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

Copying a few tables with Slony


Once Slony has been installed and is running on both nodes, we can actually make use of it and copy tables to a remote database. For high availability PostgreSQL servers, making data available to external systems means long-running and potentially disruptive ad hoc queries run elsewhere. It also means that reporting environments have direct copies of relevant tables and do not need to retrieve this data from our OLTP systems.

While it is possible for OLTP servers to act as OLAP systems as well, these workloads are quite different. For the best performance possible and the least risk of outages, each server should be specialized. So, let's use Slony to do just that.

Getting ready

We will be continuing where we left off in the Setting up Slony recipe. Please make sure to have completed that recipe before continuing. As we want tables to test Slony with, we should create some. The pgbench utility can do this quickly. Execute this command on the primary PostgreSQL...