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

Chapter 4. Developing MapReduce Programs

Now that we have explored the technology of MapReduce, we will spend this chapter looking at how to put it to use. In particular, we will take a more substantial dataset and look at ways to approach its analysis by using the tools provided by MapReduce.

In this chapter we will cover the following topics:

  • Hadoop Streaming and its uses

  • The UFO sighting dataset

  • Using Streaming as a development/debugging tool

  • Using multiple mappers in a single job

  • Efficiently sharing utility files and data across the cluster

  • Reporting job and task status and log information useful for debugging

Throughout this chapter, the goal is to introduce both concrete tools and ideas about how to approach the analysis of a new data set. We shall start by looking at how to use scripting programming languages to aid MapReduce prototyping and initial analysis. Though it may seem strange to learn the Java API in the previous chapter and immediately move to different languages, our goal here...