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Posted to issues@spark.apache.org by "Keith Sun (JIRA)" <ji...@apache.org> on 2018/01/02 01:49:00 UTC

[jira] [Commented] (SPARK-22902) do not count failures if the speculative task is killed as the same task finished in other executor

    [ https://issues.apache.org/jira/browse/SPARK-22902?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16307596#comment-16307596 ] 

Keith Sun commented on SPARK-22902:
-----------------------------------

I could propose a simple solution for this : once the task in one stage is marked as success, then spark could ignore any failures for the same task (not only the active killing , but also the real failures like OOM, system crash, etc). 


> do not count failures if the speculative task is killed as the same task finished in other executor
> ---------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-22902
>                 URL: https://issues.apache.org/jira/browse/SPARK-22902
>             Project: Spark
>          Issue Type: Bug
>          Components: Block Manager
>    Affects Versions: 2.1.1
>            Reporter: Keith Sun
>            Priority: Minor
>
> It is a logic issue, so i did not include much env but my log in the ticket.
> Spark conf related to this issue :
> spark.task.maxFailures=2
> spark.speculation=true 
> My case is this : my task 239 failed first  on an executor and then restarted in another executor while due to it is kind of running slow, spark started another speculative job as we set speculative execution as true.  
> After some short time, the second task finished and then spark killed the specutive task.
> But this cause the whole spark job aborted as the task failure is 2 (first failure due to some other issue + the killed specutive one).
> This is confusing as the task 239 is actually finished successfully and the specutive is killed ,not failed by itself.
> Shall we ignore the speculative failure caused by active kill ?
> On the spark configuration doc, i found the explanation to the spark.taskmaxFailure :
> {noformat}
> Number of failures of any particular task before giving up on the job. The total number of failures spread across different tasks will not cause the job to fail; a particular task has to fail this number of attempts. Should be greater than or equal to 1. Number of allowed retries = this value - 1.
> {noformat}
> My log :
> {noformat}
> 17/12/25 12:25:02 INFO TaskSetManager: Starting task 239.0 in stage 1.0 (TID 10254, host-620-1507-026.lvs02xxxx, executor 208, partition 239, PROCESS_LOCAL, 5910 bytes)
> 17/12/25 12:36:18 INFO TaskSetManager: 
> Lost task 239.0 in stage 1.0 (TID 10254) on host-620-1507-026.lvs02xxxx, executor 208: org.apache.spark.SparkException (Task failed while writing rows) [duplicate 1]
> 17/12/25 12:36:18 INFO TaskSetManager: Starting task 239.1 in stage 1.0 (TID 10601, host-620-1507-038.lvs01xxxx, executor 343, partition 239, PROCESS_LOCAL, 5910 bytes)
> 17/12/25 12:39:19 INFO TaskSetManager: Marking task 239 in stage 1.0 (on host-620-1507-038.lvs01xxxx) as speculatable because it ran more than 45608 ms
> 17/12/25 12:39:19 INFO TaskSetManager: Starting task 239.2 in stage 1.0 (TID 15142, host-620-1507-030.lvs03xxxx, executor 361, partition 239, PROCESS_LOCAL, 5910 bytes)
> 17/12/25 12:39:22 INFO TaskSetManager: Killing attempt 2 for task 239.2 in stage 1.0 (TID 15142) on host-620-1507-030.lvs03xxxx as the attempt 1 succeeded on host-620-1507-038.lvs01xxxx
> 17/12/25 12:39:22 INFO TaskSetManager: Finished task 239.1 in stage 1.0 (TID 10601) in 183663 ms on host-620-1507-038.lvs01xxxx (executor 343) (4606/5000)
> 17/12/25 12:39:28 INFO TaskSetManager: Task 239.2 in stage 1.0 (TID 15142) failed, but another instance of the task has already succeeded, so not re-queuing the task to be re-executed.
> 17/12/25 12:39:28 ERROR TaskSetManager: Task 239 in stage 1.0 failed 2 times; aborting job
> 17/12/25 12:39:28 INFO YarnClusterScheduler: Cancelling stage 1
> 17/12/25 12:39:28 INFO YarnClusterScheduler: Stage 1 was cancelled
> 17/12/25 12:39:28 INFO DAGScheduler: ResultStage 1 (sql at SparkStatement.scala:61) failed in 865.935 s due to Job aborted due to stage failure: Task 239 in stage 1.0 failed 2 times, most recent failure: Lost task 239.2 in stage 1.0 (TID 15142, host-620-1507-030.lvs03xxxx, executor 361): org.apache.spark.SparkException: Task failed while writing rows
> {noformat}



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