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https://issues.apache.org/jira/browse/HADOOP-17935?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17420341#comment-17420341
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Steve Loughran commented on HADOOP-17935:
-----------------------------------------
we shouldn't be doing retry-in-retry, so I'll look at that...does provide a
reason for the problem.
The 503 events hints that this could be HADOOP-16823, "HADOOP-16823. Large
DeleteObject requests are their own Thundering Herd."
turns out each object in a bulk delete request counts as 1 write of your quota
of 3500/s, so a page of 1000 entries will be rejected if there's more writes
going on in same partition of a bucket. The AWS SDK throttle retry handler
blindly retries, and so does the S3A one.
Are you writing files down a deep tree? And is it likely there's other writes
going on to the same tree in the bucket?
Assuming this is the case, you've got two options
* stay on 3.2.x & workaround: set fs.s3a.multiobjectdelete.enable= false. Yet,
it'll be slower.
* Upgrade to 3.3.0, or even better, 3.3.1 -looking at HADOOP-17771 to see a
workaround you'll need to fix.
3.3.1 does a lot on the magic committer, and, with the latest version of spark,
you'll even get the progress counters reporting the amount of data written.
Lots of other s3a improvements, too, including the ability to turn off
directory marker deletion entirely.
disabling multi-object delete is a quick test to see if this the cause; if it
goes away, then yes, upgrade time. And no, before you ask -the fix isn't going
to be backported....way too much change in the code.
> Spark job stuck in S3A StagingCommitter::setupJob
> -------------------------------------------------
>
> Key: HADOOP-17935
> URL: https://issues.apache.org/jira/browse/HADOOP-17935
> Project: Hadoop Common
> Issue Type: Bug
> Components: fs/s3
> Affects Versions: 3.2.1
> Environment: Spark 2.4.4
> Hadoop 3.2.1
> "spark.hadoop.fs.s3a.committer.name": "directory"
> Reporter: Brandon
> Priority: Major
>
> This is using the S3A directory staging committer, the Spark driver gets
> stuck in a retry loop inside setupJob. Here's a stack trace:
> {noformat}
> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:229)
> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:271)
> org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:290)
> org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:676)
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
> org.apache.spark.sql.execution.SQLExecution$$$Lambda$1753/2105635903.apply(Unknown
> Source)
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:78)
> org.apache.spark.sql.DataFrameWriter$$Lambda$1752/114484787.apply(Unknown
> Source)
> org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:676)
> org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:85)
> org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:85)
> => holding Monitor(org.apache.spark.sql.execution.QueryExecution@705144571})
> org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> org.apache.spark.sql.execution.SparkPlan$$Lambda$1574/1384254911.apply(Unknown
> Source)
> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:155)
> org.apache.spark.sql.execution.SparkPlan$$Lambda$1573/696771575.apply(Unknown
> Source)
> org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:131)
> org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:122)
> org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:102)
> org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:104)
> => holding
> Monitor(org.apache.spark.sql.execution.command.DataWritingCommandExec@539925125})
