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

Configuring JVM Reuse


MapReduce tasks are executed by JVM processes/threads, which are forked by the TaskTracker. The creation of a JVM, which includes the initialization of execution environments, is costly, especially when the number of tasks is large. In the default configuration, the number of JVMs needed to finish a job should be equal to the number of the tasks. In other words, the default setting uses one JVM to execute one task. When the execution of a task completes, its JVM will be killed by the TaskTracker.

JVM Reuse is an optimization of reusing JVMs for multiple tasks. If it is enabled, multiple tasks can be executed sequentially with one JVM.

In this recipe we will outline the steps to configure JVM Reuse.

Getting ready

We assume that the Hadoop cluster has been properly configured and all the daemons are running without any issues.

Log in from the Hadoop cluster administrator machine to the cluster master node using the following command:

ssh hduser@master

How to do it...

Use the...