Snappy/v2.0.1 #17
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Snappy/v2.0.1 #17
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## What changes were proposed in this pull request? This PR is a small follow-up to apache#14554. This also widens the visibility of a few (similar) Hive classes. ## How was this patch tested? No test. Only a visibility change. Author: Herman van Hovell <[email protected]> Closes apache#14654 from hvanhovell/SPARK-16964-hive. (cherry picked from commit 8fdc6ce) Signed-off-by: Reynold Xin <[email protected]>
…on package" This reverts commit 2e2c787.
…ecution package [Backport] ## What changes were proposed in this pull request? This PR backports apache#14554 to branch-2.0. I have also changed the visibility of a few similar Hive classes. ## How was this patch tested? (Only a package visibility change) Author: Herman van Hovell <[email protected]> Author: Reynold Xin <[email protected]> Closes apache#14652 from hvanhovell/SPARK-16964.
… in R CMD check Rename RDD functions for now to avoid CRAN check warnings. Some RDD functions are sharing generics with DataFrame functions (hence the problem) so after the renames we need to add new generics, for now. unit tests Author: Felix Cheung <[email protected]> Closes apache#14626 from felixcheung/rrddfunctions. (cherry picked from commit c34b546) Signed-off-by: Shivaram Venkataraman <[email protected]>
To plugin SnappyData's Unified Memory Manager (SnappyUnifiedMemoryManager), the MemoryManager is made configurable using "spark.memory.manager" configuration property that is set to the SnappyData's manager in embedded mode.
## What changes were proposed in this pull request? Remove the api doc link for mapReduceTriplets operator because in latest api they are remove so when user link to that api they will not get mapReduceTriplets there so its more good to remove than confuse the user. ## How was this patch tested? Run all the test cases  Author: sandy <[email protected]> Closes apache#14669 from phalodi/SPARK-17089. (cherry picked from commit e28a8c5) Signed-off-by: Reynold Xin <[email protected]>
## What changes were proposed in this pull request? This PR renames `ParserUtils.assert` to `ParserUtils.validate`. This is done because this method is used to check requirements, and not to check if the program is in an invalid state. ## How was this patch tested? Simple rename. Compilation should do. Author: Herman van Hovell <[email protected]> Closes apache#14665 from hvanhovell/SPARK-17084. (cherry picked from commit 4a2c375) Signed-off-by: Reynold Xin <[email protected]>
…cumenation for jdbc APIs ## What changes were proposed in this pull request? This should be credited to mvervuurt. The main purpose of this PR is - simply to include the change for the same instance in `DataFrameReader` just to match up. - just avoid duplicately verifying the PR (as I already did). The documentation for both should be the same because both assume the `properties` should be the same `dict` for the same option. ## How was this patch tested? Manually building Python documentation. This will produce the output as below: - `DataFrameReader`  - `DataFrameWriter`  Closes apache#14624 Author: hyukjinkwon <[email protected]> Author: mvervuurt <[email protected]> Closes apache#14677 from HyukjinKwon/typo-python. (cherry picked from commit 0f6aa8a) Signed-off-by: Reynold Xin <[email protected]>
…s beyond 64 KB ## What changes were proposed in this pull request? This PR splits the generated code for ```SafeProjection.apply``` by using ```ctx.splitExpressions()```. This is because the large code body for ```NewInstance``` may grow beyond 64KB bytecode size for ```apply()``` method. Here is [the original PR](apache#13243) for SPARK-15285. However, it breaks a build with Scala 2.10 since Scala 2.10 does not a case class with large number of members. Thus, it was reverted by [this commit](apache@fa244e5). ## How was this patch tested? Added new tests by using `DefinedByConstructorParams` instead of case class for scala-2.10 Author: Kazuaki Ishizaki <[email protected]> Closes apache#14670 from kiszk/SPARK-15285-2. (cherry picked from commit 56d8674) Signed-off-by: Wenchen Fan <[email protected]>
## What changes were proposed in this pull request? We use reflection to convert `TreeNode` to json string, and currently don't support arbitrary object. `UserDefinedGenerator` takes a function object, so we should skip json format test for it, or the tests can be flacky, e.g. `DataFrameSuite.simple explode`, this test always fail with scala 2.10(branch 1.6 builds with scala 2.10 by default), but pass with scala 2.11(master branch builds with scala 2.11 by default). ## How was this patch tested? N/A Author: Wenchen Fan <[email protected]> Closes apache#14679 from cloud-fan/json. (cherry picked from commit 928ca1c) Signed-off-by: Yin Huai <[email protected]>
…gh the StreamingQueryListener ## What changes were proposed in this pull request? Currently, the stackTrace (as `Array[StackTraceElements]`) reported through StreamingQueryListener.onQueryTerminated is useless as it has the stack trace of where StreamingQueryException is defined, not the stack trace of underlying exception. For example, if a streaming query fails because of a / by zero exception in a task, the `QueryTerminated.stackTrace` will have ``` org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches(StreamExecution.scala:211) org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:124) ``` This is basically useless, as it is location where the