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Posted to issues@spark.apache.org by "Jason Moore (JIRA)" <ji...@apache.org> on 2016/04/10 08:48:25 UTC

[jira] [Resolved] (SPARK-14357) Tasks that fail due to CommitDeniedException (a side-effect of speculation) can cause job failure

     [ https://issues.apache.org/jira/browse/SPARK-14357?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Jason Moore resolved SPARK-14357.
---------------------------------
    Resolution: Fixed

Issue resolved by pull request 12228
https://github.com/apache/spark/pull/12228

> Tasks that fail due to CommitDeniedException (a side-effect of speculation) can cause job failure
> -------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-14357
>                 URL: https://issues.apache.org/jira/browse/SPARK-14357
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 1.5.2, 1.6.0, 1.6.1
>            Reporter: Jason Moore
>            Assignee: Jason Moore
>            Priority: Critical
>             Fix For: 1.6.2, 2.0.0, 1.5.2
>
>
> Speculation can often result in a CommitDeniedException, but ideally this shouldn't result in the job failing.  So changes were made along with SPARK-8167 to ensure that the CommitDeniedException is caught and given a failure reason that doesn't increment the failure count.
> However, I'm still noticing that this exception is causing jobs to fail using the 1.6.1 release version.
> {noformat}
> 16/04/04 11:36:02 ERROR InsertIntoHadoopFsRelation: Aborting job.
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 18 in stage 315.0 failed 8 times, most recent failure: Lost task 18.8 in stage 315.0 (TID 100793, qaphdd099.quantium.com.au.local): org.apache.spark.SparkException: Task failed while writing rows.
>         at org.apache.spark.sql.execution.datasources.DefaultWriterContainer.writeRows(WriterContainer.scala:272)
>         at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
>         at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
>         at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
>         at org.apache.spark.scheduler.Task.run(Task.scala:89)
>         at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
>         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:745)
> Caused by: java.lang.RuntimeException: Failed to commit task
>         at org.apache.spark.sql.execution.datasources.DefaultWriterContainer.commitTask$1(WriterContainer.scala:287)
>         at org.apache.spark.sql.execution.datasources.DefaultWriterContainer.writeRows(WriterContainer.scala:267)
>         ... 8 more
> Caused by: org.apache.spark.executor.CommitDeniedException: attempt_201604041136_0315_m_000018_8: Not committed because the driver did not authorize commit
>         at org.apache.spark.mapred.SparkHadoopMapRedUtil$.commitTask(SparkHadoopMapRedUtil.scala:135)
>         at org.apache.spark.sql.execution.datasources.BaseWriterContainer.commitTask(WriterContainer.scala:219)
>         at org.apache.spark.sql.execution.datasources.DefaultWriterContainer.commitTask$1(WriterContainer.scala:282)
>         ... 9 more
> {noformat}
> It seems to me that the CommitDeniedException gets wrapped into a RuntimeException at [WriterContainer.scala#L286|https://github.com/apache/spark/blob/branch-1.6/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/WriterContainer.scala#L286] and then into a SparkException at [InsertIntoHadoopFsRelation.scala#L154|https://github.com/apache/spark/blob/branch-1.6/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/InsertIntoHadoopFsRelation.scala#L154] which results in it not being able to be handled properly at [Executor.scala#L290|https://github.com/apache/spark/blob/branch-1.6/core/src/main/scala/org/apache/spark/executor/Executor.scala#L290]
> The solution might be that this catch block should type match on the inner-most cause of an error?



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