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Posted to issues@spark.apache.org by "Imran Rashid (JIRA)" <ji...@apache.org> on 2018/08/13 20:16:00 UTC
[jira] [Comment Edited] (SPARK-24918) Executor Plugin API
[ https://issues.apache.org/jira/browse/SPARK-24918?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16578858#comment-16578858 ]
Imran Rashid edited comment on SPARK-24918 at 8/13/18 8:15 PM:
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[~lucacanali] OK I see the case for what you're proposing -- its hard to setup that communication between the driver & executors without *some* initial setup message.
Still ... I'm a bit reluctant to include that now, until we see someone actually builds something that uses it. I realizes you might be hesitant to do that until you know it can be built on a stable api, but I don't think we can get around that.
was (Author: irashid):
[~lucacanali] OK I see the case for what you're proposing -- its hard too setup that communication between the driver & executors without *some* initial setup message.
Still ... I'm a bit reluctant to include that now, until we see someone actually builds something that uses it. I realizes you might be hesitant to do that until you know it can be built on a stable api, but I don't think we can get around that.
> Executor Plugin API
> -------------------
>
> Key: SPARK-24918
> URL: https://issues.apache.org/jira/browse/SPARK-24918
> Project: Spark
> Issue Type: New Feature
> Components: Spark Core
> Affects Versions: 2.4.0
> Reporter: Imran Rashid
> Priority: Major
> Labels: SPIP, memory-analysis
>
> It would be nice if we could specify an arbitrary class to run within each executor for debugging and instrumentation. Its hard to do this currently because:
> a) you have no idea when executors will come and go with DynamicAllocation, so don't have a chance to run custom code before the first task
> b) even with static allocation, you'd have to change the code of your spark app itself to run a special task to "install" the plugin, which is often tough in production cases when those maintaining regularly running applications might not even know how to make changes to the application.
> For example, https://github.com/squito/spark-memory could be used in a debugging context to understand memory use, just by re-running an application with extra command line arguments (as opposed to rebuilding spark).
> I think one tricky part here is just deciding the api, and how its versioned. Does it just get created when the executor starts, and thats it? Or does it get more specific events, like task start, task end, etc? Would we ever add more events? It should definitely be a {{DeveloperApi}}, so breaking compatibility would be allowed ... but still should be avoided. We could create a base class that has no-op implementations, or explicitly version everything.
> Note that this is not needed in the driver as we already have SparkListeners (even if you don't care about the SparkListenerEvents and just want to inspect objects in the JVM, its still good enough).
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