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https://issues.apache.org/jira/browse/MAPREDUCE-6302?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14517651#comment-14517651
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Benjamin Tortorelli commented on MAPREDUCE-6302:
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We're seeing this issue as well. Although our job is map only. Some runs seems
to hang and have to be killed, others only take a very long amount of time to
complete. This occurs with varying numbers of workers and memory. Yarn logs for
the job always show one worker with an extremely large log file compared to the
other workers (50 MB vs 500 KB).
> deadlock in a job between map and reduce cores allocation
> ----------------------------------------------------------
>
> Key: MAPREDUCE-6302
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-6302
> Project: Hadoop Map/Reduce
> Issue Type: Bug
> Affects Versions: 2.6.0
> Reporter: mai shurong
> Assignee: Karthik Kambatla
> Priority: Critical
> Attachments: AM_log_head100000.txt.gz, AM_log_tail100000.txt.gz,
> log.txt, mr-6302-prelim.patch, queue_with_max163cores.png,
> queue_with_max263cores.png, queue_with_max333cores.png
>
>
> I submit a big job, which has 500 maps and 350 reduce, to a
> queue(fairscheduler) with 300 max cores. When the big mapreduce job is
> running 100% maps, the 300 reduces have occupied 300 max cores in the queue.
> And then, a map fails and retry, waiting for a core, while the 300 reduces
> are waiting for failed map to finish. So a deadlock occur. As a result, the
> job is blocked, and the later job in the queue cannot run because no
> available cores in the queue.
> I think there is the similar issue for memory of a queue .
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