Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Hadoop Beginner's Guide

You're reading from   Hadoop Beginner's Guide Get your mountain of data under control with Hadoop. This guide requires no prior knowledge of the software or cloud services – just a willingness to learn the basics from this practical step-by-step tutorial.

Arrow left icon
Product type Paperback
Published in Feb 2013
Publisher Packt
ISBN-13 9781849517300
Length 398 pages
Edition 1st Edition
Tools
Arrow right icon
Toc

Table of Contents (19) Chapters Close

Hadoop Beginner's Guide
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. What It's All About 2. Getting Hadoop Up and Running FREE CHAPTER 3. Understanding MapReduce 4. Developing MapReduce Programs 5. Advanced MapReduce Techniques 6. When Things Break 7. Keeping Things Running 8. A Relational View on Data with Hive 9. Working with Relational Databases 10. Data Collection with Flume 11. Where to Go Next Pop Quiz Answers Index

A note on EMR


One of the main benefits of using cloud services such as those offered by Amazon Web Services is that much of the maintenance overhead is borne by the service provider. Elastic MapReduce can create Hadoop clusters tied to the execution of a single task (non-persistent job flows) or allow long-running clusters that can be used for multiple jobs (persistent job flows). When non-persistent job flows are used, the actual mechanics of how the underlying Hadoop cluster is configured and run are largely invisible to the user. Consequently, users employing non-persistent job flows will not need to consider many of the topics in this chapter. If you are using EMR with persistent job flows, many topics (but not all) do become relevant.

We will generally talk about local Hadoop clusters in this chapter. If you need to reconfigure a persistent job flow, use the same Hadoop properties but set them as described in Chapter 3, Writing MapReduce Jobs.

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image