PySpark and AWS: Master Big Data with PySpark and AWS - Project (UDF and WithColumn)

The video tutorial explains how to create and use a User Defined Function (UDF) to increase the salary of employees over the age of 45 by $500. It covers the steps to define the UDF, implement the logic to check the age condition, register the UDF, and apply it to a data frame to update the salary column. The tutorial emphasizes the importance of running the cell after modifications to ensure changes are applied.

What is the primary condition for increasing an employee's salary by $500?

• If the employee's age is less than 45

• If the employee's age is exactly 45

• If the employee's age is greater than 45

• If the employee's salary is below a certain threshold

What inputs does the UDF require to determine the salary increment?

• Employee's department and current salary

• Employee's age and current salary

• Employee's performance rating and salary

• Employee's years of service and age

What is the purpose of registering a function as a UDF?

• To allow it to be used in data frames

• To increase its execution speed

• To make it available for use in SQL queries

• To convert it into a machine learning model

Which method is used to update the salary column in the data frame?

• updateColumn

• modifyColumn

• withColumn

• changeColumn

How does the UDF determine if a salary should be increased?

• By checking if the salary is below a certain amount

• By checking if the employee has received a bonus

• By checking if the age is greater than 45

• By checking if the employee has been promoted

What happens to the salary if the employee's age is under 45?

• It is doubled

• It remains the same

• It is decreased by $500

• It is increased by $500

What is the result when the UDF is applied to an employee aged 47?

• The salary is doubled

• The salary is increased by $500

• The salary remains unchanged

• The salary is decreased by $500