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Date: Fri, 1 May 2015 21:52:06 +0000 (UTC)
From: "Wangda Tan (JIRA)" <jira@apache.org>
To: yarn-issues@hadoop.apache.org
Message-ID: <JIRA.12690987.1390553310000.51990.1430517126660@Atlassian.JIRA>
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Subject: [jira] [Commented] (YARN-1631) Container allocation issue in
 Leafqueue assignContainers()
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    [ https://issues.apache.org/jira/browse/YARN-1631?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14524039#comment-14524039 ] 

Wangda Tan commented on YARN-1631:
----------------------------------

Just offline discussed with [~vinodkv] and [~jianhe], now our consensus is, if we allow skip first submitted application because of queueMax resource limit, it violates FIFO. This is different from user-limit, if we skip it, first application with large resource request may be starved. 

Another problem in your example is, app1 shouldn't reserve container in node_1 because app_1's AM is running on that node too. Queue continuous reservation looking can solve this problem.

Closing it as won't fix. [~sunilg], please reopen it if you still think it's a problem.

> Container allocation issue in Leafqueue assignContainers()
> ----------------------------------------------------------
>
>                 Key: YARN-1631
>                 URL: https://issues.apache.org/jira/browse/YARN-1631
>             Project: Hadoop YARN
>          Issue Type: Bug
>          Components: scheduler
>    Affects Versions: 2.2.0
>         Environment: SuSe 11 Linux 
>            Reporter: Sunil G
>            Assignee: Sunil G
>         Attachments: Yarn-1631.1.patch, Yarn-1631.2.patch
>
>
> Application1 has a demand of 8GB[Map Task Size as 8GB] which is more than Node_1 can handle.
> Node_1 has a size of 8GB and 2GB is used by Application1's AM.
> Hence reservation happened for remaining 6GB in Node_1 by Application1.
> A new job is submitted with 2GB AM size and 2GB task size with only 2 Maps to run.
> Node_2 also has 8GB capability.
> But Application2's AM cannot be launched in Node_2. And Application2 waits longer as only 2 Nodes are available in cluster.


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