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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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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

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

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