Book Image

PostgreSQL 12 High Availability Cookbook - Third Edition

By : Shaun Thomas
Book Image

PostgreSQL 12 High Availability Cookbook - Third Edition

By: Shaun Thomas

Overview of this book

Databases are nothing without the data they store. In the event of an outage or technical catastrophe, immediate recovery is essential. This updated edition ensures that you will learn the important concepts related to node architecture design, as well as techniques such as using repmgr for failover automation. From cluster layout and hardware selection to software stacks and horizontal scalability, this PostgreSQL cookbook will help you build a PostgreSQL cluster that will survive crashes, resist data corruption, and grow smoothly with customer demand. You’ll start by understanding how to plan a PostgreSQL database architecture that is resistant to outages and scalable, as it is the scaffolding on which everything rests. With the bedrock established, you'll cover the topics that PostgreSQL database administrators need to know to manage a highly available cluster. This includes configuration, troubleshooting, monitoring and alerting, backups through proxies, failover automation, and other considerations that are essential for a healthy PostgreSQL cluster. Later, you’ll learn to use multi-master replication to maximize server availability. Later chapters will guide you through managing major version upgrades without downtime. By the end of this book, you’ll have learned how to build an efficient and adaptive PostgreSQL 12 database cluster.
Table of Contents (17 chapters)

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. 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 that we want to split and drop the schemas that we don't need on each server. Consider a database with two shards. Our end goal is to produce something like the following:

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...