[SPARK-23457][SQL] Register task completion listeners first in ParquetFileFormat by dongjoon-hyun · Pull Request #20619 · apache/spark

dongjoon-hyun · 2018-02-15T16:59:12Z

What changes were proposed in this pull request?

ParquetFileFormat leaks opened files in some cases. This PR prevents that by registering task completion listers first before initialization.

Caused by: sbt.ForkMain$ForkError: java.lang.Throwable: null
at org.apache.spark.DebugFilesystem$.addOpenStream(DebugFilesystem.scala:36)
at org.apache.spark.DebugFilesystem.open(DebugFilesystem.scala:70)
at org.apache.hadoop.fs.FileSystem.open(FileSystem.java:769)
at org.apache.parquet.hadoop.ParquetFileReader.<init>(ParquetFileReader.java:538)
at org.apache.spark.sql.execution.datasources.parquet.SpecificParquetRecordReaderBase.initialize(SpecificParquetRecordReaderBase.java:149)
at org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.initialize(VectorizedParquetRecordReader.java:133)
at org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anonfun$buildReaderWithPartitionValues$1.apply(ParquetFileFormat.scala:400)
at

How was this patch tested?

Manual. The following test case generates the same leakage.

 test("SPARK-23457 Register task completion listeners first in ParquetFileFormat") {
withSQLConf(SQLConf.PARQUET_VECTORIZED_READER_BATCH_SIZE.key ->s"${Int.MaxValue}") {
withTempDir { dir =>valbasePath= dir.getCanonicalPath
Seq(0).toDF("a").write.format("parquet").save(newPath(basePath, "first").toString)
Seq(1).toDF("a").write.format("parquet").save(newPath(basePath, "second").toString)
valdf= spark.read.parquet(
newPath(basePath, "first").toString,
newPath(basePath, "second").toString)
vale= intercept[SparkException] {
df.collect()
}
assert(e.getCause.isInstanceOf[OutOfMemoryError])
}
}
}

…etFileFormat

dongjoon-hyun · 2018-02-15T17:01:43Z

Hi, @cloud-fan and @gatorsmile .
This is the same kind of PR about opened file leakage for ParquetFileFormat. Could you review this?

kiszk · 2018-02-15T17:39:07Z

 // UnsafeRowParquetRecordReader appends the columns internally to avoid another copy.
- if (parquetReader.isInstanceOf[VectorizedParquetRecordReader] &&
- enableVectorizedReader) {
+ if (enableVectorizedReader) {


Would it be possible to merge this if-statement into the above if-statement?

Yep. It looks possible. I'll update together after getting more reviews. Thanks, @kiszk .

yea it seems more reasonable to merge this if-else now.

gatorsmile · 2018-02-15T17:45:04Z

cc @ala @michal-databricks @cloud-fan

dongjoon-hyun · 2018-02-15T17:56:09Z

 }

- val iter = new RecordReaderIterator(parquetReader)
- taskContext.foreach(_.addTaskCompletionListener(_ => iter.close()))


According to the reported leakage, this is too late.

SparkQA · 2018-02-15T20:11:03Z

Test build #87482 has finished for PR 20619 at commit 43f809f.

This patch passes all tests.
This patch merges cleanly.
This patch adds no public classes.

kiszk · 2018-02-16T02:40:17Z

It looks good to me that we move the registrations to the new (earlier) places.

felixcheung · 2018-02-16T09:39:44Z

 val vectorizedReader = new VectorizedParquetRecordReader(
 convertTz.orNull, enableOffHeapColumnVector && taskContext.isDefined, capacity)
+ val recordReaderIterator = new RecordReaderIterator(vectorizedReader)
+ // Register a task completion lister before `initalization`.


could new VectorizedParquetRecordReader or new RecordReaderIterator fail?

Those constructors didn't look heavy to me.

cloud-fan · 2018-02-16T14:53:25Z

can we provide a manual test like the OOM one in your ORC PR?

dongjoon-hyun · 2018-02-16T18:48:23Z

Yep. I'll try for this, too. @cloud-fan .

dongjoon-hyun · 2018-02-17T03:20:07Z

The reproducible test case is added into PR description and the code is updated according to @kiszk and @cloud-fan 's comments.

cloud-fan · 2018-02-17T03:23:24Z

LGTM

dongjoon-hyun · 2018-02-17T03:25:00Z

Thank you for last-minute review before your vacation. I'm lucky. :)

gatorsmile · 2018-02-17T04:34:06Z

He is already on vacation. : )

SparkQA · 2018-02-17T04:59:39Z

Test build #87516 has finished for PR 20619 at commit e08d06c.

