Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/22610#discussion_r223217249
--- Diff: python/pyspark/sql/functions.py ---
@@ -2909,6 +2909,12 @@ def pandas_udf(f=None, returnType=None,
functionType=None):
can fail on special rows, the workaround is to incorporate the
condition into the functions.
.. note:: The user-defined functions do not take keyword arguments on
the calling side.
+
+ .. note:: The data type of returned `pandas.Series` from the
user-defined functions should be
+ matched with defined returnType (see :meth:`types.to_arrow_type`
and
+ :meth:`types.from_arrow_type`). When there is mismatch between
them, Spark might do
+ conversion on returned data. The conversion is not guaranteed to
be correct and results
+ should be checked for accuracy by users.
--- End diff --
I am merging this since this describes the current status but let's make it
clear and try to get rid of this note within 3.0.
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