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Mastering Hadoop

You're reading from   Mastering Hadoop Go beyond the basics and master the next generation of Hadoop data processing platforms

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Product type Paperback
Published in Dec 2014
Publisher
ISBN-13 9781783983643
Length 374 pages
Edition 1st Edition
Tools
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Author (1):
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Sandeep Karanth Sandeep Karanth
Author Profile Icon Sandeep Karanth
Sandeep Karanth
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Table of Contents (15) Chapters Close

Preface 1. Hadoop 2.X FREE CHAPTER 2. Advanced MapReduce 3. Advanced Pig 4. Advanced Hive 5. Serialization and Hadoop I/O 6. YARN – Bringing Other Paradigms to Hadoop 7. Storm on YARN – Low Latency Processing in Hadoop 8. Hadoop on the Cloud 9. HDFS Replacements 10. HDFS Federation 11. Hadoop Security 12. Analytics Using Hadoop A. Hadoop for Microsoft Windows Index

Amazon Elastic MapReduce (EMR)

Amazon AWS offers Hadoop as a PaaS. Organizations and individuals can provision Hadoop clusters on the fly, run their workloads, and download results. Provisioning a Hadoop cluster using EMR takes a few minutes and is a few clicks away.

Note

Usage of any Amazon Web Service requires an Amazon account. Visit http://aws.amazon.com and register for a free account. A credit card is mandatory to register for an Amazon account. However, it will be charged only on usage beyond the free tier offered by Amazon. The registered e-mail is subsequently used as the username.

The general steps to create and run workloads on EMR are as follows:

  1. The application is developed locally in Java using Hadoop's MapReduce APIs, Hive, Pig, or a language of the user's choice. Non-Java-based languages can be executed in a Hadoop cluster using Hadoop Streaming. A developer guide can be found at http://docs.aws.amazon.com/ElasticMapReduce/latest/DeveloperGuide/emr-what-is-emr.html...
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