Once we have created an RDD, we have a distributed collection of records that we can manipulate. In Spark's programming model, operations are split into transformations and actions. Generally speaking, a transformation operation applies some function to all the records in the dataset, changing the records in some way. An action typically runs some computation or aggregation operation and returns the result to the driver program where SparkContext is running.
Spark operations are functional in style. For programmers familiar with functional programming in Scala, Python, or Lambda expressions in Java 8, these operations should seem natural. For those without experience in functional programming, don't worry; the Spark API is ...
