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From Michael Schmei├čer (JIRA) <j...@apache.org>
Subject [jira] [Commented] (SPARK-636) Add mechanism to run system management/configuration tasks on all workers
Date Sat, 15 Oct 2016 15:18:20 GMT

    [ https://issues.apache.org/jira/browse/SPARK-636?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15578294#comment-15578294
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Michael Schmei├čer commented on SPARK-636:
-----------------------------------------

I agree, that's why I also feel that these issues are no duplicates. 

> Add mechanism to run system management/configuration tasks on all workers
> -------------------------------------------------------------------------
>
>                 Key: SPARK-636
>                 URL: https://issues.apache.org/jira/browse/SPARK-636
>             Project: Spark
>          Issue Type: New Feature
>          Components: Spark Core
>            Reporter: Josh Rosen
>
> It would be useful to have a mechanism to run a task on all workers in order to perform
system management tasks, such as purging caches or changing system properties.  This is useful
for automated experiments and benchmarking; I don't envision this being used for heavy computation.
> Right now, I can mimic this with something like
> {code}
> sc.parallelize(0 until numMachines, numMachines).foreach { } 
> {code}
> but this does not guarantee that every worker runs a task and requires my user code to
know the number of workers.
> One sample use case is setup and teardown for benchmark tests.  For example, I might
want to drop cached RDDs, purge shuffle data, and call {{System.gc()}} between test runs.
 It makes sense to incorporate some of this functionality, such as dropping cached RDDs, into
Spark itself, but it might be helpful to have a general mechanism for running ad-hoc tasks
like {{System.gc()}}.



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