Unit = { // TODO: Database support... catalog.refreshTable("default", tableName) @@ -133,6 +110,7 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { * Right now, it only supports Hive tables and it only updates the size of a Hive table * in the Hive metastore. */ + @Experimental def analyze(tableName: String) { val relation = EliminateAnalysisOperators(catalog.lookupRelation(Seq(tableName))) @@ -289,7 +267,6 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { results } - /** * Execute the command using Hive and return the results as a sequence. Each element * in the sequence is one row. @@ -345,7 +322,7 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { } @transient - val hivePlanner = new SparkPlanner with HiveStrategies { + private val hivePlanner = new SparkPlanner with HiveStrategies { val hiveContext = self override def strategies: Seq[Strategy] = experimental.extraStrategies ++ Seq( @@ -410,7 +387,8 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { } } -object HiveContext { + +private object HiveContext { protected val primitiveTypes = Seq(StringType, IntegerType, LongType, DoubleType, FloatType, BooleanType, ByteType, ShortType, DateType, TimestampType, BinaryType) From 3c8650c12ad7a97852e7bd76153210493fd83e92 Mon Sep 17 00:00:00 2001 From: Davies Liu Date: Thu, 15 Jan 2015 11:40:41 -0800 Subject: [PATCH 259/320] [SPARK-5224] [PySpark] improve performance of parallelize list/ndarray After the default batchSize changed to 0 (batched based on the size of object), but parallelize() still use BatchedSerializer with batchSize=1, this PR will use batchSize=1024 for parallelize by default. Also, BatchedSerializer did not work well with list and numpy.ndarray, this improve BatchedSerializer by using __len__ and __getslice__. Here is the benchmark for parallelize 1 millions int with list or ndarray: | before | after | improvements ------- | ------------ | ------------- | ------- list | 11.7 s | 0.8 s | 14x numpy.ndarray | 32 s | 0.7 s | 40x Author: Davies Liu Closes #4024 from davies/opt_numpy and squashes the following commits: 7618c7c [Davies Liu] improve performance of parallelize list/ndarray --- python/pyspark/context.py | 2 +- python/pyspark/serializers.py | 4 ++++ 2 files changed, 5 insertions(+), 1 deletion(-) diff --git a/python/pyspark/context.py b/python/pyspark/context.py index 593d74bca5fff..64f6a3ca6bf4c 100644 --- a/python/pyspark/context.py +++ b/python/pyspark/context.py @@ -319,7 +319,7 @@ def f(split, iterator): # Make sure we distribute data evenly if it's smaller than self.batchSize if "__len__" not in dir(c): c = list(c) # Make it a list so we can compute its length - batchSize = max(1, min(len(c) // numSlices, self._batchSize)) + batchSize = max(1, min(len(c) // numSlices, self._batchSize or 1024)) serializer = BatchedSerializer(self._unbatched_serializer, batchSize) serializer.dump_stream(c, tempFile) tempFile.close() diff --git a/python/pyspark/serializers.py b/python/pyspark/serializers.py index bd08c9a6d20d6..b8bda835174b2 100644 --- a/python/pyspark/serializers.py +++ b/python/pyspark/serializers.py @@ -181,6 +181,10 @@ def __init__(self, serializer, batchSize=UNLIMITED_BATCH_SIZE): def _batched(self, iterator): if self.batchSize == self.UNLIMITED_BATCH_SIZE: yield list(iterator) + elif hasattr(iterator, "__len__") and hasattr(iterator, "__getslice__"): + n = len(iterator) + for i in xrange(0, n, self.batchSize): + yield iterator[i: i + self.batchSize] else: items = [] count = 0 From 1881431dd50e93a6948e4966d33742727f27e917 Mon Sep 17 00:00:00 2001 From: Reynold Xin Date: Thu, 15 Jan 2015 16:15:12 -0800 Subject: [PATCH 260/320] [SPARK-5274][SQL] Reconcile Java and Scala UDFRegistration. As part of SPARK-5193: 1. Removed UDFRegistration as a mixin in SQLContext and made it a field ("udf"). 2. For Java UDFs, renamed dataType to returnType. 3. For Scala UDFs, added type tags. 4. Added all Java UDF registration methods to Scala's UDFRegistration. 5. Documentation Author: Reynold Xin Closes #4056 from rxin/udf-registration and squashes the following commits: ae9c556 [Reynold Xin] Updated example. 675a3c9 [Reynold Xin] Style fix 47c24ff [Reynold Xin] Python fix. 5f00c45 [Reynold Xin] Restore data type position in java udf and added typetags. 032f006 [Reynold Xin] [SPARK-5193][SQL] Reconcile Java and Scala UDFRegistration. --- python/pyspark/sql.py | 16 +- .../org/apache/spark/sql/SQLContext.scala | 29 +- .../apache/spark/sql/UdfRegistration.scala | 692 ++++++++++++++++-- .../org/apache/spark/sql/SQLQuerySuite.scala | 2 +- .../scala/org/apache/spark/sql/UDFSuite.scala | 9 +- .../spark/sql/UserDefinedTypeSuite.scala | 2 +- .../sql/hive/execution/HiveUdfSuite.scala | 2 +- 7 files changed, 674 insertions(+), 78 deletions(-) diff --git a/python/pyspark/sql.py b/python/pyspark/sql.py index 014ac1791c849..dcd3b60a6062b 100644 --- a/python/pyspark/sql.py +++ b/python/pyspark/sql.py @@ -1281,14 +1281,14 @@ def registerFunction(self, name, f, returnType=StringType()): self._sc._gateway._gateway_client) includes = ListConverter().convert(self._sc._python_includes, self._sc._gateway._gateway_client) - self._ssql_ctx.registerPython(name, - bytearray(pickled_command), - env, - includes, - self._sc.pythonExec, - broadcast_vars, - self._sc._javaAccumulator, - returnType.json()) + self._ssql_ctx.udf().registerPython(name, + bytearray(pickled_command), + env, + includes, + self._sc.pythonExec, + broadcast_vars, + self._sc._javaAccumulator, + returnType.json()) def inferSchema(self, rdd, samplingRatio=None): """Infer and apply a schema to an RDD of L{Row}. diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala index 279671ced0a17..8ad1753dab757 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala @@ -54,7 +54,6 @@ class SQLContext(@transient val sparkContext: SparkContext) extends org.apache.spark.Logging with CacheManager with ExpressionConversions - with UDFRegistration with Serializable { self => @@ -338,6 +337,34 @@ class SQLContext(@transient val sparkContext: SparkContext) */ val experimental: ExperimentalMethods = new ExperimentalMethods(this) + /** + * A collection of methods for registering user-defined functions (UDF). + * + * The following example registers a Scala closure as UDF: + * {{{ + * sqlContext.udf.register("myUdf", (arg1: Int, arg2: String) => arg2 + arg1) + * }}} + * + * The following example registers a UDF in Java: + * {{{ + * sqlContext.udf().register("myUDF", + * new UDF2() { + * @Override + * public String call(Integer arg1, String arg2) { + * return arg2 + arg1; + * } + * }, DataTypes.StringType); + * }}} + * + * Or, to use Java 8 lambda syntax: + * {{{ + * sqlContext.udf().register("myUDF", + * (Integer arg1, String arg2) -> arg2 + arg1), + * DataTypes.StringType); + * }}} + */ + val udf: UDFRegistration = new UDFRegistration(this) + protected[sql] class SparkPlanner extends SparkStrategies { val sparkContext: SparkContext = self.sparkContext diff --git a/sql/core/src/main/scala/org/apache/spark/sql/UdfRegistration.scala b/sql/core/src/main/scala/org/apache/spark/sql/UdfRegistration.scala index 5fb472686c9e1..2e9d037f93c03 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/UdfRegistration.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/UdfRegistration.scala @@ -19,22 +19,26 @@ package org.apache.spark.sql import java.util.{List => JList, Map => JMap} +import scala.reflect.runtime.universe.TypeTag + import org.apache.spark.Accumulator import org.apache.spark.api.python.PythonBroadcast import org.apache.spark.broadcast.Broadcast +import org.apache.spark.sql.api.java._ import org.apache.spark.sql.catalyst.ScalaReflection import org.apache.spark.sql.catalyst.expressions.{Expression, ScalaUdf} import org.apache.spark.sql.execution.PythonUDF +import org.apache.spark.sql.types.DataType -import scala.reflect.runtime.universe.{TypeTag, typeTag} /** - * Functions for registering scala lambda functions as UDFs in a SQLContext. + * Functions for registering user-defined functions. */ -private[sql] trait UDFRegistration { - self: SQLContext => +class UDFRegistration (sqlContext: SQLContext) extends org.apache.spark.Logging { + + private val functionRegistry = sqlContext.functionRegistry - private[spark] def registerPython( + protected[sql] def registerPython( name: String, command: Array[Byte], envVars: JMap[String, String], @@ -55,7 +59,7 @@ private[sql] trait UDFRegistration { """.stripMargin) - val dataType = parseDataType(stringDataType) + val dataType = sqlContext.parseDataType(stringDataType) def builder(e: Seq[Expression]) = PythonUDF( @@ -72,133 +76,699 @@ private[sql] trait UDFRegistration { functionRegistry.registerFunction(name, builder) } - /** registerFunction 0-22 were generated by this script + // scalastyle:off + + /* registerFunction 0-22 were generated by this script (0 to 22).map { x => - val types = (1 to x).foldRight("T")((_, s) => {s"_, $s"}) - s""" - def registerFunction[T: TypeTag](name: String, func: Function$x[$types]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + val types = (1 to x).foldRight("RT")((i, s) => {s"A$i, $s"}) + val typeTags = (1 to x).map(i => s"A${i}: TypeTag").foldLeft("RT: TypeTag")(_ + ", " + _) + val argDocs = (1 to x).map(i => s" * @tparam A$i type of the UDF argument at position $i.").foldLeft("")(_ + "\n" + _) + println(s""" + /** + * Register a Scala closure of ${x} arguments as user-defined function (UDF). + * @tparam RT return type of UDF.$argDocs + */ + def register[$typeTags](name: String, func: Function$x[$types]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) - } - """ + }""") } - */ - // scalastyle:off - def registerFunction[T: TypeTag](name: String, func: Function0[T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + (1 to 22).foreach { i => + val extTypeArgs = (1 to i).map(_ => "_").mkString(", ") + val anyTypeArgs = (1 to i).map(_ => "Any").mkString(", ") + val anyCast = s".asInstanceOf[UDF$i[$anyTypeArgs, Any]]" + val anyParams = (1 to i).map(_ => "_: Any").mkString(", ") + println(s""" + |/** + | * Register a user-defined function with ${i} arguments. + | */ + |def register(name: String, f: UDF$i[$extTypeArgs, _], returnType: DataType) = { + | functionRegistry.registerFunction( + | name, + | (e: Seq[Expression]) => ScalaUdf(f$anyCast.call($anyParams), returnType, e)) + |}""".stripMargin) + } + */ + + /** + * Register a Scala closure of 0 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + */ + def register[RT: TypeTag](name: String, func: Function0[RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function1[_, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 1 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + */ + def register[RT: TypeTag, A1: TypeTag](name: String, func: Function1[A1, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function2[_, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 2 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag](name: String, func: Function2[A1, A2, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function3[_, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 3 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag](name: String, func: Function3[A1, A2, A3, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function4[_, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 4 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag](name: String, func: Function4[A1, A2, A3, A4, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function5[_, _, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 5 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + * @tparam A5 type of the UDF argument at position 5. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag](name: String, func: Function5[A1, A2, A3, A4, A5, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function6[_, _, _, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 6 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + * @tparam A5 type of the UDF argument at position 5. + * @tparam A6 type of the UDF argument at position 6. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag](name: String, func: Function6[A1, A2, A3, A4, A5, A6, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function7[_, _, _, _, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 7 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + * @tparam A5 type of the UDF argument at position 5. + * @tparam A6 type of the UDF argument at position 6. + * @tparam A7 type of the UDF argument at position 7. