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https://issues.apache.org/jira/browse/SPARK-1706?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13988868#comment-13988868
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Mridul Muralidharan commented on SPARK-1706:
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Oh my, this was supposed to be logical addition once yarn changes were done.
Yarn changes were very heavily modelled on standalone mode (hence why
yarn-standalone !) : and it was supposed to be a two way street : changes made
for yarn support (multi-tennancy, etc) was supposed to have been added back to
standalone mode when yarn support stabilized.
Did not realize I never got around to it - my apologies !
> Allow multiple executors per worker in Standalone mode
> ------------------------------------------------------
>
> Key: SPARK-1706
> URL: https://issues.apache.org/jira/browse/SPARK-1706
> Project: Spark
> Issue Type: Improvement
> Components: Deploy
> Reporter: Patrick Wendell
> Fix For: 1.1.0
>
>
> Right now if people want to launch multiple executors on each machine they
> need to start multiple standalone workers. This is not too difficult, but it
> means you have extra JVM's sitting around.
> We should just allow users to set a number of cores they want per-executor in
> standalone mode and then allow packing multiple executors on each node. This
> would make standalone mode more consistent with YARN in the way you request
> resources.
> It's not too big of a change as far as I can see. You'd need to:
> 1. Introduce a configuration for how many cores you want per executor.
> 2. Change the scheduling logic in Master.scala to take this into account.
> 3. Change CoarseGrainedSchedulerBackend to not assume a 1<->1 correspondence
> between hosts and executors.
> And maybe modify a few other places.
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