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https://issues.apache.org/jira/browse/YARN-389?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13579562#comment-13579562
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Zhijie Shen commented on YARN-389:
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I've checked reason why the requested AM size is larger than
yarn.scheduler.maximum-allocation-mb. In fact, the AM size is not checked
before requesting a container. It is because MR jobs are submitted through
ResourceMgrDelegate and managed by MRAppMaster, while checking AM size against
the maximum resource capability is only implemented in Client and
ApplicationMaster of the distributed shell.
In addition, since the requested AM size will be rounded up, it is at the risk
of the roundup value goes beyond yarn.scheduler.maximum-allocation-mb.
Anyway, the aforementioned situation is a separate issue, which I've filed in
YARN-407. Here, the focused issue is that if the requested resource is
impossible to be supplied, there should be some mechanism to stop the infinite
loop of assignment. This issue seems to be similar to YARN-56 and YARN-394.
> Infinitely assigning containers when the required resource exceeds the
> cluster's absolute capacity
> --------------------------------------------------------------------------------------------------
>
> Key: YARN-389
> URL: https://issues.apache.org/jira/browse/YARN-389
> Project: Hadoop YARN
> Issue Type: Bug
> Reporter: Zhijie Shen
> Assignee: Zhijie Shen
>
> I've run wordcount example on branch-2 and trunk. I've set
> yarn.nodemanager.resource.memory-mb to 1G and
> yarn.app.mapreduce.am.resource.mb to 1.5G. Therefore, resourcemanager is to
> assign a 2G AM container for AM. However, the nodemanager doesn't have enough
> memory to assign the container. The problem is that the assignment operation
> will be repeated infinitely, if the assignment cannot be accomplished. Logs
> follow.
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