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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 FREE CHAPTER 2. Loading Data from Various DBs 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

Read path

Hadoop design is based on the Sequence file format, which is used to append key/value pairs; this stems from the HDFS append-only capability.

This design is retrofitted by a concept of MapFiles and an extension of SequenceFile.

MapFile is nothing but a bundle of two Sequences Files in a directory. The first file is /data and the second is /index. This allows us to append key/value pairs and every N key; we can configure N as needed. This setup also allows us to store the key and the offset in the index. This gives us the flexibility to do extremely fast lookups as the data and the index have less entries. Once you are aware of the block, data file location can be done at a very fast pace.

MapFile is effective as we can look up keys and the values:

Row Length short

Row Key

Byte[]

Family length byte

Column Family byte[]

Column Qualifier bytes[]

Timestamp

long

Key Type

byte

Hbase key has the preceding structure: row key, column family, column qualifier, timestamp...

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