In this chapter, we have introduced graph theory using Facebook as an example; Apache Spark's graph processing library GraphX, VertexRDD, and EdgeRDDs; graph operators, aggregateMessages, TriangleCounting, and the Pregel API; and use cases such as the PageRank algorithm. We have also seen the traveling salesman problem and connected components and so on. We have seen how the GraphX API can be used to develop graph processing algorithms at scale.

In Chapter 11, Learning Machine Learning - Spark MLlib and ML, we will explore the exciting world of Apache Spark's Machine Learning library.