Book Image

PostgreSQL High Availability Cookbook - Second Edition

By : Shaun Thomas
Book Image

PostgreSQL High Availability Cookbook - Second Edition

By: Shaun Thomas

Overview of this book

Databases are nothing without the data they store. In the event of a failure - catastrophic or otherwise - immediate recovery is essential. By carefully combining multiple servers, it’s even possible to hide the fact a failure occurred at all. From hardware selection to software stacks and horizontal scalability, this book will help you build a versatile PostgreSQL cluster that will survive crashes, resist data corruption, and grow smoothly with customer demand. It all begins with hardware selection for the skeleton of an efficient PostgreSQL database cluster. Then it’s on to preventing downtime as well as troubleshooting some real life problems that administrators commonly face. Next, we add database monitoring to the stack, using collectd, Nagios, and Graphite. And no stack is complete without replication using multiple internal and external tools, including the newly released pglogical extension. Pacemaker or Raft consensus tools are the final piece to grant the cluster the ability to heal itself. We even round off by tackling the complex problem of data scalability. This book exploits many new features introduced in PostgreSQL 9.6 to make the database more efficient and adaptive, and most importantly, keep it running.
Table of Contents (18 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.Packtpub.com
Customer Feedback
Preface

Transforming foreign tables into local tables


Remote tables provide an easy and convenient way to access remote data in a PostgreSQL database. This is good for highly available systems, as a properly compartmentalized system invites segmented maintenance. Yet, remote data comes with a rather drastic cost regarding data fetching and handling overhead.

PostgreSQL 9.3 introduced internal support for materialized views. Traditionally, materialized views merely instantiate a view into a physical structure to avoid expensive or complicated query plans and result sets. They also make it possible to index or optimize a view in ways not normally possible. Now, imagine what we can do with such a structure when utilizing foreign tables.

In this recipe, we will explore how materialized views can drastically increase local data access capability within a PostgreSQL database.

Getting ready

As we will be using the pgbench_accounts foreign table in this recipe, please follow all recipes up to Creating a foreign...