Book Image

Hadoop Beginner's Guide

Book Image

Hadoop Beginner's Guide

Overview of this book

Data is arriving faster than you can process it and the overall volumes keep growing at a rate that keeps you awake at night. Hadoop can help you tame the data beast. Effective use of Hadoop however requires a mixture of programming, design, and system administration skills."Hadoop Beginner's Guide" removes the mystery from Hadoop, presenting Hadoop and related technologies with a focus on building working systems and getting the job done, using cloud services to do so when it makes sense. From basic concepts and initial setup through developing applications and keeping the system running as the data grows, the book gives the understanding needed to effectively use Hadoop to solve real world problems.Starting with the basics of installing and configuring Hadoop, the book explains how to develop applications, maintain the system, and how to use additional products to integrate with other systems.While learning different ways to develop applications to run on Hadoop the book also covers tools such as Hive, Sqoop, and Flume that show how Hadoop can be integrated with relational databases and log collection.In addition to examples on Hadoop clusters on Ubuntu uses of cloud services such as Amazon, EC2 and Elastic MapReduce are covered.
Table of Contents (19 chapters)
Hadoop Beginner's Guide
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
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...