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PostgreSQL 16 Administration Cookbook

PostgreSQL 16 Administration Cookbook

By : GIANNI CIOLLI, Boriss Mejías, Jimmy Angelakos, Vibhor Kumar, Simon Riggs
4.8 (27)
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PostgreSQL 16 Administration Cookbook

PostgreSQL 16 Administration Cookbook

4.8 (27)
By: GIANNI CIOLLI, Boriss Mejías, Jimmy Angelakos, Vibhor Kumar, Simon Riggs

Overview of this book

PostgreSQL has seen a huge increase in its customer base in the past few years and is becoming one of the go-to solutions for anyone who has a database-specific challenge. This PostgreSQL book touches on all the fundamentals of Database Administration in a problem-solution format. It is intended to be the perfect desk reference guide. This new edition focuses on recipes based on the new PostgreSQL 16 release. The additions include handling complex batch loading scenarios with the SQL MERGE statement, security improvements, running Postgres on Kubernetes or with TPA and Ansible, and more. This edition also focuses on certain performance gains, such as query optimization, and the acceleration of specific operations, such as sort. It will help you understand roles, ensuring high availability, concurrency, and replication. It also draws your attention to aspects like validating backups, recovery, monitoring, and scaling aspects. This book will act as a one-stop solution to all your real-world database administration challenges. By the end of this book, you will be able to manage, monitor, and replicate your PostgreSQL 16 database for efficient administration and maintenance with the best practices from experts.
Table of Contents (15 chapters)
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13
Other Books You May Enjoy
14
Index

Forcing a query to use an index

Often, we think we know better than the database optimizer. Most of the time, your expectations are wrong, and if you look carefully, you’ll see that. So, recheck everything and come back later.

It is a classic error to try to get the database optimizer to use indexes when the database has very little data in it. Put some genuine data in the database first, then worry about it. Better yet, load some data on a test server first, rather than doing this in production.

Sometimes, the optimizer gets it wrong. You feel elated—and possibly angry—that the database optimizer doesn’t see what you see. Please bear in mind that the data distributions within your database change over time, and this causes the optimizer to change its plans over time as well.

If you have found a case where the optimizer is wrong, this can sometimes change over time as the data changes. It might have been correct last week and will be correct...

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