Book Image

Mastering PostgreSQL 11 - Second Edition

By : Hans-Jürgen Schönig
Book Image

Mastering PostgreSQL 11 - Second Edition

By: Hans-Jürgen Schönig

Overview of this book

This second edition of Mastering PostgreSQL 11 helps you build dynamic database solutions for enterprise applications using the latest release of PostgreSQL, which enables database analysts to design both the physical and technical aspects of the system architecture with ease. This book begins with an introduction to the newly released features in PostgreSQL 11 to help you build efficient and fault-tolerant PostgreSQL applications. You’ll examine all of the advanced aspects of PostgreSQL in detail, including logical replication, database clusters, performance tuning, monitoring, and user management. You will also work with the PostgreSQL optimizer, configuring PostgreSQL for high speed, and see how to move from Oracle to PostgreSQL. As you progress through the chapters, you will cover transactions, locking, indexes, and optimizing queries to improve performance. Additionally, you’ll learn to manage network security and explore backups and replications, while understanding the useful extensions of PostgreSQL so that you can optimize the speed and performance of large databases. By the end of this book, you will be able to use your database to its utmost capacity by implementing advanced administrative tasks with ease.
Table of Contents (15 chapters)
Free Chapter
1
PostgreSQL Overview

Making use of ordered sets

Ordered sets are powerful features, but are not widely regarded as such and not widely known in the developer community. The idea is actually quite simple: data is grouped normally, and then the data inside each group is ordered given a certain condition. The calculation is then performed on this sorted data.

A classic example would be the calculation of the median.

The median is the middle value. If you are, for example, earning the median income, the number of people earning less and more than you is identical; 50% of people do better and 50% of people do worse.

One way to get the median is to take sorted data and move 50% into the dataset. This is an example of what the WITHIN GROUP clause will ask PostgreSQL to do:

test=# SELECT region, 
percentile_disc(0.5) WITHIN GROUP (ORDER BY production)
FROM t_oil
GROUP BY 1;
region | percentile_disc...