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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
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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

Summary

Cloud is a cost-efficient and effective way of developing pre-operationalized analytics. The self-serve, pay-as-you-go, and elastic deployment features of the cloud are reasons for the cost benefits. Many companies such as Yelp and Netflix run massive analytic workloads using the cloud infrastructure. Apache Hadoop is available as a PaaS offering on all major cloud service providers.

Some key takeaways from this chapter are as follows:

  • Amazon's Hadoop offering is called Elastic MapReduce (EMR), and it has been around since 2009. Microsoft launched its Hadoop offering in 2012, which is known as HDInsight on Microsoft Azure.
  • Using an AWS account, a Hadoop cluster can be launched in a matter of minutes. The number of EC2 instances in the Hadoop cluster is currently limited to 20. For more instances, a special request needs to be mailed to Amazon. Here's a word of caution for you: remember to terminate your Hadoop EMR cluster after use. If this is not done, charges will be incurred...
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