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag](name: String, func: Function7[A1, A2, A3, A4, A5, A6, A7, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function8[_, _, _, _, _, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 8 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + * @tparam A5 type of the UDF argument at position 5. + * @tparam A6 type of the UDF argument at position 6. + * @tparam A7 type of the UDF argument at position 7. + * @tparam A8 type of the UDF argument at position 8. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag](name: String, func: Function8[A1, A2, A3, A4, A5, A6, A7, A8, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function9[_, _, _, _, _, _, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 9 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + * @tparam A5 type of the UDF argument at position 5. + * @tparam A6 type of the UDF argument at position 6. + * @tparam A7 type of the UDF argument at position 7. + * @tparam A8 type of the UDF argument at position 8. + * @tparam A9 type of the UDF argument at position 9. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag](name: String, func: Function9[A1, A2, A3, A4, A5, A6, A7, A8, A9, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function10[_, _, _, _, _, _, _, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 10 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + * @tparam A5 type of the UDF argument at position 5. + * @tparam A6 type of the UDF argument at position 6. + * @tparam A7 type of the UDF argument at position 7. + * @tparam A8 type of the UDF argument at position 8. + * @tparam A9 type of the UDF argument at position 9. + * @tparam A10 type of the UDF argument at position 10. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag](name: String, func: Function10[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function11[_, _, _, _, _, _, _, _, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 11 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + * @tparam A5 type of the UDF argument at position 5. + * @tparam A6 type of the UDF argument at position 6. + * @tparam A7 type of the UDF argument at position 7. + * @tparam A8 type of the UDF argument at position 8. + * @tparam A9 type of the UDF argument at position 9. + * @tparam A10 type of the UDF argument at position 10. + * @tparam A11 type of the UDF argument at position 11. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag](name: String, func: Function11[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function12[_, _, _, _, _, _, _, _, _, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 12 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + * @tparam A5 type of the UDF argument at position 5. + * @tparam A6 type of the UDF argument at position 6. + * @tparam A7 type of the UDF argument at position 7. + * @tparam A8 type of the UDF argument at position 8. + * @tparam A9 type of the UDF argument at position 9. + * @tparam A10 type of the UDF argument at position 10. + * @tparam A11 type of the UDF argument at position 11. + * @tparam A12 type of the UDF argument at position 12. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag](name: String, func: Function12[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function13[_, _, _, _, _, _, _, _, _, _, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 13 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + * @tparam A5 type of the UDF argument at position 5. + * @tparam A6 type of the UDF argument at position 6. + * @tparam A7 type of the UDF argument at position 7. + * @tparam A8 type of the UDF argument at position 8. + * @tparam A9 type of the UDF argument at position 9. + * @tparam A10 type of the UDF argument at position 10. + * @tparam A11 type of the UDF argument at position 11. + * @tparam A12 type of the UDF argument at position 12. + * @tparam A13 type of the UDF argument at position 13. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag](name: String, func: Function13[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function14[_, _, _, _, _, _, _, _, _, _, _, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 14 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + * @tparam A5 type of the UDF argument at position 5. + * @tparam A6 type of the UDF argument at position 6. + * @tparam A7 type of the UDF argument at position 7. + * @tparam A8 type of the UDF argument at position 8. + * @tparam A9 type of the UDF argument at position 9. + * @tparam A10 type of the UDF argument at position 10. + * @tparam A11 type of the UDF argument at position 11. + * @tparam A12 type of the UDF argument at position 12. + * @tparam A13 type of the UDF argument at position 13. + * @tparam A14 type of the UDF argument at position 14. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag, A14: TypeTag](name: String, func: Function14[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function15[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 15 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + * @tparam A5 type of the UDF argument at position 5. + * @tparam A6 type of the UDF argument at position 6. + * @tparam A7 type of the UDF argument at position 7. + * @tparam A8 type of the UDF argument at position 8. + * @tparam A9 type of the UDF argument at position 9. + * @tparam A10 type of the UDF argument at position 10. + * @tparam A11 type of the UDF argument at position 11. + * @tparam A12 type of the UDF argument at position 12. + * @tparam A13 type of the UDF argument at position 13. + * @tparam A14 type of the UDF argument at position 14. + * @tparam A15 type of the UDF argument at position 15. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag, A14: TypeTag, A15: TypeTag](name: String, func: Function15[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function16[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 16 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + * @tparam A5 type of the UDF argument at position 5. + * @tparam A6 type of the UDF argument at position 6. + * @tparam A7 type of the UDF argument at position 7. + * @tparam A8 type of the UDF argument at position 8. + * @tparam A9 type of the UDF argument at position 9. + * @tparam A10 type of the UDF argument at position 10. + * @tparam A11 type of the UDF argument at position 11. + * @tparam A12 type of the UDF argument at position 12. + * @tparam A13 type of the UDF argument at position 13. + * @tparam A14 type of the UDF argument at position 14. + * @tparam A15 type of the UDF argument at position 15. + * @tparam A16 type of the UDF argument at position 16. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag, A14: TypeTag, A15: TypeTag, A16: TypeTag](name: String, func: Function16[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function17[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 17 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + * @tparam A5 type of the UDF argument at position 5. + * @tparam A6 type of the UDF argument at position 6. + * @tparam A7 type of the UDF argument at position 7. + * @tparam A8 type of the UDF argument at position 8. + * @tparam A9 type of the UDF argument at position 9. + * @tparam A10 type of the UDF argument at position 10. + * @tparam A11 type of the UDF argument at position 11. + * @tparam A12 type of the UDF argument at position 12. + * @tparam A13 type of the UDF argument at position 13. + * @tparam A14 type of the UDF argument at position 14. + * @tparam A15 type of the UDF argument at position 15. + * @tparam A16 type of the UDF argument at position 16. + * @tparam A17 type of the UDF argument at position 17. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag, A14: TypeTag, A15: TypeTag, A16: TypeTag, A17: TypeTag](name: String, func: Function17[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function18[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 18 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + * @tparam A5 type of the UDF argument at position 5. + * @tparam A6 type of the UDF argument at position 6. + * @tparam A7 type of the UDF argument at position 7. + * @tparam A8 type of the UDF argument at position 8. + * @tparam A9 type of the UDF argument at position 9. + * @tparam A10 type of the UDF argument at position 10. + * @tparam A11 type of the UDF argument at position 11. + * @tparam A12 type of the UDF argument at position 12. + * @tparam A13 type of the UDF argument at position 13. + * @tparam A14 type of the UDF argument at position 14. + * @tparam A15 type of the UDF argument at position 15. + * @tparam A16 type of the UDF argument at position 16. + * @tparam A17 type of the UDF argument at position 17. + * @tparam A18 type of the UDF argument at position 18. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag, A14: TypeTag, A15: TypeTag, A16: TypeTag, A17: TypeTag, A18: TypeTag](name: String, func: Function18[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function19[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 19 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + * @tparam A5 type of the UDF argument at position 5. + * @tparam A6 type of the UDF argument at position 6. + * @tparam A7 type of the UDF argument at position 7. + * @tparam A8 type of the UDF argument at position 8. + * @tparam A9 type of the UDF argument at position 9. + * @tparam A10 type of the UDF argument at position 10. + * @tparam A11 type of the UDF argument at position 11. + * @tparam A12 type of the UDF argument at position 12. + * @tparam A13 type of the UDF argument at position 13. + * @tparam A14 type of the UDF argument at position 14. + * @tparam A15 type of the UDF argument at position 15. + * @tparam A16 type of the UDF argument at position 16. + * @tparam A17 type of the UDF argument at position 17. + * @tparam A18 type of the UDF argument at position 18. + * @tparam A19 type of the UDF argument at position 19. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag, A14: TypeTag, A15: TypeTag, A16: TypeTag, A17: TypeTag, A18: TypeTag, A19: TypeTag](name: String, func: Function19[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, A19, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function20[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 20 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + * @tparam A5 type of the UDF argument at position 5. + * @tparam A6 type of the UDF argument at position 6. + * @tparam A7 type of the UDF argument at position 7. + * @tparam A8 type of the UDF argument at position 8. + * @tparam A9 type of the UDF argument at position 9. + * @tparam A10 type of the UDF argument at position 10. + * @tparam A11 type of the UDF argument at position 11. + * @tparam A12 type of the UDF argument at position 12. + * @tparam A13 type of the UDF argument at position 13. + * @tparam A14 type of the UDF argument at position 14. + * @tparam A15 type of the UDF argument at position 15. + * @tparam A16 type of the UDF argument at position 16. + * @tparam A17 type of the UDF argument at position 17. + * @tparam A18 type of the UDF argument at position 18. + * @tparam A19 type of the UDF argument at position 19. + * @tparam A20 type of the UDF argument at position 20. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag, A14: TypeTag, A15: TypeTag, A16: TypeTag, A17: TypeTag, A18: TypeTag, A19: TypeTag, A20: TypeTag](name: String, func: Function20[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, A19, A20, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function21[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 21 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + * @tparam A5 type of the UDF argument at position 5. + * @tparam A6 type of the UDF argument at position 6. + * @tparam A7 type of the UDF argument at position 7. + * @tparam A8 type of the UDF argument at position 8. + * @tparam A9 type of the UDF argument at position 9. + * @tparam A10 type of the UDF argument at position 10. + * @tparam A11 type of the UDF argument at position 11. + * @tparam A12 type of the UDF argument at position 12. + * @tparam A13 type of the UDF argument at position 13. + * @tparam A14 type of the UDF argument at position 14. + * @tparam A15 type of the UDF argument at position 15. + * @tparam A16 type of the UDF argument at position 16. + * @tparam A17 type of the UDF argument at position 17. + * @tparam A18 type of the UDF argument at position 18. + * @tparam A19 type of the UDF argument at position 19. + * @tparam A20 type of the UDF argument at position 20. + * @tparam A21 type of the UDF argument at position 21. