Book Image

PostgreSQL 11 Administration Cookbook

By : Simon Riggs, Gianni Ciolli, Sudheer Kumar Meesala
Book Image

PostgreSQL 11 Administration Cookbook

By: Simon Riggs, Gianni Ciolli, Sudheer Kumar Meesala

Overview of this book

PostgreSQL is a powerful, open source database management system with an enviable reputation for high performance and stability. With many new features in its arsenal, PostgreSQL 11 allows you to scale up your PostgreSQL infrastructure. This book takes a step-by-step, recipe-based approach to effective PostgreSQL administration. The book will introduce you to new features such as logical replication, native table partitioning, additional query parallelism, and much more to help you to understand and control, crash recovery and plan backups. You will learn how to tackle a variety of problems and pain points for any database administrator such as creating tables, managing views, improving performance, and securing your database. As you make steady progress, the book will draw attention to important topics such as monitoring roles, backup, and recovery of your PostgreSQL 11 database to help you understand roles and produce a summary of log files, ensuring high availability, concurrency, and replication. By the end of this book, you will have the necessary knowledge to manage your PostgreSQL 11 database efficiently.
Table of Contents (19 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Creating time series tables


In many applications, we need to store data in time series.

There are various mechanisms in PostgreSQL that are designed to support this, and it is an area that has changed dramatically in PostgreSQL 11.

How to do it…

If you have a huge table and a query to select only a subset of that table, then you may wish to use a BRIN index (block range index). These indexes give performance improvements when the data is naturally ordered as it is added to the table, such as logtime columns or a naturally ascending OrderId column. Adding a BRIN index is fast and very easy, and works well for the use case of time series data logging, though it works less well under intensive updates. INSERTs into BRIN indexes are specifically designed to not slow down as the table gets bigger, so they perform much better than B-tree indexes.

You may also think that you need to manually partition a table. This can involve significant effort to set up an effective partitioning scheme using multiple...