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https://issues.apache.org/jira/browse/YARN-3415?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14394522#comment-14394522
 ] 

Hudson commented on YARN-3415:
------------------------------

FAILURE: Integrated in Hadoop-Hdfs-trunk #2084 (See 
[https://builds.apache.org/job/Hadoop-Hdfs-trunk/2084/])
YARN-3415. Non-AM containers can be counted towards amResourceUsage of a 
fairscheduler queue (Zhihai Xu via Sandy Ryza) (sandy: rev 
6a6a59db7f1bfda47c3c14fb49676a7b22d2eb06)
* hadoop-yarn-project/CHANGES.txt
* 
hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/main/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/FairScheduler.java
* 
hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/main/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/FSLeafQueue.java
* 
hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/main/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/FSAppAttempt.java
* 
hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-resourcemanager/src/test/java/org/apache/hadoop/yarn/server/resourcemanager/scheduler/fair/TestFairScheduler.java


> Non-AM containers can be counted towards amResourceUsage of a Fair Scheduler 
> queue
> ----------------------------------------------------------------------------------
>
>                 Key: YARN-3415
>                 URL: https://issues.apache.org/jira/browse/YARN-3415
>             Project: Hadoop YARN
>          Issue Type: Bug
>          Components: fairscheduler
>    Affects Versions: 2.6.0
>            Reporter: Rohit Agarwal
>            Assignee: zhihai xu
>            Priority: Critical
>             Fix For: 2.8.0
>
>         Attachments: YARN-3415.000.patch, YARN-3415.001.patch, 
> YARN-3415.002.patch
>
>
> We encountered this problem while running a spark cluster. The 
> amResourceUsage for a queue became artificially high and then the cluster got 
> deadlocked because the maxAMShare constrain kicked in and no new AM got 
> admitted to the cluster.
> I have described the problem in detail here: 
> https://github.com/apache/spark/pull/5233#issuecomment-87160289
> In summary - the condition for adding the container's memory towards 
> amResourceUsage is fragile. It depends on the number of live containers 
> belonging to the app. We saw that the spark AM went down without explicitly 
> releasing its requested containers and then one of those containers memory 
> was counted towards amResource.
> cc - [~sandyr]



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