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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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Toc

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

Avro serialization


Avro is a popular data serialization framework that is part of Apache Software Foundation. Its key features are as follows:

  • It supports a number of data structures for serialization.

  • It is neutral to particular programming languages and provides fast and compact binary serialization.

  • Code generation is optional in Avro. Data can be read, written, or used in RPCs without having to generate classes or code.

Avro uses schemas during the reading and writing of data. Schemas make the compact representation of the serialized object conducive. The self-describing capability of schemas makes it possible to get rid of object-type metadata to be present along with the serialized byte stream, the method used in Java serialization. The schemas are described in the Javascript Object Notation (JSON) format that has evolved as a popular object description notation on the Web. Schema changes can be handled by having both the old and new schema available when processing data.

The following...

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