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

Identifying and fixing bloated tables and indexes


PostgreSQL implements Multiversion Concurrency Control (MVCC), which allows users to read data at the same time as writers make changes. This is an important feature for concurrency in database applications, as it can allow the following:

  • Better performance because of fewer locks
  • Greatly reduced deadlocking
  • Simplified application design and management

Bloated tables and indexes are a natural consequence of MVCC design in PostgreSQL. It is caused mainly by updates, as we must retain both the old and new updates for a certain period of time.  

Bloating results in increased disk consumption, as well as performance loss—if a table is twice as big as it should be, scanning it takes twice as long. VACUUM is one of the best ways of removing bloat.

Many users execute VACUUM far too frequently, while at the same time complaining about the cost of doing so. This recipe is all about understanding when you need to run VACUUM by estimating the amount of bloat...