PySpark and AWS: Master Big Data with PySpark and AWS - Solution (UDFs)

The video tutorial guides viewers through reading data from a CSV file into a DataFrame, creating a new column for employee increments based on state-specific criteria, and writing a Python function to calculate these increments. The function is registered as a User Defined Function (UDF) and applied to the DataFrame. The tutorial also covers handling data types and debugging common errors.

What is the first step to take when working with the employee data?

Describe how to create a new column for increment in the data frame.

Explain the process of registering a function as a UDF.

What criteria should be used to calculate the increment for employees in NY state?

What changes need to be made for the increment calculation for employees in California?

How do you ensure that the return type of the function is correct?

What steps should be taken if the function is returning a float value instead of an integer?