Resync from upstream master #307
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## What changes were proposed in this pull request? All other classes in the reader/writer package doesn't have `V2` in their names, and the streaming reader/writer don't have `V2` either. It's more consistent to remove `V2` from `DataSourceV2Reader` and `DataSourceVWriter`. Also rename `DataSourceV2Option` to remote the `V2`, we should only have `V2` in the root interface: `DataSourceV2`. This PR also fixes some places that the mix-in interface doesn't extend the interface it aimed to mix in. ## How was this patch tested? existing tests. Author: Wenchen Fan <[email protected]> Closes apache#20427 from cloud-fan/ds-v2.
## What changes were proposed in this pull request? Rename the public APIs and names of pandas udfs. - `PANDAS SCALAR UDF` -> `SCALAR PANDAS UDF` - `PANDAS GROUP MAP UDF` -> `GROUPED MAP PANDAS UDF` - `PANDAS GROUP AGG UDF` -> `GROUPED AGG PANDAS UDF` ## How was this patch tested? The existing tests Author: gatorsmile <[email protected]> Closes apache#20428 from gatorsmile/renamePandasUDFs.
## What changes were proposed in this pull request? It is reported that the test `Cancelling stage in a query with Range` in `DataFrameRangeSuite` fails a few times in unrelated PRs. I personally also saw it too in my PR. This test is not very flaky actually but only fails occasionally. Based on how the test works, I guess that is because `range` finishes before the listener calls `cancelStage`. I increase the range number from `1000000000L` to `100000000000L` and count the range in one partition. I also reduce the `interval` of checking stage id. Hopefully it can make the test not flaky anymore. ## How was this patch tested? The modified tests. Author: Liang-Chi Hsieh <[email protected]> Closes apache#20431 from viirya/SPARK-23222.
…ore file. ## What changes were proposed in this pull request? This is a follow-up pr of apache#20338 which changed the downloaded file name of the python code style checker but it's not contained in .gitignore file so the file remains as an untracked file for git after running the checker. This pr adds the file name to .gitignore file. ## How was this patch tested? Tested manually. Author: Takuya UESHIN <[email protected]> Closes apache#20432 from ueshin/issues/SPARK-23174/fup1.
## What changes were proposed in this pull request? Still saw the performance regression introduced by `spark.sql.codegen.hugeMethodLimit` in our internal workloads. There are two major issues in the current solution. - The size of the complied byte code is not identical to the bytecode size of the method. The detection is still not accurate. - The bytecode size of a single operator (e.g., `SerializeFromObject`) could still exceed 8K limit. We saw the performance regression in such scenario. Since it is close to the release of 2.3, we decide to increase it to 64K for avoiding the perf regression. ## How was this patch tested? N/A Author: gatorsmile <[email protected]> Closes apache#20434 from gatorsmile/revertConf.
…he laptop (Mac) with OOM
## What changes were proposed in this pull request?
hive tests have been failing when they are run locally (Mac Os) after a recent change in the trunk. After running the tests for some time, the test fails with OOM with Error: unable to create new native thread.
I noticed the thread count goes all the way up to 2000+ after which we start getting these OOM errors. Most of the threads seem to be related to the connection pool in hive metastore (BoneCP-xxxxx-xxxx ). This behaviour change is happening after we made the following change to HiveClientImpl.reset()
``` SQL
def reset(): Unit = withHiveState {
try {
// code
} finally {
runSqlHive("USE default") ===> this is causing the issue
}
```
I am proposing to temporarily back-out part of a fix made to address SPARK-23000 to resolve this issue while we work-out the exact reason for this sudden increase in thread counts.
## How was this patch tested?
Ran hive/test multiple times in different machines.
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Dilip Biswal <[email protected]>
Closes apache#20441 from dilipbiswal/hive_tests.
## What changes were proposed in this pull request? Consistency in style, grammar and removal of extraneous characters. ## How was this patch tested? Manually as this is a doc change. Author: Shashwat Anand <[email protected]> Closes apache#20436 from ashashwat/SPARK-23174.
…nSuite ## What changes were proposed in this pull request? Like Parquet, ORC test suites should enable UDT tests. ## How was this patch tested? Pass the Jenkins with newly enabled test cases. Author: Dongjoon Hyun <[email protected]> Closes apache#20440 from dongjoon-hyun/SPARK-23276.
…r contains the references that are not in the left output ## What changes were proposed in this pull request? This PR is to fix the `ReplaceExceptWithFilter` rule when the right's Filter contains the references that are not in the left output. Before this PR, we got the error like ``` java.util.NoSuchElementException: key not found: a at scala.collection.MapLike$class.default(MapLike.scala:228) at scala.collection.AbstractMap.default(Map.scala:59) at scala.collection.MapLike$class.apply(MapLike.scala:141) at scala.collection.AbstractMap.apply(Map.scala:59) ``` After this PR, `ReplaceExceptWithFilter ` will not take an effect in this case. ## How was this patch tested? Added tests Author: gatorsmile <[email protected]> Closes apache#20444 from gatorsmile/fixReplaceExceptWithFilter.
## What changes were proposed in this pull request? Console sink will redistribute collected local data and trigger a distributed job in each batch, this is not necessary, so here change to local job. ## How was this patch tested? Existing UT and manual verification. Author: jerryshao <[email protected]> Closes apache#20447 from jerryshao/console-minor.
