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[SPARK-22347][PySpark][DOC] Add document to notice users for using udfs with conditional expressions #19617

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[SPARK-22347][PySpark][DOC] Add document to notice users for using udfs with conditional expressions #19617

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Add document to notice users for using udfs with conditional expressi…
viirya Oct 31, 2017
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Address comments.
viirya Oct 31, 2017
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14 changes: 14 additions & 0 deletions python/pyspark/sql/functions.py
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Expand Up @@ -2185,6 +2185,13 @@ def udf(f=None, returnType=StringType()):
duplicate invocations may be eliminated or the function may even be invoked more times than
it is present in the query.

.. note:: The user-defined functions do not support conditional execution by using them with
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@HyukjinKwon HyukjinKwon Oct 31, 2017

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Hm, should we maybe clarify the output itself is correct if it does not cause the runtime failure by the condition? Maybe I am too much worried but think it might mislead the output is incorrect at all.

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@viirya viirya Oct 31, 2017

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Yes. I think this is a valid worry. Thanks.

SQL conditional expressions such as `when` or `if`. The functions still apply on all rows no
matter the conditions are met or not. So the output is correct if the functions can be
correctly run on all rows without failure. If the functions can cause runtime failure on the
rows that do not satisfy the conditions, the suggested workaround is to incorporate the
condition logic into the functions.

:param f: python function if used as a standalone function
:param returnType: a :class:`pyspark.sql.types.DataType` object

Expand Down Expand Up @@ -2278,6 +2285,13 @@ def pandas_udf(f=None, returnType=StringType()):
.. seealso:: :meth:`pyspark.sql.GroupedData.apply`

.. note:: The user-defined function must be deterministic.

.. note:: The user-defined functions do not support conditional execution by using them with
SQL conditional expressions such as `when` or `if`. The functions still apply on all rows no
matter the conditions are met or not. So the output is correct if the functions can be
correctly run on all rows without failure. If the functions can cause runtime failure on the
rows that do not satisfy the conditions, the suggested workaround is to incorporate the
condition logic into the functions.
"""
return _create_udf(f, returnType=returnType, pythonUdfType=PythonUdfType.PANDAS_UDF)

Expand Down