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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 ‚Äì just a willingness to learn the basics from this practical step-by-step tutorial.

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Product type Paperback
Published in Feb 2013
Publisher Packt
ISBN-13 9781849517300
Length 398 pages
Edition 1st Edition
Tools
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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 FREE CHAPTER 2. Getting Hadoop Up and Running 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

Chapter 3, Understanding MapReduce


Pop quiz – key/value pairs

Q1

2

Q2

3

Pop quiz – walking through a run of WordCount

Q1

1

Q2

3

Q3

2. Reducer C cannot be used because if such reduction were to occur, the final reducer could receive from the combiner a series of means with no knowledge of how many items were used to generate them, meaning the overall mean is impossible to calculate. Reducer D is subtle as the individual tasks of selecting a maximum or minimum are safe for use as combiner operations. But if the goal is to determine the overall variance between the maximum and minimum value for each key, this would not work. If the combiner that received the maximum key had values clustered around it, this would generate small results; similarly for the one receiving the minimum value. These subranges have little value in isolation and again the final reducer cannot construct the desired result.

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