Github user icexelloss commented on a diff in the pull request:
https://github.com/apache/spark/pull/20217#discussion_r160858034
--- Diff: python/pyspark/sql/catalog.py ---
@@ -255,26 +255,67 @@ def registerFunction(self, name, f,
returnType=StringType()):
>>> _ = spark.udf.register("stringLengthInt", len, IntegerType())
>>> spark.sql("SELECT stringLengthInt('test')").collect()
[Row(stringLengthInt(test)=4)]
+ """
+
+ # This is to check whether the input function is a wrapped/native
UserDefinedFunction
+ if hasattr(f, 'asNondeterministic'):
+ raise ValueError("Please use registerUDF for registering UDF.
The expected function of "
+ "registerFunction is a Python function
(including lambda function)")
+ udf = UserDefinedFunction(f, returnType=returnType, name=name,
+ evalType=PythonEvalType.SQL_BATCHED_UDF)
+ self._jsparkSession.udf().registerPython(name, udf._judf)
+ return udf._wrapped()
+
+ @ignore_unicode_prefix
+ @since(2.3)
+ def registerUDF(self, name, f):
+ """Registers a :class:`UserDefinedFunction`. The registered UDF
can be used in SQL
+ statement.
+
+ :param name: name of the UDF
--- End diff --
Maybe something like "name of the UDF in SQL statement" to be more specific.
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