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:170)
> org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:139)
> org.apache.spark.internal.io.HadoopMapReduceCommitProtocol.setupJob(HadoopMapReduceCommitProtocol.scala:163)
> org.apache.hadoop.fs.s3a.commit.staging.DirectoryStagingCommitter.setupJob(DirectoryStagingCommitter.java:65)
> org.apache.hadoop.fs.s3a.commit.staging.StagingCommitter.setupJob(StagingCommitter.java:458)
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.setupJob(FileOutputCommitter.java:355)
> org.apache.hadoop.fs.FileSystem.mkdirs(FileSystem.java:2275)
> org.apache.hadoop.fs.s3a.S3AFileSystem.mkdirs(S3AFileSystem.java:2062)
> org.apache.hadoop.fs.s3a.S3AFileSystem.innerMkdirs(S3AFileSystem.java:2129)
> org.apache.hadoop.fs.s3a.S3AFileSystem.createFakeDirectory(S3AFileSystem.java:2808)
> org.apache.hadoop.fs.s3a.S3AFileSystem.createEmptyObject(S3AFileSystem.java:2833)
> org.apache.hadoop.fs.s3a.Invoker.retry(Invoker.java:236)
> org.apache.hadoop.fs.s3a.Invoker.retry(Invoker.java:261)
> org.apache.hadoop.fs.s3a.Invoker.retryUntranslated(Invoker.java:322)
> org.apache.hadoop.fs.s3a.Invoker$$Lambda$232/695085082.execute(Unknown Source)
> org.apache.hadoop.fs.s3a.Invoker.lambda$retry$3(Invoker.java:265)
> org.apache.hadoop.fs.s3a.Invoker.once(Invoker.java:109)
> org.apache.hadoop.fs.s3a.S3AFileSystem$$Lambda$1932/855044548.execute(Unknown
> Source)
> org.apache.hadoop.fs.s3a.S3AFileSystem.lambda$createEmptyObject$13(S3AFileSystem.java:2835)
> org.apache.hadoop.fs.s3a.S3AFileSystem.putObjectDirect(S3AFileSystem.java:1589)
> org.apache.hadoop.fs.s3a.S3AFileSystem.finishedWrite(S3AFileSystem.java:2751)
> org.apache.hadoop.fs.s3a.S3AFileSystem.deleteUnnecessaryFakeDirectories(S3AFileSystem.java:2785)
> org.apache.hadoop.fs.s3a.S3AFileSystem.removeKeys(S3AFileSystem.java:1717)
> org.apache.hadoop.fs.s3a.S3AFileSystem.deleteObjects(S3AFileSystem.java:1457)
> org.apache.hadoop.fs.s3a.Invoker.retryUntranslated(Invoker.java:285)
> org.apache.hadoop.fs.s3a.Invoker.retryUntranslated(Invoker.java:322)
> org.apache.hadoop.fs.s3a.S3AFileSystem$$Lambda$1933/1245120662.execute(Unknown
> Source)
> org.apache.hadoop.fs.s3a.S3AFileSystem.lambda$deleteObjects$8(S3AFileSystem.java:1461)
> com.amazonaws.services.s3.AmazonS3Client.deleteObjects(AmazonS3Client.java:2136)
> com.amazonaws.services.s3.AmazonS3Client.invoke(AmazonS3Client.java:4315)
> com.amazonaws.services.s3.AmazonS3Client.invoke(AmazonS3Client.java:4368)
> com.amazonaws.http.AmazonHttpClient.execute(AmazonHttpClient.java:513)
> com.amazonaws.http.AmazonHttpClient$RequestExecutionBuilderImpl.execute(AmazonHttpClient.java:649)
> com.amazonaws.http.AmazonHttpClient$RequestExecutor.access$500(AmazonHttpClient.java:667)
> com.amazonaws.http.AmazonHttpClient$RequestExecutor.execute(AmazonHttpClient.java:699)
> com.amazonaws.http.AmazonHttpClient$RequestExecutor.executeWithTimer(AmazonHttpClient.java:717)
> com.amazonaws.http.AmazonHttpClient$RequestExecutor.doExecute(AmazonHttpClient.java:743)
> com.amazonaws.http.AmazonHttpClient$RequestExecutor.executeHelper(AmazonHttpClient.java:1058)
> com.amazonaws.http.AmazonHttpClient$RequestExecutor.executeOneRequest(AmazonHttpClient.java:1191)
> com.amazonaws.http.AmazonHttpClient$RequestExecutor.pauseBeforeRetry(AmazonHttpClient.java:1653)
> com.amazonaws.http.AmazonHttpClient$RequestExecutor.doPauseBeforeRetry(AmazonHttpClient.java:1679)
> {noformat}
> Another thing of note in this setup, is the staging committer is using an S3
> bucket to track pending commits (used to use HDFS for this, but switched to
> S3 once it became strongly consistent).
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