## What changes were proposed in this pull request? `ColumnVector` is aimed to support all the data types, but `CalendarIntervalType` is missing. Actually we do support interval type for inner fields, e.g. `ColumnarRow`, `ColumnarArray` both support interval type. It's weird if we don't support interval type at the top level. This PR adds the interval type support. This PR also makes `ColumnVector.getChild` protect. We need it public because `MutableColumnaRow.getInterval` needs it. Now the interval implementation is in `ColumnVector.getInterval`. ## How was this patch tested? a new test. Author: Wenchen Fan <[email protected]> Closes apache#20438 from cloud-fan/interval.
…or changes. Add breaking changes, as well as update behavior changes, to `2.3` ML migration guide. ## How was this patch tested? Doc only Author: Nick Pentreath <[email protected]> Closes apache#20421 from MLnick/SPARK-23112-ml-guide.
…ultSession
## What changes were proposed in this pull request?
In the current PySpark code, Python created `jsparkSession` doesn't add to JVM's defaultSession, this `SparkSession` object cannot be fetched from Java side, so the below scala code will be failed when loaded in PySpark application.
```scala
class TestSparkSession extends SparkListener with Logging {
override def onOtherEvent(event: SparkListenerEvent): Unit = {
event match {
case CreateTableEvent(db, table) =>
val session = SparkSession.getActiveSession.orElse(SparkSession.getDefaultSession)
assert(session.isDefined)
val tableInfo = session.get.sharedState.externalCatalog.getTable(db, table)
logInfo(s"Table info ${tableInfo}")
case e =>
logInfo(s"event $e")
}
}
}
```
So here propose to add fresh create `jsparkSession` to `defaultSession`.
## How was this patch tested?
Manual verification.
Author: jerryshao <[email protected]>
Author: hyukjinkwon <[email protected]>
Author: Saisai Shao <[email protected]>
Closes apache#20404 from jerryshao/SPARK-23228.
## What changes were proposed in this pull request? In apache#19980 , we thought `anyNullsSet` can be simply implemented by `numNulls() > 0`. This is logically true, but may have performance problems. `OrcColumnVector` is an example. It doesn't have the `numNulls` property, only has a `noNulls` property. We will lose a lot of performance if we use `numNulls() > 0` to check null. This PR simply revert apache#19980, with a renaming to call it `hasNull`. Better name suggestions are welcome, e.g. `nullable`? ## How was this patch tested? existing test Author: Wenchen Fan <[email protected]> Closes apache#20452 from cloud-fan/null.
## What changes were proposed in this pull request? Change DataSourceScanExec so that when grouping blocks together into partitions, also checks the end of the sorted list of splits to more efficiently fill out partitions. ## How was this patch tested? Updated old test to reflect the new logic, which causes the # of partitions to drop from 4 -> 3 Also, a current test exists to test large non-splittable files at https://github.com/glentakahashi/spark/blob/c575977a5952bf50b605be8079c9be1e30f3bd36/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileSourceStrategySuite.scala#L346 ## Rationale The current bin-packing method of next-fit descending for blocks into partitions is sub-optimal in a lot of cases and will result in extra partitions, un-even distribution of block-counts across partitions, and un-even distribution of partition sizes. As an example, 128 files ranging from 1MB, 2MB,...127MB,128MB. will result in 82 partitions with the current algorithm, but only 64 using this algorithm. Also in this example, the max # of blocks per partition in NFD is 13, while in this algorithm is is 2. More generally, running a simulation of 1000 runs using 128MB blocksize, between 1-1000 normally distributed file sizes between 1-500Mb, you can see an improvement of approx 5% reduction of partition counts, and a large reduction in standard deviation of blocks per partition. This algorithm also runs in O(n) time as NFD does, and in every case is strictly better results than NFD. Overall, the more even distribution of blocks across partitions and therefore reduced partition counts should result in a small but significant performance increase across the board Author: Glen Takahashi <[email protected]> Closes apache#20372 from glentakahashi/feature/improved-block-merging.
The code was ignoring the error code from the AddBlock RPC, which means that a failure to write to the WAL was being ignored by the receiver, and would lead to the block being acked (in the case of the Flume receiver) and data potentially lost. Author: Marcelo Vanzin <[email protected]> Closes apache#20161 from vanzin/SPARK-21525.
…omposite order by clause refers to both original columns and aliases
## What changes were proposed in this pull request?
Here is the test snippet.
``` SQL
scala> Seq[(Integer, Integer)](
| (1, 1),
| (1, 3),
| (2, 3),
| (3, 3),
| (4, null),
| (5, null)
| ).toDF("key", "value").createOrReplaceTempView("src")
scala> sql(
| """
| |SELECT MAX(value) as value, key as col2
| |FROM src
| |GROUP BY key
| |ORDER BY value desc, key
| """.stripMargin).show
+-----+----+
|value|col2|
+-----+----+
| 3| 3|
| 3| 2|
| 3| 1|
| null| 5|
| null| 4|
+-----+----+
```SQL
Here is the explain output :
```SQL
== Parsed Logical Plan ==
'Sort ['value DESC NULLS LAST, 'key ASC NULLS FIRST], true
+- 'Aggregate ['key], ['MAX('value) AS value#9, 'key AS col2#10]
+- 'UnresolvedRelation `src`
== Analyzed Logical Plan ==
value: int, col2: int
Project [value#9, col2#10]
+- Sort [value#9 DESC NULLS LAST, col2#10 DESC NULLS LAST], true
+- Aggregate [key#5], [max(value#6) AS value#9, key#5 AS col2#10]
+- SubqueryAlias src
+- Project [_1#2 AS key#5, _2#3 AS value#6]
+- LocalRelation [_1#2, _2#3]
``` SQL
The sort direction is being wrongly changed from ASC to DSC while resolving ```Sort``` in
resolveAggregateFunctions.
