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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

File formats


There are a number of file formats that are data structures by themselves. In the chapter on Hive, we saw ORC files, an optimized form of record columnar file storage. There are a few other popular file container formats supported by Hadoop. We will look at them in this section.

The Sequence file format

A Sequence file is a container format for binary key-value pairs. Each record in a Sequence file contains a key and its associated value. Sequence files are used to combine smaller files into a single large file to alleviate the small file problem in Hadoop. In this situation, the filename forms the key and the file contents are the values associated with the key. Sequence files have a broader applicability as they can be split into configurable blocks. They can be combined with fast compression methods such as LZO or Snappy and can provide speed as well as storage and bandwidth.

The next image shows the format of a Sequence file. The start of the file has a magic number, a binary...

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