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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

Summary


In this chapter, we have looked at the integration of Hadoop and relational databases. In particular, we explored the most common use cases and saw that Hadoop and relational databases can be highly complimentary technologies. We considered ways of exporting data from a relational database onto HDFS files and realized that issues such as primary key column partitioning and long-running tasks make it harder than it first seems.

We then introduced Sqoop, a Cloudera tool now donated to the Apache Software Foundation and that provides a framework for such data migration. We used Sqoop to import data from MySQL into HDFS and then Hive, highlighting how we must consider aspects of datatype compatibility in such tasks. We also used Sqoop to do the reverse—copying data from HDFS into a MySQL database—and found out that this path has more subtle considerations than the other direction, briefly discussed issues of file formats and update versus insert tasks, and introduced additional Sqoop...

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