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https://issues.apache.org/jira/browse/SPARK-11293?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15083326#comment-15083326
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Daniel Darabos commented on SPARK-11293:
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Sorry, my example was overly complicated. This one triggers the same leak.
{code}
sc.parallelize(0 to 10000000, 2).map(x => x % 10000 ->
x).groupByKey.mapPartitions { it => it.take(1) }.collect
{code}
> Spillable collections leak shuffle memory
> -----------------------------------------
>
> Key: SPARK-11293
> URL: https://issues.apache.org/jira/browse/SPARK-11293
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.3.1, 1.4.1, 1.5.1
> Reporter: Josh Rosen
> Assignee: Josh Rosen
> Priority: Critical
> Fix For: 1.6.0
>
>
> I discovered multiple leaks of shuffle memory while working on my memory
> manager consolidation patch, which added the ability to do strict memory leak
> detection for the bookkeeping that used to be performed by the
> ShuffleMemoryManager. This uncovered a handful of places where tasks can
> acquire execution/shuffle memory but never release it, starving themselves of
> memory.
> Problems that I found:
> * {{ExternalSorter.stop()}} should release the sorter's shuffle/execution
> memory.
> * BlockStoreShuffleReader should call {{ExternalSorter.stop()}} using a
> {{CompletionIterator}}.
> * {{ExternalAppendOnlyMap}} exposes no equivalent of {{stop()}} for freeing
> its resources.
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