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Aggregate function: indicates whether a specified column in a GROUP BY list is aggregated or not, returns 1 for aggregated or 0 for not aggregated in the result set.
Syntax
from pyspark.sql import functions as sf
sf.grouping(col)
Parameters
| Parameter | Type | Description |
|---|---|---|
col |
pyspark.sql.Column or str |
Column to check if it's aggregated. |
Returns
pyspark.sql.Column: returns 1 for aggregated or 0 for not aggregated in the result set.
Examples
Example 1: Check grouping status in cube operation
from pyspark.sql import functions as sf
df = spark.createDataFrame([("Alice", 2), ("Bob", 5)], ("name", "age"))
df.cube("name").agg(sf.grouping("name"), sf.sum("age")).orderBy("name").show()
+-----+--------------+--------+
| name|grouping(name)|sum(age)|
+-----+--------------+--------+
| NULL| 1| 7|
|Alice| 0| 2|
| Bob| 0| 5|
+-----+--------------+--------+