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https://issues.apache.org/jira/browse/STORM-1093?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14951022#comment-14951022
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ASF GitHub Bot commented on STORM-1093:
---------------------------------------

Github user zhuoliu commented on the pull request:

    https://github.com/apache/storm/pull/790#issuecomment-146962992
  
    Just manual test with RAS, it works well, and we can see each worker is 
being launched with different JVM heap sizes (added up by their tasks' 
specified memory usage).
    May I have your reviews when you have time @revans2  @d2r ?


> Launching Workers with resources specified in resource-aware schedulers
> -----------------------------------------------------------------------
>
>                 Key: STORM-1093
>                 URL: https://issues.apache.org/jira/browse/STORM-1093
>             Project: Apache Storm
>          Issue Type: Story
>          Components: storm-core
>            Reporter: Zhuo Liu
>            Assignee: Zhuo Liu
>
> Currently, we have Resource Aware Scheduler (STORM-894) in nimbus, which can 
> allocate different types of resource (CPU, onheap-memory, offheap-memory) to 
> the workers assigned to each topology's tasks.
> However, such resources are not visible to the supervisor, therefore, 
> supervisor will still launch workers with fixed amount of heap size memory 
> (e.g., -Xmx=768M). 
> Therefore, we need a whole set of schemes that allow nimbus to put different 
> types of resources to each worker slot, then push the resources with 
> assignment to ZooKeepers; also, at the supervisor side, such resources in 
> each worker slot should be used by supervisor for launching a worker's JVM 
> (initially, the JVM heap size).
> This scheme can be used not only by RAS scheduler (STORM-893), but also by 
> any customized scheduler for conducting mem/cpu/network resource 
> specified-scheduling.
> In the future, the resources of memory, CPU and network can also be used by 
> supervisor to launch a worker in a resource-segregated container, such as a 
> CGroup or Docker, with isolated Memory/CPU/Network resources.



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