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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