Graph Algorithms: Practical Examples in Apache Spark and Neo4j

Amy Hodler, Mark Needham

Graph Algorithms: Practical Examples in Apache Spark and Neo4j

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商品描述

Discover how graph algorithms can help you leverage the relationships within your data to create novel inventions and develop more intelligent solutions faster. You’ll learn how graph analytics are uniquely suited to unfold complex structures and surface relationships as well as why this is leading to an explosion of graph applications. Whether you are trying to build network models or predict dynamic behavior, this book illustrates how graph algorithms can be used to uncover routes, model flows and estimate resiliency.

With an emphasis on practical uses, you’ll see how to approach implementing graph algorithms in Apache Spark and Neo4j—two of the most common choices for graph analytics. In this book, we’ll include sample code and tips for over 15 of the most significant algorithms that cover pathfinding, centrality and community detection.

  • Find out how graph analytics is different from common statistical analysis
  • Understand the uses of graph algorithms and whether you have a graph analytics challenge
  • Learn about various graph processing approaches and challenges
  • Find out how common graph algorithms work and how they are applied
  • Obtain guidance on which algorithms to use for different types of questions or data
  • Explore examples with working code and sample datasets for both Spark and Neo4j

商品描述(中文翻譯)

發現圖形演算法如何幫助您利用數據中的關係創造新穎的發明，並更快地開發更智能的解決方案。您將學習圖形分析如何獨特地適合展開複雜結構和揭示關係，以及為什麼這導致了圖形應用的爆炸。無論您是嘗試建立網絡模型還是預測動態行為，本書都將演示如何使用圖形演算法來發現路徑、建模流程和估計彈性。

本書著重於實際應用，您將看到如何在Apache Spark和Neo4j中實施圖形演算法，這兩者是圖形分析的最常見選擇。在本書中，我們將提供超過15個最重要的演算法的示例代碼和技巧，涵蓋了路徑查找、中心性和社區檢測等領域。


  • 了解圖形分析與常見統計分析的不同之處

  • 了解圖形演算法的用途以及您是否面臨圖形分析的挑戰

  • 了解各種圖形處理方法和挑戰

  • 了解常見圖形演算法的工作原理和應用方式

  • 獲得有關在不同類型問題或數據中使用哪些演算法的指導

  • 探索使用Spark和Neo4j的工作代碼和示例數據集的示例

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