Book Image

PostgreSQL 11 Administration Cookbook

By : Simon Riggs, Gianni Ciolli, Sudheer Kumar Meesala
Book Image

PostgreSQL 11 Administration Cookbook

By: Simon Riggs, Gianni Ciolli, Sudheer Kumar Meesala

Overview of this book

PostgreSQL is a powerful, open source database management system with an enviable reputation for high performance and stability. With many new features in its arsenal, PostgreSQL 11 allows you to scale up your PostgreSQL infrastructure. This book takes a step-by-step, recipe-based approach to effective PostgreSQL administration. The book will introduce you to new features such as logical replication, native table partitioning, additional query parallelism, and much more to help you to understand and control, crash recovery and plan backups. You will learn how to tackle a variety of problems and pain points for any database administrator such as creating tables, managing views, improving performance, and securing your database. As you make steady progress, the book will draw attention to important topics such as monitoring roles, backup, and recovery of your PostgreSQL 11 database to help you understand roles and produce a summary of log files, ensuring high availability, concurrency, and replication. By the end of this book, you will have the necessary knowledge to manage your PostgreSQL 11 database efficiently.
Table of Contents (19 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Finding a unique key for a set of data


Sometimes, it can be difficult to find a unique set of key columns that describe the data.

Getting ready

Let's start with a small table, where the answer is fairly obvious:

postgres=# select * from ord;

We assume that the output is as follows:

orderid  | customerid |  amt  
---------+------------+--------
   10677 |          2 |   5.50
    5019 |          3 | 277.44
    9748 |          3 |  77.17
(3 rows)

How to do it…

First of all, there's no need to do this through a brute-force approach. Checking all the permutations of columns to see which is unique might take you a long time.

Let's start by using PostgreSQL's own optimizer statistics. Run the following command on our table to get a fresh sample of statistics:

postgres=# analyze ord;
ANALYZE

This runs quickly, so we don't have to wait too long. Now we can examine the relevant columns of the statistics:

postgres=# SELECT attname, n_distinct 
                           FROM pg_stats
                        ...