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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

Preventing duplicate rows

Preventing duplicate rows is one of the most important aspects of data quality for any database. PostgreSQL offers some useful features in this area, extending beyond most relational databases.

Getting ready

Identify the set of columns that you wish to make unique. Does this apply to all rows or just a subset of rows?

Let’s find out with our example table:

postgres=# SELECT * FROM new_cust;
customerid
------------
          1
          2
          3
          4
(4 rows)

How to do it…

To prevent duplicate rows, we need to create a unique index that the database server can use to enforce the uniqueness of a particular set of columns. We can do this in the following three similar ways for basic data types:

  1. Create a primary key constraint on the set of columns. We are allowed only one of these per table. The values of the data rows must not be NULL, as we force the columns to be NOT NULL if they aren’t...

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