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag, A14: TypeTag, A15: TypeTag, A16: TypeTag, A17: TypeTag, A18: TypeTag, A19: TypeTag, A20: TypeTag, A21: TypeTag](name: String, func: Function21[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, A19, A20, A21, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } - def registerFunction[T: TypeTag](name: String, func: Function22[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]): Unit = { - def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[T].dataType, e) + /** + * Register a Scala closure of 22 arguments as user-defined function (UDF). + * @tparam RT return type of UDF. + * @tparam A1 type of the UDF argument at position 1. + * @tparam A2 type of the UDF argument at position 2. + * @tparam A3 type of the UDF argument at position 3. + * @tparam A4 type of the UDF argument at position 4. + * @tparam A5 type of the UDF argument at position 5. + * @tparam A6 type of the UDF argument at position 6. + * @tparam A7 type of the UDF argument at position 7. + * @tparam A8 type of the UDF argument at position 8. + * @tparam A9 type of the UDF argument at position 9. + * @tparam A10 type of the UDF argument at position 10. + * @tparam A11 type of the UDF argument at position 11. + * @tparam A12 type of the UDF argument at position 12. + * @tparam A13 type of the UDF argument at position 13. + * @tparam A14 type of the UDF argument at position 14. + * @tparam A15 type of the UDF argument at position 15. + * @tparam A16 type of the UDF argument at position 16. + * @tparam A17 type of the UDF argument at position 17. + * @tparam A18 type of the UDF argument at position 18. + * @tparam A19 type of the UDF argument at position 19. + * @tparam A20 type of the UDF argument at position 20. + * @tparam A21 type of the UDF argument at position 21. + * @tparam A22 type of the UDF argument at position 22. + */ + def register[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag, A14: TypeTag, A15: TypeTag, A16: TypeTag, A17: TypeTag, A18: TypeTag, A19: TypeTag, A20: TypeTag, A21: TypeTag, A22: TypeTag](name: String, func: Function22[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, A19, A20, A21, A22, RT]): Unit = { + def builder(e: Seq[Expression]) = ScalaUdf(func, ScalaReflection.schemaFor[RT].dataType, e) functionRegistry.registerFunction(name, builder) } + + /** + * Register a user-defined function with 1 arguments. + */ + def register(name: String, f: UDF1[_, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF1[Any, Any]].call(_: Any), returnType, e)) + } + + /** + * Register a user-defined function with 2 arguments. + */ + def register(name: String, f: UDF2[_, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF2[Any, Any, Any]].call(_: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 3 arguments. + */ + def register(name: String, f: UDF3[_, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF3[Any, Any, Any, Any]].call(_: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 4 arguments. + */ + def register(name: String, f: UDF4[_, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF4[Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 5 arguments. + */ + def register(name: String, f: UDF5[_, _, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF5[Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 6 arguments. + */ + def register(name: String, f: UDF6[_, _, _, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF6[Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 7 arguments. + */ + def register(name: String, f: UDF7[_, _, _, _, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF7[Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 8 arguments. + */ + def register(name: String, f: UDF8[_, _, _, _, _, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF8[Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 9 arguments. + */ + def register(name: String, f: UDF9[_, _, _, _, _, _, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF9[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 10 arguments. + */ + def register(name: String, f: UDF10[_, _, _, _, _, _, _, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF10[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 11 arguments. + */ + def register(name: String, f: UDF11[_, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF11[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 12 arguments. + */ + def register(name: String, f: UDF12[_, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF12[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 13 arguments. + */ + def register(name: String, f: UDF13[_, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF13[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 14 arguments. + */ + def register(name: String, f: UDF14[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF14[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 15 arguments. + */ + def register(name: String, f: UDF15[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF15[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 16 arguments. + */ + def register(name: String, f: UDF16[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF16[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 17 arguments. + */ + def register(name: String, f: UDF17[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF17[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 18 arguments. + */ + def register(name: String, f: UDF18[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF18[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 19 arguments. + */ + def register(name: String, f: UDF19[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF19[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 20 arguments. + */ + def register(name: String, f: UDF20[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF20[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 21 arguments. + */ + def register(name: String, f: UDF21[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF21[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), returnType, e)) + } + + /** + * Register a user-defined function with 22 arguments. + */ + def register(name: String, f: UDF22[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType) = { + functionRegistry.registerFunction( + name, + (e: Seq[Expression]) => ScalaUdf(f.asInstanceOf[UDF22[Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any, Any]].call(_: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any, _: Any), returnType, e)) + } + // scalastyle:on } diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala index cbdb3e64bb66b..6c95bad6974d1 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala @@ -766,7 +766,7 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll { } test("SPARK-3371 Renaming a function expression with group by gives error") { - registerFunction("len", (s: String) => s.length) + udf.register("len", (s: String) => s.length) checkAnswer( sql("SELECT len(value) as temp FROM testData WHERE key = 1 group by len(value)"), 1) } diff --git a/sql/core/src/test/scala/org/apache/spark/sql/UDFSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/UDFSuite.scala index 720953ae3765a..0c98120031242 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/UDFSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/UDFSuite.scala @@ -27,23 +27,22 @@ case class FunctionResult(f1: String, f2: String) class UDFSuite extends QueryTest { test("Simple UDF") { - registerFunction("strLenScala", (_: String).length) + udf.register("strLenScala", (_: String).length) assert(sql("SELECT strLenScala('test')").first().getInt(0) === 4) } test("ZeroArgument UDF") { - registerFunction("random0", () => { Math.random()}) + udf.register("random0", () => { Math.random()}) assert(sql("SELECT random0()").first().getDouble(0) >= 0.0) } test("TwoArgument UDF") { - registerFunction("strLenScala", (_: String).length + (_:Int)) + udf.register("strLenScala", (_: String).length + (_:Int)) assert(sql("SELECT strLenScala('test', 1)").first().getInt(0) === 5) } - test("struct UDF") { - registerFunction("returnStruct", (f1: String, f2: String) => FunctionResult(f1, f2)) + udf.register("returnStruct", (f1: String, f2: String) => FunctionResult(f1, f2)) val result= sql("SELECT returnStruct('test', 'test2') as ret") diff --git a/sql/core/src/test/scala/org/apache/spark/sql/UserDefinedTypeSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/UserDefinedTypeSuite.scala index a0d54d17f5f13..fbc8704f7837b 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/UserDefinedTypeSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/UserDefinedTypeSuite.scala @@ -81,7 +81,7 @@ class UserDefinedTypeSuite extends QueryTest { } test("UDTs and UDFs") { - registerFunction("testType", (d: MyDenseVector) => d.isInstanceOf[MyDenseVector]) + udf.register("testType", (d: MyDenseVector) => d.isInstanceOf[MyDenseVector]) pointsRDD.registerTempTable("points") checkAnswer( sql("SELECT testType(features) from points"), diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUdfSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUdfSuite.scala index 5fc8d8dbe3a9f..5dafcd6c0a76a 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUdfSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUdfSuite.scala @@ -50,7 +50,7 @@ class HiveUdfSuite extends QueryTest { import TestHive._ test("spark sql udf test that returns a struct") { - registerFunction("getStruct", (_: Int) => Fields(1, 2, 3, 4, 5)) + udf.register("getStruct", (_: Int) => Fields(1, 2, 3, 4, 5)) assert(sql( """ |SELECT getStruct(1).f1, From 65858ba555c4c0aea988b8f4b1c8476c42377eb9 Mon Sep 17 00:00:00 2001 From: Kousuke Saruta Date: Thu, 15 Jan 2015 17:07:44 -0800 Subject: [PATCH 261/320] [Minor] Fix tiny typo in BlockManager In BlockManager, there is a word `BlockTranserService` but I think it's typo for `BlockTransferService`. Author: Kousuke Saruta Closes #4046 from sarutak/fix-tiny-typo and squashes the following commits: a3e2a2f [Kousuke Saruta] Fixed tiny typo in BlockManager --- .../main/scala/org/apache/spark/storage/BlockManager.scala | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/storage/BlockManager.scala b/core/src/main/scala/org/apache/spark/storage/BlockManager.scala index d7b184f8a10e9..1427305d91cff 100644 --- a/core/src/main/scala/org/apache/spark/storage/BlockManager.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockManager.scala @@ -34,10 +34,9 @@ import org.apache.spark.executor._ import org.apache.spark.io.CompressionCodec import org.apache.spark.network._ import org.apache.spark.network.buffer.{ManagedBuffer, NioManagedBuffer} -import org.apache.spark.network.netty.{SparkTransportConf, NettyBlockTransferService} +import org.apache.spark.network.netty.SparkTransportConf import org.apache.spark.network.shuffle.ExternalShuffleClient import org.apache.spark.network.shuffle.protocol.ExecutorShuffleInfo -import org.apache.spark.network.util.{ConfigProvider, TransportConf} import org.apache.spark.serializer.Serializer import org.apache.spark.shuffle.ShuffleManager import org.apache.spark.shuffle.hash.HashShuffleManager @@ -120,7 +119,7 @@ private[spark] class BlockManager( private[spark] var shuffleServerId: BlockManagerId = _ // Client to read other executors' shuffle files. This is either an external service, or just the - // standard BlockTranserService to directly connect to other Executors. + // standard BlockTransferService to directly connect to other Executors. private[spark] val shuffleClient = if (externalShuffleServiceEnabled) { val transConf = SparkTransportConf.fromSparkConf(conf, numUsableCores) new ExternalShuffleClient(transConf, securityManager, securityManager.isAuthenticationEnabled()) From 96c2c714f4f9abe20d4c42d99ffaafcb269714a1 Mon Sep 17 00:00:00 2001 From: Kostas Sakellis Date: Thu, 15 Jan 2015 17:53:42 -0800 Subject: [PATCH 262/320] [SPARK-4857] [CORE] Adds Executor membership events to SparkListener Adds onExecutorAdded and onExecutorRemoved events to the SparkListener. This will allow a client to get notified when an executor has been added/removed and provide additional information such as how many vcores it is consuming. In addition, this commit adds a SparkListenerAdapter to the Java API that provides default implementations to the SparkListener. This is to get around the fact that default implementations for traits don't work in Java. Having Java clients extend SparkListenerAdapter moving forward will prevent breakage in java when we add new events to SparkListener. Author: Kostas Sakellis Closes #3711 from ksakellis/kostas-spark-4857 and squashes the following commits: 946d2c5 [Kostas Sakellis] Added executorAdded/Removed events to MesosSchedulerBackend b1d054a [Kostas Sakellis] Remove executorInfo from ExecutorRemoved event 1727b38 [Kostas Sakellis] Renamed ExecutorDetails back to ExecutorInfo and other CR feedback 14fe78d [Kostas Sakellis] Added executor added/removed events to json protocol 93d087b [Kostas Sakellis] [SPARK-4857] [CORE] Adds Executor membership events to SparkListener --- .../org/apache/spark/JavaSparkListener.java | 97 +++++++++++++++++++ .../spark/deploy/master/ApplicationInfo.scala | 14 +-- ...