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

Hardware and software options


In this recipe, we will discuss the hardware and software option to take account of while considering the Hadoop cluster.

There are many vendors for hardware and software and the options can be overwhelming. But some important things which must be taken into account are as follows:

  1. Run benchmark tests on different hardware examples from HP, IBM, or Dell and compare them for the throughput per unit cost.

  2. What is the roadmap for the hardware you choose? How long will the vendor support it?

  3. Every year, the new hardware will be a better value for compute per unit. What will be the buyback strategy for the old hardware? Will the vendor take back the old hardware and give the new hardware at discounted rates?

  4. Does the hardware have tightly coupled components, which could be difficult to replace in isolation?

  5. What software options does the user have in terms of vendors? Should we go for HDP, Cloudera, or Mapr distribution or use the Apache Hadoop distribution.

  6. Total cost...