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https://issues.apache.org/jira/browse/YARN-4218?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15056649#comment-15056649
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Hadoop QA commented on YARN-4218:
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| (x) *{color:red}-1 overall{color}* |
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|| Vote || Subsystem || Runtime || Comment ||
| {color:red}-1{color} | {color:red} patch {color} | {color:red} 0m 4s {color} 
| {color:red} YARN-4218 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/12777564/YARN-4218.2.patch |
| JIRA Issue | YARN-4218 |
| Powered by | Apache Yetus 0.1.0   http://yetus.apache.org |
| Console output | 
https://builds.apache.org/job/PreCommit-YARN-Build/9973/console |


This message was automatically generated.



> Metric for resource*time that was preempted
> -------------------------------------------
>
>                 Key: YARN-4218
>                 URL: https://issues.apache.org/jira/browse/YARN-4218
>             Project: Hadoop YARN
>          Issue Type: Bug
>            Reporter: Chang Li
>            Assignee: Chang Li
>         Attachments: YARN-4218.2.patch, YARN-4218.2.patch, YARN-4218.2.patch, 
> YARN-4218.2.patch, YARN-4218.patch, YARN-4218.wip.patch, screenshot-1.png, 
> screenshot-2.png, screenshot-3.png
>
>
> After YARN-415 we have the ability to track the resource*time footprint of a 
> job and preemption metrics shows how many containers were preempted on a job. 
> However we don't have a metric showing the resource*time footprint cost of 
> preemption. In other words, we know how many containers were preempted but we 
> don't have a good measure of how much work was lost as a result of preemption.
> We should add this metric so we can analyze how much work preemption is 
> costing on a grid and better track which jobs were heavily impacted by it. A 
> job that has 100 containers preempted that only lasted a minute each and were 
> very small is going to be less impacted than a job that only lost a single 
> container but that container was huge and had been running for 3 days.



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