BryanCutler commented on a change in pull request #31738: URL: https://github.com/apache/spark/pull/31738#discussion_r597241868
########## File path: python/docs/source/user_guide/arrow_pandas.rst ########## @@ -410,3 +410,11 @@ described in `SPARK-29367 <https://issues.apache.org/jira/browse/SPARK-29367>`_ ``pandas_udf``\s or :meth:`DataFrame.toPandas` with Arrow enabled. More information about the Arrow IPC change can be read on the Arrow 0.15.0 release `blog <https://arrow.apache.org/blog/2019/10/06/0.15.0-release/#columnar-streaming-protocol-change-since-0140>`_. +Setting Arrow ``self_destruct`` for memory savings +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +Since Spark 3.2, the Spark configuration ``spark.sql.execution.arrow.pyspark.selfDestruct.enabled`` can be used to enable PyArrow's ``self_destruct`` feature, which can save memory when creating a Pandas dataframe via ``toPandas`` by freeing Arrow-allocated memory while building the Pandas dataframe. +This option is experimental, and some operations may fail on the resulting Pandas dataframe due to immutable backing arrays. +Typically, you would see the error ``ValueError: buffer source array is read-only``. Review comment: Would it be good to say a workaround is to make a copy of the column(s) used in the operation? I suppose they could just disable the setting is most cases though. -- 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: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
