Cover; Copyright; Table of Contents; Preface; What's in This Book; Conventions Used in This Book; Using Code Examples; O'Reilly Online Learning; How to Contact Us; Acknowledgments; Foreword; Chapter 1. Introduction; What Are Graphs?; What Are Graph Analytics and Algorithms?; Graph Processing, Databases, Queries, and Algorithms; OLTP and OLAP; Why Should We Care About Graph Algorithms?; Graph Analytics Use Cases; Conclusion; Chapter 2. Graph Theory and Concepts; Terminology; Graph Types and Structures; Random, Small-World, Scale-Free Structures; Flavors of Graphs
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All Pairs Shortest Path with Apache SparkAll Pairs Shortest Path with Neo4j; Single Source Shortest Path; When Should I Use Single Source Shortest Path?; Single Source Shortest Path with Apache Spark; Single Source Shortest Path with Neo4j; Minimum Spanning Tree; When Should I Use Minimum Spanning Tree?; Minimum Spanning Tree with Neo4j; Random Walk; When Should I Use Random Walk?; Random Walk with Neo4j; Summary; Chapter 5. Centrality Algorithms; Example Graph Data: The Social Graph; Importing the Data into Apache Spark; Importing the Data into Neo4j; Degree Centrality; Reach
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Chapter 4. Pathfinding and Graph Search AlgorithmsExample Data: The Transport Graph; Importing the Data into Apache Spark; Importing the Data into Neo4j; Breadth First Search; Breadth First Search with Apache Spark; Depth First Search; Shortest Path; When Should I Use Shortest Path?; Shortest Path with Neo4j; Shortest Path (Weighted) with Neo4j; Shortest Path (Weighted) with Apache Spark; Shortest Path Variation: A*; Shortest Path Variation: Yen's k-Shortest Paths; All Pairs Shortest Path; A Closer Look at All Pairs Shortest Path; When Should I Use All Pairs Shortest Path?
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Connected Versus Disconnected GraphsUnweighted Graphs Versus Weighted Graphs; Undirected Graphs Versus Directed Graphs; Acyclic Graphs Versus Cyclic Graphs; Sparse Graphs Versus Dense Graphs; Monopartite, Bipartite, and k-Partite Graphs; Types of Graph Algorithms; Pathfinding; Centrality; Community Detection; Summary; Chapter 3. Graph Platforms and Processing; Graph Platform and Processing Considerations; Platform Considerations; Processing Considerations; Representative Platforms; Selecting Our Platform; Apache Spark; Neo4j Graph Platform; Summary
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When Should I Use Degree Centrality?Degree Centrality with Apache Spark; Closeness Centrality; When Should I Use Closeness Centrality?; Closeness Centrality with Apache Spark; Closeness Centrality with Neo4j; Closeness Centrality Variation: Wasserman and Faust; Closeness Centrality Variation: Harmonic Centrality; Betweenness Centrality; When Should I Use Betweenness Centrality?; Betweenness Centrality with Neo4j; Betweenness Centrality Variation: Randomized-Approximate Brandes; PageRank; Influence; The PageRank Formula; Iteration, Random Surfers, and Rank Sinks; When Should I Use PageRank?