This code demonstrates how to integrate PySpark with datasets and perform simple data transformations. It loads a sample dataset using PySpark's built-in functionalities or reads data from external sources and converts it into a PySpark DataFrame for distributed processing and manipulation.
Using Apache pySpark on DataBricks, I was able to do feature Engineering on Customer Data, trained and used a Linear Regression Model to predict their bill based on previous customer trends.