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https://issues.apache.org/jira/browse/SPARK-636?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon updated SPARK-636:
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Labels: bulk-closed (was: )
> 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
> Priority: Major
> Labels: bulk-closed
>
> 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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