Hadoop MapReduce CookBook - Big Data Hadoop Book PDF
Recipes for analyzing large and complex datasets with Hadoop MarReduce
"Hadoop MapReduce Cookbook helps readers learn to process large and complex datasets. The book starts in a simple manner, but still provides in-depth knowledge of Hadoop. It is a simple one-stop guide on how to get things done. It has 90 recipes, presented in a simple and straightforward manner, with step-by-step instructions and real world examples."
Who this book is for?
"For big data enthusiasts and would be Hadoop programmers. The books for Java programmers who either have not worked with Hadoop at all, or who knows Hadoop and MapReduce but want to try out things and get into details. It is also a one-stop reference for most of your Hadoop tasks."
What you will learn from this book:
1 - Getting Hadoop Up and Running in a Cluster, explains how to install and run Hadoop both as a single node as well as a cluster.
2 - Advanced HDFS, introduces a set of advanced HDFS operations that would be useful when performing large-scale data processing with Hadoop MapReduce as well as with non-MapReduce use cases.
3 - Advanced Hadoop MapReduce Administration, explains how to change configurations and security of a Hadoop installation and how tu debug.
4 - Developing Complex Hadoop MapReduce Applications, introduces you to several advanced Hadoop MapReduce features that will help you to develop highly customized, efficient Mapreduce applications.
5 - Hadoop Ecosystem, introduces the other projects related to Hadoop such HBase, Hive, and Pig.
6 - Analytics, explains how to calculate basic analytics using Hadoop.
7 - Searching and Indexing, introduces you to several tools and techniques that you can use with Apache Hadoop to perform large-scale searching and indexing.
8 - Classifications, Recommendations, and Finding Relationships, explains how to implement complex algorithms such as classifications, recommendations, and finding relationships using Hadoop.
9 - Mass Text Data Processing, explains how to use Hadoop and Mahout to process large text datasets, and how to perform data preprocessing and loading operations using Hadoop.
10 - Cloud Deployments: Using Hadoop on Clouds, explains how to use Amazon Elastic MapReduce (EMR) and Apache Whirr to deploy and execute Hadoop MapReduce, Pig, Hive, and HBase computations on cloud infrastructures.
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