Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/22610#discussion_r223177785
--- Diff: python/pyspark/sql/functions.py ---
@@ -2909,6 +2909,11 @@ 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. When there is mismatch between
them, it is not guaranteed
+ that the conversion by SparkSQL during serialization is correct at
all and users might get
--- End diff --
Yeah, as actually we don't intentionally cast the returned data.
How about:
```
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.
```
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
