Github user chenghao-intel commented on a diff in the pull request:
https://github.com/apache/spark/pull/6311#discussion_r30773786
--- Diff: python/pyspark/sql/dataframe.py ---
@@ -755,6 +755,52 @@ def groupBy(self, *cols):
from pyspark.sql.group import GroupedData
return GroupedData(jdf, self.sql_ctx)
+ def rollup(self, *cols):
+ """
+ Create a multi-dimensional rollup for the current
:class:`DataFrame` using
+ the specified columns, so we can run aggregation on them.
+
+ >>> df.rollup('name', df.age).count().show()
+ +-----+----+-----+
+ | name| age|count|
+ +-----+----+-----+
+ |Alice|null| 1|
+ | Bob| 5| 1|
+ | Bob|null| 1|
+ | null|null| 2|
+ |Alice| 2| 1|
+ +-----+----+-----+
+
+ .. versionadded:: 1.4
+ """
+ jdf = self._jdf.rollup(self._jcols(*cols))
--- End diff --
`jdf` -> `jgd`? otherwise it's probably confusing.
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