Along with Spark MLlib for machine learning, which we have already encountered a few times in this book, and others like Spark Streaming, which we will cover in Chapter 8, Lending Club Loan Prediction, Spark GraphX is one of the core components of the Spark ecosphere. GraphX is tailored for processing large graphs in an efficient way by building on top of RDDs.
Using the nomenclature developed in the last section, a graph in GraphX is a finite multigraph with loops, where by graph, we actually mean the property graph extension discussed earlier. Next, we will see how graphs are built internally in GraphX.
For the examples used, we recommend firing up spark-shell locally, which will automatically provide dependencies for GraphX. To test whether this works properly in your setup, try importing the full GraphX core module using Scala&apos...