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https://issues.apache.org/jira/browse/YARN-3758?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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skrho updated YARN-3758:
------------------------
Description:
Hello there~~
I have 2 clusters
First cluster is 5 node , default 1 application queue, Capacity scheduler, 8G
Physical memory each node
Second cluster is 10 node, 2 application queuey, fair-scheduler, 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 & mapred-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~~
was:
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 & mapred-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~~
> The mininum memory setting(yarn.scheduler.minimum-allocation-mb) is not
> working in container
> --------------------------------------------------------------------------------------------
>
> Key: YARN-3758
> URL: https://issues.apache.org/jira/browse/YARN-3758
> Project: Hadoop YARN
> Issue Type: Bug
> Components: resourcemanager
> Affects Versions: 2.4.0
> Reporter: skrho
>
> Hello there~~
> I have 2 clusters
> First cluster is 5 node , default 1 application queue, Capacity scheduler, 8G
> Physical memory each node
> Second cluster is 10 node, 2 application queuey, fair-scheduler, 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 & mapred-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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