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

Generating planner statistics


In this recipe, we will be discussing how we can use PostgreSQL to generate statistics.

Getting ready

Database statistical information plays a crucial role in deciding the proper execution plan for the given SQL statement. PostgreSQL provides a utility command called ANALYZE, which collects statistics from tables and makes them available to the planner. PostgreSQL also provides another utility background process called autovacuum, which does a similar job to analyze. All these collected statistics will be stored into the PostgreSQL catalog tables.

How to do it...

Now, for demonstration let's create a test table and populate a few entries in it:

postgres=# CREATE TABLE test(t INT); 
CREATE TABLE 
postgres=# SELECT COUNT(*) FROM pg_stats WHERE tablename = 'test'; 
 count 
------- 
     0 
(1 row) 
postgres=# INSERT INTO test VALUES(generate_series(1, 1000));      
INSERT 0 1000 
postgres=# ANALYZE test; 
ANALYZE &...