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Date: Fri, 14 Jun 2013 00:24:21 +0000 (UTC)
From: "Junping Du (JIRA)" <jira@apache.org>
To: yarn-issues@hadoop.apache.org
Message-ID: <JIRA.12625135.1356250634544.112989.1371169461449@arcas>
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References: <JIRA.12625135.1356250634544@arcas>
Subject: [jira] [Commented] (YARN-291) Dynamic resource configuration
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    [ https://issues.apache.org/jira/browse/YARN-291?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13682936#comment-13682936 ] 

Junping Du commented on YARN-291:
---------------------------------

Sure. I will add more unit tests later to cover this case and make sure things don't break.
Persist runtime change on capacity or not? it depends on how we think the life cycle of these changes. IMO, when NM is restart (no matter by plan or not), it should be seen as a fresh node as we are not sure previous resource setting condition (resource competition between different types of Apps) is still there so better to start with original value. Let me know if you have different thoughts. Thanks! 

                
> Dynamic resource configuration
> ------------------------------
>
>                 Key: YARN-291
>                 URL: https://issues.apache.org/jira/browse/YARN-291
>             Project: Hadoop YARN
>          Issue Type: New Feature
>          Components: nodemanager, scheduler
>            Reporter: Junping Du
>            Assignee: Junping Du
>              Labels: features
>         Attachments: Elastic Resources for YARN-v0.2.pdf, YARN-291-AddClientRMProtocolToSetNodeResource-03.patch, YARN-291-all-v1.patch, YARN-291-core-HeartBeatAndScheduler-01.patch, YARN-291-JMXInterfaceOnNM-02.patch, YARN-291-OnlyUpdateWhenResourceChange-01-fix.patch, YARN-291-YARNClientCommandline-04.patch
>
>
> The current Hadoop YARN resource management logic assumes per node resource is static during the lifetime of the NM process. Allowing run-time configuration on per node resource will give us finer granularity of resource elasticity. This allows Hadoop workloads to coexist with other workloads on the same hardware efficiently, whether or not the environment is virtualized. More background and design details can be found in attached proposal.

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