Book Image

Mastering PostgreSQL 13 - Fourth Edition

By : Hans-Jürgen Schönig
Book Image

Mastering PostgreSQL 13 - Fourth Edition

By: Hans-Jürgen Schönig

Overview of this book

Thanks to its reliability, robustness, and high performance, PostgreSQL has become one of the most advanced open source databases on the market. This updated fourth edition will help you understand PostgreSQL administration and how to build dynamic database solutions for enterprise apps with the latest release of PostgreSQL, including designing both physical and technical aspects of the system architecture with ease. Starting with an introduction to the new features in PostgreSQL 13, this book will guide you in building efficient and fault-tolerant PostgreSQL apps. You’ll explore advanced PostgreSQL features, such as logical replication, database clusters, performance tuning, advanced indexing, monitoring, and user management, to manage and maintain your database. You’ll then work with the PostgreSQL optimizer, configure PostgreSQL for high speed, and move from Oracle to PostgreSQL. The book also covers transactions, locking, and indexes, and shows you how to improve performance with query optimization. You’ll also focus on how to manage network security and work with backups and replication while exploring useful PostgreSQL extensions that optimize the performance of large databases. By the end of this PostgreSQL book, you’ll be able to get the most out of your database by executing advanced administrative tasks.
Table of Contents (15 chapters)

Understanding PostgreSQL index types

So far, only binary trees have been discussed. However, in many cases, B-trees are just not enough. Why is that? As we've already discussed in this chapter, B-trees are basically based on sorting. The <, <=, =, >=, and > operators can be handled using B-trees. The trouble is, not every data type can be sorted in a useful way. Just imagine a polygon. How would you sort these objects in a useful way? Sure, you can sort by the area covered, its length, and so on, but doing this won't allow you to actually find them using a geometric search.

The solution to this problem is to provide more than just one index type. Each index will serve a special purpose and do exactly what is needed. The following six index types are available (as of PostgreSQL 10.0):

test=# SELECT * FROM pg_am;
oid | amname | amhandler | amtype
2 | heap | heap_tableam_handler | t
403 | btree | bthandler...