call_udf

Call a user-defined function.

Syntax

import pyspark.sql.functions as sf

sf.call_udf(udfName=<udfName>, *cols)

Parameters

Parameter	Type	Description
udfName	str	Name of the user defined function (UDF).
cols	pyspark.sql.Column or str	Column names or Columns to be used in the UDF.

Returns

pyspark.sql.Column: result of executed udf.

Examples

Example 1: Using call_udf with an integer UDF.

from pyspark.sql.functions import call_udf, col
from pyspark.sql.types import IntegerType, StringType
df = spark.createDataFrame([(1, "a"),(2, "b"), (3, "c")],["id", "name"])
_ = spark.udf.register("intX2", lambda i: i * 2, IntegerType())
df.select(call_udf("intX2", "id")).show()

+---------+
|intX2(id)|
+---------+
|        2|
|        4|
|        6|
+---------+

Example 2: Using call_udf with a string UDF.

from pyspark.sql.functions import call_udf, col
from pyspark.sql.types import IntegerType, StringType
df = spark.createDataFrame([(1, "a"),(2, "b"), (3, "c")],["id", "name"])
_ = spark.udf.register("strX2", lambda s: s * 2, StringType())
df.select(call_udf("strX2", col("name"))).show()

+-----------+
|strX2(name)|
+-----------+
|         aa|
|         bb|
|         cc|
+-----------+