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Hadoop Essentials

You're reading from   Hadoop Essentials Delve into the key concepts of Hadoop and get a thorough understanding of the Hadoop ecosystem

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Product type Paperback
Published in Apr 2015
Publisher Packt
ISBN-13 9781784396688
Length 194 pages
Edition 1st Edition
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Author (1):
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Shiva Achari Shiva Achari
Author Profile Icon Shiva Achari
Shiva Achari
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Table of Contents (9) Chapters Close

Preface 1. Introduction to Big Data and Hadoop FREE CHAPTER 2. Hadoop Ecosystem 3. Pillars of Hadoop – HDFS, MapReduce, and YARN 4. Data Access Components – Hive and Pig 5. Storage Component – HBase 6. Data Ingestion in Hadoop – Sqoop and Flume 7. Streaming and Real-time Analysis – Storm and Spark Index

Compaction


In HBase, the MemStore in Regions creates many HFiles for a Column Family. This large number of files will require more time to read and hence, can impact the read performance. To improve the performance, HBase performs compaction to merge files in order to reduce their number and to keep the data manageable. The compaction process identifies the StoreFiles to merge by running an algorithm which is called compaction policy. There are two types of compactions: minor compactions and major compactions.

The Compaction policy

Compaction policy is the algorithm which can be used to select the StoreFiles for merging. Two policies are possible and the available ones are ExploringCompactionPolicy and RatioBasedCompactionPolicy. To set the policy algorithm, we have to set the value of the property hbase.hstore.defaultengine.compactionpolicy.class of hbase-site.xml. RatioBasedCompactionPolicy was available as the default policy prior to HBase 0.96 and is still available. ExploringCompactionPolicy...

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