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

Using materialized views

Every time we select rows from a view, we actually select from the result of the underlying query. If that query is slow and we need to use it more than once, then it makes sense to run the query once, save its output as a table, and then select the rows from the latter.

This procedure has been available for a long time, and there is a dedicated syntax, CREATE MATERIALIZED VIEW, which we will describe in this recipe.

Getting ready

Let's create two randomly populated tables, of which one is large:

, dish_description text

( eater_id SERIAL
, eating_date date
, dish_id int REFERENCES dish (dish_id)
INSERT INTO dish (dish_description)
VALUES ('Lentils'), ('Mango'), ('Plantain'), ('Rice'), ('Tea');

INSERT INTO eater(eating_date, dish_id)
SELECT floor(abs(sin(n)) * 365) :: int + date '2014-01-01'
, ceil(abs(sin(n :: float * n))*5) :: int
FROM generate_series(1,500000) AS rand(n);

Notice that the data...