call_udf
Call a user-defined function.
Syntax
Python
import pyspark.sql.functions as sf
sf.call_udf(udfName=<udfName>, *cols)
Parameters
Parameter | Type | Description |
|---|---|---|
|
| Name of the user defined function (UDF). |
|
| 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.
Python
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()
Output
+---------+
|intX2(id)|
+---------+
| 2|
| 4|
| 6|
+---------+
Example 2: Using call_udf with a string UDF.
Python
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()
Output
+-----------+
|strX2(name)|
+-----------+
| aa|
| bb|
| cc|
+-----------+