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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

Overview of Hive


Hive is a data warehouse that uses MapReduce to analyze data stored on HDFS. In particular, it provides a query language called HiveQL that closely resembles the common Structured Query Language (SQL) standard.

Why use Hive?

In Chapter 4, Developing MapReduce Programs, we introduced Hadoop Streaming and explained that one large benefit of Streaming is how it allows faster turn-around in the development of MapReduce jobs. Hive takes this a step further. Instead of providing a way of more quickly developing map and reduce tasks, it offers a query language based on the industry standard SQL. Hive takes these HiveQL statements and immediately and automatically translates the queries into one or more MapReduce jobs. It then executes the overall MapReduce program and returns the results to the user. Whereas Hadoop Streaming reduces the required code/compile/submit cycle, Hive removes it entirely and instead only requires the composition of HiveQL statements.

This interface to Hadoop...

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