StreamingQueryException was defined. What we want is Here is the right way to reason about what should be posted as through StreamingQueryListener.onQueryTerminated - The actual exception could either be a SparkException, or an arbitrary exception. - SparkException reports the relevant executor stack trace of a failed task as a string in the the exception message. The `Array[StackTraceElements]` returned by `SparkException.stackTrace()` is mostly irrelevant. - For any arbitrary exception, the `Array[StackTraceElements]` returned by `exception.stackTrace()` may be relevant. - When there is an error in a streaming query, it's hard to reason whether the `Array[StackTraceElements]` is useful or not. In fact, it is not clear whether it is even useful to report the stack trace as this array of Java objects. It may be sufficient to report the strack trace as a string, along with the message. This is how Spark reported executor stra - Hence, this PR simplifies the API by removing the array `stackTrace` from `QueryTerminated`. Instead the `exception` returns a string containing the message and the stack trace of the actual underlying exception that failed the streaming query (i.e. not that of the StreamingQueryException). If anyone is interested in the actual stack trace as an array, can always access them through `streamingQuery.exception` which returns the exception object. With this change, if a streaming query fails because of a / by zero exception in a task, the `QueryTerminated.exception` will be ``` org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in stage 0.0 failed 1 times, most recent failure: Lost task 1.0 in stage 0.0 (TID 1, localhost): java.lang.ArithmeticException: / by zero at org.apache.spark.sql.streaming.StreamingQueryListenerSuite$$anonfun$5$$anonfun$apply$mcV$sp$4$$anonfun$apply$mcV$sp$5.apply$mcII$sp(StreamingQueryListenerSuite.scala:153) at org.apache.spark.sql.streaming.StreamingQueryListenerSuite$$anonfun$5$$anonfun$apply$mcV$sp$4$$anonfun$apply$mcV$sp$5.apply(StreamingQueryListenerSuite.scala:153) at org.apache.spark.sql.streaming.StreamingQueryListenerSuite$$anonfun$5$$anonfun$apply$mcV$sp$4$$anonfun$apply$mcV$sp$5.apply(StreamingQueryListenerSuite.scala:153) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370) at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:232) at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:226) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) at org.apache.spark.scheduler.Task.run(Task.scala:86) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) at java.lang.Thread.run(Thread.java:744) Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1429) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1417) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1416) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1416) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802) ... ``` It contains the relevant executor stack trace. In a case non-SparkException, if the streaming source MemoryStream throws an exception, exception message will have the relevant stack trace. ``` java.lang.RuntimeException: this is the exception message at org.apache.spark.sql.execution.streaming.MemoryStream.getBatch(memory.scala:103) at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$5.apply(StreamExecution.scala:316) at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$5.apply(StreamExecution.scala:313) at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241) at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241) at scala.collection.Iterator$class.foreach(Iterator.scala:893) at scala.collection.AbstractIterator.foreach(Iterator.scala:1336) at scala.collection.IterableLike$class.foreach(IterableLike.scala:72) at org.apache.spark.sql.execution.streaming.StreamProgress.foreach(StreamProgress.scala:25) at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241) at org.apache.spark.sql.execution.streaming.StreamProgress.flatMap(StreamProgress.scala:25) at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runBatch(StreamExecution.scala:313) at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches$1.apply$mcZ$sp(StreamExecution.scala:197) at org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:43) at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches(StreamExecution.scala:187) at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:124) ``` Note that this change in the public `QueryTerminated` class is okay as the APIs are still experimental. ## How was this patch tested? Unit tests that test whether the right information is present in the exception message reported through QueryTerminated object. Author: Tathagata Das <[email protected]> Closes apache#14675 from tdas/SPARK-17096. (cherry picked from commit d60af8f) Signed-off-by: Tathagata Das <[email protected]>
…dBatch' https://issues.apache.org/jira/browse/SPARK-17038 ## What changes were proposed in this pull request? StreamingSource's lastReceivedBatch_submissionTime, lastReceivedBatch_processingTimeStart, and lastReceivedBatch_processingTimeEnd all use data from lastCompletedBatch instead of lastReceivedBatch. In particular, this makes it impossible to match lastReceivedBatch_records with a batchID/submission time. This is apparent when looking at StreamingSource.scala, lines 89-94. ## How was this patch tested? Manually running unit tests on local laptop Author: Xin Ren <[email protected]> Closes apache#14681 from keypointt/SPARK-17038. (cherry picked from commit e6bef7d) Signed-off-by: Shixiong Zhu <[email protected]>