This patch fails Spark unit tests.
This patch merges cleanly.
This patch adds no public classes.

dongjoon-hyun · 2018-02-17T06:11:38Z

Oh.. It was a review from a vacation.

dongjoon-hyun · 2018-02-17T06:11:45Z

Retest this please.

dongjoon-hyun · 2018-02-17T06:12:55Z

The failure is irrelevant to this PR.

org.apache.spark.sql.hive.client.HiveClientSuites.(It is not a test it is a sbt.testing.NestedSuiteSelector)

SparkQA · 2018-02-17T07:52:06Z

Test build #87518 has finished for PR 20619 at commit e08d06c.

This patch fails Spark unit tests.
This patch merges cleanly.
This patch adds no public classes.

gatorsmile · 2018-02-17T07:58:45Z

retest this please

dongjoon-hyun · 2018-02-17T08:07:45Z

Thank you for retriggering, @gatorsmile .

SparkQA · 2018-02-17T10:24:18Z

Test build #87520 has finished for PR 20619 at commit e08d06c.

This patch fails Spark unit tests.
This patch merges cleanly.
This patch adds no public classes.

kiszk · 2018-02-17T10:27:34Z

Would it be worth to add this JIRA number in a comment as we did for ORC?

kiszk · 2018-02-17T10:28:02Z

retest this please

SparkQA · 2018-02-17T12:50:47Z

Test build #87523 has finished for PR 20619 at commit e08d06c.

This patch fails Spark unit tests.
This patch merges cleanly.
This patch adds no public classes.

kiszk · 2018-02-17T14:48:19Z

Umm, we still see the following exception in the log ...

Caused by: sbt.ForkMain$ForkError: java.lang.Throwable: null
at org.apache.spark.DebugFilesystem$.addOpenStream(DebugFilesystem.scala:36)
at org.apache.spark.DebugFilesystem.open(DebugFilesystem.scala:70)
at org.apache.hadoop.fs.FileSystem.open(FileSystem.java:766)
at org.apache.orc.impl.RecordReaderUtils$DefaultDataReader.open(RecordReaderUtils.java:173)
at org.apache.orc.impl.RecordReaderImpl.<init>(RecordReaderImpl.java:254)
at org.apache.orc.impl.ReaderImpl.rows(ReaderImpl.java:633)
at org.apache.spark.sql.execution.datasources.orc.OrcColumnarBatchReader.initialize(OrcColumnarBatchReader.java:140)
at org.apache.spark.sql.execution.datasources.orc.OrcFileFormat$$anonfun$buildReaderWithPartitionValues$2.apply(OrcFileFormat.scala:197)
at org.apache.spark.sql.execution.datasources.orc.OrcFileFormat$$anonfun$buildReaderWithPartitionValues$2.apply(OrcFileFormat.scala:161)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:125)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:179)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:106)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.scan_nextBatch$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1834)
at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1162)
at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:1162)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2063)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2063)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
... 3 more

dongjoon-hyun · 2018-02-17T17:13:20Z

Yep. @kiszk . @mgaido91 also reports that, so I'm investigating that more.

However, that doesn't mean this approach is not proper. You can see the manual test case example in previous ORC-related PR and this PR. This approach definitely reduces the number of point of failures.

For the remaining issue, I think we may need a different approach in a different code path.

dongjoon-hyun · 2018-02-17T17:13:45Z

For the following, I'll create another one.

Would it be worth to add this JIRA number in a comment as we did for ORC?

mgaido91 · 2018-02-17T17:27:09Z

LGTM

dongjoon-hyun · 2018-02-17T17:47:49Z

Thank you for review, @mgaido91 .

kiszk · 2018-02-17T17:56:57Z

LGTM with one minor comment

dongjoon-hyun · 2018-02-17T18:02:27Z

Thank you, @kiszk . I added SPARK-23390 in the PR description.

