Spark Programming in Python for Beginners with Apache Spark 3 - Creating and Using UDF

The video tutorial explains how to create and use User Defined Functions (UDFs) in Apache Spark. It covers the creation of a UDF to standardize gender data, registration of the UDF for use in both column and SQL expressions, and the differences between these registration methods. The tutorial also demonstrates how to transform data using the 'withColumn' method and how to query the Spark catalog for registered functions.

What are the two methods mentioned for creating expressions in Spark?

Explain the purpose of a User Defined Function (UDF) in Spark.

What is the role of regular expressions in the parse gender function?

What is the significance of the 'with column' transformation in Spark?

Describe the process of registering a UDF in Spark.

How does the registration of a UDF differ when using it in a DataFrame versus a SQL expression?

What does the term 'catalog' refer to in the context of Spark UDFs?

How can you check if a UDF is registered in the Spark catalog?

What are the expected outputs after applying the parse gender function to the data frame?

What is the final outcome of using the with column transformation on the gender field?