The above testcase models TPCDS-Q71 and thus we have the same issue in Q71 as well.
## How was this patch tested?
A few tests are added in SQLQuerySuite.
Author: Dilip Biswal <[email protected]>
Closes apache#20453 from dilipbiswal/local_spark.
Author: Henry Robinson <[email protected]> Closes apache#20443 from henryr/SPARK-23157.
## What changes were proposed in this pull request? Fill the last missing piece of `ColumnVector`: the map type support. The idea is similar to the array type support. A map is basically 2 arrays: keys and values. We ask the implementations to provide a key array, a value array, and an offset and length to specify the range of this map in the key/value array. In `WritableColumnVector`, we put the key array in first child vector, and value array in second child vector, and offsets and lengths in the current vector, which is very similar to how array type is implemented here. ## How was this patch tested? a new test Author: Wenchen Fan <[email protected]> Closes apache#20450 from cloud-fan/map.
…ns in Scan Data Source
## What changes were proposed in this pull request?
Currently, we scan the execution plan of the data source, first the unsafe operation of each row of data, and then re traverse the data for the count of rows. In terms of performance, this is not necessary. this PR combines the two operations and makes statistics on the number of rows while performing the unsafe operation.
Before modified,
```
val unsafeRow = rdd.mapPartitionsWithIndexInternal { (index, iter) =>
val proj = UnsafeProjection.create(schema)
proj.initialize(index)
iter.map(proj)
}
val numOutputRows = longMetric("numOutputRows")
unsafeRow.map { r =>
numOutputRows += 1
r
}
```
After modified,
val numOutputRows = longMetric("numOutputRows")
rdd.mapPartitionsWithIndexInternal { (index, iter) =>
val proj = UnsafeProjection.create(schema)
proj.initialize(index)
iter.map( r => {
numOutputRows += 1
proj(r)
})
}
## How was this patch tested?
the existed test cases.
Author: caoxuewen <[email protected]>
Closes apache#20415 from heary-cao/DataSourceScanExec.
## What changes were proposed in this pull request?
1. create a new package for partitioning/distribution related classes.
As Spark will add new concrete implementations of `Distribution` in new releases, it is good to
have a new package for partitioning/distribution related classes.
2. move streaming related class to package `org.apache.spark.sql.sources.v2.reader/writer.streaming`, instead of `org.apache.spark.sql.sources.v2.streaming.reader/writer`.
So that the there won't be package reader/writer inside package streaming, which is quite confusing.
Before change:
```
v2
├── reader
├── streaming
│ ├── reader
│ └── writer
└── writer
```
After change:
```
v2
├── reader
│ └── streaming
└── writer
└── streaming
```
## How was this patch tested?
Unit test.
Author: Wang Gengliang <[email protected]>
Closes apache#20435 from gengliangwang/new_pkg.
… Thriftserver Signed-off-by: Atallah Hezbor <atallahhezborgmail.com> ## What changes were proposed in this pull request? This PR proposes modifying the match statement that gets the columns of a row in HiveThriftServer. There was previously no case for `UserDefinedType`, so querying a table that contained them would throw a match error. The changes catch that case and return the string representation. ## How was this patch tested? While I would have liked to add a unit test, I couldn't easily incorporate UDTs into the ``HiveThriftServer2Suites`` pipeline. With some guidance I would be happy to push a commit with tests. Instead I did a manual test by loading a `DataFrame` with Point UDT in a spark shell with a HiveThriftServer. Then in beeline, connecting to the server and querying that table. Here is the result before the change ``` 0: jdbc:hive2://localhost:10000> select * from chicago; Error: scala.MatchError: org.apache.spark.sql.PointUDT2d980dc3 (of class org.apache.spark.sql.PointUDT) (state=,code=0) ``` And after the change: ``` 0: jdbc:hive2://localhost:10000> select * from chicago; +---------------------------------------+--------------+------------------------+---------------------+--+ | __fid__ | case_number | dtg | geom | +---------------------------------------+--------------+------------------------+---------------------+--+ | 109602f9-54f8-414b-8c6f-42b1a337643e | 2 | 2016-01-01 19:00:00.0 | POINT (-77 38) | | 709602f9-fcff-4429-8027-55649b6fd7ed | 1 | 2015-12-31 19:00:00.0 | POINT (-76.5 38.5) | | 009602f9-fcb5-45b1-a867-eb8ba10cab40 | 3 | 2016-01-02 19:00:00.0 | POINT (-78 39) | +---------------------------------------+--------------+------------------------+---------------------+--+ ``` Author: Atallah Hezbor <[email protected]> Closes apache#20385 from atallahhezbor/udts_over_hive.
…able ## What changes were proposed in this pull request? This PR include the following changes: - Make the capacity of `VectorizedParquetRecordReader` configurable; - Make the capacity of `OrcColumnarBatchReader` configurable; - Update the error message when required capacity in writable columnar vector cannot be fulfilled. ## How was this patch tested? N/A Author: Xingbo Jiang <[email protected]> Closes apache#20361 from jiangxb1987/vectorCapacity.
