min shi commented on SPARK-14168:

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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