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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

Getting data into Hadoop


Now that we have put in all that up-front effort, let us look at ways of bringing the data out of MySQL and into Hadoop.

Using MySQL tools and manual import

The simplest way to export data into Hadoop is to use existing command-line tools and statements. To export an entire table (or indeed an entire database), MySQL offers the mysqldump utility. To do a more precise export, we can use a SELECT statement of the following form:

SELECT col1, col2 from table
INTO OUTFILE '/tmp/out.csv'
FIELDS TERMINATED by ',', LINES TERMINATED BY '\n';

Once we have an export file, we can move it into HDFS using hadoop fs -put or into Hive through the methods discussed in the previous chapter.

Have a go hero – exporting the employee table into HDFS

We don't want this chapter to turn into a MySQL tutorial, so look up the syntax of the mysqldump utility, and use it or the SELECT … INTO OUTFILE statement to export the employee table into a tab-separated file you then copy onto HDFS.

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