[GitHub] [spark] Kimahriman commented on pull request #41569: [SPARK-39979][SQL][FOLLOW-UP] Support large variable types in pandas UDF, createDataFrame and toPandas with Arrow

["Kimahriman (via GitHub)" <gi...@apache.org>]

Kimahriman commented on PR #41569:
URL: https://github.com/apache/spark/pull/41569#issuecomment-1589122701

   Yeah I was trying to understand all the possible flows and definitely knew it wasn't covering the Python originated ones. It looked like all the things originating from the JVM detected the schema from the arrow data coming back. But you're right about the Pandas UDF one, it's the special one that does the pandas to arrow conversion based on the python to_arrow_type. Thanks for the follow up here, it's definitely useful to have it for all those cases as well.
   
   Sorta unrelated but curious if you think this should ever be enabled by default, since most of the rest of Spark tries to avoid 2GiB limits in any places?


-- 
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org

For queries about this service, please contact Infrastructure at:
users@infra.apache.org


---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For additional commands, e-mail: reviews-help@spark.apache.org