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

Building a sharding API

When building a horizontally scalable system, we need a database library that facilitates its use. Without this, ad hoc tables can derail the whole process by producing a heterogeneous environment incompatible with a horizontal architecture. We need consistency if we also want reliability.

In the previous recipe, we discussed the necessary components of a function that can generate unique IDs across thousands of logical shards. This will form the core of our API as it ensures that ID collisions are avoided within our application. However, what about the rest? How do we manage each shard? How do we add tables to the application? How can we automate as much management as possible to encourage adherence to the API?

This recipe will attempt to answer these questions and many more by having you create the necessary functions to manage a shard-driven system.

Getting ready

This recipe depends on the work we performed in the Creating a scalable nextval replacement recipe. Please...