Many practical computing problems concern large graphs, like the Web graph and various social networks. In Detail Apache Spark is the next standard of open-source cluster-computing engine for processing big data. Develop iterative and efficient graph algorithms using message aggregation and Pregel abstraction Extract subgraphs and use it to discover common clusters Analyze graph data and solve various data science problems using real-world datasets. Build and analyze large-scale network datasets Analyze and transform graphs using RDD and graph-specific operations Implement new custom graph operations tailored to specific needs. What You Will Learn Write, build and deploy Spark applications with the Scala Build Tool. Basic programming experience with Scala is assumed. Who This Book Is For This book is for data scientists and big data developers who want to learn the processing and analyzing graph datasets at scale. A concise guide to processing large-scale networks with Apache Spark. Build, process and analyze large-scale graph data effectively with Spark About This Book Find solutions for every stage of data processing from loading and transforming graph data to Improve the scalability of your graphs with a variety of real-world applications with complete Scala code.
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