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https://issues.apache.org/jira/browse/YARN-2172?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14354306#comment-14354306
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Hadoop QA commented on YARN-2172:
---------------------------------

{color:red}-1 overall{color}.  Here are the results of testing the latest 
attachment 
  
http://issues.apache.org/jira/secure/attachment/12658578/hadoop_job_suspend_resume.patch
  against trunk revision 47f7f18.

    {color:red}-1 patch{color}.  The patch command could not apply the patch.

Console output: https://builds.apache.org/job/PreCommit-YARN-Build/6899//console

This message is automatically generated.

> Suspend/Resume Hadoop Jobs
> --------------------------
>
>                 Key: YARN-2172
>                 URL: https://issues.apache.org/jira/browse/YARN-2172
>             Project: Hadoop YARN
>          Issue Type: New Feature
>          Components: resourcemanager, webapp
>    Affects Versions: 2.2.0
>         Environment: CentOS 6.5, Hadoop 2.2.0
>            Reporter: Richard Chen
>              Labels: hadoop, jobs, resume, suspend
>         Attachments: Hadoop Job Suspend Resume Design.docx, 
> hadoop_job_suspend_resume.patch
>
>   Original Estimate: 336h
>  Remaining Estimate: 336h
>
> In a multi-application cluster environment, jobs running inside Hadoop YARN 
> may be of lower-priority than jobs running outside Hadoop YARN like HBase. To 
> give way to other higher-priority jobs inside Hadoop, a user or some 
> cluster-level resource scheduling service should be able to suspend and/or 
> resume some particular jobs within Hadoop YARN.
> When target jobs inside Hadoop are suspended, those already allocated and 
> running task containers will continue to run until their completion or active 
> preemption by other ways. But no more new containers would be allocated to 
> the target jobs. In contrast, when suspended jobs are put into resume mode, 
> they will continue to run from the previous job progress and have new task 
> containers allocated to complete the rest of the jobs.
> My team has completed its implementation and our tests showed it works in a 
> rather solid  and convenient way.



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