{ExecutorInfo.scala => ExecutorDesc.scala} | 4 +- .../apache/spark/deploy/master/Master.scala | 2 +- .../spark/deploy/master/WorkerInfo.scala | 6 +- .../deploy/master/ui/ApplicationPage.scala | 4 +- .../scheduler/EventLoggingListener.scala | 4 + .../spark/scheduler/SparkListener.scala | 22 ++++- .../spark/scheduler/SparkListenerBus.scala | 4 + .../CoarseGrainedSchedulerBackend.scala | 6 +- .../scheduler/cluster/ExecutorData.scala | 6 +- .../scheduler/cluster/ExecutorInfo.scala | 45 +++++++++ .../cluster/mesos/MesosSchedulerBackend.scala | 32 ++++-- .../org/apache/spark/util/JsonProtocol.scala | 40 +++++++- .../scheduler/EventLoggingListenerSuite.scala | 3 +- .../SparkListenerWithClusterSuite.scala | 62 ++++++++++++ .../mesos/MesosSchedulerBackendSuite.scala | 16 ++- .../apache/spark/util/JsonProtocolSuite.scala | 41 ++++++++ 18 files changed, 375 insertions(+), 33 deletions(-) create mode 100644 core/src/main/java/org/apache/spark/JavaSparkListener.java rename core/src/main/scala/org/apache/spark/deploy/master/{ExecutorInfo.scala => ExecutorDesc.scala} (95%) create mode 100644 core/src/main/scala/org/apache/spark/scheduler/cluster/ExecutorInfo.scala create mode 100644 core/src/test/scala/org/apache/spark/scheduler/SparkListenerWithClusterSuite.scala diff --git a/core/src/main/java/org/apache/spark/JavaSparkListener.java b/core/src/main/java/org/apache/spark/JavaSparkListener.java new file mode 100644 index 0000000000000..646496f313507 --- /dev/null +++ b/core/src/main/java/org/apache/spark/JavaSparkListener.java @@ -0,0 +1,97 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark; + +import org.apache.spark.scheduler.SparkListener; +import org.apache.spark.scheduler.SparkListenerApplicationEnd; +import org.apache.spark.scheduler.SparkListenerApplicationStart; +import org.apache.spark.scheduler.SparkListenerBlockManagerAdded; +import org.apache.spark.scheduler.SparkListenerBlockManagerRemoved; +import org.apache.spark.scheduler.SparkListenerEnvironmentUpdate; +import org.apache.spark.scheduler.SparkListenerExecutorAdded; +import org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate; +import org.apache.spark.scheduler.SparkListenerExecutorRemoved; +import org.apache.spark.scheduler.SparkListenerJobEnd; +import org.apache.spark.scheduler.SparkListenerJobStart; +import org.apache.spark.scheduler.SparkListenerStageCompleted; +import org.apache.spark.scheduler.SparkListenerStageSubmitted; +import org.apache.spark.scheduler.SparkListenerTaskEnd; +import org.apache.spark.scheduler.SparkListenerTaskGettingResult; +import org.apache.spark.scheduler.SparkListenerTaskStart; +import org.apache.spark.scheduler.SparkListenerUnpersistRDD; + +/** + * Java clients should extend this class instead of implementing + * SparkListener directly. This is to prevent java clients + * from breaking when new events are added to the SparkListener + * trait. + * + * This is a concrete class instead of abstract to enforce + * new events get added to both the SparkListener and this adapter + * in lockstep. + */ +public class JavaSparkListener implements SparkListener { + + @Override + public void onStageCompleted(SparkListenerStageCompleted stageCompleted) { } + + @Override + public void onStageSubmitted(SparkListenerStageSubmitted stageSubmitted) { } + + @Override + public void onTaskStart(SparkListenerTaskStart taskStart) { } + + @Override + public void onTaskGettingResult(SparkListenerTaskGettingResult taskGettingResult) { } + + @Override + public void onTaskEnd(SparkListenerTaskEnd taskEnd) { } + + @Override + public void onJobStart(SparkListenerJobStart jobStart) { } + + @Override + public void onJobEnd(SparkListenerJobEnd jobEnd) { } + + @Override + public void onEnvironmentUpdate(SparkListenerEnvironmentUpdate environmentUpdate) { } + + @Override + public void onBlockManagerAdded(SparkListenerBlockManagerAdded blockManagerAdded) { } + + @Override + public void onBlockManagerRemoved(SparkListenerBlockManagerRemoved blockManagerRemoved) { } + + @Override + public void onUnpersistRDD(SparkListenerUnpersistRDD unpersistRDD) { } + + @Override + public void onApplicationStart(SparkListenerApplicationStart applicationStart) { } + + @Override + public void onApplicationEnd(SparkListenerApplicationEnd applicationEnd) { } + + @Override + public void onExecutorMetricsUpdate(SparkListenerExecutorMetricsUpdate executorMetricsUpdate) { } + + @Override + public void onExecutorAdded(SparkListenerExecutorAdded executorAdded) { } + + @Override + public void onExecutorRemoved(SparkListenerExecutorRemoved executorRemoved) { } +} diff --git a/core/src/main/scala/org/apache/spark/deploy/master/ApplicationInfo.scala b/core/src/main/scala/org/apache/spark/deploy/master/ApplicationInfo.scala index ad7d81747c377..ede0a9dbefb8d 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/ApplicationInfo.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/ApplicationInfo.scala @@ -38,8 +38,8 @@ private[spark] class ApplicationInfo( extends Serializable { @transient var state: ApplicationState.Value = _ - @transient var executors: mutable.HashMap[Int, ExecutorInfo] = _ - @transient var removedExecutors: ArrayBuffer[ExecutorInfo] = _ + @transient var executors: mutable.HashMap[Int, ExecutorDesc] = _ + @transient var removedExecutors: ArrayBuffer[ExecutorDesc] = _ @transient var coresGranted: Int = _ @transient var endTime: Long = _ @transient var appSource: ApplicationSource = _ @@ -55,12 +55,12 @@ private[spark] class ApplicationInfo( private def init() { state = ApplicationState.WAITING - executors = new mutable.HashMap[Int, ExecutorInfo] + executors = new mutable.HashMap[Int, ExecutorDesc] coresGranted = 0 endTime = -1L appSource = new ApplicationSource(this) nextExecutorId = 0 - removedExecutors = new ArrayBuffer[ExecutorInfo] + removedExecutors = new ArrayBuffer[ExecutorDesc] } private def newExecutorId(useID: Option[Int] = None): Int = { @@ -75,14 +75,14 @@ private[spark] class ApplicationInfo( } } - def addExecutor(worker: WorkerInfo, cores: Int, useID: Option[Int] = None): ExecutorInfo = { - val exec = new ExecutorInfo(newExecutorId(useID), this, worker, cores, desc.memoryPerSlave) + def addExecutor(worker: WorkerInfo, cores: Int, useID: Option[Int] = None): ExecutorDesc = { + val exec = new ExecutorDesc(newExecutorId(useID), this, worker, cores, desc.memoryPerSlave) executors(exec.id) = exec coresGranted += cores exec } - def removeExecutor(exec: ExecutorInfo) { + def removeExecutor(exec: ExecutorDesc) { if (executors.contains(exec.id)) { removedExecutors += executors(exec.id) executors -= exec.id diff --git a/core/src/main/scala/org/apache/spark/deploy/master/ExecutorInfo.scala b/core/src/main/scala/org/apache/spark/deploy/master/ExecutorDesc.scala similarity index 95% rename from core/src/main/scala/org/apache/spark/deploy/master/ExecutorInfo.scala rename to core/src/main/scala/org/apache/spark/deploy/master/ExecutorDesc.scala index d417070c51016..5d620dfcabad5 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/ExecutorInfo.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/ExecutorDesc.scala @@ -19,7 +19,7 @@ package org.apache.spark.deploy.master import org.apache.spark.deploy.{ExecutorDescription, ExecutorState} -private[spark] class ExecutorInfo( +private[spark] class ExecutorDesc( val id: Int, val application: ApplicationInfo, val worker: WorkerInfo, @@ -37,7 +37,7 @@ private[spark] class ExecutorInfo( override def equals(other: Any): Boolean = { other match { - case info: ExecutorInfo => + case info: ExecutorDesc => fullId == info.fullId && worker.id == info.worker.id && cores == info.cores && diff --git a/core/src/main/scala/org/apache/spark/deploy/master/Master.scala b/core/src/main/scala/org/apache/spark/deploy/master/Master.scala index 4b631ec639071..d92d99310a583 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/Master.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/Master.scala @@ -581,7 +581,7 @@ private[spark] class Master( } } - def launchExecutor(worker: WorkerInfo, exec: ExecutorInfo) { + def launchExecutor(worker: WorkerInfo, exec: ExecutorDesc) { logInfo("Launching executor " + exec.fullId + " on worker " + worker.id) worker.addExecutor(exec) worker.actor ! LaunchExecutor(masterUrl, diff --git a/core/src/main/scala/org/apache/spark/deploy/master/WorkerInfo.scala b/core/src/main/scala/org/apache/spark/deploy/master/WorkerInfo.scala index 473ddc23ff0f3..e94aae93e4495 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/WorkerInfo.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/WorkerInfo.scala @@ -38,7 +38,7 @@ private[spark] class WorkerInfo( Utils.checkHost(host, "Expected hostname") assert (port > 0) - @transient var executors: mutable.HashMap[String, ExecutorInfo] = _ // executorId => info + @transient var executors: mutable.HashMap[String, ExecutorDesc] = _ // executorId => info @transient var drivers: mutable.HashMap[String, DriverInfo] = _ // driverId => info @transient var state: WorkerState.Value = _ @transient var coresUsed: Int = _ @@ -70,13 +70,13 @@ private[spark] class WorkerInfo( host + ":" + port } - def addExecutor(exec: ExecutorInfo) { + def addExecutor(exec: ExecutorDesc) { executors(exec.fullId) = exec coresUsed += exec.cores memoryUsed += exec.memory } - def removeExecutor(exec: ExecutorInfo) { + def removeExecutor(exec: ExecutorDesc) { if (executors.contains(exec.fullId)) { executors -= exec.fullId coresUsed -= exec.cores diff --git a/core/src/main/scala/org/apache/spark/deploy/master/ui/ApplicationPage.scala b/core/src/main/scala/org/apache/spark/deploy/master/ui/ApplicationPage.scala index 4588c130ef439..3aae2b95d7396 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/ui/ApplicationPage.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/ui/ApplicationPage.scala @@ -27,7 +27,7 @@ import org.json4s.JValue import org.apache.spark.deploy.{ExecutorState, JsonProtocol} import org.apache.spark.deploy.DeployMessages.{MasterStateResponse, RequestMasterState} -import org.apache.spark.deploy.master.ExecutorInfo +import org.apache.spark.deploy.master.ExecutorDesc import org.apache.spark.ui.{UIUtils, WebUIPage} import org.apache.spark.util.Utils @@ -109,7 +109,7 @@ private[spark] class ApplicationPage(parent: MasterWebUI) extends WebUIPage("app UIUtils.basicSparkPage(content, "Application: " + app.desc.name) } - private def executorRow(executor: ExecutorInfo): Seq[Node] = { + private def executorRow(executor: ExecutorDesc): Seq[Node] = {