…pedDataset created from DataFrame containing a column created with lit/expr
## What changes were proposed in this pull request?
A TreeNodeException is thrown when executing the following minimal example in Spark 2.0.
import spark.implicits._
case class test (x: Int, q: Int)
val d = Seq(1).toDF("x")
d.withColumn("q", lit(0)).as[test].groupByKey(_.x).flatMapGroups{case (x, iter) => List[Int]()}.show
d.withColumn("q", expr("0")).as[test].groupByKey(_.x).flatMapGroups{case (x, iter) => List[Int]()}.show
The problem is at `FoldablePropagation`. The rule will do `transformExpressions` on `LogicalPlan`. The query above contains a `MapGroups` which has a parameter `dataAttributes:Seq[Attribute]`. One attributes in `dataAttributes` will be transformed to an `Alias(literal(0), _)` in `FoldablePropagation`. `Alias` is not an `Attribute` and causes the error.
We can't easily detect such type inconsistency during transforming expressions. A direct approach to this problem is to skip doing `FoldablePropagation` on object operators as they should not contain such expressions.
## How was this patch tested?
Jenkins tests.
Author: Liang-Chi Hsieh <[email protected]>
Closes apache#14648 from viirya/flat-mapping.
(cherry picked from commit 10204b9)
Signed-off-by: Wenchen Fan <[email protected]>
## What changes were proposed in this pull request? This patch introduces a new private ReduceAggregator interface that is a subclass of Aggregator. ReduceAggregator only requires a single associative and commutative reduce function. ReduceAggregator is also used to implement KeyValueGroupedDataset.reduceGroups in order to support partial aggregation. Note that the pull request was initially done by viirya. ## How was this patch tested? Covered by original tests for reduceGroups, as well as a new test suite for ReduceAggregator. Author: Reynold Xin <[email protected]> Author: Liang-Chi Hsieh <[email protected]> Closes apache#14576 from rxin/reduceAggregator. (cherry picked from commit 1748f82) Signed-off-by: Wenchen Fan <[email protected]>
## What changes were proposed in this pull request? This patch fixes the problem described in SPARK-17117, i.e. "SELECT 1 / NULL" throws an analysis exception: ``` org.apache.spark.sql.AnalysisException: cannot resolve '(1 / NULL)' due to data type mismatch: differing types in '(1 / NULL)' (int and null). ``` The problem is that division type coercion did not take null type into account. ## How was this patch tested? A unit test for the type coercion, and a few end-to-end test cases using SQLQueryTestSuite. Author: petermaxlee <[email protected]> Closes apache#14695 from petermaxlee/SPARK-17117. (cherry picked from commit 68f5087) Signed-off-by: Herman van Hovell <[email protected]>
## What changes were proposed in this pull request? R API documentation for "coltypes" is confusing, found when working on another ticket. Current version http://spark.apache.org/docs/2.0.0/api/R/coltypes.html, where parameters have 2 "x" which is a duplicate, and also the example is not very clear   ## How was this patch tested? Tested manually on local machine. And the screenshots are like below:   Author: Xin Ren <[email protected]> Closes apache#14489 from keypointt/rExample. (cherry picked from commit 1203c84) Signed-off-by: Shivaram Venkataraman <[email protected]>
This adds analyzer rules for resolving table-valued functions, and adds one builtin implementation for range(). The arguments for range() are the same as those of `spark.range()`. Unit tests. cc hvanhovell Author: Eric Liang <[email protected]> Closes apache#14656 from ericl/sc-4309. (cherry picked from commit 412dba6) Signed-off-by: Reynold Xin <[email protected]>
…inline tables This patch improves inline table support with the following: 1. Support type coercion. 2. Support using foldable expressions. Previously only literals were supported. 3. Improve error message handling. 4. Improve test coverage. Added a new unit test suite ResolveInlineTablesSuite and a new file-based end-to-end test inline-table.sql. Author: petermaxlee <[email protected]> Closes apache#14676 from petermaxlee/SPARK-16947. (cherry picked from commit f5472dd) Signed-off-by: Reynold Xin <[email protected]>
(cherry picked from commit b482c09) Signed-off-by: Reynold Xin <[email protected]>
