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 how to use it interactively. Along the way, you'll collect practical techniques for enhancing applications and applying machine learning algorithms to graph data.
About the Technology
GraphX is a powerful graph processing API for the Apache Spark analytics engine that lets you draw insights from large datasets. GraphX gives you unprecedented speed and capacity for running massively parallel and machine learning algorithms.
Spark GraphX in Action begins with the big picture of what graphs can be used for. This example-based tutorial teaches you how to use GraphX interactively. You'll start with a crystal-clear introduction to building big data graphs from regular data, and then explore the problems and possibilities of implementing graph algorithms and architecting graph processing pipelines. Along the way, you'll collect practical techniques for enhancing applications and applying machine learning algorithms to graph data.
What's Inside • Understanding graph technology • Using the GraphX API • Developing algorithms for big graphs • Machine learning with graphs • Graph visualization
Table of Contents PART 1 SPARK AND GRAPHS • Two important technologies: Spark and graphs • GraphX quick start • Some fundamentals. PART 2 CONNECTING VERTICES • GraphX Basics • Built-in algorithms • Other useful graph algorithms • Machine learning. PART 3 OVER THE ARC • The missing algorithms • Performance and monitoring • Other languages and tools
