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.

About the Book

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

About the Reader

Readers should be comfortable writing code. Experience with Apache Spark and Scala is not required.

About the Authors

Michael Malak

has worked on Spark applications for Fortune 500 companies since early 2013.

Robin East

has worked as a consultant to large organizations for over 15 years and is a data scientist at Worldpay.

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

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