Spark GraphX in Action

Sample Chapter

By Michael S. Malak

While graphs are often the most natural way to represent the connections among data, the complexity of large graphs makes them conceptually difficult and computationally expensive to explore, query, and analyze. GraphX, a powerful graph processing API for the Apache Spark analytics engine, makes it possible to efficiently explore and interpret large-scale graph data at near-realtime speeds. GraphX works with Spark's in-memory distributed framework to give you unprecedented speed and capacity for analyzing social media data, performing complex textual analysis, handling important machine learning algorithms, and much more.

Spark GraphX in Action starts out with an overview of Apache Spark and the GraphX graph processing API. This example-based tutorial then teaches you how to configure GraphX and use GraphX interactively. You'll get a crystal-clear introduction to graph elements, which you need to build big data graphs, and then explore the problems and possibilities of graph algorithm implementations. Along the way, you'll collect practical techniques for enhancing applications and applying machine learning algorithms to graph data.

The free sample PDF available here includes chapter 1. All registrants qualify for a Lightbend discount and will save 40% off the price of Spark GraphX in Action (all formats) as it becomes available by referencing promotional code 15tssgx. If you are interested in purchasing the full book get it here. Offer only valid at

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About Lightbend

Lightbend (Twitter: @Lightbend) is dedicated to helping developers build Reactive applications on the JVM. With the Lightbend Reactive Platform, developers can create message-driven applications that scale on multicore and cloud computing architectures by using projects like Lagom, Play Framework, Akka, Scala, Java, and Apache Spark. To help our customers succeed, Lightbend partners with technology pioneers such as Databricks, IBM, and Mesosphere.