JIRA issue link: https://issues.apache.org/jira/browse/SPARK-16961 Changed one line of Utils.randomizeInPlace to allow elements to stay in place. Created a unit test that runs a Pearson's chi squared test to determine whether the output diverges significantly from a uniform distribution. Author: Nick Lavers <[email protected]> Closes apache#14551 from nicklavers/SPARK-16961-randomizeInPlace. (cherry picked from commit 5377fc6) Signed-off-by: Sean Owen <[email protected]>
## What changes were proposed in this pull request? This patch changes predicate pushdown optimization rule (PushDownPredicate) from using a blacklist to a whitelist. That is to say, operators must be explicitly allowed. This approach is more future-proof: previously it was possible for us to introduce a new operator and then render the optimization rule incorrect. This also fixes the bug that previously we allowed pushing filter beneath limit, which was incorrect. That is to say, before this patch, the optimizer would rewrite ``` select * from (select * from range(10) limit 5) where id > 3 to select * from range(10) where id > 3 limit 5 ``` ## How was this patch tested? - a unit test case in FilterPushdownSuite - an end-to-end test in limit.sql Author: Reynold Xin <[email protected]> Closes apache#14713 from rxin/SPARK-16994. (cherry picked from commit 67e59d4) Signed-off-by: Wenchen Fan <[email protected]>
…HA is enabled.
## What changes were proposed in this pull request?
If the following conditions are satisfied, executors don't load properties in `hdfs-site.xml` and UnknownHostException can be thrown.
(1) NameNode HA is enabled
(2) spark.eventLogging is disabled or logging path is NOT on HDFS
(3) Using Standalone or Mesos for the cluster manager
(4) There are no code to load `HdfsCondition` class in the driver regardless of directly or indirectly.
(5) The tasks access to HDFS
(There might be some more conditions...)
For example, following code causes UnknownHostException when the conditions above are satisfied.
```
sc.textFile("<path on HDFS>").collect
```
```
java.lang.IllegalArgumentException: java.net.UnknownHostException: hacluster
at org.apache.hadoop.security.SecurityUtil.buildTokenService(SecurityUtil.java:378)
at org.apache.hadoop.hdfs.NameNodeProxies.createNonHAProxy(NameNodeProxies.java:310)
at org.apache.hadoop.hdfs.NameNodeProxies.createProxy(NameNodeProxies.java:176)
at org.apache.hadoop.hdfs.DFSClient.<init>(DFSClient.java:678)
at org.apache.hadoop.hdfs.DFSClient.<init>(DFSClient.java:619)
at org.apache.hadoop.hdfs.DistributedFileSystem.initialize(DistributedFileSystem.java:149)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2653)
at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:92)
at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2687)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2669)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:371)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:170)
at org.apache.hadoop.mapred.JobConf.getWorkingDirectory(JobConf.java:656)
at org.apache.hadoop.mapred.FileInputFormat.setInputPaths(FileInputFormat.java:438)
at org.apache.hadoop.mapred.FileInputFormat.setInputPaths(FileInputFormat.java:411)
at org.apache.spark.SparkContext$$anonfun$hadoopFile$1$$anonfun$32.apply(SparkContext.scala:986)
at org.apache.spark.SparkContext$$anonfun$hadoopFile$1$$anonfun$32.apply(SparkContext.scala:986)
at org.apache.spark.rdd.HadoopRDD$$anonfun$getJobConf$6.apply(HadoopRDD.scala:177)
at org.apache.spark.rdd.HadoopRDD$$anonfun$getJobConf$6.apply(HadoopRDD.scala:177)
at scala.Option.map(Option.scala:146)
at org.apache.spark.rdd.HadoopRDD.getJobConf(HadoopRDD.scala:177)
at org.apache.spark.rdd.HadoopRDD$$anon$1.<init>(HadoopRDD.scala:213)
at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:209)
at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:102)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:318)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:282)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:318)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:282)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:85)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.net.UnknownHostException: hacluster
```
But following code doesn't cause the Exception because `textFile` method loads `HdfsConfiguration` indirectly.
```
sc.textFile("<path on HDFS>").collect
```
When a job includes some operations which access to HDFS, the object of `org.apache.hadoop.Configuration` is wrapped by `SerializableConfiguration`, serialized and broadcasted from driver to executors and each executor deserialize the object with `loadDefaults` false so HDFS related properties should be set before broadcasted.
