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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2019/02/16 17:19:31 UTC

[GitHub] HyukjinKwon commented on issue #23810: [SPARK-26901][SQL][R] Avoid to prune columns for vectorized gapply()

HyukjinKwon commented on issue #23810: [SPARK-26901][SQL][R] Avoid to prune columns for vectorized gapply()
URL: https://github.com/apache/spark/pull/23810#issuecomment-464364408
 
 
   cc @cloud-fan and @viirya .
   
   I have been separately taking a look for this. I was thinking I might need a Python UDF like extraction and projection rules but looks I don't need it if I am not mistaken.
   
   FYI, regular `gapply` passes since it's always wrapped by `SerializeFromObject`. In case of Pandas UDFs, I think they are guided by Python UDF extraction + projection.
   
   Can you take a look and see if it makes sense to you?

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