pyspark.sql.functions.call_udf

pyspark.sql.functions.call_udf(udfName: str, *cols: ColumnOrName) → pyspark.sql.column.Column[source]

Call an user-defined function.

New in version 3.4.0.

Parameters
udfNamestr

name of the user defined function (UDF)

colsColumn or str

column names or Columns to be used in the UDF

Returns
Column

result of executed udf.

Examples

>>> 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|
+---------+
>>> _ = spark.udf.register("strX2", lambda s: s * 2, StringType())
>>> df.select(call_udf("strX2", col("name"))).show()
+-----------+
|strX2(name)|
+-----------+
|         aa|
|         bb|
|         cc|
+-----------+