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https://issues.apache.org/jira/browse/YARN-5795?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15690456#comment-15690456
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Daniel Templeton commented on YARN-5795:
----------------------------------------
[~yufeigu] is in the process of overhauling the resource normalization process
in YARN-5774. At a minimum, we should wait until that change is in. It would
be nice, though, to also fix this issue in that patch.
> 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
> Attachments: 0001-YARN-5795.patch
>
>
> 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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