## How was this patch tested?
Tested manually on my standalone cluster.
Author: Kousuke Saruta <[email protected]>
Closes apache#13738 from sarutak/SPARK-11227.
(cherry picked from commit 071eaaf)
Signed-off-by: Tom Graves <[email protected]>
…d by ColumnPruning We push down `Project` through `Sample` in `Optimizer` by the rule `PushProjectThroughSample`. However, if the projected columns produce new output, they will encounter whole data instead of sampled data. It will bring some inconsistency between original plan (Sample then Project) and optimized plan (Project then Sample). In the extreme case such as attached in the JIRA, if the projected column is an UDF which is supposed to not see the sampled out data, the result of UDF will be incorrect. Since the rule `ColumnPruning` already handles general `Project` pushdown. We don't need `PushProjectThroughSample` anymore. The rule `ColumnPruning` also avoids the described issue. Jenkins tests. Author: Liang-Chi Hsieh <[email protected]> Closes apache#14327 from viirya/fix-sample-pushdown. (cherry picked from commit 7b06a89) Signed-off-by: Reynold Xin <[email protected]>
## What changes were proposed in this pull request? This PR fixes executor OOM in offheap mode due to bug in Cooperative Memory Management for UnsafeExternSorter. UnsafeExternalSorter was checking if memory page is being used by upstream by comparing the base object address of the current page with the base object address of upstream. However, in case of offheap memory allocation, the base object addresses are always null, so there was no spilling happening and eventually the operator would OOM. Following is the stack trace this issue addresses - java.lang.OutOfMemoryError: Unable to acquire 1220 bytes of memory, got 0 at org.apache.spark.memory.MemoryConsumer.allocatePage(MemoryConsumer.java:120) at org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter.acquireNewPageIfNecessary(UnsafeExternalSorter.java:341) at org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter.insertRecord(UnsafeExternalSorter.java:362) at org.apache.spark.sql.execution.UnsafeExternalRowSorter.insertRow(UnsafeExternalRowSorter.java:93) at org.apache.spark.sql.execution.UnsafeExternalRowSorter.sort(UnsafeExternalRowSorter.java:170) ## How was this patch tested? Tested by running the failing job. Author: Sital Kedia <[email protected]> Closes apache#14693 from sitalkedia/fix_offheap_oom. (cherry picked from commit cf0cce9) Signed-off-by: Davies Liu <[email protected]>
## What changes were proposed in this pull request? This patch creates array.sql in SQLQueryTestSuite for testing array related functions, including: - indexing - array creation - size - array_contains - sort_array ## How was this patch tested? The patch itself is about adding tests. Author: petermaxlee <[email protected]> Closes apache#14708 from petermaxlee/SPARK-17149. (cherry picked from commit a117afa) Signed-off-by: Reynold Xin <[email protected]>
…rals ## What changes were proposed in this pull request? Modifies error message for numeric literals to Numeric literal <literal> does not fit in range [min, max] for type <T> ## How was this patch tested? Fixed up the error messages for literals.sql in SqlQueryTestSuite and re-ran via sbt. Also fixed up error messages in ExpressionParserSuite Author: Srinath Shankar <[email protected]> Closes apache#14721 from srinathshankar/sc4296. (cherry picked from commit ba1737c) Signed-off-by: Reynold Xin <[email protected]>
## What changes were proposed in this pull request? This patch adds support for SQL generation for inline tables. With this, it would be possible to create a view that depends on inline tables. ## How was this patch tested? Added a test case in LogicalPlanToSQLSuite. Author: petermaxlee <[email protected]> Closes apache#14709 from petermaxlee/SPARK-17150. (cherry picked from commit 45d40d9) Signed-off-by: Wenchen Fan <[email protected]>
…ntics of MultiInstanceRelation ## What changes were proposed in this pull request? Currently `LogicalRelation.newInstance()` simply creates another `LogicalRelation` object with the same parameters. However, the `newInstance()` method inherited from `MultiInstanceRelation` should return a copy of object with unique expression ids. Current `LogicalRelation.newInstance()` can cause failure when doing self-join. ## How was this patch tested? Jenkins tests. Author: Liang-Chi Hsieh <[email protected]> Closes apache#14682 from viirya/fix-localrelation. (cherry picked from commit 31a0155) Signed-off-by: Wenchen Fan <[email protected]>
… and allow multiple aggregates per column
## What changes were proposed in this pull request?
This patch fixes a longstanding issue with one of the RelationalGroupedDataset.agg function. Even though the signature accepts vararg of pairs, the underlying implementation turns the seq into a map, and thus not order preserving nor allowing multiple aggregates per column.