    {executor.id} diff --git a/core/src/main/scala/org/apache/spark/scheduler/EventLoggingListener.scala b/core/src/main/scala/org/apache/spark/scheduler/EventLoggingListener.scala index 27bf4f1599076..30075c172bdb1 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/EventLoggingListener.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/EventLoggingListener.scala @@ -168,6 +168,10 @@ private[spark] class EventLoggingListener( logEvent(event, flushLogger = true) override def onApplicationEnd(event: SparkListenerApplicationEnd) = logEvent(event, flushLogger = true) + override def onExecutorAdded(event: SparkListenerExecutorAdded) = + logEvent(event, flushLogger = true) + override def onExecutorRemoved(event: SparkListenerExecutorRemoved) = + logEvent(event, flushLogger = true) // No-op because logging every update would be overkill override def onExecutorMetricsUpdate(event: SparkListenerExecutorMetricsUpdate) { } diff --git a/core/src/main/scala/org/apache/spark/scheduler/SparkListener.scala b/core/src/main/scala/org/apache/spark/scheduler/SparkListener.scala index b62b0c1312693..4840d8bd2d2f0 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/SparkListener.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/SparkListener.scala @@ -25,6 +25,7 @@ import scala.collection.mutable import org.apache.spark.{Logging, TaskEndReason} import org.apache.spark.annotation.DeveloperApi import org.apache.spark.executor.TaskMetrics +import org.apache.spark.scheduler.cluster.ExecutorInfo import org.apache.spark.storage.BlockManagerId import org.apache.spark.util.{Distribution, Utils} @@ -84,6 +85,14 @@ case class SparkListenerBlockManagerRemoved(time: Long, blockManagerId: BlockMan @DeveloperApi case class SparkListenerUnpersistRDD(rddId: Int) extends SparkListenerEvent +@DeveloperApi +case class SparkListenerExecutorAdded(executorId: String, executorInfo: ExecutorInfo) + extends SparkListenerEvent + +@DeveloperApi +case class SparkListenerExecutorRemoved(executorId: String) + extends SparkListenerEvent + /** * Periodic updates from executors. * @param execId executor id @@ -109,7 +118,8 @@ private[spark] case object SparkListenerShutdown extends SparkListenerEvent /** * :: DeveloperApi :: * Interface for listening to events from the Spark scheduler. Note that this is an internal - * interface which might change in different Spark releases. + * interface which might change in different Spark releases. Java clients should extend + * {@link JavaSparkListener} */ @DeveloperApi trait SparkListener { @@ -183,6 +193,16 @@ trait SparkListener { * Called when the driver receives task metrics from an executor in a heartbeat. */ def onExecutorMetricsUpdate(executorMetricsUpdate: SparkListenerExecutorMetricsUpdate) { } + + /** + * Called when the driver registers a new executor. + */ + def onExecutorAdded(executorAdded: SparkListenerExecutorAdded) { } + + /** + * Called when the driver removes an executor. + */ + def onExecutorRemoved(executorRemoved: SparkListenerExecutorRemoved) { } } /** diff --git a/core/src/main/scala/org/apache/spark/scheduler/SparkListenerBus.scala b/core/src/main/scala/org/apache/spark/scheduler/SparkListenerBus.scala index e79ffd7a3587d..e700c6af542f4 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/SparkListenerBus.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/SparkListenerBus.scala @@ -70,6 +70,10 @@ private[spark] trait SparkListenerBus extends Logging { foreachListener(_.onApplicationEnd(applicationEnd)) case metricsUpdate: SparkListenerExecutorMetricsUpdate => foreachListener(_.onExecutorMetricsUpdate(metricsUpdate)) + case executorAdded: SparkListenerExecutorAdded => + foreachListener(_.onExecutorAdded(executorAdded)) + case executorRemoved: SparkListenerExecutorRemoved => + foreachListener(_.onExecutorRemoved(executorRemoved)) case SparkListenerShutdown => } } diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala index fe9914b50bc54..5786d367464f4 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala @@ -28,7 +28,7 @@ import akka.pattern.ask import akka.remote.{DisassociatedEvent, RemotingLifecycleEvent} import org.apache.spark.{ExecutorAllocationClient, Logging, SparkEnv, SparkException, TaskState} -import org.apache.spark.scheduler.{SchedulerBackend, SlaveLost, TaskDescription, TaskSchedulerImpl, WorkerOffer} +import org.apache.spark.scheduler._ import org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages._ import org.apache.spark.util.{ActorLogReceive, SerializableBuffer, AkkaUtils, Utils} @@ -66,6 +66,8 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val actorSyste // Number of executors requested from the cluster manager that have not registered yet private var numPendingExecutors = 0 + private val listenerBus = scheduler.sc.listenerBus + // Executors we have requested the cluster manager to kill that have not died yet private val executorsPendingToRemove = new HashSet[String] @@ -106,6 +108,7 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val actorSyste logDebug(s"Decremented number of pending executors ($numPendingExecutors left)") } } + listenerBus.post(SparkListenerExecutorAdded(executorId, data)) makeOffers() } @@ -213,6 +216,7 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val actorSyste totalCoreCount.addAndGet(-executorInfo.totalCores) totalRegisteredExecutors.addAndGet(-1) scheduler.executorLost(executorId, SlaveLost(reason)) + listenerBus.post(SparkListenerExecutorRemoved(executorId)) case None => logError(s"Asked to remove non-existent executor $executorId") } } diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/ExecutorData.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/ExecutorData.scala index b71bd5783d6df..eb52ddfb1eab1 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/cluster/ExecutorData.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/ExecutorData.scala @@ -31,7 +31,7 @@ import akka.actor.{Address, ActorRef} private[cluster] class ExecutorData( val executorActor: ActorRef, val executorAddress: Address, - val executorHost: String , + override val executorHost: String, var freeCores: Int, - val totalCores: Int -) + override val totalCores: Int +) extends ExecutorInfo(executorHost, totalCores) diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/ExecutorInfo.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/ExecutorInfo.scala new file mode 100644 index 0000000000000..b4738e64c9391 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/ExecutorInfo.scala @@ -0,0 +1,45 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.spark.scheduler.cluster + +import org.apache.spark.annotation.DeveloperApi + +/** + * :: DeveloperApi :: + * Stores information about an executor to pass from the scheduler to SparkListeners. + */ +@DeveloperApi +class ExecutorInfo( + val executorHost: String, + val totalCores: Int +) { + + def canEqual(other: Any): Boolean = other.isInstanceOf[ExecutorInfo] + + override def equals(other: Any): Boolean = other match { + case that: ExecutorInfo => + (that canEqual this) && + executorHost == that.executorHost && + totalCores == that.totalCores + case _ => false + } + + override def hashCode(): Int = { + val state = Seq(executorHost, totalCores) + state.map(_.hashCode()).foldLeft(0)((a, b) => 31 * a + b) + } +} diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackend.scala index 75d8ddf375e27..d252fe8595fb8 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackend.scala @@ -27,9 +27,11 @@ import scala.collection.mutable.{HashMap, HashSet} import org.apache.mesos.protobuf.ByteString import org.apache.mesos.{Scheduler => MScheduler} import org.apache.mesos._ -import org.apache.mesos.Protos.{TaskInfo => MesosTaskInfo, TaskState => MesosTaskState, _} +import org.apache.mesos.Protos.{TaskInfo => MesosTaskInfo, TaskState => MesosTaskState, + ExecutorInfo => MesosExecutorInfo, _} import org.apache.spark.{Logging, SparkContext, SparkException, TaskState} +import org.apache.spark.scheduler.cluster.ExecutorInfo import org.apache.spark.scheduler._ import org.apache.spark.util.Utils @@ -62,6 +64,9 @@ private[spark] class MesosSchedulerBackend( var classLoader: ClassLoader = null + // The listener bus to publish executor added/removed events. + val listenerBus = sc.listenerBus + @volatile var appId: String = _ override def start() { @@ -87,7 +92,7 @@ private[spark] class MesosSchedulerBackend( } } - def createExecutorInfo(execId: String): ExecutorInfo = { + def createExecutorInfo(execId: String): MesosExecutorInfo = { val executorSparkHome = sc.conf.getOption("spark.mesos.executor.home") .orElse(sc.getSparkHome()) // Fall back to driver Spark home for backward compatibility .getOrElse { @@ -141,7 +146,7 @@ private[spark] class MesosSchedulerBackend( Value.Scalar.newBuilder() .setValue(MemoryUtils.calculateTotalMemory(sc)).build()) .build() - ExecutorInfo.newBuilder() + MesosExecutorInfo.newBuilder() .setExecutorId(ExecutorID.newBuilder().setValue(execId).build()) .setCommand(command) .setData(ByteString.copyFrom(createExecArg())) @@ -237,6 +242,7 @@ private[spark] class MesosSchedulerBackend( } val slaveIdToOffer = usableOffers.map(o => o.getSlaveId.getValue -> o).toMap + val slaveIdToWorkerOffer = workerOffers.map(o => o.executorId -> o).toMap val mesosTasks = new HashMap[String, JArrayList[MesosTaskInfo]] @@ -260,6 +266,10 @@ private[spark] class MesosSchedulerBackend( val filters = Filters.newBuilder().setRefuseSeconds(1).build() // TODO: lower timeout? mesosTasks.foreach { case (slaveId, tasks) => + slaveIdToWorkerOffer.get(slaveId).foreach(o => + listenerBus.post(SparkListenerExecutorAdded(slaveId, + new ExecutorInfo(o.host, o.cores))) + ) d.launchTasks(Collections.singleton(slaveIdToOffer(slaveId).getId), tasks, filters) } @@ -315,7 +325,7 @@ private[spark] class MesosSchedulerBackend( synchronized { if (status.getState == MesosTaskState.TASK_LOST && taskIdToSlaveId.contains(tid)) { // We lost the executor on this slave, so remember that it's gone - slaveIdsWithExecutors -= taskIdToSlaveId(tid) + removeExecutor(taskIdToSlaveId(tid)) } if (isFinished(status.getState)) { taskIdToSlaveId.remove(tid) @@ -344,12 +354,20 @@ private[spark] class MesosSchedulerBackend( override def frameworkMessage(d: SchedulerDriver, e: ExecutorID, s: SlaveID, b: Array[Byte]) {} + /** + * Remove executor associated with slaveId in a thread safe manner. + */ + private def removeExecutor(slaveId: String) = { + synchronized { + listenerBus.post(SparkListenerExecutorRemoved(slaveId)) + slaveIdsWithExecutors -= slaveId + } + } + private def recordSlaveLost(d: SchedulerDriver, slaveId: SlaveID, reason: ExecutorLossReason) { inClassLoader() { logInfo("Mesos slave lost: " + slaveId.getValue) - synchronized { - slaveIdsWithExecutors -= slaveId.getValue - } + removeExecutor(slaveId.getValue) scheduler.executorLost(slaveId.getValue, reason) } } diff --git a/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala b/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala index d94e8252650d2..a025011006156 100644 --- a/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala +++ b/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala @@ -19,6 +19,8 @@ package org.apache.spark.util import java.util.{Properties, UUID} +import org.apache.spark.scheduler.cluster.ExecutorInfo + import scala.collection.JavaConverters._ import scala.collection.Map @@ -83,7 +85,10 @@ private[spark] object JsonProtocol { applicationStartToJson(applicationStart) case applicationEnd: SparkListenerApplicationEnd => applicationEndToJson(applicationEnd) - + case executorAdded: SparkListenerExecutorAdded => + executorAddedToJson(executorAdded) + case executorRemoved: SparkListenerExecutorRemoved => + executorRemovedToJson(executorRemoved) // These aren't used, but keeps compiler happy case SparkListenerShutdown => JNothing case SparkListenerExecutorMetricsUpdate(_, _) => JNothing @@ -194,6 +199,16 @@ private[spark] object JsonProtocol { ("Timestamp" -> applicationEnd.time) } + def executorAddedToJson(executorAdded: SparkListenerExecutorAdded): JValue = { + ("Event" -> Utils.getFormattedClassName(executorAdded)) ~ + ("Executor ID" -> executorAdded.executorId) ~ + ("Executor Info" -> executorInfoToJson(executorAdded.executorInfo)) + } + + def executorRemovedToJson(executorRemoved: SparkListenerExecutorRemoved): JValue = { + ("Event" -> Utils.getFormattedClassName(executorRemoved)) ~ + ("Executor ID" -> executorRemoved.executorId) + } /** ------------------------------------------------------------------- * * JSON serialization methods for classes SparkListenerEvents depend on | @@ -362,6 +377,10 @@ private[spark] object JsonProtocol { ("Disk Size" -> blockStatus.diskSize) } + def executorInfoToJson(executorInfo: ExecutorInfo): JValue = { + ("Host" -> executorInfo.executorHost) ~ + ("Total Cores" -> executorInfo.totalCores) + } /** ------------------------------ * * Util JSON serialization methods | @@ -416,6 +435,8 @@ private[spark] object JsonProtocol { val unpersistRDD = Utils.getFormattedClassName(SparkListenerUnpersistRDD) val applicationStart = Utils.getFormattedClassName(SparkListenerApplicationStart) val applicationEnd = Utils.getFormattedClassName(SparkListenerApplicationEnd) + val executorAdded = Utils.getFormattedClassName(SparkListenerExecutorAdded) + val executorRemoved = Utils.getFormattedClassName(SparkListenerExecutorRemoved) (json \ "Event").extract[String] match { case `stageSubmitted` => stageSubmittedFromJson(json) @@ -431,6 +452,8 @@ private[spark] object JsonProtocol { case `unpersistRDD` => unpersistRDDFromJson(json) case `applicationStart` => applicationStartFromJson(json) case `applicationEnd` => applicationEndFromJson(json) + case `executorAdded` => executorAddedFromJson(json) + case `executorRemoved` => executorRemovedFromJson(json) } } @@ -523,6 +546,16 @@ private[spark] object JsonProtocol { SparkListenerApplicationEnd((json \ "Timestamp").extract[Long]) } + def executorAddedFromJson(json: JValue): SparkListenerExecutorAdded = { + val executorId = (json \ "Executor ID").extract[String] + val executorInfo = executorInfoFromJson(json \ "Executor Info") + SparkListenerExecutorAdded(executorId, executorInfo) + } + + def