Learn how to use Hadoop MapReduce to analyze large and complex datasets with this comprehensive cookbook. Over fifty recipes with step-by-step instructions quickly take your Hadoop skills to the next level.
Overview
In Detail
We are facing an avalanche of data. The unstructured data we gather can contain many insights that might hold the key to business success or failure. Harnessing the ability to analyze and process this data with Hadoop MapReduce is one of the most highly sought after skills in today's job market.
"Hadoop MapReduce Cookbook" is a one-stop guide to processing large and complex data sets using the Hadoop ecosystem. The book introduces you to simple examples and then dives deep to solve in-depth big data use cases.
"Hadoop MapReduce Cookbook" presents more than 50 ready-to-use Hadoop MapReduce recipes in a simple and straightforward manner, with step-by-step instructions and real world examples.
Start with how to install, then configure, extend, and administer Hadoop. Then write simple examples, learn MapReduce patterns, harness the Hadoop landscape, and finally jump to the cloud.
The book deals with many exciting topics such as setting up Hadoop security, using MapReduce to solve analytics, classifications, on-line marketing, recommendations, and searching use cases. You will learn how to harness components from the Hadoop ecosystem including HBase, Hadoop, Pig, and Mahout, then learn how to set up cloud environments to perform Hadoop MapReduce computations.
"Hadoop MapReduce Cookbook" teaches you how process large and complex data sets using real examples providing a comprehensive guide to get things done using Hadoop MapReduce.
What you will learn from this book
Approach
Individual self-contained code recipes. Solve specific problems using individual recipes, or work through the book to develop your capabilities.
Who this book is written for
If you are a big data enthusiast and striving to use Hadoop to solve your problems, this book is for you. Aimed at Java programmers with some knowledge of Hadoop MapReduce, this is also a comprehensive reference for developers and system admins who want to get up to speed using Hadoop.
"synopsis" may belong to another edition of this title.
Individual self-contained code recipes. Solve specific problems using individual recipes, or work through the book to develop your capabilities. If you are a big data enthusiast and striving to use Hadoop to solve your problems, this book is for you. Aimed at Java programmers with some knowledge of Hadoop MapReduce, this is also a comprehensive reference for developers and system admins who want to get up to speed using Hadoop.
Srinath Perera.
Srinath Perera is a Senior Software Architect at WSO2 Inc., where he overlooks 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 at Department of Computer Science and Engineering, University of Moratuwa. He is a co-founder of Apache Axis2 open source project, and he has been involved with the Apache Web Service project since 2002, and is a member of Apache Software foundation and Apache Web Service project PMC. Srinath is also a committer of Apache open source projects Axis, Axis2, and Geronimo.
He received his Ph.D. and M.Sc. in Computer Sciences from Indiana University, Bloomington, USA and received his Bachelor of Science in Computer Science and Engineering from University of Moratuwa, Sri Lanka.
Srinath has authored many technical and peer reviewed research articles, and more detail can be found from his website. He is also a frequent speaker at technical venues.
He has worked with large-scale distributed systems for a long time. He closely works with Big Data technologies, such as Hadoop and Cassandra daily. He also teaches a parallel programming graduate class at University of Moratuwa, which is primarily based on Hadoop.
"About this title" may belong to another edition of this title.
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