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https://issues.apache.org/jira/browse/YARN-3416?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14386186#comment-14386186
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mai shurong commented on YARN-3416:
-----------------------------------

There are methods to work around: temporarily increase max cores in the queue,  
or kill the job, but the problem is  a bug.

> 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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