Guide to High Performance Distributed Computing - Case Studies with Hadoop, Scalding and Spark (Hardcover, 2015 ed.)

This timely text/reference describes the development and implementation of large-scale distributed processing systems using open source tools and technologies. Comprehensive 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. Features: describes the fundamentals of building scalable software systems for large-scale data processing in the new paradigm of high performance distributed computing; presents an overview of the Hadoop ecosystem, followed by step-by-step instruction on its installation, programming and execution; Reviews the basics of Spark, including resilient distributed datasets, and examines Hadoop streaming and working with Scalding; Provides detailed case studies on approaches to clustering, data classification and regression analysis; Explains the process of creating a working recommender system using Scalding and Spark.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Computer Communications and Networks
Release date:	March 2015
First published:	2015
Authors:	K.G. Srinivasa • Anil Kumar Muppalla
Dimensions:	235 x 155 x 23mm (L x W x T)
Format:	Hardcover
Pages:	304
Edition:	2015 ed.
ISBN-13:	978-3-319-13496-3
Categories:	Books > Computing & IT > Computer programming > General Books > Computing & IT > Computer communications & networking > General Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-319-13496-5
Barcode:	9783319134963

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