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


Hadoop performance tuning is a challenging task, mainly due to the distributed feature of the system. The sheer number of configuration properties can tell, from another perspective, how complicated it is to configure a Hadoop cluster. Many of the configuration parameters have an effect on the performance of the cluster. Sometimes, different settings of the properties can lead to dramatic performance differences. And some properties are more relevant and sensitive than others with regard to the performance of a Hadoop cluster.

A Hadoop cluster is composed of many components. A systematic way of performance tuning is to tune the components based on their contribution on the cluster performance. Most of the Big Data applications are I/O bound, so is Hadoop. So, configurations that are closely related to I/O requests should be the first priority for performance tuning. For example, suboptimal configuration on data replication properties can cause a large number of data block copies...