[GitHub] [spark] abhishekd0907 commented on pull request #29242: [SPARK-31448] [PYTHON] Fix storage level used in cache() in dataframe.py

[GitBox <gi...@apache.org>]

abhishekd0907 commented on pull request #29242:
URL: https://github.com/apache/spark/pull/29242#issuecomment-687838113


   > Are you sure the last commit is consistent with the discussion above? I'm not quite following.
   
   @srowen 
   As @cloud-fan suggested in the comment below, the only change needed is to keep the storage level in `scalaDataFrame.persist()` and `pysparkDataframe.persist()` same i.e. `StorageLevel(true, true, false, true)`
   
   > I'm not sure if it worth. The CachedBatch is mostly a wrapper of byte[] so keeping the serialized or deserialized form in memory doesn't matter too much.
   I think the important thing is to keep Scala and Python cache/persistent consistent, although the Scala side has more builtin StorageLevels.
   
   @cloud-fan let me know in case I misunderstood your point or you intend to achieve the same thing in some other way.
   Apologies for so much delay in updating this PR.


----------------------------------------------------------------
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.

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