Would it be worth to add this JIRA number in a comment as we did for ORC?

dongjoon-hyun · 2018-02-17T18:02:55Z

Retest this please.

dongjoon-hyun · 2018-02-17T18:37:27Z

Oh, @kiszk . The following meat really comment in the code. Sorry, I misunderstood.

Would it be worth to add this JIRA number in a comment as we did for ORC?

dongjoon-hyun · 2018-02-17T18:39:09Z

 val vectorizedReader = new VectorizedParquetRecordReader(
 convertTz.orNull, enableOffHeapColumnVector && taskContext.isDefined, capacity)
+ val iter = new RecordReaderIterator(vectorizedReader)
+ // SPARK-23457 Register a task completion lister before `initialization`.


Now, SPARK-23457 is added.

SparkQA · 2018-02-17T20:27:45Z

Test build #87527 has finished for PR 20619 at commit e08d06c.

This patch fails Spark unit tests.
This patch merges cleanly.
This patch adds no public classes.

SparkQA · 2018-02-17T21:01:21Z

Test build #87528 has finished for PR 20619 at commit 8bd02d8.

This patch fails Spark unit tests.
This patch merges cleanly.
This patch adds no public classes.

dongjoon-hyun · 2018-02-17T23:58:15Z

The final failure is irrelevant to this.

org.apache.spark.sql.sources.CreateTableAsSelectSuite.(It is not a test it is a sbt.testing.SuiteSelector)

dongjoon-hyun · 2018-02-17T23:58:21Z

Retest this please.

SparkQA · 2018-02-18T02:32:50Z

Test build #87533 has finished for PR 20619 at commit 8bd02d8.

This patch fails Spark unit tests.
This patch merges cleanly.
This patch adds no public classes.

kiszk · 2018-02-18T06:10:58Z

retest this please

SparkQA · 2018-02-18T08:05:01Z

Test build #87534 has finished for PR 20619 at commit 8bd02d8.

This patch fails due to an unknown error code, -9.
This patch merges cleanly.
This patch adds no public classes.

kiszk · 2018-02-18T08:14:32Z

retest this please

SparkQA · 2018-02-18T09:59:25Z

Test build #87535 has finished for PR 20619 at commit 8bd02d8.

This patch fails Spark unit tests.
This patch merges cleanly.
This patch adds no public classes.

viirya · 2018-02-18T13:52:32Z

retest this please.

SparkQA · 2018-02-18T17:05:53Z

Test build #87537 has finished for PR 20619 at commit 8bd02d8.

This patch passes all tests.
This patch merges cleanly.
This patch adds no public classes.

cloud-fan · 2018-02-20T05:33:18Z

thanks, merging to master!

dongjoon-hyun · 2018-02-20T06:08:33Z

Thank you all!

dongjoon-hyun · 2018-03-01T18:19:22Z

Hi, @cloud-fan .
Since 2.3 is announced, can we have this in branch-2.3 for Apache Spark 2.3.1?

cloud-fan · 2018-03-02T03:28:50Z

Yea, please go ahead.

dongjoon-hyun · 2018-03-02T04:29:15Z

Thank you, @cloud-fan !

[SPARK-23390][SQL] Register task completion listerners first in Parqu…
43f809f
…etFileFormat

kiszk reviewed Feb 15, 2018
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dongjoon-hyun commented Feb 15, 2018
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felixcheung reviewed Feb 16, 2018
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dongjoon-hyun changed the title ~~[SPARK-23390][SQL] Register task completion listerners first in ParquetFileFormat~~[SPARK-23390][SQL] Register task completion listeners first in ParquetFileFormatFeb 17, 2018

Address comments
e08d06c

dongjoon-hyun changed the title ~~[SPARK-23390][SQL] Register task completion listeners first in ParquetFileFormat~~[SPARK-23457][SQL] Register task completion listeners first in ParquetFileFormatFeb 17, 2018

Address comment.
8bd02d8

dongjoon-hyun commented Feb 17, 2018
View reviewed changes

asfgit closed this in f5850e7Feb 20, 2018

dongjoon-hyun deleted the SPARK-23390 branch February 20, 2018 06:08

dongjoon-hyun mentioned this pull request Mar 3, 2018
[SPARK-23457][SQL][BRANCH-2.3] Register task completion listeners first in ParquetFileFormat #20714
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