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From "Wangda Tan (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (MAPREDUCE-6302) deadlock in a job between map and reduce cores allocation
Date Tue, 14 Apr 2015 20:33:59 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-6302?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14494812#comment-14494812
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Wangda Tan commented on MAPREDUCE-6302:
---------------------------------------

bq. In other words, I guess I am proposing MR use the headroom from YARN more as a heuristic
than an absolute guarantee. MR should use the resources given to it in the best possible way
it can.
+1 to make the headroom more heuristic, actually it can only be "heuristic", YARN RM cannot
precisely know what's the headroom of an app in most cases. Changing it to "heuristic" can
avoid lots of deadlock between mappers and reducers like this. 

> 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, 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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