executorRemovedFromJson(json: JValue): SparkListenerExecutorRemoved = { + val executorId = (json \ "Executor ID").extract[String] + SparkListenerExecutorRemoved(executorId) + } /** --------------------------------------------------------------------- * * JSON deserialization methods for classes SparkListenerEvents depend on | @@ -745,6 +778,11 @@ private[spark] object JsonProtocol { BlockStatus(storageLevel, memorySize, diskSize, tachyonSize) } + def executorInfoFromJson(json: JValue): ExecutorInfo = { + val executorHost = (json \ "Host").extract[String] + val totalCores = (json \ "Total Cores").extract[Int] + new ExecutorInfo(executorHost, totalCores) + } /** -------------------------------- * * Util JSON deserialization methods | diff --git a/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala index 1de7e130039a5..437d8693c0b1f 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala @@ -160,7 +160,7 @@ class EventLoggingListenerSuite extends FunSuite with BeforeAndAfter with Loggin */ private def testApplicationEventLogging(compressionCodec: Option[String] = None) { val conf = getLoggingConf(testDirPath, compressionCodec) - val sc = new SparkContext("local", "test", conf) + val sc = new SparkContext("local-cluster[2,2,512]", "test", conf) assert(sc.eventLogger.isDefined) val eventLogger = sc.eventLogger.get val expectedLogDir = testDir.toURI().toString() @@ -184,6 +184,7 @@ class EventLoggingListenerSuite extends FunSuite with BeforeAndAfter with Loggin val eventSet = mutable.Set( SparkListenerApplicationStart, SparkListenerBlockManagerAdded, + SparkListenerExecutorAdded, SparkListenerEnvironmentUpdate, SparkListenerJobStart, SparkListenerJobEnd, diff --git a/core/src/test/scala/org/apache/spark/scheduler/SparkListenerWithClusterSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/SparkListenerWithClusterSuite.scala new file mode 100644 index 0000000000000..623a687c359a2 --- /dev/null +++ b/core/src/test/scala/org/apache/spark/scheduler/SparkListenerWithClusterSuite.scala @@ -0,0 +1,62 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler + +import org.apache.spark.scheduler.cluster.ExecutorInfo +import org.apache.spark.{SparkContext, LocalSparkContext} + +import org.scalatest.{FunSuite, BeforeAndAfter, BeforeAndAfterAll} + +import scala.collection.mutable + +/** + * Unit tests for SparkListener that require a local cluster. + */ +class SparkListenerWithClusterSuite extends FunSuite with LocalSparkContext + with BeforeAndAfter with BeforeAndAfterAll { + + /** Length of time to wait while draining listener events. */ + val WAIT_TIMEOUT_MILLIS = 10000 + + before { + sc = new SparkContext("local-cluster[2,1,512]", "SparkListenerSuite") + } + + test("SparkListener sends executor added message") { + val listener = new SaveExecutorInfo + sc.addSparkListener(listener) + + val rdd1 = sc.parallelize(1 to 100, 4) + val rdd2 = rdd1.map(_.toString) + rdd2.setName("Target RDD") + rdd2.count() + + assert(sc.listenerBus.waitUntilEmpty(WAIT_TIMEOUT_MILLIS)) + assert(listener.addedExecutorInfo.size == 2) + assert(listener.addedExecutorInfo("0").totalCores == 1) + assert(listener.addedExecutorInfo("1").totalCores == 1) + } + + private class SaveExecutorInfo extends SparkListener { + val addedExecutorInfo = mutable.Map[String, ExecutorInfo]() + + override def onExecutorAdded(executor: SparkListenerExecutorAdded) { + addedExecutorInfo(executor.executorId) = executor.executorInfo + } + } +} diff --git a/core/src/test/scala/org/apache/spark/scheduler/mesos/MesosSchedulerBackendSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/mesos/MesosSchedulerBackendSuite.scala index 48f5e40f506d9..78a30a40bf19a 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/mesos/MesosSchedulerBackendSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/mesos/MesosSchedulerBackendSuite.scala @@ -18,17 +18,20 @@ package org.apache.spark.scheduler.mesos import org.scalatest.FunSuite -import org.apache.spark.{scheduler, SparkConf, SparkContext, LocalSparkContext} -import org.apache.spark.scheduler.{TaskDescription, WorkerOffer, TaskSchedulerImpl} +import org.apache.spark.{SparkConf, SparkContext, LocalSparkContext} +import org.apache.spark.scheduler.{SparkListenerExecutorAdded, LiveListenerBus, + TaskDescription, WorkerOffer, TaskSchedulerImpl} +import org.apache.spark.scheduler.cluster.ExecutorInfo import org.apache.spark.scheduler.cluster.mesos.{MemoryUtils, MesosSchedulerBackend} import org.apache.mesos.SchedulerDriver -import org.apache.mesos.Protos._ -import org.scalatest.mock.EasyMockSugar +import org.apache.mesos.Protos.{ExecutorInfo => MesosExecutorInfo, _} import org.apache.mesos.Protos.Value.Scalar import org.easymock.{Capture, EasyMock} import java.nio.ByteBuffer import java.util.Collections import java.util +import org.scalatest.mock.EasyMockSugar + import scala.collection.mutable import scala.collection.mutable.ArrayBuffer @@ -52,11 +55,16 @@ class MesosSchedulerBackendSuite extends FunSuite with LocalSparkContext with Ea val driver = EasyMock.createMock(classOf[SchedulerDriver]) val taskScheduler = EasyMock.createMock(classOf[TaskSchedulerImpl]) + val listenerBus = EasyMock.createMock(classOf[LiveListenerBus]) + listenerBus.post(SparkListenerExecutorAdded("s1", new ExecutorInfo("host1", 2))) + EasyMock.replay(listenerBus) + val sc = EasyMock.createMock(classOf[SparkContext]) EasyMock.expect(sc.executorMemory).andReturn(100).anyTimes() EasyMock.expect(sc.getSparkHome()).andReturn(Option("/path")).anyTimes() EasyMock.expect(sc.executorEnvs).andReturn(new mutable.HashMap).anyTimes() EasyMock.expect(sc.conf).andReturn(new SparkConf).anyTimes() + EasyMock.expect(sc.listenerBus).andReturn(listenerBus) EasyMock.replay(sc) val minMem = MemoryUtils.calculateTotalMemory(sc).toInt diff --git a/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala b/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala index 63c2559c5c5f5..5ba94ff67d395 100644 --- a/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala +++ b/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala @@ -19,6 +19,7 @@ package org.apache.spark.util import java.util.Properties +import org.apache.spark.scheduler.cluster.ExecutorInfo import org.apache.spark.shuffle.MetadataFetchFailedException import scala.collection.Map @@ -69,6 +70,9 @@ class JsonProtocolSuite extends FunSuite { val unpersistRdd = SparkListenerUnpersistRDD(12345) val applicationStart = SparkListenerApplicationStart("The winner of all", None, 42L, "Garfield") val applicationEnd = SparkListenerApplicationEnd(42L) + val executorAdded = SparkListenerExecutorAdded("exec1", + new ExecutorInfo("Hostee.awesome.com", 11)) + val executorRemoved = SparkListenerExecutorRemoved("exec2") testEvent(stageSubmitted, stageSubmittedJsonString) testEvent(stageCompleted, stageCompletedJsonString) @@ -85,6 +89,8 @@ class JsonProtocolSuite extends FunSuite { testEvent(unpersistRdd, unpersistRDDJsonString) testEvent(applicationStart, applicationStartJsonString) testEvent(applicationEnd, applicationEndJsonString) + testEvent(executorAdded, executorAddedJsonString) + testEvent(executorRemoved, executorRemovedJsonString) } test("Dependent Classes") { @@ -94,6 +100,7 @@ class JsonProtocolSuite extends FunSuite { testTaskMetrics(makeTaskMetrics( 33333L, 44444L, 55555L, 66666L, 7, 8, hasHadoopInput = false, hasOutput = false)) testBlockManagerId(BlockManagerId("Hong", "Kong", 500)) + testExecutorInfo(new ExecutorInfo("host", 43)) // StorageLevel testStorageLevel(StorageLevel.NONE) @@ -303,6 +310,10 @@ class JsonProtocolSuite extends FunSuite { assert(blockId === newBlockId) } + private def testExecutorInfo(info: ExecutorInfo) { + val newInfo = JsonProtocol.executorInfoFromJson(JsonProtocol.executorInfoToJson(info)) + assertEquals(info, newInfo) + } /** -------------------------------- * | Util methods for comparing events | @@ -335,6 +346,11 @@ class JsonProtocolSuite extends FunSuite { assertEquals(e1.jobResult, e2.jobResult) case (e1: SparkListenerEnvironmentUpdate, e2: SparkListenerEnvironmentUpdate) => assertEquals(e1.environmentDetails, e2.environmentDetails) + case (e1: SparkListenerExecutorAdded, e2: SparkListenerExecutorAdded) => + assert(e1.executorId == e1.executorId) + assertEquals(e1.executorInfo, e2.executorInfo) + case (e1: SparkListenerExecutorRemoved, e2: SparkListenerExecutorRemoved) => + assert(e1.executorId == e1.executorId) case (e1, e2) => assert(e1 === e2) case _ => fail("Events don't match in types!") @@ -387,6 +403,11 @@ class JsonProtocolSuite extends FunSuite { assert(info1.accumulables === info2.accumulables) } + private def assertEquals(info1: ExecutorInfo, info2: ExecutorInfo) { + assert(info1.executorHost == info2.executorHost) + assert(info1.totalCores == info2.totalCores) + } + private def assertEquals(metrics1: TaskMetrics, metrics2: TaskMetrics) { assert(metrics1.hostname === metrics2.hostname) assert(metrics1.executorDeserializeTime === metrics2.executorDeserializeTime) @@ -1407,4 +1428,24 @@ class JsonProtocolSuite extends FunSuite { | "Timestamp": 42 |} """ + + private val executorAddedJsonString = + """ + |{ + | "Event": "SparkListenerExecutorAdded", + | "Executor ID": "exec1", + | "Executor Info": { + | "Host": "Hostee.awesome.com", + | "Total Cores": 11 + | } + |} + """ + + private val executorRemovedJsonString = + """ + |{ + | "Event": "SparkListenerExecutorRemoved", + | "Executor ID": "exec2" + |} + """ } From a79a9f923c47f2ce7da93cf0ecfe2b66fcb9fdd4 Mon Sep 17 00:00:00 2001 From: Kostas Sakellis Date: Thu, 15 Jan 2015 18:48:39 -0800 Subject: [PATCH 263/320] [SPARK-4092] [CORE] Fix InputMetrics for coalesce'd Rdds When calculating the input metrics there was an assumption that one task only reads from one block - this is not true for some operations including coalesce. This patch simply increments the task's input metrics if previous ones existed of the same read method. A limitation to this patch is that if a task reads from two different blocks of different read methods, one will override the other. Author: Kostas Sakellis Closes #3120 from ksakellis/kostas-spark-4092 and squashes the following commits: 54e6658 [Kostas Sakellis] Drops metrics if conflicting read methods exist f0e0cc5 [Kostas Sakellis] Add bytesReadCallback to InputMetrics a2a36d4 [Kostas Sakellis] CR feedback 5a0c770 [Kostas Sakellis] [SPARK-4092] [CORE] Fix InputMetrics for coalesce'd Rdds --- .../scala/org/apache/spark/CacheManager.scala | 6 +- .../org/apache/spark/executor/Executor.scala | 1 + .../apache/spark/executor/TaskMetrics.scala | 75 ++++++- .../org/apache/spark/rdd/HadoopRDD.scala | 39 ++-- .../org/apache/spark/rdd/NewHadoopRDD.scala | 40 ++-- .../apache/spark/storage/BlockManager.scala | 2 +- .../org/apache/spark/util/JsonProtocol.scala | 6 +- .../metrics/InputOutputMetricsSuite.scala | 195 ++++++++++++++---- .../ui/jobs/JobProgressListenerSuite.scala | 4 +- .../apache/spark/util/JsonProtocolSuite.scala | 4 +- 10 files changed, 270 insertions(+), 102 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/CacheManager.scala b/core/src/main/scala/org/apache/spark/CacheManager.scala index 80da62c44edc5..a0c0372b7f0ef 100644 --- a/core/src/main/scala/org/apache/spark/CacheManager.scala +++ b/core/src/main/scala/org/apache/spark/CacheManager.scala @@ -44,7 +44,11 @@ private[spark] class CacheManager(blockManager: BlockManager) extends Logging { blockManager.get(key) match { case Some(blockResult) => // Partition is already materialized, so just return its values - context.taskMetrics.inputMetrics = Some(blockResult.inputMetrics) + val inputMetrics = blockResult.inputMetrics + val existingMetrics = context.taskMetrics + .getInputMetricsForReadMethod(inputMetrics.readMethod) + existingMetrics.addBytesRead(inputMetrics.bytesRead) + new InterruptibleIterator(context, blockResult.data.asInstanceOf[Iterator[T]]) case None => diff --git a/core/src/main/scala/org/apache/spark/executor/Executor.scala b/core/src/main/scala/org/apache/spark/executor/Executor.scala index b75c77b5b4457..6660b98eb8ce9 100644 --- a/core/src/main/scala/org/apache/spark/executor/Executor.scala +++ b/core/src/main/scala/org/apache/spark/executor/Executor.scala @@ -379,6 +379,7 @@ private[spark] class Executor( if (!taskRunner.attemptedTask.isEmpty) { Option(taskRunner.task).flatMap(_.metrics).foreach { metrics => metrics.updateShuffleReadMetrics + metrics.updateInputMetrics() metrics.jvmGCTime = curGCTime - taskRunner.startGCTime if (isLocal) { // JobProgressListener will hold an reference of it during diff --git a/core/src/main/scala/org/apache/spark/executor/TaskMetrics.scala