why is `spark.sql.codegen.wholeStage` set to. `fal...
# kotlin-sparke
Eric Rodriguez
03/13/2024, 9:41 PMwhy is
spark.sql.codegen.wholeStagefalsej
Jolan Rensen [JB]
03/18/2024, 9:58 AMHonestly, I don't remember 😅 are you able to turn it on like
%use spark(spark.sql.codegen.wholeStage=true)e
Eric Rodriguez
03/18/2024, 10:07 AMhaven't tried it since I don't think it affects me
Eric Rodriguez
03/18/2024, 10:07 AMwill let u kn ow when I get a chance to try it
j
Jolan Rensen [JB]
03/18/2024, 1:32 PMI suspect we turned it off because it tries to collapse java code calls (as described here https://jaceklaskowski.gitbooks.io/mastering-spark-sql/content/spark-sql-whole-stage-codegen.html). This might cause issues since we wrap java functions with kotlin ones. Plus, in Jupyter, we're working with Kotlin REPL which is again an abstraction on top of Kotlin, so the more Spark optimizations we can turn off, the more stable it will be
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Eric Rodriguez
03/18/2024, 1:38 PMI see.
What's the best place to understand how you do the kotlin-> Scala translation?
Eric Rodriguez
03/18/2024, 1:38 PMj
Jolan Rensen [JB]
03/18/2024, 1:44 PMWell yes, I'm working on a revamp to support Spark 3.4+. They reworked their internals, so our old hacky approach no longer works. However, this new approach is still a WIP and not yet published anywhere (apart from the draft PR). It should become way less hacky and support Spark Connect (in theory). But it still has some issues, as described in that issue thread.
To see how we generate encoders/schemas/datatypes from Kotlin in the latest release you can check out
Enocding.kt and KotlinReflection.scala. I gave more explanation in this comment.
We also provide many wrappers for functions, like the ones here.
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