sum

Returns the sum of all values in the expression.

Syntax

from pyspark.sql import functions as sf

sf.sum(col)

Parameters

Parameter	Type	Description
col	pyspark.sql.Column or column name	Target column to compute on.

Returns

pyspark.sql.Column: the column for computed results.

Examples

Example 1: Calculating the sum of values in a column

from pyspark.sql import functions as sf
df = spark.range(10)
df.select(sf.sum(df["id"])).show()

+-------+
|sum(id)|
+-------+
|     45|
+-------+

Example 2: Using a plus expression together to calculate the sum

from pyspark.sql import functions as sf
df = spark.createDataFrame([(1, 2), (3, 4)], ["A", "B"])
df.select(sf.sum(sf.col("A") + sf.col("B"))).show()

+------------+
|sum((A + B))|
+------------+
|          10|
+------------+

Example 3: Calculating the summation of ages with None

import pyspark.sql.functions as sf
df = spark.createDataFrame([(1982, None), (1990, 2), (2000, 4)], ["birth", "age"])
df.select(sf.sum("age")).show()

+--------+
|sum(age)|
+--------+
|       6|
+--------+