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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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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

Backing up and restoring Hbase


Amazon Elastic MapReduce provides multiple ways to back up and restore Hbase data to S3 cloud. It also allows us to do an incremental backup; during the backup process Hbase continues to execute the write commands, helping us to keep working while the backup process continues.

Note

There is a risk of having an inconsistency in the data. If consistence is of prime importance, then the write needs to be stopped during the initial backup process, synchronized across nodes. This can be achieved by passing the–consistent parameter when requesting a backup.

When you back up HBase data, you should specify a different backup directory for each cluster.

An easy way to do this is to use the cluster identifier as part of the path specified for the backup directory.

For example, s3://mybucket/backups/j-3AEXXXXXX16F2. This ensures that any future incremental backups reference the correct HBase cluster.

How to do it…

When you are ready to delete old backup files that are no longer...

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