Book Image

Hadoop Operations and Cluster Management Cookbook

By : Shumin Guo
Book Image

Hadoop Operations and Cluster Management Cookbook

By: Shumin Guo

Overview of this book

<p>We are facing an avalanche of data. The unstructured data we gather can contain many insights that could hold the key to business success or failure. Harnessing the ability to analyze and process this data with Hadoop is one of the most highly sought after skills in today's job market. Hadoop, by combining the computing and storage powers of a large number of commodity machines, solves this problem in an elegant way!</p> <p>Hadoop Operations and Cluster Management Cookbook is a practical and hands-on guide for designing and managing a Hadoop cluster. It will help you understand how Hadoop works and guide you through cluster management tasks.</p> <p>This book explains real-world, big data problems and the features of Hadoop that enables it to handle such problems. It breaks down the mystery of a Hadoop cluster and will guide you through a number of clear, practical recipes that will help you to manage a Hadoop cluster.</p> <p>We will start by installing and configuring a Hadoop cluster, while explaining hardware selection and networking considerations. We will also cover the topic of securing a Hadoop cluster with Kerberos, configuring cluster high availability and monitoring a cluster. And if you want to know how to build a Hadoop cluster on the Amazon EC2 cloud, then this is a book for you.</p>
Table of Contents (15 chapters)
Hadoop Operations and Cluster Management Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Introduction


Today, many organizations are facing the Big Data problem. Managing and processing Big Data can incur a lot of challenges for traditional data processing platforms such as relational database systems. Hadoop was designed to be a distributed and scalable system for dealing with Big Data problems.

The design, implementation, and deployment of a Big Data platform require a clear definition of the Big Data problem by system architects and administrators. A Hadoop-based Big Data platform uses Hadoop as the data storage and processing engine. It deals with the problem by transforming the Big Data input into the expected output. On one hand, the Big Data problem determines how the Big Data platform should be designed, for example, which modules or subsystems should be integrated into the platform and so on. On the other hand, the architectural design of the platform can determine complexity and efficiency of the platform.

Different Big Data problems have different properties. A Hadoop-based Big Data platform is capable of dealing with most of the Big Data problems, but might not be good fit for others. Because of these and many other reasons, we need to choose from Hadoop alternatives.