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PostgreSQL High Performance Cookbook

You're reading from   PostgreSQL High Performance Cookbook Mastering query optimization, database monitoring, and performance-tuning for PostgreSQL

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781785284335
Length 360 pages
Edition 1st Edition
Languages
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Authors (2):
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Chitij Chauhan Chitij Chauhan
Author Profile Icon Chitij Chauhan
Chitij Chauhan
Dinesh Kumar Dinesh Kumar
Author Profile Icon Dinesh Kumar
Dinesh Kumar
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Toc

Table of Contents (13) Chapters Close

Preface 1. Database Benchmarking FREE CHAPTER 2. Server Configuration and Control 3. Device Optimization 4. Monitoring Server Performance 5. Connection Pooling and Database Partitioning 6. High Availability and Replication 7. Working with Third-Party Replication Management Utilities 8. Database Monitoring and Performance 9. Vacuum Internals 10. Data Migration from Other Databases to PostgreSQL and Upgrading the PostgreSQL Cluster 11. Query Optimization 12. Database Indexing

Dealing with bloating tables and indexes


In this recipe, we will be discussing how to deal with bloats using PostgreSQL's garbage collector processes.

Getting ready

We all know that PostgreSQL's storage implementation is based on MVCC. As a result of MVCC, PostgreSQL needs to reclaim the dead space/bloats from the physical storage, using its garbage collector processes called vacuum or autovacuum. If we do not reclaim these dead rows, then the table or index will keep growing until the disk space gets full. In a worst case scenario, a single live row in a table can cause the disk space outage. We will discuss these garbage collector processes in more detail in the next recipe, but for now let's find out which tables or indexes have more dead space.

How to do it...

To identify the bloat of an object, we have to use the pgstattuple extension, otherwise we have to follow the approach that is mentioned at: http://www.databasesoup.com/2014/10/new-table-bloat-query.html:

postgres=# CREATE EXTENSION...
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