This change also allows users to use this function to run multiple different aggregations for a single column, e.g.
```
agg("age" -> "max", "age" -> "count")
```
## How was this patch tested?
Added a test case in DataFrameAggregateSuite.
Author: petermaxlee <[email protected]>
Closes apache#14697 from petermaxlee/SPARK-17124.
(cherry picked from commit 9560c8d)
Signed-off-by: Wenchen Fan <[email protected]>
… it work well on Windows ## What changes were proposed in this pull request? Update ```SparkContext.addFile``` to correct the use of ```URI``` and ```Path```, then it can work well on Windows. This is used for branch-2.0 backport, more details at apache#15131. ## How was this patch tested? Backport, checked by appveyor. Author: Yanbo Liang <[email protected]> Closes apache#15217 from yanboliang/uri-2.0.
This PR sets the R package version while tagging releases. Note that since R doesn't accept `-SNAPSHOT` in version number field, we remove that while setting the next version Tested manually by running locally Author: Shivaram Venkataraman <[email protected]> Closes apache#15223 from shivaram/sparkr-version-change. (cherry picked from commit 7c38252) Signed-off-by: Reynold Xin <[email protected]>
…ze configurable (branch 2.0) ## What changes were proposed in this pull request? Backport apache#14269 to 2.0. ## How was this patch tested? Jenkins. Author: Dhruve Ashar <[email protected]> Closes apache#15222 from zsxwing/SPARK-15703-2.0.
…dition to existing null string array ## What changes were proposed in this pull request? To match Tokenizer and for compatibility with Word2Vec, output a nullable string array type in NGram ## How was this patch tested? Jenkins tests. Author: Sean Owen <[email protected]> Closes apache#15179 from srowen/SPARK-10835. (cherry picked from commit f3fe554) Signed-off-by: Sean Owen <[email protected]>
## What changes were proposed in this pull request? When a malformed URL was sent to Executors through `sc.addJar` and `sc.addFile`, the executors become unusable, because they constantly throw `MalformedURLException`s and can never acknowledge that the file or jar is just bad input. This PR tries to fix that problem by making sure MalformedURLs can never be submitted through `sc.addJar` and `sc.addFile`. Another solution would be to blacklist bad files and jars on Executors. Maybe fail the first time, and then ignore the second time (but print a warning message). ## How was this patch tested? Unit tests in SparkContextSuite Author: Burak Yavuz <[email protected]> Closes apache#15224 from brkyvz/SPARK-17650. (cherry picked from commit 59d87d2) Signed-off-by: Shixiong Zhu <[email protected]>
…enerBus ## What changes were proposed in this pull request? Log how many Spark events got dropped in LiveListenerBus so that the user can get insights on how to set a correct event queue size. ## How was this patch tested? Jenkins Author: Shixiong Zhu <[email protected]> Closes apache#15220 from zsxwing/SPARK-17649. (cherry picked from commit bde85f8) Signed-off-by: Shixiong Zhu <[email protected]>
## What changes were proposed in this pull request? This minor patch fixes a confusing exception message while reserving additional capacity in the vectorized parquet reader. ## How was this patch tested? Exisiting Unit Tests Author: Sameer Agarwal <[email protected]> Closes apache#15225 from sameeragarwal/error-msg. (cherry picked from commit 7c7586a) Signed-off-by: Yin Huai <[email protected]>
Corrected a link to the configuration.html page, it was pointing to a page that does not exist (configurations.html). Documentation change, verified in preview. Author: Andrew Mills <[email protected]> Closes apache#15244 from ammills01/master. (cherry picked from commit 00be16d) Signed-off-by: Andrew Or <[email protected]>
… other formats This patch ports changes from apache#15185 to Spark 2.x. In that patch, a correctness bug in Spark 1.6.x which was caused by an invalid `equals()` comparison between an `UnsafeRow` and another row of a different format. Spark 2.x is not affected by that specific correctness bug but it can still reap the error-prevention benefits of that patch's changes, which modify ``UnsafeRow.equals()` to throw an IllegalArgumentException if it is called with an object that is not an `UnsafeRow`. Author: Josh Rosen <[email protected]> Closes apache#15265 from JoshRosen/SPARK-17618-master. (cherry picked from commit 2f84a68) Signed-off-by: Josh Rosen <[email protected]>
