How to create / register and drop a UDF in Databricks Spark using Python

Below is an example of how to create and drop a UDF in Python using Databricks:

Creating a UDF:

from pyspark.sql.functions import udf

from pyspark.sql.types import IntegerType

# Define the function you want to use in your UDF

def multiply_by_two(x):

    return x * 2

# Create the UDF using the function you defined

multiply_by_two_udf = udf(multiply_by_two, IntegerType())

# Register the UDF so it can be used in your Spark SQL queries

spark.udf.register("multiply_by_two", multiply_by_two_udf)

Dropping a UDF:

# Unregister the UDF so it can no longer be used in your Spark SQL queries

spark.catalog.dropTempView("multiply_by_two")

Note that in the above examples, we're using spark to access the SparkSession object, which is the entry point to using Spark functionality. If you're running this code in a Databricks notebook, the SparkSession object is automatically created for you.