[jira] [Commented] (YARN-4678) Cluster used capacity is > 100 when container reserved

["Brahma Reddy Battula (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/YARN-4678?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15189237#comment-15189237 ] 

Brahma Reddy Battula commented on YARN-4678:
--------------------------------------------

[~sunilg]  Patch almost looks good to me...

one more scenario which is found by [~bibinchundatt].

Parent and leaf queue usage percentages are  different when only one subqueue is present( i.e default) and reservation happens.

So I am thinking , can we handle as part of this jira only..? and fix can be like following,, what do you say..?

{{QueueBlock#render(Block html)}}

{code}
-        used = partitionQueueCapsInfo.getUsedCapacity() / 100;
+        used =
+            (partitionQueueCapsInfo.getUsedCapacity() - partitionQueueCapsInfo
+                .getReservedCapacity()) / 100;
         absCap = partitionQueueCapsInfo.getAbsoluteCapacity() / 100;
         absMaxCap = partitionQueueCapsInfo.getAbsoluteMaxCapacity() / 100;
         absUsedCap = partitionQueueCapsInfo.getAbsoluteUsedCapacity() / 100;
{code}

> Cluster used capacity is > 100 when container reserved 
> -------------------------------------------------------
>
>                 Key: YARN-4678
>                 URL: https://issues.apache.org/jira/browse/YARN-4678
>             Project: Hadoop YARN
>          Issue Type: Bug
>            Reporter: Brahma Reddy Battula
>            Assignee: Sunil G
>         Attachments: 0001-YARN-4678.patch, 0002-YARN-4678.patch
>
>
>  *Scenario:* 
> * Start cluster with Three NM's each having 8GB (cluster memory:24GB).
> * Configure queues with elasticity and userlimitfactor=10.
> * disable pre-emption.
> * run two job with different priority in different queue at the same time
> ** yarn jar hadoop-mapreduce-examples-2.7.2.jar pi -Dyarn.app.priority=LOW -Dmapreduce.job.queuename=QueueA -Dmapreduce.map.memory.mb=4096 -Dyarn.app.mapreduce.am.resource.mb=1536 -Dmapreduce.job.reduce.slowstart.completedmaps=1.0 10 1000000000000
> ** yarn jar hadoop-mapreduce-examples-2.7.2.jar pi -Dyarn.app.priority=HIGH -Dmapreduce.job.queuename=QueueB -Dmapreduce.map.memory.mb=4096 -Dyarn.app.mapreduce.am.resource.mb=1536 3 1000000000000
> * observe the cluster capacity which was used in RM web UI



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)