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https://issues.apache.org/jira/browse/SPARK-11701?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15003601#comment-15003601
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Saisai Shao commented on SPARK-11701:
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Hi [~tgraves], I think I also hit this issue, it is caused by recent change of
executor detection mechanism in CoarseGrainedSchedulerBackend, it will make
dynamic allocation fail to run. I just create a JIRA SPARK-11718 to fix this.
Thanks.
> YARN - dynamic allocation and speculation active task accounting wrong
> ----------------------------------------------------------------------
>
> Key: SPARK-11701
> URL: https://issues.apache.org/jira/browse/SPARK-11701
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.5.1
> Reporter: Thomas Graves
> Priority: Critical
>
> I am using dynamic container allocation and speculation and am seeing issues
> with the active task accounting. The Executor UI still shows active tasks on
> the an executor but the job/stage is all completed. I think its also
> affecting the dynamic allocation being able to release containers because it
> thinks there are still tasks.
> Its easily reproduce by using spark-shell, turn on dynamic allocation, then
> run just a wordcount on decent sized file and set the speculation parameters
> low:
> spark.dynamicAllocation.enabled true
> spark.shuffle.service.enabled true
> spark.dynamicAllocation.maxExecutors 10
> spark.dynamicAllocation.minExecutors 2
> spark.dynamicAllocation.initialExecutors 10
> spark.dynamicAllocation.executorIdleTimeout 40s
> $SPARK_HOME/bin/spark-shell --conf spark.speculation=true --conf
> spark.speculation.multiplier=0.2 --conf spark.speculation.quantile=0.1
> --master yarn --deploy-mode client --executor-memory 4g --driver-memory 4g
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