Book Image

PostgreSQL High Performance Cookbook

By : Chitij Chauhan, Dinesh Kumar
Book Image

PostgreSQL High Performance Cookbook

By: Chitij Chauhan, Dinesh Kumar

Overview of this book

PostgreSQL is one of the most powerful and easy to use database management systems. It has strong support from the community and is being actively developed with a new release every year. PostgreSQL supports the most advanced features included in SQL standards. It also provides NoSQL capabilities and very rich data types and extensions. All of this makes PostgreSQL a very attractive solution in software systems. If you run a database, you want it to perform well and you want to be able to secure it. As the world’s most advanced open source database, PostgreSQL has unique built-in ways to achieve these goals. This book will show you a multitude of ways to enhance your database’s performance and give you insights into measuring and optimizing a PostgreSQL database to achieve better performance. This book is your one-stop guide to elevate your PostgreSQL knowledge to the next level. First, you’ll get familiarized with essential developer/administrator concepts such as load balancing, connection pooling, and distributing connections to multiple nodes. Next, you will explore memory optimization techniques before exploring the security controls offered by PostgreSQL. Then, you will move on to the essential database/server monitoring and replication strategies with PostgreSQL. Finally, you will learn about query processing algorithms.
Table of Contents (19 chapters)
PostgreSQL High Performance Cookbook
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

Detecting a missing index


In this recipe, we will be discussing how to identify the tables that need to be indexed.

Getting ready

To find the missing indexes in a database is a tricky task. To find the missing indexes on a table, we have to use the sequential, index scan counter values from the catalog tables. In case we see too many sequential scans on a table, then we can't confirm that the table is a candidate for the index. To confirm this, we have to analyze the queries that we execute on that table using hypothetical indexes.

In general, it is always recommended that you create indexes on foreign key columns, as it helps the query to choose an index while joining parent and child tables. The foreign key's index also improves the key validation among child and parent tables. It is also recommended that you create indexes on the child tables, while creating child tables by inheriting from parent tables.

How to do it...

Let's query the database as to whether the delta of seq_scan, idx_scan...