b/core/src/main/scala/org/apache/spark/executor/TaskMetrics.scala index 51b5328cb4c8f..7eb10f95e023b 100644 --- a/core/src/main/scala/org/apache/spark/executor/TaskMetrics.scala +++ b/core/src/main/scala/org/apache/spark/executor/TaskMetrics.scala @@ -17,6 +17,11 @@ package org.apache.spark.executor +import java.util.concurrent.atomic.AtomicLong + +import org.apache.spark.executor.DataReadMethod +import org.apache.spark.executor.DataReadMethod.DataReadMethod + import scala.collection.mutable.ArrayBuffer import org.apache.spark.annotation.DeveloperApi @@ -80,7 +85,17 @@ class TaskMetrics extends Serializable { * If this task reads from a HadoopRDD or from persisted data, metrics on how much data was read * are stored here. */ - var inputMetrics: Option[InputMetrics] = None + private var _inputMetrics: Option[InputMetrics] = None + + def inputMetrics = _inputMetrics + + /** + * This should only be used when recreating TaskMetrics, not when updating input metrics in + * executors + */ + private[spark] def setInputMetrics(inputMetrics: Option[InputMetrics]) { + _inputMetrics = inputMetrics + } /** * If this task writes data externally (e.g. to a distributed filesystem), metrics on how much @@ -133,6 +148,30 @@ class TaskMetrics extends Serializable { readMetrics } + /** + * Returns the input metrics object that the task should use. Currently, if + * there exists an input metric with the same readMethod, we return that one + * so the caller can accumulate bytes read. If the readMethod is different + * than previously seen by this task, we return a new InputMetric but don't + * record it. + * + * Once https://issues.apache.org/jira/browse/SPARK-5225 is addressed, + * we can store all the different inputMetrics (one per readMethod). + */ + private[spark] def getInputMetricsForReadMethod(readMethod: DataReadMethod): + InputMetrics =synchronized { + _inputMetrics match { + case None => + val metrics = new InputMetrics(readMethod) + _inputMetrics = Some(metrics) + metrics + case Some(metrics @ InputMetrics(method)) if method == readMethod => + metrics + case Some(InputMetrics(method)) => + new InputMetrics(readMethod) + } + } + /** * Aggregates shuffle read metrics for all registered dependencies into shuffleReadMetrics. */ @@ -146,6 +185,10 @@ class TaskMetrics extends Serializable { } _shuffleReadMetrics = Some(merged) } + + private[spark] def updateInputMetrics() = synchronized { + inputMetrics.foreach(_.updateBytesRead()) + } } private[spark] object TaskMetrics { @@ -179,10 +222,38 @@ object DataWriteMethod extends Enumeration with Serializable { */ @DeveloperApi case class InputMetrics(readMethod: DataReadMethod.Value) { + + private val _bytesRead: AtomicLong = new AtomicLong() + /** * Total bytes read. */ - var bytesRead: Long = 0L + def bytesRead: Long = _bytesRead.get() + @volatile @transient var bytesReadCallback: Option[() => Long] = None + + /** + * Adds additional bytes read for this read method. + */ + def addBytesRead(bytes: Long) = { + _bytesRead.addAndGet(bytes) + } + + /** + * Invoke the bytesReadCallback and mutate bytesRead. + */ + def updateBytesRead() { + bytesReadCallback.foreach { c => + _bytesRead.set(c()) + } + } + + /** + * Register a function that can be called to get up-to-date information on how many bytes the task + * has read from an input source. + */ + def setBytesReadCallback(f: Option[() => Long]) { + bytesReadCallback = f + } } /** diff --git a/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala b/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala index 37e0c13029d8b..3b99d3a6cafd1 100644 --- a/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala @@ -213,18 +213,19 @@ class HadoopRDD[K, V]( logInfo("Input split: " + split.inputSplit) val jobConf = getJobConf() - val inputMetrics = new InputMetrics(DataReadMethod.Hadoop) + val inputMetrics = context.taskMetrics + .getInputMetricsForReadMethod(DataReadMethod.Hadoop) + // Find a function that will return the FileSystem bytes read by this thread. Do this before // creating RecordReader, because RecordReader's constructor might read some bytes - val bytesReadCallback = if (split.inputSplit.value.isInstanceOf[FileSplit]) { - SparkHadoopUtil.get.getFSBytesReadOnThreadCallback( - split.inputSplit.value.asInstanceOf[FileSplit].getPath, jobConf) - } else { - None - } - if (bytesReadCallback.isDefined) { - context.taskMetrics.inputMetrics = Some(inputMetrics) - } + val bytesReadCallback = inputMetrics.bytesReadCallback.orElse( + split.inputSplit.value match { + case split: FileSplit => + SparkHadoopUtil.get.getFSBytesReadOnThreadCallback(split.getPath, jobConf) + case _ => None + } + ) + inputMetrics.setBytesReadCallback(bytesReadCallback) var reader: RecordReader[K, V] = null val inputFormat = getInputFormat(jobConf) @@ -237,8 +238,6 @@ class HadoopRDD[K, V]( val key: K = reader.createKey() val value: V = reader.createValue() - var recordsSinceMetricsUpdate = 0 - override def getNext() = { try { finished = !reader.next(key, value) @@ -246,16 +245,6 @@ class HadoopRDD[K, V]( case eof: EOFException => finished = true } - - // Update bytes read metric every few records - if (recordsSinceMetricsUpdate == HadoopRDD.RECORDS_BETWEEN_BYTES_READ_METRIC_UPDATES - && bytesReadCallback.isDefined) { - recordsSinceMetricsUpdate = 0 - val bytesReadFn = bytesReadCallback.get - inputMetrics.bytesRead = bytesReadFn() - } else { - recordsSinceMetricsUpdate += 1 - } (key, value) } @@ -263,14 +252,12 @@ class HadoopRDD[K, V]( try { reader.close() if (bytesReadCallback.isDefined) { - val bytesReadFn = bytesReadCallback.get - inputMetrics.bytesRead = bytesReadFn() + inputMetrics.updateBytesRead() } else if (split.inputSplit.value.isInstanceOf[FileSplit]) { // If we can't get the bytes read from the FS stats, fall back to the split size, // which may be inaccurate. try { - inputMetrics.bytesRead = split.inputSplit.value.getLength - context.taskMetrics.inputMetrics = Some(inputMetrics) + inputMetrics.addBytesRead(split.inputSplit.value.getLength) } catch { case e: java.io.IOException => logWarning("Unable to get input size to set InputMetrics for task", e) diff --git a/core/src/main/scala/org/apache/spark/rdd/NewHadoopRDD.scala b/core/src/main/scala/org/apache/spark/rdd/NewHadoopRDD.scala index e55d03d391e03..890ec677c2690 100644 --- a/core/src/main/scala/org/apache/spark/rdd/NewHadoopRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/NewHadoopRDD.scala @@ -109,18 +109,19 @@ class NewHadoopRDD[K, V]( logInfo("Input split: " + split.serializableHadoopSplit) val conf = confBroadcast.value.value - val inputMetrics = new InputMetrics(DataReadMethod.Hadoop) + val inputMetrics = context.taskMetrics + .getInputMetricsForReadMethod(DataReadMethod.Hadoop) + // Find a function that will return the FileSystem bytes read by this thread. Do this before // creating RecordReader, because RecordReader's constructor might read some bytes - val bytesReadCallback = if (split.serializableHadoopSplit.value.isInstanceOf[FileSplit]) { - SparkHadoopUtil.get.getFSBytesReadOnThreadCallback( - split.serializableHadoopSplit.value.asInstanceOf[FileSplit].getPath, conf) - } else { - None - } - if (bytesReadCallback.isDefined) { - context.taskMetrics.inputMetrics = Some(inputMetrics) - } + val bytesReadCallback = inputMetrics.bytesReadCallback.orElse( + split.serializableHadoopSplit.value match { + case split: FileSplit => + SparkHadoopUtil.get.getFSBytesReadOnThreadCallback(split.getPath, conf) + case _ => None + } + ) + inputMetrics.setBytesReadCallback(bytesReadCallback) val attemptId = newTaskAttemptID(jobTrackerId, id, isMap = true, split.index, 0) val hadoopAttemptContext = newTaskAttemptContext(conf, attemptId) @@ -153,34 +154,19 @@ class NewHadoopRDD[K, V]( throw new java.util.NoSuchElementException("End of stream") } havePair = false - - // Update bytes read metric every few records - if (recordsSinceMetricsUpdate == HadoopRDD.RECORDS_BETWEEN_BYTES_READ_METRIC_UPDATES - && bytesReadCallback.isDefined) { - recordsSinceMetricsUpdate = 0 - val bytesReadFn = bytesReadCallback.get - inputMetrics.bytesRead = bytesReadFn() - } else { - recordsSinceMetricsUpdate += 1 - } - (reader.getCurrentKey, reader.getCurrentValue) } private def close() { try { reader.close() - - // Update metrics with final amount if (bytesReadCallback.isDefined) { - val bytesReadFn = bytesReadCallback.get - inputMetrics.bytesRead = bytesReadFn() + inputMetrics.updateBytesRead() } else if (split.serializableHadoopSplit.value.isInstanceOf[FileSplit]) { // If we can't get the bytes read from the FS stats, fall back to the split size, // which may be inaccurate. try { - inputMetrics.bytesRead = split.serializableHadoopSplit.value.getLength - context.taskMetrics.inputMetrics = Some(inputMetrics) + inputMetrics.addBytesRead(split.serializableHadoopSplit.value.getLength) } catch { case e: java.io.IOException => logWarning("Unable to get input size to set InputMetrics for task", e) diff --git a/core/src/main/scala/org/apache/spark/storage/BlockManager.scala b/core/src/main/scala/org/apache/spark/storage/BlockManager.scala index 1427305d91cff..8bc5a1cd18b64 100644 --- a/core/src/main/scala/org/apache/spark/storage/BlockManager.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockManager.scala @@ -53,7 +53,7 @@ private[spark] class BlockResult( readMethod: DataReadMethod.Value, bytes: Long) { val inputMetrics = new InputMetrics(readMethod) - inputMetrics.bytesRead = bytes + inputMetrics.addBytesRead(bytes) } /** diff --git a/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala b/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala index a025011006156..ee3756c226fe3 100644 --- a/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala +++ b/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala @@ -637,8 +637,8 @@ private[spark] object JsonProtocol { Utils.jsonOption(json \ "Shuffle Read Metrics").map(shuffleReadMetricsFromJson)) metrics.shuffleWriteMetrics = Utils.jsonOption(json \ "Shuffle Write Metrics").map(shuffleWriteMetricsFromJson) - metrics.inputMetrics = - Utils.jsonOption(json \ "Input Metrics").map(inputMetricsFromJson) + metrics.setInputMetrics( + Utils.jsonOption(json \ "Input Metrics").map(inputMetricsFromJson)) metrics.outputMetrics = Utils.jsonOption(json \ "Output Metrics").map(outputMetricsFromJson) metrics.updatedBlocks = @@ -671,7 +671,7 @@ private[spark] object JsonProtocol { def inputMetricsFromJson(json: JValue): InputMetrics = { val metrics = new InputMetrics( DataReadMethod.withName((json \ "Data Read Method").extract[String])) - metrics.bytesRead = (json \ "Bytes Read").extract[Long] + metrics.addBytesRead((json \ "Bytes Read").extract[Long]) metrics } diff --git a/core/src/test/scala/org/apache/spark/metrics/InputOutputMetricsSuite.scala b/core/src/test/scala/org/apache/spark/metrics/InputOutputMetricsSuite.scala index f8bcde12a371a..10a39990f80ce 100644 --- a/core/src/test/scala/org/apache/spark/metrics/InputOutputMetricsSuite.scala +++ b/core/src/test/scala/org/apache/spark/metrics/InputOutputMetricsSuite.scala @@ -17,66 +17,185 @@ package org.apache.spark.metrics -import java.io.{FileWriter, PrintWriter, File} +import java.io.{File, FileWriter, PrintWriter} -import org.apache.spark.SharedSparkContext -import org.apache.spark.deploy.SparkHadoopUtil -import org.apache.spark.scheduler.{SparkListenerTaskEnd, SparkListener} +import scala.collection.mutable.ArrayBuffer import org.scalatest.FunSuite -import org.scalatest.Matchers import org.apache.hadoop.conf.Configuration -import org.apache.hadoop.fs.{Path, FileSystem} +import org.apache.hadoop.fs.{FileSystem, Path} +import org.apache.hadoop.io.{LongWritable, Text} +import org.apache.hadoop.mapreduce.lib.input.{TextInputFormat => NewTextInputFormat} -import scala.collection.mutable.ArrayBuffer +import org.apache.spark.SharedSparkContext +import org.apache.spark.deploy.SparkHadoopUtil +import org.apache.spark.scheduler.