## What changes were proposed in this pull request? SpecifiedWindowFrame.defaultWindowFrame(hasOrderSpecification, acceptWindowFrame) was designed to handle the cases when some Window functions don't support setting a window frame (e.g. rank). However this param is never used. We may inline the whole of this function to simplify the code. ## How was this patch tested? Existing tests. Author: Xingbo Jiang <[email protected]> Closes apache#20463 from jiangxb1987/defaultWindowFrame.
…restore" This reverts commit d172181. The patch is not fully tested and out-of-date. So revert it.
… of `assertRaisesRegex`. ## What changes were proposed in this pull request? This is a follow-up pr of apache#19872 which uses `assertRaisesRegex` but it doesn't exist in Python 2, so some tests fail when running tests in Python 2 environment. Unfortunately, we missed it because currently Python 2 environment of the pr builder doesn't have proper versions of pandas or pyarrow, so the tests were skipped. This pr modifies to use `assertRaisesRegexp` instead of `assertRaisesRegex`. ## How was this patch tested? Tested manually in my local environment. Author: Takuya UESHIN <[email protected]> Closes apache#20467 from ueshin/issues/SPARK-22274/fup1.
## What changes were proposed in this pull request? Audit new APIs and docs in 2.3.0. ## How was this patch tested? No test. Author: Yanbo Liang <[email protected]> Closes apache#20459 from yanboliang/SPARK-23107.
## What changes were proposed in this pull request? This is a follow-up of apache#20450 which broke lint-java checks. This pr fixes the lint-java issues. ``` [ERROR] src/main/java/org/apache/spark/sql/vectorized/ColumnVector.java:[20,8] (imports) UnusedImports: Unused import - org.apache.spark.sql.catalyst.util.MapData. [ERROR] src/main/java/org/apache/spark/sql/vectorized/ColumnarArray.java:[21,8] (imports) UnusedImports: Unused import - org.apache.spark.sql.catalyst.util.MapData. [ERROR] src/main/java/org/apache/spark/sql/vectorized/ColumnarRow.java:[22,8] (imports) UnusedImports: Unused import - org.apache.spark.sql.catalyst.util.MapData. ``` ## How was this patch tested? Checked manually in my local environment. Author: Takuya UESHIN <[email protected]> Closes apache#20468 from ueshin/issues/SPARK-23280/fup1.
## What changes were proposed in this pull request? This is a followup pr of apache#20450. We should've enabled `MutableColumnarRow.getMap()` as well. ## How was this patch tested? Existing tests. Author: Takuya UESHIN <[email protected]> Closes apache#20471 from ueshin/issues/SPARK-23280/fup2.
## What changes were proposed in this pull request? The current DataSourceWriter API makes it hard to implement `onTaskCommit(taskCommit: TaskCommitMessage)` in `FileCommitProtocol`. In general, on receiving commit message, driver can start processing messages(e.g. persist messages into files) before all the messages are collected. The proposal to add a new API: `add(WriterCommitMessage message)`: Handles a commit message on receiving from a successful data writer. This should make the whole API of DataSourceWriter compatible with `FileCommitProtocol`, and more flexible. There was another radical attempt in apache#20386. This one should be more reasonable. ## How was this patch tested? Unit test Author: Wang Gengliang <[email protected]> Closes apache#20454 from gengliangwang/write_api.
## What changes were proposed in this pull request? Include stacktrace in the diagnostics message upon abnormal unregister from RM ## How was this patch tested? Tested with a failing job, and confirmed a stacktrace in the client output and YARN webUI. Author: Gera Shegalov <[email protected]> Closes apache#20470 from gerashegalov/gera/stacktrace-diagnostics.
…t APIs when accessing null slot ## What changes were proposed in this pull request? For some ColumnVector get APIs such as getDecimal, getBinary, getStruct, getArray, getInterval, getUTF8String, we should clearly document their behaviors when accessing null slot. They should return null in this case. Then we can remove null checks from the places using above APIs. For the APIs of primitive values like getInt, getInts, etc., this also documents their behaviors when accessing null slots. Their returning values are undefined and can be anything. ## How was this patch tested? Added tests into `ColumnarBatchSuite`. Author: Liang-Chi Hsieh <[email protected]> Closes apache#20455 from viirya/SPARK-23272-followup.
First the bad news: there's an unfixable race in the launcher code. (By unfixable I mean it would take a lot more effort than this change to fix it.) The good news is that it should only affect super short lived applications, such as the one run by the flaky test, so it's possible to work around it in our test. The fix also uncovered an issue with the recently added "closeAndWait()" method; closing the connection would still possibly cause data loss, so this change waits a while for the connection to finish itself, and closes the socket if that times out. The existing connection timeout is reused so that if desired it's possible to control how long to wait. As part of that I also restored the old behavior that disconnect() would force a disconnection from the child app; the "wait for data to arrive" approach is only taken when disposing of the handle. I tested this by inserting a bunch of sleeps in the test and the socket handling code in the launcher library; with those I was able to reproduce the error from the jenkins jobs. With the changes, even with all the sleeps still in place, all tests pass. Author: Marcelo Vanzin <[email protected]> Closes apache#20462 from vanzin/SPARK-23020.
