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

Moving a shard to another server

The final important aspect of database sharding that we are going to explore in this chapter is reorganization. The purpose of allocating a large number of logical shards is to prepare for future expansion needs. If we started with 2,048 shards, all of which are currently mapped to a single server, we will eventually want to move some of them elsewhere.

The easiest way to do this is to leverage PostgreSQL replication. Essentially, we will create a streaming replica for the server we want to split and drop the schemas we don't need on each server. Consider a database with two shards. Our end goal is to produce something like this:

On each server, we simply drop the schema indicated by the dashed box. This way, we still have two shards, and only the location of myapp2 has changed; its data remains unharmed.

This recipe will cover the process described here, making it easy to move shards to a new physical location.

Getting ready

This recipe depends on the work we...