Book Image

Apache Spark Graph Processing

Book Image

Apache Spark Graph Processing

Overview of this book

Table of Contents (16 chapters)
Apache Spark Graph Processing
Credits
Foreword
About the Author
About the Reviewer
www.PacktPub.com
Preface
Index

Chapter 6. Iterative Graph-Parallel Processing with Pregel

Graphs are a very useful abstraction for solving many practical computing problems. For example, we can search through nearly five billion web pages today, thanks to the PageRank graph algorithm. Apart from the web search, there are other applications, such as social media, for which iterative graph processing is needed. In this chapter, we will learn how to use Pregel, a computational model, which is suitable for this task. Pregel was initially proposed by Google and has also been adopted by Spark as a generic programming interface for iterative graph computations. In this chapter, you will understand the Pregel model of computation. In addition, our learning goal is to clarify both the interface and implementation of the Pregel operator in Spark. After working through the concrete examples, you will be able to formulate your own algorithms with the Pregel interface.