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

Forcing a query to use an index


In this recipe, we will be discussing how to force a query to pick an index.

Getting ready

As we discussed in the previous chapters, the optimizer generates a set of plans based on the statistics it collected. Among all these plans, whatever plan has the least cost value would be preferred as a final execution plan of that query. Forcing a specific index to the SQL query is not possible in the current release of PostgreSQL; however, you can somehow guide the planner to pick the index scan over the other bitmap and sequential scans by disabling the session level optimizer parameters. Otherwise, you have to change the arbitrary cost value of random_page_cost so that it is close to the value of the seq_page_cost parameter.

How to do it...

Let's write a sample SQL query that prefers the sequential scan, as follows:

benchmarksql=# EXPLAIN ANALYZE SELECT COUNT(*) FROM bmsql_item WHERE i_price BETWEEN 10 AND 80; 
                                                     ...