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https://issues.apache.org/jira/browse/IGNITE-4037?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15586289#comment-15586289
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Ivan Veselovsky commented on IGNITE-4037:
-----------------------------------------
Additions to the suggested solution plan. Difference with Hadoop shuffle
implementation:
1) push of merged map results instead of Hadoop pull mechanism (TBD);
2) using ad-hoc temp files (possibly accompanied with mapped memory buffers)
instead of files created with FileSystem .
3) storing map outputs in a sorted memory buffer instead of "store -> sort ->
spill" logic used in Hadoop.
> High memory consumption when executing TeraSort Hadoop example
> --------------------------------------------------------------
>
> Key: IGNITE-4037
> URL: https://issues.apache.org/jira/browse/IGNITE-4037
> Project: Ignite
> Issue Type: Bug
> Affects Versions: 1.6
> Reporter: Ivan Veselovsky
> Assignee: Ivan Veselovsky
> Fix For: 1.7
>
>
> When executing TeraSort Hadoop example, we observe high memory consumption
> that frequently leads to cluster malfunction.
> The problem can be reproduced in unit test, even with 1 node, and with not
> huge input data set as 100Mb.
> Dump analysis shows that memory is taken in various queues:
> org.apache.ignite.internal.processors.hadoop.taskexecutor.HadoopExecutorService#queue
>
> and
> task queue of
> org.apache.ignite.internal.processors.hadoop.jobtracker.HadoopJobTracker#evtProcSvc
> .
> Since objects stored in these queues hold byte arrays of significant size,
> memory if consumed very fast.
> It looks like real cause of the problem is that some tasks are blocked.
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