What is UDF in Spark ?

In Spark, a UDF is a way to extend the functionality of Spark by allowing developers to define their own custom functions that can be applied to DataFrame columns. These functions can be used to perform complex operations on the data that are not readily available through built-in Spark functions.

UDFs are especially useful when you need to apply a custom transformation or calculation to one or more columns in a DataFrame. They enable you to leverage the full power of a programming language like Python, Scala, or Java to process data in Spark.