[GitHub] [spark] WeichenXu123 commented on a change in pull request #31738: [SPARK-34463][PYSPARK][DOCS] Document caveats of Arrow selfDestruct

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WeichenXu123 commented on a change in pull request #31738:
URL: https://github.com/apache/spark/pull/31738#discussion_r589288599



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File path: python/docs/source/user_guide/arrow_pandas.rst
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@@ -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``.
+Newer versions of Pandas may fix these errors by improving support for such cases.
+Additionally, this conversion may be slower because it is single-threaded.

Review comment:
       Could we explicitly say which version pandas will trigger the bug ?
   
   Currently my test show that pandas version > 1.0.5 will trigger the bug.




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