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

Using sample data sets


There are enough sample data sets that are available for PostgreSQL, and most of the data sets are implemented by considering real-time business cases.

Note

Find the list of sample data sets that are available for postgres at this URL: https://wiki.postgresql.org/wiki/Sample_Databases.

Benchmarking tools such as pgBench and BenchmarkSQL will initiate a sample data set, on which they generate a real-time database load and do the benchmarking. In this chapter, to demonstrate a few aspects of the optimizer, let's choose the BenchmarkSQL's catalog tables, which will generate enough data load for this chapter's demonstrations.

Getting ready

BenchmarkSQL is an open source implementation of the popular TPC/C OLTP database benchmark, which supports Firebird, Oracle, and PostgreSQL and captures detailed benchmark results in CSV files, which can later be turned into an HTML report. BenchmarkSQL also captures the OS metrics, such as CPU and memory usages.

How to do it…

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