Transformations vs actions in Apache Spark - Quick Revision & Key Differences

Recall & Review

beginner

What is a transformation in Apache Spark?

A transformation is an operation on an RDD or DataFrame that returns a new RDD or DataFrame. It is lazy, meaning it does not execute immediately but builds a plan for computation.

beginner

What is an action in Apache Spark?

An action triggers the execution of the transformations and returns a result to the driver or writes data to storage. Actions cause Spark to compute the data.

intermediate

Why are transformations called lazy in Spark?

Because Spark does not run transformations immediately. It waits until an action is called to optimize and execute the whole set of transformations together.

beginner

Give an example of a transformation and an action in Spark.

Transformation example: map(), filter(). Action example: collect(), count().

intermediate

How do actions affect performance in Spark?

Actions trigger computation, so they can be expensive. Minimizing actions and combining transformations helps Spark optimize execution and improve performance.

Which of the following is a transformation in Spark?

A filter()

B count()

C collect()

D take()

filter() is a transformation that returns a new RDD or DataFrame without triggering computation.

What does an action in Spark do?

A Creates a new RDD lazily

B Triggers execution of transformations

C Defines a data schema

D Caches data in memory

Actions trigger Spark to execute all pending transformations and return results or write data.

Why are transformations in Spark considered lazy?

A They build a plan but do not execute until an action runs

B They cache data

C They write data to disk

D They execute immediately

Transformations only build a computation plan and wait for an action to trigger execution.

Which of these is an action in Spark?

A map()

B flatMap()

C filter()

D reduce()

reduce() is an action that aggregates data and triggers computation.

What happens if you call multiple transformations without an action?

A Spark executes each transformation immediately

B Spark caches all data automatically

C No computation happens until an action is called

D Spark throws an error

Transformations are lazy and do not execute until an action triggers computation.

Explain the difference between transformations and actions in Apache Spark.

Think about when Spark actually runs the code.

Why is lazy evaluation important in Spark's transformations?

Consider how Spark saves time and resources.