## What changes were proposed in this pull request? here is race condition in TaskMemoryManger, which may cause OOM. The memory released may be taken by another task because there is a gap between releaseMemory and acquireMemory, e.g., UnifiedMemoryManager, causing the OOM. if the current is the only one that can perform spill. It can happen to BytesToBytesMap, as it only spill required bytes. Loop on current consumer if it still has memory to release. ## How was this patch tested? The race contention is hard to reproduce, but the current logic seems causing the issue. Please review http://spark.apache.org/contributing.html before opening a pull request. Author: Zhan Zhang <[email protected]> Closes apache#20480 from zhzhan/oom.
…ry expressions ## What changes were proposed in this pull request? This PR fixes a mistake in the `PushDownOperatorsToDataSource` rule, the column pruning logic is incorrect about `Project`. ## How was this patch tested? a new test case for column pruning with arbitrary expressions, and improve the existing tests to make sure the `PushDownOperatorsToDataSource` really works. Author: Wenchen Fan <[email protected]> Closes apache#20476 from cloud-fan/push-down.
## What changes were proposed in this pull request? https://issues.apache.org/jira/browse/SPARK-23309 reported a performance regression about cached table in Spark 2.3. While the investigating is still going on, this PR adds a conf to turn off the vectorized cache reader, to unblock the 2.3 release. ## How was this patch tested? a new test Author: Wenchen Fan <[email protected]> Closes apache#20483 from cloud-fan/cache.
…when there is not an existing one ## What changes were proposed in this pull request? Shuffle Index temporay file is used for atomic creating shuffle index file, it is not needed when the index file already exists after another attempts of same task had it done. ## How was this patch tested? exitsting ut cc squito Author: Kent Yao <[email protected]> Closes apache#20422 from yaooqinn/SPARK-23253.
…rsions in make-distribution.sh ## What changes were proposed in this pull request? When we specified a wrong profile to make a spark distribution, such as `-Phadoop1000`, we will get an odd package named like `spark-[WARNING] The requested profile "hadoop1000" could not be activated because it does not exist.-bin-hadoop-2.7.tgz`, which actually should be `"spark-$VERSION-bin-$NAME.tgz"` ## How was this patch tested? ### before ``` build/mvn help:evaluate -Dexpression=scala.binary.version -Phadoop1000 2>/dev/null | grep -v "INFO" | tail -n 1 [WARNING] The requested profile "hadoop1000" could not be activated because it does not exist. ``` ``` build/mvn help:evaluate -Dexpression=project.version -Phadoop1000 2>/dev/null | grep -v "INFO" | tail -n 1 [WARNING] The requested profile "hadoop1000" could not be activated because it does not exist. ``` ### after ``` build/mvn help:evaluate -Dexpression=project.version -Phadoop1000 2>/dev/null | grep -v "INFO" | grep -v "WARNING" | tail -n 1 2.4.0-SNAPSHOT ``` ``` build/mvn help:evaluate -Dexpression=scala.binary.version -Dscala.binary.version=2.11.1 2>/dev/null | grep -v "INFO" | grep -v "WARNING" | tail -n 1 2.11.1 ``` cloud-fan srowen Author: Kent Yao <[email protected]> Closes apache#20469 from yaooqinn/dist-minor.
## What changes were proposed in this pull request? Further clarification of caveats in using stream-stream outer joins. ## How was this patch tested? N/A Author: Tathagata Das <[email protected]> Closes apache#20494 from tdas/SPARK-23064-2.
## What changes were proposed in this pull request? This patch adds a small example to the schema string definition of schema function. It isn't obvious how to use it, so an example would be useful. ## How was this patch tested? N/A - doc only. Author: Reynold Xin <[email protected]> Closes apache#20491 from rxin/schema-doc.
## What changes were proposed in this pull request? In the document of `ContinuousReader.setOffset`, we say this method is used to specify the start offset. We also have a `ContinuousReader.getStartOffset` to get the value back. I think it makes more sense to rename `ContinuousReader.setOffset` to `setStartOffset`. ## How was this patch tested? N/A Author: Wenchen Fan <[email protected]> Closes apache#20486 from cloud-fan/rename.
…eTypedFilters ## What changes were proposed in this pull request? In the current test case for CombineTypedFilters, we lack the test of FilterFunction, so let's add it. In addition, in TypedFilterOptimizationSuite's existing test cases, Let's extract a common LocalRelation. ## How was this patch tested? add new test cases. Author: caoxuewen <[email protected]> Closes apache#20482 from heary-cao/TypedFilterOptimizationSuite.
…r all file-based data sources ## What changes were proposed in this pull request? Like Parquet, all file-based data source handles `spark.sql.files.ignoreMissingFiles` correctly. We had better have a test coverage for feature parity and in order to prevent future accidental regression for all data sources. ## How was this patch tested? Pass Jenkins with a newly added test case. Author: Dongjoon Hyun <[email protected]> Closes apache#20479 from dongjoon-hyun/SPARK-23305.
