pyspark.sql.functions.grouping_id¶
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pyspark.sql.functions.
grouping_id
(*cols)[source]¶ Aggregate function: returns the level of grouping, equals to
(grouping(c1) << (n-1)) + (grouping(c2) << (n-2)) + … + grouping(cn)
New in version 2.0.0.
Notes
The list of columns should match with grouping columns exactly, or empty (means all the grouping columns).
Examples
>>> df.cube("name").agg(grouping_id(), sum("age")).orderBy("name").show() +-----+-------------+--------+ | name|grouping_id()|sum(age)| +-----+-------------+--------+ | null| 1| 7| |Alice| 0| 2| | Bob| 0| 5| +-----+-------------+--------+