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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


Hadoop is made of the compute and storage layers. The compute layer has been replaced by YARN in Hadoop 2.X, helping other paradigms to co-exist on the Hadoop cluster hardware. The storage layer is making rapid progress towards a similar goal. Features such as HDFS Federation are one step closer in making the storage layer generic. By loosely coupling Block Storage from the Namespace, this can become a reality soon.

The key takeaways from this chapter are as follows:

  • With HDFS Federation, it is possible to run multiple NameNodes. This not only helps in isolation, but it can also aid in performance by load balancing. Horizontal scaling of the NameNode is easier.

  • Block pools are the abstractions that facilitate federation. Blocks from a single Namespace belong to a single pool. Each pool is given an identifier for addressability. The DataNodes remain shared among the different NameNodes.

  • In Hadoop 2.X, there are a number of different options to ensure NameNode recovery from failures. Secondary...

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