Master programming with Hadoop MapReduce in an Instant using Packt's new eBook
Submitted by: Packt Publishing
2013-08-01 00:01:55
Practical recipes to write your own MapReduce solution patterns for Hadoop programs
Birmingham, AL (OPENPRESS) Packt is pleased to announce the release of Instant MapReduce Patterns — Hadoop Essentials How-to, a concise guide to Hadoop and programming with MapReduce. The book is available now in all the popular eBook formats.
About the Author:
Srinath Perera is a senior software architect at WSO2 Inc., where he oversees the overall WSO2 platform architecture with the CTO. He also serves as a research scientist at Lanka Software Foundation and teaches as a visiting faculty member at the Department of Computer Science and Engineering, University of Moratuwa. He is a co-founder of the Apache Axis2 open source project, and he has been involved with the Apache Web Service project since 2002 and is a member of the Apache Software foundation and Apache Web Service project PMC. Srinath also teaches a parallel programming graduate class at University of Moratuwa, which is primarily based on Hadoop.
Hadoop MapReduce is a software framework for easily writing applications that process vast amounts of data (multi-terabyte data-sets) in-parallel on large clusters (thousands of nodes) of commodity hardware in a reliable, fault-tolerant way.
Instant MapReduce Patterns — Hadoop Essentials How-to will give readers an introduction to programming with Hadoop, helping them to understand and solve any potential MapReduce problems. It starts by explaining the configuration of Hadoop, before moving on to writing simple examples and discussing MapReduce programming patterns.
The book starts by guiding the reader through installing Hadoop and writing a word count program. Moving forward it explains the seven styles of MapReduce programs: analytics, set operations, cross correlation, search, graph, joins, and clustering. In each case, readers will learn the pattern and create a representative example program. The book also features additional pointers to further enhance Hadoop skills.
This book will be useful for big data enthusiasts and would-be Hadoop programmers. It is also aimed at Java programmers who have either not worked with Hadoop at all, or who know Hadoop and MapReduce but are not sure on the best way to deepen their understanding. More information about the book on the Packt book web-page.
