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https://issues.apache.org/jira/browse/SPARK-14168?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16118128#comment-16118128
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min shi commented on SPARK-14168:
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this affects spark 1.6.0 too, what do we do if we can not upgrade our version
yet? shall we increase allowing the number of errors?
> Managed Memory Leak Msg Should Only Be a Warning
> ------------------------------------------------
>
> Key: SPARK-14168
> URL: https://issues.apache.org/jira/browse/SPARK-14168
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Affects Versions: 1.6.1
> Reporter: Imran Rashid
> Assignee: Imran Rashid
> Priority: Minor
>
> When a task is completed, executors check to see if all managed memory for
> the task was correctly released, and logs an error when it wasn't. However,
> it turns out its OK for there to be memory that wasn't released when an
> Iterator isn't read to completion, eg., with {{rdd.take()}}. This results in
> a scary error msg in the executor logs:
> {noformat}
> 16/01/05 17:02:49 ERROR Executor: Managed memory leak detected; size =
> 16259594 bytes, TID = 24
> {noformat}
> Furthermore, if tasks fails for any reason, this msg is also triggered. This
> can lead users to believe that the failure was from the memory leak, when the
> root cause could be entirely different. Eg., the same error msg appears in
> executor logs with this clearly broken user code run with {{spark-shell
> --master 'local-cluster[2,2,1024]'}}
> {code}
> sc.parallelize(0 to 10000000, 2).map(x => x % 10000 ->
> x).groupByKey.mapPartitions { it => throw new RuntimeException("user error!")
> }.collect
> {code}
> We should downgrade the msg to a warning and link to a more detailed
> explanation.
> See https://issues.apache.org/jira/browse/SPARK-11293 for more reports from
> users (and perhaps a true fix)
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