Preface

What can graphs—the things with edges and vertices, not the things with axes and tick marks—do and how can they be used with Spark? These are the questions we try to answer in this book.

Frequently it is said, “Graphs can do anything,” or at least, “There are a bunch of different things you can do with graphs.” That says nothing, of course, so in this book we show a number of specific, real-life ways you can apply graphs and talk about how to implement such solutions in Spark GraphX.

A lot of technology buzzwords are applicable to this book: Big Data, Hadoop, Spark, graphs, machine learning, Scala, and functional programming. We break it all down for you. Even though we end up in some fairly advanced areas, we don’t assume anything more than an ability to program in some language such as Java.

This chart from Google Trends shows the relative interest in these buzzwords through early 2016:

Note that for the generic terms spark and graphs we had to substitute the overly specific Apache Spark and edges and vertices, but the trends can still be seen. A couple of these technologies, machine learning and graphs, have long histories within academic computer science and are attracting new interest in the commercial realm as the availability of Big Data is now mainstreaming these technologies. If you studied these technologies in school as theory, the world is ready now for you to put them into practice.