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Apache Spark Graph Processing

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Apache Spark Graph Processing

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Apache Spark Graph Processing
Sep, 2015 | 148 pages
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Table of Contents (16 chapters)
Apache Spark Graph Processing
Apache Spark Graph Processing
Credits
Credits
Foreword
Foreword
About the Author
About the Author
About the Reviewer
About the Reviewer
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Getting Started with Spark and GraphX
Getting Started with Spark and GraphX
Downloading and installing Spark 1.4.1
Experimenting with the Spark shell
Getting started with GraphX
Summary
2
Building and Exploring Graphs
Building and Exploring Graphs
Network datasets
Graph builders
Building graphs
Computing the degrees of the network nodes
Summary
3
Graph Analysis and Visualization
Graph Analysis and Visualization
Network datasets
The graph visualization
The analysis of network connectedness
The network centrality and PageRank
Scala Build Tool revisited
Summary
4
Transforming and Shaping Up Graphs to Your Needs
Transforming and Shaping Up Graphs to Your Needs
Transforming the vertex and edge attributes
Modifying graph structures
Joining graph datasets
Data operations on VertexRDD and EdgeRDD
Summary
5
Creating Custom Graph Aggregation Operators
Creating Custom Graph Aggregation Operators
NCAA College Basketball datasets
The aggregateMessages operator
Joining average stats into a graph
Performance optimization
The MapReduceTriplets operator
Summary
6
Iterative Graph-Parallel Processing with Pregel
Iterative Graph-Parallel Processing with Pregel
The Pregel computational model
The Pregel API in GraphX
Community detection through label propagation
The Pregel implementation of PageRank
Summary
7
Learning Graph Structures
Learning Graph Structures
Community clustering in graphs
Applications – music fan community detection
Summary
References
References
Chapter 2, Building and Exploring Graphs
Chapter 3, Graph Analysis and Visualization
Chapter 7, Learning Graph Structures
Index
Index

Chapter 7, Learning Graph Structures

Lin, F. and Cohen W. W. (2010) Power Iteration Clustering, in Johannes Fürnkranz and Thorsten Joachims, ed., ICML, Omnipress, pp. 655-662.

Luxburg, U. von. A Tutorial on Spectral Clustering. Statistics and Computing 17(4): 395-416, 2007.

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