In summary, Pregel is a generic and simplified interface for writing custom iterative, and parallel algorithms on large graphs. In this chapter, we have seen how to implement different iterative graph processing using this simple abstraction. In the next chapter, we will see how to use Spark's MLlib and GraphX to solve some machine learning problems with graph data.
Apache Spark Graph Processing
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
Free Chapter
Getting Started with Spark and GraphX
Building and Exploring Graphs
Graph Analysis and Visualization
Transforming and Shaping Up Graphs to Your Needs
Creating Custom Graph Aggregation Operators
Iterative Graph-Parallel Processing with Pregel
Learning Graph Structures
References
Index
Customer Reviews