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https://issues.apache.org/jira/browse/YARN-4148?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15346577#comment-15346577
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Hadoop QA commented on YARN-4148:
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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-4148 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/12812850/free_in_scheduler_but_not_node_prototype-branch-2.7.patch
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| JIRA Issue | YARN-4148 |
| Console output |
https://builds.apache.org/job/PreCommit-YARN-Build/12119/console |
| Powered by | Apache Yetus 0.3.0 http://yetus.apache.org |
This message was automatically generated.
> When killing app, RM releases app's resource before they are released by NM
> ---------------------------------------------------------------------------
>
> Key: YARN-4148
> URL: https://issues.apache.org/jira/browse/YARN-4148
> Project: Hadoop YARN
> Issue Type: Bug
> Components: resourcemanager
> Reporter: Jun Gong
> Assignee: Jun Gong
> Attachments: YARN-4148.001.patch, YARN-4148.wip.patch,
> free_in_scheduler_but_not_node_prototype-branch-2.7.patch
>
>
> When killing a app, RM scheduler releases app's resource as soon as possible,
> then it might allocate these resource for new requests. But NM have not
> released them at that time.
> The problem was found when we supported GPU as a resource(YARN-4122). Test
> environment: a NM had 6 GPUs, app A used all 6 GPUs, app B was requesting 3
> GPUs. Killed app A, then RM released A's 6 GPUs, and allocated 3 GPUs to B.
> But when B tried to start container on NM, NM found it didn't have 3 GPUs to
> allocate because it had not released A's GPUs.
> I think the problem also exists for CPU/Memory. It might cause OOM when
> memory is overused.
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