pyspark.sql.GroupedData.sum#

GroupedData.sum(*cols)[source]#

Computes the sum for each numeric columns for each group.

New in version 1.3.0.

Changed in version 3.4.0: Supports Spark Connect.

Parameters

colsstr: column names. Non-numeric columns are ignored.

Examples

>>> df = spark.createDataFrame([
...     (2, "Alice", 80), (3, "Alice", 100),
...     (5, "Bob", 120), (10, "Bob", 140)], ["age", "name", "height"])
>>> df.show()
+---+-----+------+
|age| name|height|
+---+-----+------+
|  2|Alice|    80|
|  3|Alice|   100|
|  5|  Bob|   120|
| 10|  Bob|   140|
+---+-----+------+

Group-by name, and calculate the sum of the age in each group.

>>> df.groupBy("name").sum("age").sort("name").show()
+-----+--------+
| name|sum(age)|
+-----+--------+
|Alice|       5|
|  Bob|      15|
+-----+--------+

Calculate the sum of the age and height in all data.

>>> df.groupBy().sum("age", "height").show()
+--------+-----------+
|sum(age)|sum(height)|
+--------+-----------+
|      20|        440|
+--------+-----------+