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

Using languages other than Java with Hadoop


We have mentioned previously that MapReduce programs don't have to be written in Java. Most programs are written in Java, but there are several reasons why you may want or need to write your map and reduce tasks in another language. Perhaps you have existing code to leverage or need to use third-party binaries—the reasons are varied and valid.

Hadoop provides a number of mechanisms to aid non-Java development, primary amongst these are Hadoop Pipes that provides a native C++ interface to Hadoop and Hadoop Streaming that allows any program that uses standard input and output to be used for map and reduce tasks. We will use Hadoop Streaming heavily in this chapter.

How Hadoop Streaming works

With the MapReduce Java API, both map and reduce tasks provide implementations for methods that contain the task functionality. These methods receive the input to the task as method arguments and then output results via the Context object. This is a clear and...