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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.

Product type Paperback

Published in Feb 2013

Publisher Packt

ISBN-13 9781849517300

Length 398 pages

Edition 1st Edition

Tools

Hadoop

Concepts

Data Processing

Table of Contents (19) Chapters

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

Chapter 8. A Relational View on Data with Hive

MapReduce is a powerful paradigm which enables complex data processing that can reveal valuable insights. However, it does require a different mindset and some training and experience on the model of breaking processing analytics into a series of map and reduce steps. There are several products that are built atop Hadoop to provide higher-level or more familiar views on the data held within HDFS. This chapter will introduce one of the most popular of these tools, Hive .

In this chapter, we will cover:

What Hive is and why you may want to use it
How to install and configure Hive
Using Hive to perform SQL-like analysis of the UFO data set
How Hive can approximate common features of a relational database such as joins and views
How to efficiently use Hive across very large data sets
How Hive allows the incorporation of user-defined functions into its queries
How Hive complements another common tool, Pig

The rest of the chapter is locked

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