PySpark and AWS: Master Big Data with PySpark and AWS - Spark RDDs

The video tutorial introduces Spark RDDs, explaining them as immutable distributed collections of objects that enable parallel data processing. It covers the concepts of transformations and actions, highlighting that transformations are lazy and only executed when an action is called. The tutorial emphasizes the importance of understanding lazy evaluation in Spark, using analogies to clarify the concept. The video concludes with a summary of how Spark RDDs operate under transformations and actions, preparing viewers for hands-on practice in future videos.

What does RDD stand for in Spark?

What are the two types of functions in Spark that interact with RDDs?

Describe the difference between transformations and actions in Spark.

Explain the concept of lazy evaluation in Spark.

How does Spark handle data processing when transformations are called?

What happens when an action is triggered in Spark?

Can you provide an example of how Spark creates new RDDs during transformations?