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https://issues.apache.org/jira/browse/YARN-2413?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14094873#comment-14094873
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Allen Wittenauer commented on YARN-2413:
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I might have missed something, but there appears to be a very bad bug here.
Given the following settings:
{code}
"mapreduce.map.cpu.vcores": 10
"yarn.scheduler.maximum-allocation-vcores": 220
"mapreduce.reduce.cpu.vcores": 10
"yarn.app.mapreduce.am.resource.cpu-vcores": 10
"yarn.scheduler.minimum-allocation-vcores": 10
"yarn.nodemanager.resource.cpu-vcores": 221
{code}
The resource manager is only allocating 1 vcore per container:
{code}
2014-08-12 15:49:31,809 INFO
org.apache.hadoop.yarn.server.resourcemanager.scheduler.SchedulerNode: Assigned
container container_1407883573269_0001_01_000001 of capacity <memory:2048,
vCores:1> on host 10.248.3.50:8041, which has 1 containers, <memory:2048,
vCores:1> used and <memory:2050, vCores:220> available after allocation
{code}
... which is clearly wrong, as the number of vcores requested should have been
10 and the available remaining should have been 211.
> capacity scheduler will overallocate vcores
> -------------------------------------------
>
> Key: YARN-2413
> URL: https://issues.apache.org/jira/browse/YARN-2413
> Project: Hadoop YARN
> Issue Type: Bug
> Components: scheduler
> Affects Versions: 3.0.0, 2.2.0
> Reporter: Allen Wittenauer
> Priority: Critical
>
> It doesn't appear that the capacity scheduler is properly allocation vcores
> when making scheduling decisions, which results in overallocation of CPU
> resources.
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