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https://issues.apache.org/jira/browse/HADOOP-17935?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17419971#comment-17419971
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Brandon commented on HADOOP-17935:
----------------------------------
[[email protected]]
Thanks for the quick reply, Steve.
I should clarify that the Spark jobs _almost always_ work just fine. This bug
only happens rarely and unpredictably, in jobs that otherwise have no issue. So
I don't think permissions issues in the job are to blame.
# I could try enabling debug logging on `org.apache.hadoop.fs.s3a` and wait for
another driver to get stuck. The job does a lot of big table writes, so I'm a
bit concerned that leaving debug logging on all the time might slow down the
driver or clog up the log storage system.
# I didn't have bucket logs enabled at the time, for the pending-commit bucket.
I could try enabling that. However, I do have request metrics for that bucket,
which shows a lot of HTTP 5xx responses around the time when the driver got
stuck. So it's likely that the the driver got a "HTTP 503 Slow Down" response,
which led to the retry loop seen in the stack trace. I'm also noticing that
this stack trace shows a retry-within-a-retry.
# I could share a snippet of storediag output if you can specify which part
you're interested in. There's a lot there. Also, running storediag on my laptop
is not going to capture all the settings in effect in the actual Spark job.
# Could you elaborate on how increasing `fs.s3a.threads.max` would help? Does
that thread count have an impact on the mkdirs call?
> 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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