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

The video tutorial demonstrates how to filter a DataFrame to select employees older than 45 and save the filtered data as a CSV file in a specified directory. It also covers verifying the saved data by creating a table view using a cluster. The tutorial aims to enhance understanding of DataFrame operations and data handling in a programming environment.

What is the primary condition used to filter the DataFrame in the tutorial?

• Employees with age less than 30

• Employees with age greater than 45

• Employees with age equal to 45

• Employees with age less than 45

What file format is used to save the filtered DataFrame?

• CSV

• TXT

• XML

• JSON

Where is the output path for the CSV file specified?

• In the root directory

• In a temporary directory

• In the same directory as the input

• In a new directory

What is the purpose of creating multiple files in the output folder?

• To store different data types

• To improve file access speed

• To handle large data by partitioning

• To create backups

How can the output data be verified after writing to the CSV?

• By creating a table view using the cluster

• By comparing with the original DataFrame

• By opening the CSV in a text editor

• By checking the file size