Spark RDD

Resilient Distributed Datasets (RDDs) are the basic building block of a Spark application. An RDD represents a read-only collection of objects distributed across multiple machines. Spark can distribute a collection of records using an RDD and process them in parallel on different machines. 

In this chapter, we shall learn about the following:

• • What is an RDD? 
  • How do you create RDDs?
  • Different operations available to work on RDDs
  • Important types of RDD
  • Caching an RDD
  • Partitions of an RDD
  • Drawbacks of using RDDs

The code examples in this chapter are written in Python and Scala only. If you wish to go through the Java and R APIs, you can visit the Spark documentation page at https://spark.apache.org/.