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

Time for action – running WordCount on EMR


We will now show you how to run this same JAR file on EMR. Remember, as always, that this costs money!

  1. Go to the AWS console at http://aws.amazon.com/console, sign in, and select S3.

  2. You'll need two buckets: one to hold the JAR file and another for the job output. You can use existing buckets or create new ones.

  3. Open the bucket where you will store the job file, click on Upload, and add the wc1.jar file created earlier.

  4. Return to the main console home page, and then go to the EMR portion of the console by selecting Elastic MapReduce.

  5. Click on the Create a New Job Flow button and you'll see a familiar screen as shown in the following screenshot:

  6. Previously, we used a sample application; to run our code, we need to perform different steps. Firstly, select the Run your own application radio button.

  7. In the Select a Job Type combobox, select Custom JAR.

  8. Click on the Continue button and you'll see a new form, as shown in the following screenshot:

We now specify...