[jira] [Resolved] (YARN-3757) The mininum memory setting(yarn.scheduler.minimum-allocation-mb) is not working in container

["skrho (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/YARN-3757?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

skrho resolved YARN-3757.
-------------------------
    Resolution: Duplicate

> The mininum memory setting(yarn.scheduler.minimum-allocation-mb) is not working in container
> --------------------------------------------------------------------------------------------
>
>                 Key: YARN-3757
>                 URL: https://issues.apache.org/jira/browse/YARN-3757
>             Project: Hadoop YARN
>          Issue Type: Bug
>          Components: resourcemanager
>    Affects Versions: 2.4.0
>         Environment: Hadoop 2.4.0
>            Reporter: skrho
>
> Hello there~~
> I have 2 clusters
> First cluster is 5 node , default 1 application queue, 8G Physical memory each node
> Second cluster is 10 node, 2 application queuey, 230G Physical memory each node
> Wherever a mapreduce job is running, I want resourcemanager is to set the minimum memory  256m to container
> So I was changing configuration in yarn-site.xml
> yarn.scheduler.minimum-allocation-mb : 256
> mapreduce.map.java.opts : -Xms256m 
> mapreduce.reduce.java.opts : -Xms256m 
> mapreduce.map.memory.mb : 256 
> mapreduce.reduce.memory.mb : 256 
> In First cluster  whenever a mapreduce job is running , I can see used memory 256m in web console( http://installedIP:8088/cluster/nodes )
> But In Second cluster whenever a mapreduce job is running , I can see used memory 1024m in web console( http://installedIP:8088/cluster/nodes ) 
> I know default memory value is 1024m, so if there is not changing memory setting, the default value is working.
> I have been testing for two weeks, but I don't know why mimimum memory setting is not working in second cluster
> Why this difference is happened? 
> Am I wrong setting configuration?
> or Is there bug?
> Thank you for reading~~



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