Spark's execution engine is designed to be Lazy. In effect, you're first up build up your analytics/data processing request through a series of Transformations which are then executed by an Action
Transformations are kind of operations which will transform your RDD data from one form to another. And when you apply this operation on any RDD, you will get a new RDD with transformed data Operations like map, filter are transformations.
Transformations create RDDs from each other, but when we want to work with the actual dataset, at that point action is performed. When the action is triggered after the result, new RDD is not formed like transformation. Ex:- count on a DF
