RDD (Resilient Distributed Dataset) is the fundamental data structure of Apache Spark which are an immutable collection of objects which computes on the different node of the cluster. Each and every dataset in Spark RDD is logically partitioned across many servers so that they can be computed on different nodes of the cluster.
In this blog, we are going to get to know about what is RDD in Apache Spark. What are the features of RDD, What is the motivation behind RDDs, RDD vs DSM? We will also cover Spark RDD operation i.e. transformations and actions, various limitations of RDD in Spark and how RDD make Spark feature rich in this Spark tutorial.