BryanCutler commented on a change in pull request #23900: [SPARK-23836][PYTHON]
Add support for StructType return in Scalar Pandas UDF
URL: https://github.com/apache/spark/pull/23900#discussion_r268758759
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File path: python/pyspark/sql/functions.py
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@@ -2868,6 +2869,15 @@ def pandas_udf(f=None, returnType=None,
functionType=None):
+----------+--------------+------------+
| 8| JOHN DOE| 22|
+----------+--------------+------------+
+ >>> @pandas_udf("first string, last string") # doctest: +SKIP
Review comment:
Sometimes type casting is necessary, for example if your integer column has
null values then Pandas will automatically upcast to floating point to
represent the nulls as NaNs. If that column is returned then it doesn't make
sense to keep it as floating point because Spark can handle the null values, so
using integer return type will cause type casting, but won't cause any problems.
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