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Posted to yarn-issues@hadoop.apache.org by "tangshangwen (JIRA)" <ji...@apache.org> on 2016/10/28 03:39:58 UTC

[jira] [Issue Comment Deleted] (YARN-5795) FairScheduler set AppMaster vcores didn't work

     [ https://issues.apache.org/jira/browse/YARN-5795?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

tangshangwen updated YARN-5795:
-------------------------------
    Comment: was deleted

(was: I think if we replace RESOURCE_CALCULATOR with DOMINANT_RESOURCE_CALCULATOR we should be able to fix the problem
{code:title=FairScheduler.java|borderStyle=solid}
  @Override
  public ResourceCalculator getResourceCalculator() {
//    return RESOURCE_CALCULATOR;
    return DOMINANT_RESOURCE_CALCULATOR;
  }
{code})

> FairScheduler set AppMaster vcores didn't work
> ----------------------------------------------
>
>                 Key: YARN-5795
>                 URL: https://issues.apache.org/jira/browse/YARN-5795
>             Project: Hadoop YARN
>          Issue Type: Bug
>          Components: resourcemanager
>    Affects Versions: 2.7.1
>            Reporter: tangshangwen
>            Assignee: tangshangwen
>
> In our cluster, we use the linux container, I would like to increase the number of cpu to get more CPU time slice, but it did not take effect, i set yarn.app.mapreduce.am.resource.cpu-vcores = 2 ,but i found the resourcemanager log
> {noformat}
> [2016-10-27T16:36:37.280 08:00] [INFO] resourcemanager.scheduler.SchedulerNode.allocateContainer(SchedulerNode.java 153) [ResourceManager Event Processor] : Assigned container container_1477059529836_336635_01_000001 of capacity <memory:2048, vCores:1>
> {noformat}
> Because scheduler.getResourceCalculator() only computes memory
> {code:title=RMAppManager.java|borderStyle=solid}
>  private ResourceRequest validateAndCreateResourceRequest(
>       ApplicationSubmissionContext submissionContext, boolean isRecovery)
>       throws InvalidResourceRequestException {
> ...
>       SchedulerUtils.normalizeRequest(amReq, scheduler.getResourceCalculator(),
>           scheduler.getClusterResource(),
>           scheduler.getMinimumResourceCapability(),
>           scheduler.getMaximumResourceCapability(),
>           scheduler.getMinimumResourceCapability());
> ...
> }
> {code}



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