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

    https://github.com/apache/spark/pull/20456#discussion_r165838097
  
    --- Diff: python/pyspark/sql/dataframe.py ---
    @@ -667,6 +667,51 @@ def repartition(self, numPartitions, *cols):
             else:
                 raise TypeError("numPartitions should be an int or Column")
     
    +    @since("2.3.0")
    +    def repartitionByRange(self, numPartitions, *cols):
    +        """
    +        Returns a new :class:`DataFrame` partitioned by the given 
partitioning expressions. The
    +        resulting DataFrame is range partitioned.
    +
    +        ``numPartitions`` can be an int to specify the target number of 
partitions or a Column.
    +        If it is a Column, it will be used as the first partitioning 
column. If not specified,
    +        the default number of partitions is used.
    +
    +        At least one partition-by expression must be specified.
    +        When no explicit sort order is specified, "ascending nulls first" 
is assumed.
    +
    +        >>> df.repartitionByRange(2, "age").rdd.getNumPartitions()
    +        2
    +        >>> df.show()
    +        +---+-----+
    +        |age| name|
    +        +---+-----+
    +        |  2|Alice|
    +        |  5|  Bob|
    +        +---+-----+
    +        >>> df.repartitionByRange(1, "age").rdd.getNumPartitions()
    +        1
    +        >>> data = df.repartitionByRange("age")
    +        >>> df.show()
    +        +---+-----+
    +        |age| name|
    +        +---+-----+
    +        |  2|Alice|
    +        |  5|  Bob|
    +        +---+-----+
    +        """
    +        if isinstance(numPartitions, int):
    +            if len(cols) == 0:
    +                return ValueError("At least one partition-by expression 
must be specified.")
    +            else:
    +                return DataFrame(
    +                    self._jdf.repartitionByRange(numPartitions, 
self._jcols(*cols)), self.sql_ctx)
    +        elif isinstance(numPartitions, (basestring, Column)):
    +            cols = (numPartitions,) + cols
    +            return 
DataFrame(self._jdf.repartitionByRange(self._jcols(*cols)), self.sql_ctx)
    +        else:
    +            raise TypeError("numPartitions should be an int or Column")
    --- End diff --
    
    `an int or Column` -> `an int, string or Column`


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