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https://issues.apache.org/jira/browse/YARN-389?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13611037#comment-13611037
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Bikas Saha commented on YARN-389:
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bq. 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.
The AM launcher checking limits is great but its the RM's responsibility to not
accept requests that it cannot fulfill. From reading the comments, it not clear
to me what exactly the root issue is in the RM itself. Is it that the RM is
accepting container requests that are greater than the maximum resource
available on any 1 node? I dont think we should be comparing against the entire
cluster resource since a container request needs to be satisfied within a
single node.
> 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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