HyukjinKwon commented on a change in pull request #31738:
URL: https://github.com/apache/spark/pull/31738#discussion_r588973127



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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:
       Hm, can we maybe file an issue in pandas side and link it here?




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