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 hypothetical aggregates

Hypothetical aggregates are pretty similar to standard ordered sets. However, they help to answer a different kind of question: what would be the result if a value was in the data? As you can see, this is not about values inside the database, but about the result if a certain value was actually there.

The only hypothetical function that's provided by PostgreSQL is rank, as shown in the following code:

test=# SELECT region, 
rank(9000) WITHIN GROUP
(ORDER BY production DESC NULLS LAST)
FROM t_oil
GROUP BY ROLLUP (1);
region | rank
---------------+------
Middle East | 21
North America | 27
| 47
(3 rows)

The preceding code tells us this: if somebody produced 9,000 barrels of oil per day, it would be ranked the 27th best year in North America and the 21st best year in Middle East.

In this example, I used NULLS LAST. When data is sorted, nulls are usually at the end. However, if the...