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

Working with hash and merge join


In this recipe, we will be discussing merge and hash join mechanisms in PostgreSQL.

Getting ready

Merge join is another joining approach to perform the join operation between two datasets. PostgreSQL optimizer will generally choose this joining method for an equi joins or for union operations. To perform this join on two datasets, it is required to sort the two join key columns first and then it will run the join condition. The optimizer prefers this node type, while joining huge tables.

Hash join is another joining approach. In general, this approach is pretty fast if and only if the server has enough memory resources. To perform this join, PostgreSQL does not need any sorted results. Rather, it will take one table data to build a hash index, which it will be comparing with the other table tuples. PostgreSQL optimizer will generally choose this joining method for an equi joins or for union operations. The optimizer prefers this node type, while joining the...