…re are occurrences of backslashes. From [PEP 257](https://www.python.org/dev/peps/pep-0257/): > For consistency, always use """triple double quotes""" around docstrings. Use r"""raw triple double quotes""" if you use any backslashes in your docstrings. For Unicode docstrings, use u"""Unicode triple-quoted strings""". For example, this is what help (kafka_wordcount) shows: ``` DESCRIPTION Counts words in UTF8 encoded, ' ' delimited text received from the network every second. Usage: kafka_wordcount.py <zk> <topic> To run this on your local machine, you need to setup Kafka and create a producer first, see http://kafka.apache.org/documentation.html#quickstart and then run the example `$ bin/spark-submit --jars external/kafka-assembly/target/scala-*/spark-streaming-kafka-assembly-*.jar examples/src/main/python/streaming/kafka_wordcount.py localhost:2181 test` ``` This is what it shows, after the fix: ``` DESCRIPTION Counts words in UTF8 encoded, '\n' delimited text received from the network every second. Usage: kafka_wordcount.py <zk> <topic> To run this on your local machine, you need to setup Kafka and create a producer first, see http://kafka.apache.org/documentation.html#quickstart and then run the example `$ bin/spark-submit --jars \ external/kafka-assembly/target/scala-*/spark-streaming-kafka-assembly-*.jar \ examples/src/main/python/streaming/kafka_wordcount.py \ localhost:2181 test` ``` The thing worth noticing is no linebreak here in the help. ## What changes were proposed in this pull request? Change triple double quotes to raw triple double quotes when there are occurrences of backslashes in docstrings. ## How was this patch tested? Manually as this is a doc fix. Author: Shashwat Anand <[email protected]> Closes apache#20497 from ashashwat/docstring-fixes.
…na.replace in PySpark" This reverts commit 0fcde87. See the discussion in [SPARK-21658](https://issues.apache.org/jira/browse/SPARK-21658), [SPARK-19454](https://issues.apache.org/jira/browse/SPARK-19454) and apache#16793 Author: hyukjinkwon <[email protected]> Closes apache#20496 from HyukjinKwon/revert-SPARK-21658.
…ader ## What changes were proposed in this pull request? This PR proposes to add `columnSchema` in Python side too. ```python >>> from pyspark.ml.image import ImageSchema >>> ImageSchema.columnSchema.simpleString() 'struct<origin:string,height:int,width:int,nChannels:int,mode:int,data:binary>' ``` ## How was this patch tested? Manually tested and unittest was added in `python/pyspark/ml/tests.py`. Author: hyukjinkwon <[email protected]> Closes apache#20475 from HyukjinKwon/SPARK-23256.
## What changes were proposed in this pull request? Fix decimalArithmeticOperations.sql test ## How was this patch tested? N/A Author: Yuming Wang <[email protected]> Author: wangyum <[email protected]> Author: Yuming Wang <[email protected]> Closes apache#20498 from wangyum/SPARK-22036.
…d timestamp before cleaning up them
## What changes were proposed in this pull request?
Sort jobs/stages/tasks/queries with the completed timestamp before cleaning up them to make the behavior consistent with 2.2.
## How was this patch tested?
- Jenkins.
- Manually ran the following codes and checked the UI for jobs/stages/tasks/queries.
```
spark.ui.retainedJobs 10
spark.ui.retainedStages 10
spark.sql.ui.retainedExecutions 10
spark.ui.retainedTasks 10
```
```
new Thread() {
override def run() {
spark.range(1, 2).foreach { i =>
Thread.sleep(10000)
}
}
}.start()
Thread.sleep(5000)
for (_ <- 1 to 20) {
new Thread() {
override def run() {
spark.range(1, 2).foreach { i =>
}
}
}.start()
}
Thread.sleep(15000)
spark.range(1, 2).foreach { i =>
}
sc.makeRDD(1 to 100, 100).foreach { i =>
}
```
Author: Shixiong Zhu <[email protected]>
Closes apache#20481 from zsxwing/SPARK-23307.
…fle reader To fix regression for TPC-DS queries Author: Sital Kedia <[email protected]> Closes apache#20492 from sitalkedia/turn_off_async_inputstream.
## What changes were proposed in this pull request? Spark SQL executions page throws the following error and the page crashes: ``` HTTP ERROR 500 Problem accessing /SQL/. Reason: Server Error Caused by: java.lang.NullPointerException at scala.collection.immutable.StringOps$.length$extension(StringOps.scala:47) at scala.collection.immutable.StringOps.length(StringOps.scala:47) at scala.collection.IndexedSeqOptimized$class.isEmpty(IndexedSeqOptimized.scala:27) at scala.collection.immutable.StringOps.isEmpty(StringOps.scala:29) at scala.collection.TraversableOnce$class.nonEmpty(TraversableOnce.scala:111) at scala.collection.immutable.StringOps.nonEmpty(StringOps.scala:29) at org.apache.spark.sql.execution.ui.ExecutionTable.descriptionCell(AllExecutionsPage.scala:182) at org.apache.spark.sql.execution.ui.ExecutionTable.row(AllExecutionsPage.scala:155) at org.apache.spark.sql.execution.ui.ExecutionTable$$anonfun$8.apply(AllExecutionsPage.scala:204) at org.apache.spark.sql.execution.ui.ExecutionTable$$anonfun$8.apply(AllExecutionsPage.scala:204) at