sum
Returns the sum of all values in the expression.
Syntax
Python
from pyspark.sql import functions as sf
sf.sum(col)
Parameters
Parameter | Type | Description |
|---|---|---|
|
| 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
Python
from pyspark.sql import functions as sf
df = spark.range(10)
df.select(sf.sum(df["id"])).show()
Output
+-------+
|sum(id)|
+-------+
| 45|
+-------+
Example 2: Using a plus expression together to calculate the sum
Python
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()
Output
+------------+
|sum((A + B))|
+------------+
| 10|
+------------+
Example 3: Calculating the summation of ages with None
Python
import pyspark.sql.functions as sf
df = spark.createDataFrame([(1982, None), (1990, 2), (2000, 4)], ["birth", "age"])
df.select(sf.sum("age")).show()
Output
+--------+
|sum(age)|
+--------+
| 6|
+--------+