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https://issues.apache.org/jira/browse/YARN-3416?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14386992#comment-14386992
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Ray Chiang commented on YARN-3416:
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There probably is a bug here, but what value do you have for the property:
mapreduce.job.reduce.slowstart.completedmaps
in mapred-default.xml? If it's close to 0.0, I'd possibly suggest increasing
it closer to 1.0 in order to keep the number of pending reducers down. This
will likely have a performance hit, but should at least allow your job to
complete.
> deadlock in a job between map and reduce cores allocation
> ----------------------------------------------------------
>
> Key: YARN-3416
> URL: https://issues.apache.org/jira/browse/YARN-3416
> Project: Hadoop YARN
> Issue Type: Bug
> Components: fairscheduler
> Affects Versions: 2.6.0
> Reporter: mai shurong
>
> 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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