…oryStore ## What changes were proposed in this pull request? There is an assert in MemoryStore's putIteratorAsValues method which is used to check if unroll memory is not released too much. This assert looks wrong. ## How was this patch tested? Jenkins tests. Author: Liang-Chi Hsieh <[email protected]> Closes apache#14642 from viirya/fix-unroll-memory. (cherry picked from commit e7bce9e) Signed-off-by: Josh Rosen <[email protected]>
…e scans (backport) This is a branch-2.0 backport of apache#15245. ## What changes were proposed in this pull request? This patch addresses a potential cause of resource leaks in data source file scans. As reported in [SPARK-17666](https://issues.apache.org/jira/browse/SPARK-17666), tasks which do not fully-consume their input may cause file handles / network connections (e.g. S3 connections) to be leaked. Spark's `NewHadoopRDD` uses a TaskContext callback to [close its record readers](https://github.com/apache/spark/blame/master/core/src/main/scala/org/apache/spark/rdd/NewHadoopRDD.scala#L208), but the new data source file scans will only close record readers once their iterators are fully-consumed. This patch modifies `RecordReaderIterator` and `HadoopFileLinesReader` to add `close()` methods and modifies all six implementations of `FileFormat.buildReader()` to register TaskContext task completion callbacks to guarantee that cleanup is eventually performed. ## How was this patch tested? Tested manually for now. Author: Josh Rosen <[email protected]> Closes apache#15271 from JoshRosen/SPARK-17666-backport.
## What changes were proposed in this pull request?
This PR proposes to fix wrongly indented examples in PySpark documentation
```
- >>> json_sdf = spark.readStream.format("json")\
- .schema(sdf_schema)\
- .load(tempfile.mkdtemp())
+ >>> json_sdf = spark.readStream.format("json") \\
+ ... .schema(sdf_schema) \\
+ ... .load(tempfile.mkdtemp())
```
```
- people.filter(people.age > 30).join(department, people.deptId == department.id)\
+ people.filter(people.age > 30).join(department, people.deptId == department.id) \\
```
```
- >>> examples = [LabeledPoint(1.1, Vectors.sparse(3, [(0, 1.23), (2, 4.56)])), \
- LabeledPoint(0.0, Vectors.dense([1.01, 2.02, 3.03]))]
+ >>> examples = [LabeledPoint(1.1, Vectors.sparse(3, [(0, 1.23), (2, 4.56)])),
+ ... LabeledPoint(0.0, Vectors.dense([1.01, 2.02, 3.03]))]
```
```
- >>> examples = [LabeledPoint(1.1, Vectors.sparse(3, [(0, -1.23), (2, 4.56e-7)])), \
- LabeledPoint(0.0, Vectors.dense([1.01, 2.02, 3.03]))]
+ >>> examples = [LabeledPoint(1.1, Vectors.sparse(3, [(0, -1.23), (2, 4.56e-7)])),
+ ... LabeledPoint(0.0, Vectors.dense([1.01, 2.02, 3.03]))]
```
```
- ... for x in iterator:
- ... print(x)
+ ... for x in iterator:
+ ... print(x)
```
## How was this patch tested?
Manually tested.
**Before**
<img width="601" alt="2016-09-27 2 29 27" src="https://cloud.githubusercontent.com/assets/6477701/18861294/29c0d5b4-84bf-11e6-99c5-3c9d913c125d.png">
<img width="1056" alt="2016-09-27 2 29 58" src="https://cloud.githubusercontent.com/assets/6477701/18861298/31694cd8-84bf-11e6-9e61-9888cb8c2089.png">
<img width="1079" alt="2016-09-27 2 30 05" src="https://cloud.githubusercontent.com/assets/6477701/18861301/359722da-84bf-11e6-97f9-5f5365582d14.png">
**After**
<img width="515" alt="2016-09-27 2 28 19" src="https://cloud.githubusercontent.com/assets/6477701/18861305/3ff88b88-84bf-11e6-902c-9f725e8a8b10.png">
<img width="652" alt="2016-09-27 3 50 59" src="https://cloud.githubusercontent.com/assets/6477701/18863053/592fbc74-84ca-11e6-8dbf-99cf57947de8.png">
<img width="709" alt="2016-09-27 3 51 03" src="https://cloud.githubusercontent.com/assets/6477701/18863060/601607be-84ca-11e6-80aa-a401df41c321.png">
Author: hyukjinkwon <[email protected]>
Closes apache#15242 from HyukjinKwon/minor-example-pyspark.
