UDFRegistration
Wrapper for user-defined function registration. This instance can be accessed by spark.udf.
Syntax
Python
# Access through SparkSession
spark.udf
Properties
Property | Description |
|---|---|
| Returns a UDFLogs instance for UDF logging. This feature is experimental and unstable. |
Methods
Method | Description |
|---|---|
Registers a Python function (including lambda functions) or a user-defined function as a SQL function. Supports Spark Connect. | |
Registers a Java user-defined function as a SQL function. When | |
Registers a Java user-defined aggregate function as a SQL function. Supports Spark Connect. |
Examples
Python
strlen = spark.udf.register("stringLengthString", lambda x: len(x))
spark.sql("SELECT stringLengthString('test')").collect()
Output
[Row(stringLengthString(test)='4')]
Python
from pyspark.sql.types import IntegerType
from pyspark.sql.functions import udf
slen = udf(lambda s: len(s), IntegerType())
_ = spark.udf.register("slen", slen)
spark.sql("SELECT slen('test')").collect()
Output
[Row(slen(test)=4)]
Python
import pandas as pd
from pyspark.sql.functions import pandas_udf
@pandas_udf("integer")
def add_one(s: pd.Series) -> pd.Series:
return s + 1
_ = spark.udf.register("add_one", add_one)
spark.sql("SELECT add_one(id) FROM range(3)").collect()
Output
[Row(add_one(id)=1), Row(add_one(id)=2), Row(add_one(id)=3)]