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HBase High Performance Cookbook

You're reading from   HBase High Performance Cookbook Solutions for optimization, scaling and performance tuning

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Product type Paperback
Published in Jan 2017
Publisher Packt
ISBN-13 9781783983063
Length 350 pages
Edition 1st Edition
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Author (1):
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Ruchir Choudhry Ruchir Choudhry
Author Profile Icon Ruchir Choudhry
Ruchir Choudhry
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Toc

Table of Contents (13) Chapters Close

Preface 1. Configuring HBase 2. Loading Data from Various DBs FREE CHAPTER 3. Working with Large Distributed Systems Part I 4. Working with Large Distributed Systems Part II 5. Working with Scalable Structure of tables 6. HBase Clients 7. Large-Scale MapReduce 8. HBase Performance Tuning 9. Performing Advanced Tasks on HBase 10. Optimizing Hbase for Cloud 11. Case Study Index

Snappy

Snappy is a library that uses very effective algorithms for compression and decompression of data. However, the goal is not to maximize compression or compatibility with other compression libraries but to focus on speed and reusable compression. HBase supports different compression mechanisms such as lzo, gzip, or snappy. Gzip comes built in with HBase while lzo/snappy compression needs to be configured separately. When creating a table, you can specify the compression/compression library; HFiles are compressed when written to disk if compression is used.

How to do it…

  1. Let's log in to our HBase setup.
  2. Once you log in, check the file on this location:
    /opt/HbaseB/ hbase-0.98.5-hadoop2/snappy-1.0.5/libs/snappy-java-1.0.4.1.jar → this has a JNL interface to the libsnappy.so.1.x.x which is a native linux-amd64-64 bit lib. 
    
  3. Once you have verified the path and the JAR file, let's do a quick test to make sure the library is performing as expected:
    $ hbase org.apache...
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