lidavidm commented on a change in pull request #31738:
URL: https://github.com/apache/spark/pull/31738#discussion_r589571748



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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:
       I think I haven't fully explained the nature of this - it's not any 
single issue in Pandas, nor is it specific to any particular version. Instead, 
it's just that depending on how each Pandas operation was implemented 
underneath, it may or may not have been _declared_ to accept an immutable 
backing array, independently of whether that operation _could be implemented_ 
on an immutable array. So whether you see this will depend on what exactly you 
do with the dataframe, and there's no one version range we can list or one 
issue we can link to. And indeed, you could see this error see this _without_ 
this Arrow option enabled; it's just much less likely, since there will be few 
cases that Arrow can perform a zero-copy conversion in that case.




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