Hadoop Essentials: A Quantitative Approach

Writer: Henry H
Published: 31 October 2012

This textbook works with the latest Hadoop stable release of 1.0.4. It adopts a unique approach to helping developers and CS students learn Hadoop MapReduce programming fast. Rather than filled with disjointed, piecemeal code snippets to show Hadoop MapReduce programming features one at a time, it is designed to place your total Hadoop MapReduce programming learning process in a common application context of mining customer spending patterns ensconced in large volumes of credit card transaction record data. Precise, end-to-end procedures are given to help you set up your Hadoop MapReduce development environment quickly on Eclipse with Maven on Mac OS X or Linux. Step-by-step procedures are also given on how to set up a four-node Linux cluster at minimum so that you can run your MapReduce programs not only in local mode but also in fully distributed mode on a real cluster. In fact, all MapReduce programs presented in the book have been tested and verified in local mode and on such a Linux cluster.

This textbook mainly focuses on teaching Hadoop MapReduce programming in a scientific, objective, quantitative approach. Rather than heavily relying on subjective, verbose (and sometimes even pompous) textual descriptions with sparse code snippets, this textbook uses Hadoop Java APIs, Hadoop configuration parameters, complete MapReduce programs and their execution logs and outputs to demonstrate how Hadoop MapReduce framework works and how to write MapReduce programs.

Pages: 356
ISBN: 1480216372
ISBN-13: 978-1480216372
Language: English
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