PySpark and AWS: Master Big Data with PySpark and AWS - RDD Filter

The video tutorial explores the use of filters in Spark RDDs, explaining how filters remove elements based on conditions. It covers the syntax of filters, the use of Lambda functions, and how to implement logic using functions. The tutorial demonstrates how true or false conditions affect the final output and provides examples of both Lambda and function-based approaches.

What is the primary purpose of using a filter in RDD?

• To sort the elements in RDD

• To remove elements based on a condition

• To merge two RDDs

• To duplicate elements in RDD

How does a lambda expression work with a filter in RDD?

• It merges elements into a single string

• It evaluates each element and includes it if the condition is true

• It duplicates each element

• It sorts the elements alphabetically

What happens when a filter expression always evaluates to true?

• Only the last element is included

• All elements are included in the output

• Only the first element is included

• All elements are excluded from the output

What is the result of using an expression that always evaluates to false in a filter?

• Only the last element is included

• No elements are included in the output

• Only the first element is included

• All elements are included in the output

How can you implement filter logic without using lambda expressions?

• By using a for loop

• By using a while loop

• By using a map function

• By writing a separate function

What is the outcome when a function used in a filter returns true?

• The element is excluded from the output

• The element is included in the output

• The element is duplicated

• The element is sorted

What does the filter function do when the condition is not met?

• It includes the element in the output

• It duplicates the element

• It excludes the element from the output

• It sorts the element