{"product_id":"guide-to-high-performance-distributed-computing-case-studies-with-hadoop-scalding-and-spark-9783319383477","title":"Guide to High Performance Distributed Computing: Case Studies with Hadoop, Scalding and Spark","description":"\u003cp\u003e • Author(s): K. G. Srinivasa\u003cbr\u003e • Publisher: Springer\u003cbr\u003e • Publisher Imprint: Springer\u003cbr\u003e • BISAC: Distributed Systems - Client-Server Computing\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eFrom the Back Cover\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eThis timely text\/reference describes the development and implementation of large-scale distributed processing systems using open source tools and technologies such as Hadoop, Scalding and Spark.\u003c\/p\u003e\u003cp\u003eComprehensive in scope, the book presents state-of-the-art material on building high performance distributed computing systems, providing practical guidance and best practices as well as describing theoretical software frameworks.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eTopics and features: \u003c\/b\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eDescribes the fundamentals of building scalable software systems for large-scale data processing in the new paradigm of high performance distributed computing\u003c\/li\u003e\n\u003cli\u003ePresents an overview of the Hadoop ecosystem, followed by step-by-step instruction on its installation, programming and execution\u003c\/li\u003e\n\u003cli\u003eReviews the basics of Spark, including resilient distributed datasets, and examines Hadoop streaming and working with Scalding\u003c\/li\u003e\n\u003cli\u003eProvides detailed case studies on approaches to clustering, data classification and regression analysis\u003c\/li\u003e\n\u003cli\u003eExplains the process of creating a working recommender system using Scalding and Spark\u003c\/li\u003e\n\u003cli\u003eSupplies a complete list of supplementary source code and datasets at an associated website\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFulfilling the need for both introductory material for undergraduate students of computer science and detailed discussions for software engineering professionals, this book will aid a broad audience to understand the esoteric aspects of practical high performance computing through its use of solved problems, research case studies and working source code.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eK.G. Srinivasa\u003c\/b\u003e is Professor and Head of the Department of Computer Science and Engineering at M.S. Ramaiah Institute of Technology (MSRIT), Bangalore, India. His other publications include the Springer title \u003ci\u003eSoft Computing for Data Mining Applications\u003c\/i\u003e. \u003cb\u003eAnil Kumar Muppalla\u003c\/b\u003e is also a researcher at MSRIT.\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Paperback","offer_id":45277054533783,"sku":"9783319383477","price":3639.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9783319383477.webp?v=1769287362","url":"https:\/\/atlanticbooks.com\/products\/guide-to-high-performance-distributed-computing-case-studies-with-hadoop-scalding-and-spark-9783319383477","provider":"Atlantic Books","version":"1.0","type":"link"}