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https://issues.apache.org/jira/browse/YARN-3126?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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ASF GitHub Bot updated YARN-3126:
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Labels: BB2015-05-TBR assignContainer fairscheduler pull-request-available
resources (was: BB2015-05-TBR assignContainer fairscheduler resources)
> 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
> Assignee: Yufei Gu
> Priority: Major
> Labels: BB2015-05-TBR, assignContainer, fairscheduler,
> pull-request-available, resources
> Fix For: trunk-win
>
> Attachments: resourcelimit-02.patch, resourcelimit-test.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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