org.apache.spark.ui.UIUtils$$anonfun$listingTable$2.apply(UIUtils.scala:339) at org.apache.spark.ui.UIUtils$$anonfun$listingTable$2.apply(UIUtils.scala:339) at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at scala.collection.TraversableLike$class.map(TraversableLike.scala:234) at scala.collection.AbstractTraversable.map(Traversable.scala:104) at org.apache.spark.ui.UIUtils$.listingTable(UIUtils.scala:339) at org.apache.spark.sql.execution.ui.ExecutionTable.toNodeSeq(AllExecutionsPage.scala:203) at org.apache.spark.sql.execution.ui.AllExecutionsPage.render(AllExecutionsPage.scala:67) at org.apache.spark.ui.WebUI$$anonfun$2.apply(WebUI.scala:82) at org.apache.spark.ui.WebUI$$anonfun$2.apply(WebUI.scala:82) at org.apache.spark.ui.JettyUtils$$anon$3.doGet(JettyUtils.scala:90) at javax.servlet.http.HttpServlet.service(HttpServlet.java:687) at javax.servlet.http.HttpServlet.service(HttpServlet.java:790) at org.eclipse.jetty.servlet.ServletHolder.handle(ServletHolder.java:848) at org.eclipse.jetty.servlet.ServletHandler.doHandle(ServletHandler.java:584) at org.eclipse.jetty.server.handler.ContextHandler.doHandle(ContextHandler.java:1180) at org.eclipse.jetty.servlet.ServletHandler.doScope(ServletHandler.java:512) at org.eclipse.jetty.server.handler.ContextHandler.doScope(ContextHandler.java:1112) at org.eclipse.jetty.server.handler.ScopedHandler.handle(ScopedHandler.java:141) at org.eclipse.jetty.server.handler.ContextHandlerCollection.handle(ContextHandlerCollection.java:213) at org.eclipse.jetty.server.handler.HandlerWrapper.handle(HandlerWrapper.java:134) at org.eclipse.jetty.server.Server.handle(Server.java:534) at org.eclipse.jetty.server.HttpChannel.handle(HttpChannel.java:320) at org.eclipse.jetty.server.HttpConnection.onFillable(HttpConnection.java:251) at org.eclipse.jetty.io.AbstractConnection$ReadCallback.succeeded(AbstractConnection.java:283) at org.eclipse.jetty.io.FillInterest.fillable(FillInterest.java:108) at org.eclipse.jetty.io.SelectChannelEndPoint$2.run(SelectChannelEndPoint.java:93) at org.eclipse.jetty.util.thread.strategy.ExecuteProduceConsume.executeProduceConsume(ExecuteProduceConsume.java:303) at org.eclipse.jetty.util.thread.strategy.ExecuteProduceConsume.produceConsume(ExecuteProduceConsume.java:148) at org.eclipse.jetty.util.thread.strategy.ExecuteProduceConsume.run(ExecuteProduceConsume.java:136) at org.eclipse.jetty.util.thread.QueuedThreadPool.runJob(QueuedThreadPool.java:671) at org.eclipse.jetty.util.thread.QueuedThreadPool$2.run(QueuedThreadPool.java:589) at java.lang.Thread.run(Thread.java:748) ``` One of the possible reason that this page fails may be the `SparkListenerSQLExecutionStart` event get dropped before processed, so the execution description and details don't get updated. This was not a issue in 2.2 because it would ignore any job start event that arrives before the corresponding execution start event, which doesn't sound like a good decision. We shall try to handle the null values in the front page side, that is, try to give a default value when `execution.details` or `execution.description` is null. Another possible approach is not to spill the `LiveExecutionData` in `SQLAppStatusListener.update(exec: LiveExecutionData)` if `exec.details` is null. This is not ideal because this way you will not see the execution if `SparkListenerSQLExecutionStart` event is lost, because `AllExecutionsPage` only read executions from KVStore. ## How was this patch tested? After the change, the page shows the following:  Author: Xingbo Jiang <[email protected]> Closes apache#20502 from jiangxb1987/executionPage.
…running ## What changes were proposed in this pull request? When a task is still running, metrics like executorRunTime are not available. Then `schedulerDelay` will be almost the same as `duration` and that's confusing. This PR makes `schedulerDelay` return 0 when the task is running which is the same behavior as 2.2. ## How was this patch tested? `AppStatusUtilsSuite.schedulerDelay` Author: Shixiong Zhu <[email protected]> Closes apache#20493 from zsxwing/SPARK-23326.
…rting Spark DataFrame to Pandas DataFrame. ## What changes were proposed in this pull request? In apache#18664, there was a change in how `DateType` is being returned to users ([line 1968 in dataframe.py](https://github.com/apache/spark/pull/18664/files#diff-6fc344560230bf0ef711bb9b5573f1faR1968)). This can cause client code which works in Spark 2.2 to fail. See [SPARK-23290](https://issues.apache.org/jira/browse/SPARK-23290?focusedCommentId=16350917&page=com.atlassian.jira.plugin.system.issuetabpanels%3Acomment-tabpanel#comment-16350917) for an example. This pr modifies to use `datetime.date` for date type as Spark 2.2 does. ## How was this patch tested? Tests modified to fit the new behavior and existing tests. Author: Takuya UESHIN <[email protected]> Closes apache#20506 from ueshin/issues/SPARK-23290.
