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


This chapter discussed the problem of how to retrieve data from across the network and make it available for processing in Hadoop. As we saw, this is actually a more general challenge and though we may use Hadoop-specific tools, such as Flume, the principles are not unique. In particular, we covered an overview of the types of data we may want to write to Hadoop, generally categorizing it as network or file data. We explored some approaches for such retrieval using existing command-line tools. Though functional, the approaches lacked sophistication and did not suit extension into more complex scenarios.

We looked at Flume as a flexible framework for defining and managing data (particularly from log files) routing and delivery, and learned the Flume architecture which sees data arrive at sources, be processed through channels, and then written to sinks.

We then explored many of Flume's capabilities such as how to use the different types of sources, sinks, and channels. We saw how the...