Book Image

PostgreSQL 14 Administration Cookbook

By : Simon Riggs, Gianni Ciolli
5 (1)
Book Image

PostgreSQL 14 Administration Cookbook

5 (1)
By: Simon Riggs, Gianni Ciolli

Overview of this book

PostgreSQL is a powerful, open-source database management system with an enviable reputation for high performance and stability. With many new features in its arsenal, PostgreSQL 14 allows you to scale up your PostgreSQL infrastructure. With this book, you'll take a step-by-step, recipe-based approach to effective PostgreSQL administration. This book will get you up and running with all the latest features of PostgreSQL 14 while helping you explore the entire database ecosystem. You’ll learn how to tackle a variety of problems and pain points you may face as a database administrator such as creating tables, managing views, improving performance, and securing your database. As you make progress, the book will draw attention to important topics such as monitoring roles, validating backups, regular maintenance, and recovery of your PostgreSQL 14 database. This will help you understand roles, ensuring high availability, concurrency, and replication. Along with updated recipes, this book touches upon important areas like using generated columns, TOAST compression, PostgreSQL on the cloud, and much more. By the end of this PostgreSQL book, you’ll have gained the knowledge you need to manage your PostgreSQL 14 database efficiently, both in the cloud and on-premise.
Table of Contents (14 chapters)

Using parallel query

PostgreSQL now has an increasingly effective parallel query feature.

Response times from long-running queries can be improved by the use of parallel processing. The concept is that if we divide a large task up into multiple smaller pieces then we get the answer faster, but we use more resources to do that.

Very short queries won't get faster by using parallel query, so if you have lots of those you'll gain more by thinking about better indexing strategies. Parallel query is aimed at making very large tasks faster, so it is useful for reporting and business intelligence (BI) queries.

How to do it…

Take a query that needs to do a big chunk of work, such as the following:

\timing
SET max_parallel_workers_per_gather = 0;
SELECT count(*) FROM big;
count
---------
1000000
(1 row)
Time: 46.399 ms
SET max_parallel_workers_per_gather = 2;
SELECT count(*) FROM big;
count
---------
1000000
(1 row)
Time: 29.085 ms

By setting the...