Book Image

Hadoop 2.x Administration Cookbook

By : Aman Singh
Book Image

Hadoop 2.x Administration Cookbook

By: Aman Singh

Overview of this book

Hadoop enables the distributed storage and processing of large datasets across clusters of computers. Learning how to administer Hadoop is crucial to exploit its unique features. With this book, you will be able to overcome common problems encountered in Hadoop administration. The book begins with laying the foundation by showing you the steps needed to set up a Hadoop cluster and its various nodes. You will get a better understanding of how to maintain Hadoop cluster, especially on the HDFS layer and using YARN and MapReduce. Further on, you will explore durability and high availability of a Hadoop cluster. You’ll get a better understanding of the schedulers in Hadoop and how to configure and use them for your tasks. You will also get hands-on experience with the backup and recovery options and the performance tuning aspects of Hadoop. Finally, you will get a better understanding of troubleshooting, diagnostics, and best practices in Hadoop administration. By the end of this book, you will have a proper understanding of working with Hadoop clusters and will also be able to secure, encrypt it, and configure auditing for your Hadoop clusters.
Table of Contents (20 chapters)
Hadoop 2.x Administration Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Index

Introduction


In this chapter, we will look at cluster planning and some of the important aspects of cluster utilization.

Although this is a recipe book, it is good to have an understanding on the Hadoop cluster layout, network components, operating system, disk arrangements, and memory. We will try to cover some of the fundamental concepts on cluster planning and a few formulas to estimate the cluster size.

Let's say we are ready with our big data initiative and want to take the plunge into the Hadoop world. The first few of the primary concerns is what size cluster do we need? How many nodes and what configurations? What will be the roadmap in terms of the software/application stack, what will be the initial investment? What hardware to choose, whether to go with the vanilla Hadoop distribution or to go with vendor-specific Hadoop distributions.

There are no straightforward answers to these or any magic formulas. Many times, these decisions are influenced by market statistics, or by an organizational...