(cherry picked from commit 2190037)
Signed-off-by: Sean Owen <[email protected]>
… failure | Time |Thread 1 , Job1 | Thread 2 , Job2 | |:-------------:|:-------------:|:-----:| | 1 | abort stage due to FetchFailed | | | 2 | failedStages += failedStage | | | 3 | | task failed due to FetchFailed | | 4 | | can not post ResubmitFailedStages because failedStages is not empty | Then job2 of thread2 never resubmit the failed stage and hang. We should not add the failedStages when abortStage for fetch failure added unit test Author: w00228970 <[email protected]> Author: wangfei <[email protected]> Closes apache#15213 from scwf/dag-resubmit. (cherry picked from commit 46d1203) Signed-off-by: Shixiong Zhu <[email protected]>
…ackport) This backports apache#15273 to branch-2.0 Also verified the test passes after the patch was applied. rxin Author: Eric Liang <[email protected]> Closes apache#15282 from ericl/spark-17673-2.
…alues. ## What changes were proposed in this pull request? We added native versions of `collect_set` and `collect_list` in Spark 2.0. These currently also (try to) collect null values, this is different from the original Hive implementation. This PR fixes this by adding a null check to the `Collect.update` method. ## How was this patch tested? Added a regression test to `DataFrameAggregateSuite`. Author: Herman van Hovell <[email protected]> Closes apache#15208 from hvanhovell/SPARK-17641. (cherry picked from commit 7d09232) Signed-off-by: Reynold Xin <[email protected]>
- don't apply numBuckets in Shuffle partitioning since Shuffle cannot create a compatible partitioning with matching numBuckets (only numPartitions) - check numBuckets too in HashPartitioning compatibility
Conflicts: sql/catalyst/src/main/scala/org/apache/spark/sql/types/AbstractDataType.scala sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVInferSchema.scala sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVTypeCastSuite.scala
Merged
ymahajan
pushed a commit
that referenced
this pull request
Jan 13, 2017
…aggregations
## What changes were proposed in this pull request?
Partial aggregations are generated in `EnsureRequirements`, but the planner fails to
check if partial aggregation satisfies sort requirements.
For the following query:
```
val df2 = (0 to 1000).map(x => (x % 2, x.toString)).toDF("a", "b").createOrReplaceTempView("t2")
spark.sql("select max(b) from t2 group by a").explain(true)
```
Now, the SortAggregator won't insert Sort operator before partial aggregation, this will break sort-based partial aggregation.
```
== Physical Plan ==
SortAggregate(key=[a#5], functions=[max(b#6)], output=[max(b)#17])
+- *Sort [a#5 ASC], false, 0
+- Exchange hashpartitioning(a#5, 200)
+- SortAggregate(key=[a#5], functions=[partial_max(b#6)], output=[a#5, max#19])
+- LocalTableScan [a#5, b#6]
```
Actually, a correct plan is:
```
== Physical Plan ==
SortAggregate(key=[a#5], functions=[max(b#6)], output=[max(b)#17])
+- *Sort [a#5 ASC], false, 0
+- Exchange hashpartitioning(a#5, 200)
+- SortAggregate(key=[a#5], functions=[partial_max(b#6)], output=[a#5, max#19])
+- *Sort [a#5 ASC], false, 0
+- LocalTableScan [a#5, b#6]
```
## How was this patch tested?
Added tests in `PlannerSuite`.
Author: Takeshi YAMAMURO <[email protected]>
Closes apache#14865 from maropu/SPARK-17289.
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What changes were proposed in this pull request?
Merged Spark v2.0.1 to Snappy branch 2.0. List of issues fixed in this release is given in
https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12315420&version=12336857
SnappyChanges :
a) MemeoryStore.scala :
SnappyUnifiedMemoryManager was causing a problem. When critical up event is raised we disallow any storage memory. However, Spark broadcasts all the task binaries and stores them storage memory section.
Also, a task , while reading any block of data it tries to store that as values in memory. ( See MemeoryStore.scala for detailed code )
For this, it uses a unroll iterator. If it can unroll the complete data it is good and no problem. If not it will unroll as far as possible, and after that, it will use original iterator which may point to disk.
Earlier it used to give a joined iterator of unroll iterator + rest of the iterator ( PartiallyUnrolledIterator) . If nothing is in unroll iterator ( which is the case with critical event up) , it used to pick from rest iterator. Due to some logic changes in PartiallyUnrolledIterator, it no longer gives a joined iterator and task tries to access an empty structure and gets NoSuchElementException. Changed the code a bit to ensure that it tries to avoid iterating over unroll iterator.
How was this patch tested?
pre-checkin