Book Image

Hadoop Beginner's Guide

Book Image

Hadoop Beginner's Guide

Overview of this book

Data is arriving faster than you can process it and the overall volumes keep growing at a rate that keeps you awake at night. Hadoop can help you tame the data beast. Effective use of Hadoop however requires a mixture of programming, design, and system administration skills."Hadoop Beginner's Guide" removes the mystery from Hadoop, presenting Hadoop and related technologies with a focus on building working systems and getting the job done, using cloud services to do so when it makes sense. From basic concepts and initial setup through developing applications and keeping the system running as the data grows, the book gives the understanding needed to effectively use Hadoop to solve real world problems.Starting with the basics of installing and configuring Hadoop, the book explains how to develop applications, maintain the system, and how to use additional products to integrate with other systems.While learning different ways to develop applications to run on Hadoop the book also covers tools such as Hive, Sqoop, and Flume that show how Hadoop can be integrated with relational databases and log collection.In addition to examples on Hadoop clusters on Ubuntu uses of cloud services such as Amazon, EC2 and Elastic MapReduce are covered.
Table of Contents (19 chapters)
Hadoop Beginner's Guide
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Summary


This chapter covered how to build, maintain, and expand a Hadoop cluster. In particular, we learned where to find the default values for Hadoop configuration properties and how to set them programmatically on a per-job level. We learned how to choose hardware for a cluster and the value in understanding your likely workload before committing to purchases, and how Hadoop can use awareness of the physical location of hosts to optimize its block placement strategy through the use of rack awareness.

We then saw how the default Hadoop security model works, its weaknesses and how to mitigate them, how to mitigate the risks of NameNode failure we introduced in Chapter 6, When Things Break, and how to swap to a new NameNode host if disaster strikes. We learned more about block replica placement, how the cluster can become unbalanced, and what to do if it does.

We also saw the Hadoop model for MapReduce job scheduling and learned how job priorities can modify the behavior, how the Capacity...