Hadoop MapReduce Cookbook

Hadoop_MapReduce_CookbookHadoop MapReduce Cookbook

Recipes for analyzing large and complex data sets with Hadoop MapReduce

  • Learn to process large and complex data sets, starting simply, then diving in deep
  • Solve complex big data problems such as classifications, finding relationships, online marketing and recommendations
  • More than 50 Hadoop MapReduce recipes, presented in a simple and straightforward manner, with step-by-step instructions and real world examples

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.

Book Details

Hadoop MapReduce Cookbook

  • By: 
  • Publisher: Packt Publishing
  • Pub. Date: 
  • Print ISBN-13: 978-1-84951-728-7
  • Pages in Print Edition: 300
  • File Size : 2.59 MB
  • Format : PDF

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