…r not in PySpark SQL tests ## What changes were proposed in this pull request? This PR proposes to log if PyArrow and Pandas are installed or not so we can check if related tests are going to be skipped or not. ## How was this patch tested? Manually tested: I don't have PyArrow installed in PyPy. ```bash $ ./run-tests --python-executables=python3 ``` ``` ... Will test against the following Python executables: ['python3'] Will test the following Python modules: ['pyspark-core', 'pyspark-ml', 'pyspark-mllib', 'pyspark-sql', 'pyspark-streaming'] Will test PyArrow related features against Python executable 'python3' in 'pyspark-sql' module. Will test Pandas related features against Python executable 'python3' in 'pyspark-sql' module. Starting test(python3): pyspark.mllib.tests Starting test(python3): pyspark.sql.tests Starting test(python3): pyspark.streaming.tests Starting test(python3): pyspark.tests ``` ```bash $ ./run-tests --modules=pyspark-streaming ``` ``` ... Will test against the following Python executables: ['python2.7', 'pypy'] Will test the following Python modules: ['pyspark-streaming'] Starting test(pypy): pyspark.streaming.tests Starting test(pypy): pyspark.streaming.util Starting test(python2.7): pyspark.streaming.tests Starting test(python2.7): pyspark.streaming.util ``` ```bash $ ./run-tests ``` ``` ... Will test against the following Python executables: ['python2.7', 'pypy'] Will test the following Python modules: ['pyspark-core', 'pyspark-ml', 'pyspark-mllib', 'pyspark-sql', 'pyspark-streaming'] Will test PyArrow related features against Python executable 'python2.7' in 'pyspark-sql' module. Will test Pandas related features against Python executable 'python2.7' in 'pyspark-sql' module. Will skip PyArrow related features against Python executable 'pypy' in 'pyspark-sql' module. PyArrow >= 0.8.0 is required; however, PyArrow was not found. Will test Pandas related features against Python executable 'pypy' in 'pyspark-sql' module. Starting test(pypy): pyspark.streaming.tests Starting test(pypy): pyspark.sql.tests Starting test(pypy): pyspark.tests Starting test(python2.7): pyspark.mllib.tests ``` ```bash $ ./run-tests --modules=pyspark-sql --python-executables=pypy ``` ``` ... Will test against the following Python executables: ['pypy'] Will test the following Python modules: ['pyspark-sql'] Will skip PyArrow related features against Python executable 'pypy' in 'pyspark-sql' module. PyArrow >= 0.8.0 is required; however, PyArrow was not found. Will test Pandas related features against Python executable 'pypy' in 'pyspark-sql' module. Starting test(pypy): pyspark.sql.tests Starting test(pypy): pyspark.sql.catalog Starting test(pypy): pyspark.sql.column Starting test(pypy): pyspark.sql.conf ``` After some modification to produce other cases: ```bash $ ./run-tests ``` ``` ... Will test against the following Python executables: ['python2.7', 'pypy'] Will test the following Python modules: ['pyspark-core', 'pyspark-ml', 'pyspark-mllib', 'pyspark-sql', 'pyspark-streaming'] Will skip PyArrow related features against Python executable 'python2.7' in 'pyspark-sql' module. PyArrow >= 20.0.0 is required; however, PyArrow 0.8.0 was found. Will skip Pandas related features against Python executable 'python2.7' in 'pyspark-sql' module. Pandas >= 20.0.0 is required; however, Pandas 0.20.2 was found. Will skip PyArrow related features against Python executable 'pypy' in 'pyspark-sql' module. PyArrow >= 20.0.0 is required; however, PyArrow was not found. Will skip Pandas related features against Python executable 'pypy' in 'pyspark-sql' module. Pandas >= 20.0.0 is required; however, Pandas 0.22.0 was found. Starting test(pypy): pyspark.sql.tests Starting test(pypy): pyspark.streaming.tests Starting test(pypy): pyspark.tests Starting test(python2.7): pyspark.mllib.tests ``` ```bash ./run-tests-with-coverage ``` ``` ... Will test against the following Python executables: ['python2.7', 'pypy'] Will test the following Python modules: ['pyspark-core', 'pyspark-ml', 'pyspark-mllib', 'pyspark-sql', 'pyspark-streaming'] Will test PyArrow related features against Python executable 'python2.7' in 'pyspark-sql' module. Will test Pandas related features against Python executable 'python2.7' in 'pyspark-sql' module. Coverage is not installed in Python executable 'pypy' but 'COVERAGE_PROCESS_START' environment variable is set, exiting. ``` Author: hyukjinkwon <[email protected]> Closes apache#20473 from HyukjinKwon/SPARK-23300.
…() to handle str type properly in Python 2.
## What changes were proposed in this pull request?
In Python 2, when `pandas_udf` tries to return string type value created in the udf with `".."`, the execution fails. E.g.,
```python
from pyspark.sql.functions import pandas_udf, col
import pandas as pd
df = spark.range(10)
str_f = pandas_udf(lambda x: pd.Series(["%s" % i for i in x]), "string")
df.select(str_f(col('id'))).show()
```
raises the following exception:
```
...
java.lang.AssertionError: assertion failed: Invalid schema from pandas_udf: expected StringType, got BinaryType
at scala.Predef$.assert(Predef.scala:170)
at org.apache.spark.sql.execution.python.ArrowEvalPythonExec$$anon$2.<init>(ArrowEvalPythonExec.scala:93)
...
```
Seems like pyarrow ignores `type` parameter for `pa.Array.from_pandas()` and consider it as binary type when the type is string type and the string values are `str` instead of `unicode` in Python 2.
This pr adds a workaround for the case.
## How was this patch tested?
Added a test and existing tests.
Author: Takuya UESHIN <[email protected]>
Closes apache#20507 from ueshin/issues/SPARK-23334.
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