Book Image

Mastering PostgreSQL 15 - Fifth Edition

By : Hans-Jürgen Schönig
Book Image

Mastering PostgreSQL 15 - Fifth Edition

By: Hans-Jürgen Schönig

Overview of this book

Starting with an introduction to the newly released features of PostgreSQL 15, this updated fifth edition will help you get to grips with PostgreSQL administration and how to build dynamic database solutions for enterprise apps, including designing both physical and technical aspects of the system. You'll explore advanced PostgreSQL features, such as logical replication, database clusters, advanced indexing, 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. Among the other skills that the book will help you build, you’ll cover transactions, handling recursions, working with JSON and JSONB data, and setting up a Patroni cluster. It will show you how to improve performance with query optimization. You'll also focus on managing 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 use your database to its utmost capacity by implementing advanced administrative tasks with ease.
Table of Contents (16 chapters)

Understanding full-text searches

If you are looking up names or looking for simple strings, you are usually querying the entire content of a field. With a full-text search, this is different. The purpose of the full-text search is to look for words or groups of words that can be found in a text. Therefore, a full-text search is more of a contains operation, as you are basically never looking for an exact string.

In PostgreSQL, a full-text search can be done using GIN indexes. The idea is to dissect a text, extract valuable lexeme (preprocessed tokens of words) strings, and index those elements rather than the underlying text. To make your search even more successful, those words are preprocessed.

Here is an example:

test=# SELECT to_tsvector('english','A car,
    I want a car. I would not even mind having many cars');
                    ...