Github user HyukjinKwon commented on a diff in the pull request:

    https://github.com/apache/spark/pull/19630#discussion_r151677913
  
    --- Diff: python/pyspark/sql/functions.py ---
    @@ -2049,132 +2050,12 @@ def map_values(col):
     
     # ---------------------------- User Defined Function 
----------------------------------
     
    -def _wrap_function(sc, func, returnType):
    -    command = (func, returnType)
    -    pickled_command, broadcast_vars, env, includes = 
_prepare_for_python_RDD(sc, command)
    -    return sc._jvm.PythonFunction(bytearray(pickled_command), env, 
includes, sc.pythonExec,
    -                                  sc.pythonVer, broadcast_vars, 
sc._javaAccumulator)
    -
    -
    -class PythonUdfType(object):
    -    # row-at-a-time UDFs
    -    NORMAL_UDF = 0
    -    # scalar vectorized UDFs
    -    PANDAS_UDF = 1
    -    # grouped vectorized UDFs
    -    PANDAS_GROUPED_UDF = 2
    -
    -
    -class UserDefinedFunction(object):
    --- End diff --
    
    Yup, I noticed it first too when I reviewed but then noticed he imported 
this indentedly:
    
    
https://github.com/icexelloss/spark/blob/cf1d1caa4f41c6bcf565cfc5b9e9901d94f56af3/python/pyspark/sql/functions.py#L35
    
    So, I guess it could be fine. I manually just double checked:
    
    ```python
    >>> from pyspark.sql import functions
    >>> functions.UserDefinedFunction
    <class 'pyspark.sql.udf.UserDefinedFunction'>
    >>> from pyspark import sql
    >>> sql.functions.UserDefinedFunction
    <class 'pyspark.sql.udf.UserDefinedFunction'>
    >>> from pyspark.sql.functions import UserDefinedFunction
    >>> from pyspark.sql.udf import UserDefinedFunction
    ```


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