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
About the Author
About the Reviewer
Customer Feedback

Installing PgBouncer

The first pooling resource we will explore is named PgBouncer. This is a very popular connection pool written by Skype developers in 2007. The project has been maintained by various developers in subsequent years, but its role of lowering the cost of connecting to PostgreSQL has never changed.

PgBouncer allows PostgreSQL to interact with orders of magnitude more clients than is otherwise possible because its connection overhead is much lower. Instead of huge libraries, accounting for temporary tables, query results, and other expensive resources, it essentially just tracks each client connection in a queue. Then, based on configuration settings, it creates several PostgreSQL connections and assigns them to the connections on a first-come, first-served basis.

This means hundreds, or even thousands of database clients, can theoretically share a single PostgreSQL connection. Of course, we will never suggest implementing a ratio that absurd without testing, yet this possibility...