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From "Hadoop QA (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (YARN-3126) FairScheduler: queue's usedResource is always more than the maxResource limit
Date Fri, 15 Apr 2016 02:19:25 GMT

    [ https://issues.apache.org/jira/browse/YARN-3126?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15242301#comment-15242301
] 

Hadoop QA commented on YARN-3126:
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| (x) *{color:red}-1 overall{color}* |
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|| Vote || Subsystem || Runtime || Comment ||
| {color:blue}0{color} | {color:blue} reexec {color} | {color:blue} 0m 0s {color} | {color:blue}
Docker mode activated. {color} |
| {color:red}-1{color} | {color:red} patch {color} | {color:red} 0m 4s {color} | {color:red}
YARN-3126 does not apply to trunk. Rebase required? Wrong Branch? See https://wiki.apache.org/hadoop/HowToContribute
for help. {color} |
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|| Subsystem || Report/Notes ||
| JIRA Patch URL | https://issues.apache.org/jira/secure/attachment/12733746/resourcelimit-test.patch
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| JIRA Issue | YARN-3126 |
| Console output | https://builds.apache.org/job/PreCommit-YARN-Build/11091/console |
| Powered by | Apache Yetus 0.2.0   http://yetus.apache.org |


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> 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: BB2015-05-TBR, assignContainer, fairscheduler, 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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