Book Image

Mastering PostgreSQL 9.6

By : Hans-Jürgen Schönig
Book Image

Mastering PostgreSQL 9.6

By: Hans-Jürgen Schönig

Overview of this book

PostgreSQL is an open source database used for handling large datasets (Big Data) and as a JSON document database. It also has applications in the software and web domains. This book will enable you to build better PostgreSQL applications and administer databases more efficiently. We begin by explaining the advanced database design concepts in PostgreSQL 9.6, along with indexing and query optimization. You will also see how to work with event triggers and perform concurrent transactions and table partitioning, along with exploring SQL and server tuning. We will walk you through implementing advanced administrative tasks such as server maintenance and monitoring, replication, recovery and high availability, and much more. You will understand the common and not-so-common troubleshooting problems and how you can overcome them. By the end of this book, you will have an expert-level command of the advanced database functionalities and will be able to implement advanced administrative tasks with PostgreSQL.
Table of Contents (14 chapters)
Free Chapter
1
PostgreSQL Overview

Making use of ordered sets

Ordered sets are a powerful feature, which is not widely regarded 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 classical 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
---------------+-----------------
Middle...