{SparkListener, SparkListenerTaskEnd} +import org.apache.spark.util.Utils + +class InputOutputMetricsSuite extends FunSuite with SharedSparkContext { -class InputOutputMetricsSuite extends FunSuite with SharedSparkContext with Matchers { - test("input metrics when reading text file with single split") { - val file = new File(getClass.getSimpleName + ".txt") - val pw = new PrintWriter(new FileWriter(file)) - pw.println("some stuff") - pw.println("some other stuff") - pw.println("yet more stuff") - pw.println("too much stuff") + @transient var tmpDir: File = _ + @transient var tmpFile: File = _ + @transient var tmpFilePath: String = _ + + override def beforeAll() { + super.beforeAll() + + tmpDir = Utils.createTempDir() + val testTempDir = new File(tmpDir, "test") + testTempDir.mkdir() + + tmpFile = new File(testTempDir, getClass.getSimpleName + ".txt") + val pw = new PrintWriter(new FileWriter(tmpFile)) + for (x <- 1 to 1000000) { + pw.println("s") + } pw.close() - file.deleteOnExit() - val taskBytesRead = new ArrayBuffer[Long]() - sc.addSparkListener(new SparkListener() { - override def onTaskEnd(taskEnd: SparkListenerTaskEnd) { - taskBytesRead += taskEnd.taskMetrics.inputMetrics.get.bytesRead - } - }) - sc.textFile("file://" + file.getAbsolutePath, 2).count() + // Path to tmpFile + tmpFilePath = "file://" + tmpFile.getAbsolutePath + } - // Wait for task end events to come in - sc.listenerBus.waitUntilEmpty(500) - assert(taskBytesRead.length == 2) - assert(taskBytesRead.sum >= file.length()) + override def afterAll() { + super.afterAll() + Utils.deleteRecursively(tmpDir) } - test("input metrics when reading text file with multiple splits") { - val file = new File(getClass.getSimpleName + ".txt") - val pw = new PrintWriter(new FileWriter(file)) - for (i <- 0 until 10000) { - pw.println("some stuff") + test("input metrics for old hadoop with coalesce") { + val bytesRead = runAndReturnBytesRead { + sc.textFile(tmpFilePath, 4).count() + } + val bytesRead2 = runAndReturnBytesRead { + sc.textFile(tmpFilePath, 4).coalesce(2).count() + } + assert(bytesRead != 0) + assert(bytesRead == bytesRead2) + assert(bytesRead2 >= tmpFile.length()) + } + + test("input metrics with cache and coalesce") { + // prime the cache manager + val rdd = sc.textFile(tmpFilePath, 4).cache() + rdd.collect() + + val bytesRead = runAndReturnBytesRead { + rdd.count() + } + val bytesRead2 = runAndReturnBytesRead { + rdd.coalesce(4).count() } - pw.close() - file.deleteOnExit() + // for count and coelesce, the same bytes should be read. + assert(bytesRead != 0) + assert(bytesRead2 == bytesRead) + } + + /** + * This checks the situation where we have interleaved reads from + * different sources. Currently, we only accumulate fron the first + * read method we find in the task. This test uses cartesian to create + * the interleaved reads. + * + * Once https://issues.apache.org/jira/browse/SPARK-5225 is fixed + * this test should break. + */ + test("input metrics with mixed read method") { + // prime the cache manager + val numPartitions = 2 + val rdd = sc.parallelize(1 to 100, numPartitions).cache() + rdd.collect() + + val rdd2 = sc.textFile(tmpFilePath, numPartitions) + + val bytesRead = runAndReturnBytesRead { + rdd.count() + } + val bytesRead2 = runAndReturnBytesRead { + rdd2.count() + } + + val cartRead = runAndReturnBytesRead { + rdd.cartesian(rdd2).count() + } + + assert(cartRead != 0) + assert(bytesRead != 0) + // We read from the first rdd of the cartesian once per partition. + assert(cartRead == bytesRead * numPartitions) + } + + test("input metrics for new Hadoop API with coalesce") { + val bytesRead = runAndReturnBytesRead { + sc.newAPIHadoopFile(tmpFilePath, classOf[NewTextInputFormat], classOf[LongWritable], + classOf[Text]).count() + } + val bytesRead2 = runAndReturnBytesRead { + sc.newAPIHadoopFile(tmpFilePath, classOf[NewTextInputFormat], classOf[LongWritable], + classOf[Text]).coalesce(5).count() + } + assert(bytesRead != 0) + assert(bytesRead2 == bytesRead) + assert(bytesRead >= tmpFile.length()) + } + + test("input metrics when reading text file") { + val bytesRead = runAndReturnBytesRead { + sc.textFile(tmpFilePath, 2).count() + } + assert(bytesRead >= tmpFile.length()) + } + + test("input metrics with interleaved reads") { + val numPartitions = 2 + val cartVector = 0 to 9 + val cartFile = new File(tmpDir, getClass.getSimpleName + "_cart.txt") + val cartFilePath = "file://" + cartFile.getAbsolutePath + + // write files to disk so we can read them later. + sc.parallelize(cartVector).saveAsTextFile(cartFilePath) + val aRdd = sc.textFile(cartFilePath, numPartitions) + + val tmpRdd = sc.textFile(tmpFilePath, numPartitions) + + val firstSize= runAndReturnBytesRead { + aRdd.count() + } + val secondSize = runAndReturnBytesRead { + tmpRdd.count() + } + + val cartesianBytes = runAndReturnBytesRead { + aRdd.cartesian(tmpRdd).count() + } + + // Computing the amount of bytes read for a cartesian operation is a little involved. + // Cartesian interleaves reads between two partitions eg. p1 and p2. + // Here are the steps: + // 1) First it creates an iterator for p1 + // 2) Creates an iterator for p2 + // 3) Reads the first element of p1 and then all the elements of p2 + // 4) proceeds to the next element of p1 + // 5) Creates a new iterator for p2 + // 6) rinse and repeat. + // As a result we read from the second partition n times where n is the number of keys in + // p1. Thus the math below for the test. + assert(cartesianBytes != 0) + assert(cartesianBytes == firstSize * numPartitions + (cartVector.length * secondSize)) + } + + private def runAndReturnBytesRead(job : => Unit): Long = { val taskBytesRead = new ArrayBuffer[Long]() sc.addSparkListener(new SparkListener() { override def onTaskEnd(taskEnd: SparkListenerTaskEnd) { taskBytesRead += taskEnd.taskMetrics.inputMetrics.get.bytesRead } }) - sc.textFile("file://" + file.getAbsolutePath, 2).count() - // Wait for task end events to come in + job + sc.listenerBus.waitUntilEmpty(500) - assert(taskBytesRead.length == 2) - assert(taskBytesRead.sum >= file.length()) + taskBytesRead.sum } test("output metrics when writing text file") { diff --git a/core/src/test/scala/org/apache/spark/ui/jobs/JobProgressListenerSuite.scala b/core/src/test/scala/org/apache/spark/ui/jobs/JobProgressListenerSuite.scala index 12af60caf7d54..f865d8ca04d1b 100644 --- a/core/src/test/scala/org/apache/spark/ui/jobs/JobProgressListenerSuite.scala +++ b/core/src/test/scala/org/apache/spark/ui/jobs/JobProgressListenerSuite.scala @@ -231,8 +231,8 @@ class JobProgressListenerSuite extends FunSuite with LocalSparkContext with Matc taskMetrics.diskBytesSpilled = base + 5 taskMetrics.memoryBytesSpilled = base + 6 val inputMetrics = new InputMetrics(DataReadMethod.Hadoop) - taskMetrics.inputMetrics = Some(inputMetrics) - inputMetrics.bytesRead = base + 7 + taskMetrics.setInputMetrics(Some(inputMetrics)) + inputMetrics.addBytesRead(base + 7) val outputMetrics = new OutputMetrics(DataWriteMethod.Hadoop) taskMetrics.outputMetrics = Some(outputMetrics) outputMetrics.bytesWritten = base + 8 diff --git a/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala b/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala index 5ba94ff67d395..71dfed1289850 100644 --- a/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala +++ b/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala @@ -630,8 +630,8 @@ class JsonProtocolSuite extends FunSuite { if (hasHadoopInput) { val inputMetrics = new InputMetrics(DataReadMethod.Hadoop) - inputMetrics.bytesRead = d + e + f - t.inputMetrics = Some(inputMetrics) + inputMetrics.addBytesRead(d + e + f) + t.setInputMetrics(Some(inputMetrics)) } else { val sr = new ShuffleReadMetrics sr.remoteBytesRead = b + d From 2be82b1e66cd188456bbf1e5abb13af04d1629d5 Mon Sep 17 00:00:00 2001 From: WangTaoTheTonic Date: Fri, 16 Jan 2015 09:16:56 -0800 Subject: [PATCH 264/320] [SPARK-1507][YARN]specify # cores for ApplicationMaster Based on top of changes in https://github.com/apache/spark/pull/3806. https://issues.apache.org/jira/browse/SPARK-1507 `--driver-cores` and `spark.driver.cores` for all cluster modes and `spark.yarn.am.cores` for yarn client mode. Author: WangTaoTheTonic Author: WangTao Closes #4018 from WangTaoTheTonic/SPARK-1507 and squashes the following commits: 01419d3 [WangTaoTheTonic] amend the args name b255795 [WangTaoTheTonic] indet thing d86557c [WangTaoTheTonic] some comments amend 43c9392 [WangTao] fix compile error b39a100 [WangTao] specify # cores for ApplicationMaster --- .../apache/spark/deploy/ClientArguments.scala | 6 ++--- .../org/apache/spark/deploy/SparkSubmit.scala | 1 + .../spark/deploy/SparkSubmitArguments.scala | 5 ++++ docs/configuration.md | 15 ++++++++---- docs/running-on-yarn.md | 17 +++++++++++++ .../org/apache/spark/deploy/yarn/Client.scala | 1 + .../spark/deploy/yarn/ClientArguments.scala | 24 +++++++++++++++---- 7 files changed, 58 insertions(+), 11 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/deploy/ClientArguments.scala b/core/src/main/scala/org/apache/spark/deploy/ClientArguments.scala index 2e1e52906ceeb..e5873ce724b9f 100644 --- a/core/src/main/scala/org/apache/spark/deploy/ClientArguments.scala +++ b/core/src/main/scala/org/apache/spark/deploy/ClientArguments.scala @@ -23,7 +23,7 @@ import scala.collection.mutable.ListBuffer import org.apache.log4j.Level -import org.apache.spark.util.MemoryParam +import org.apache.spark.util.{IntParam, MemoryParam} /** * Command-line parser for the driver client. @@ -51,8 +51,8 @@ private[spark] class ClientArguments(args: Array[String]) { parse(args.toList) def parse(args: List[String]): Unit = args match { - case ("--cores" | "-c") :: value :: tail => - cores = value.toInt + case ("--cores" | "-c") :: IntParam(value) :: tail => + cores = value parse(tail) case ("--memory" | "-m") :: MemoryParam(value) :: tail => diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala b/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala index 955cbd6dab96d..050ba91eb2bc3 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala @@ -200,6 +200,7 @@ object SparkSubmit { // Yarn cluster only OptionAssigner(args.name, YARN, CLUSTER, clOption = "--name"), OptionAssigner(args.driverMemory, YARN, CLUSTER, clOption = "--driver-memory"), + OptionAssigner(args.driverCores, YARN, CLUSTER, clOption = "--driver-cores"), OptionAssigner(args.queue, YARN, CLUSTER, clOption = "--queue"), OptionAssigner(args.numExecutors, YARN, CLUSTER, clOption = "--num-executors"), OptionAssigner(args.executorMemory, YARN, CLUSTER, clOption = "--executor-memory"), diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala index 47059b08a397f..81ec08cb6d501 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala @@ -108,6 +108,9 @@ private[spark] class SparkSubmitArguments(args: Seq[String], env: Map[String, St .orElse(sparkProperties.get("spark.driver.memory")) .orElse(env.get("SPARK_DRIVER_MEMORY")) .orNull + driverCores = Option(driverCores) + .orElse(sparkProperties.get("spark.driver.cores")) + .orNull executorMemory = Option(executorMemory) .orElse(sparkProperties.get("spark.executor.memory")) .orElse(env.get("SPARK_EXECUTOR_MEMORY")) @@ -406,6 +409,8 @@ private[spark] class SparkSubmitArguments(args: Seq[String], env: Map[String, St | --total-executor-cores NUM Total cores for all executors. | | YARN-only: + | --driver-cores NUM Number of cores used by the driver, only in cluster mode + | (Default: 1). | --executor-cores NUM Number of cores per executor (Default: 1). | --queue QUEUE_NAME The YARN queue to submit to (Default: "default"). | --num-executors NUM Number of executors to launch (Default: 2). diff --git a/docs/configuration.md b/docs/configuration.md index 673cdb371a512..efbab4085317a 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -102,11 +102,10 @@ of the most common options to set are:
    spark.executor.memory512mspark.driver.cores1 - Amount of memory to use per executor process, in the same format as JVM memory strings - (e.g. 512m, 2g). + Number of cores to use for the driver process, only in cluster mode.
    spark.executor.memory512m + Amount of memory to use per executor process, in the same format as JVM memory strings + (e.g. 512m, 2g). +
    spark.driver.maxResultSize 1g
    spark.driver.cores1 + Number of cores used by the driver in YARN cluster mode. + Since the driver is run in the same JVM as the YARN Application Master in cluster mode, this also controls the cores used by the YARN AM. + In client mode, use spark.yarn.am.cores to control the number of cores used by the YARN AM instead. +
    spark.yarn.am.cores1 + Number of cores to use for the YARN Application Master in client mode. + In cluster mode, use spark.driver.cores instead. +
    spark.yarn.am.waitTime 100000
    cogroup(otherDataset, [numTasks]) When called on datasets of type (K, V) and (K, W), returns a dataset of (K, Iterable<V>, Iterable<W>) tuples. This operation is also called groupWith. When called on datasets of type (K, V) and (K, W), returns a dataset of (K, (Iterable<V>, Iterable<W>)) tuples. This operation is also called groupWith.
    cartesian(otherDataset)
    + {formattedSubmissionTime} {formattedDuration}