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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

Using optimistic locking to avoid long lock waits

If you perform work in one long transaction, the database will lock rows for long periods of time. Long lock times often result in application performance issues because of long lock waits:

BEGIN;
SELECT * FROM accounts WHERE holder_name ='BOB' FOR UPDATE;
<do some calculations here>
UPDATE accounts SET balance = 42.00 WHERE holder_name ='BOB';
COMMIT;

If that is happening, then you may gain some performance benefits by moving from explicit locking (SELECT ... FOR UPDATE) to optimistic locking.

Optimistic locking assumes that others don’t update the same record, and checks this at update time, instead of locking the record for the time it takes to process the information on the client side.

How to do it…

Rewrite your application so that the SQL is transformed into two separate transactions, with a double-check to ensure that the rows haven’t changed (pay attention...

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