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[SPARK-17605][SPARK_SUBMIT] Add option spark.usePython and spark.useR for applications that use both pyspark and sparkr #15159
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Test build #65644 has finished for PR 15159 at commit
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Do you have a test or use case that have both Python and R code? I'm not quite sure that actually work.. |
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@felixcheung Thanks for review, as I mention in the jira description, zeppelin/livy would use both pyspark and sparkR. I try this PR with zeppelin (but needs some code change in zeppelin), and it works. |
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so now there's an isPython and usePython? Can you just use the old one?
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isPython and usePython has different semantic. isPython means it is pyspark application and the primary resource should be python script or pyspark-shell, and we use isPython to figure out the mainClass. While usePython doesn't mean it is pyspark application ( it could be scala application but use pyspark internally ), and it is not related with mainClass.
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Add @rxin @davies @JoshRosen @shivaram for more feedback. |
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Just a heads up this has conflicts with master so it might be good to update (since I know a lot of reviewers use the spark-pr dashboard and maybe skip PRs which aren't mergable). |
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@zjffdu so is the intent of this to allow people to use PySpark from Scala Spark applications? |
… for applications that use both pyspark and sparkr
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@holdenk that's correct. |
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Test build #66594 has finished for PR 15159 at commit
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I wonder if there isn't a better way to handle this without having to add more configs. e.g., just distribute things if the user asks for it. For example, if Similar things for R, although I'm not really familiar with that path. I might be overseeing something, but I think it would be nice to avoid adding more config options if possible. |
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(gentle ping @zjffdu) |
What changes were proposed in this pull request?
It is mostly for yarn mode, standalone mode don't need to distribute resources (sparkr.zip, pyspark.zip and etc) if I understand correctly. Add 2 options spark.usePython and spark.useR, so that any project using both sparkR and pyspark can leverage these 2 options.
How was this patch tested?
Use the following command to launch SparkPi and notice pyspark.zip, sparkr.zip and py4j are all distirbuted to executors.
Client output