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|
+-----------+

pyspark.sql.functions.upper pyspark.sql.functions.pandas_udf