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From "Craig Welch (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (YARN-3126) FairScheduler: queue's usedResource is always more than the maxResource limit
Date Fri, 01 May 2015 19:33:07 GMT

    [ https://issues.apache.org/jira/browse/YARN-3126?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14523764#comment-14523764
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Craig Welch commented on YARN-3126:
-----------------------------------

Hi [~Xia Hu], thanks for putting together a patch for this.  Could you add some unit tests
to verify the fix?  

> FairScheduler: queue's usedResource is always more than the maxResource limit
> -----------------------------------------------------------------------------
>
>                 Key: YARN-3126
>                 URL: https://issues.apache.org/jira/browse/YARN-3126
>             Project: Hadoop YARN
>          Issue Type: Bug
>          Components: fairscheduler
>    Affects Versions: 2.3.0
>         Environment: hadoop2.3.0. fair scheduler. spark 1.1.0. 
>            Reporter: Xia Hu
>              Labels: assignContainer, fairscheduler, resources
>             Fix For: trunk-win
>
>         Attachments: resourcelimit-02.patch, resourcelimit.patch
>
>
> When submitting spark application(both spark-on-yarn-cluster and spark-on-yarn-cleint
model), the queue's usedResources assigned by fairscheduler always can be more than the queue's
maxResources limit.
> And by reading codes of fairscheduler, I suppose this issue happened because of ignore
to check the request resources when assign Container.
> Here is the detail:
> 1. choose a queue. In this process, it will check if queue's usedResource is bigger than
its max, with assignContainerPreCheck. 
> 2. then choose a app in the certain queue. 
> 3. then choose a container. And here is the question, there is no check whether this
container would make the queue sources over its max limit. If a queue's usedResource is 13G,
the maxResource limit is 16G, then a container which asking for 4G resources may be assigned
successful. 
> This problem will always happen in spark application, cause we can ask for different
container resources in different applications. 
> By the way, I have already use the patch from YARN-2083. 



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