Book Image

PostgreSQL Development Essentials

By : Manpreet Kaur, Baji Shaik
Book Image

PostgreSQL Development Essentials

By: Manpreet Kaur, Baji Shaik

Overview of this book

PostgreSQL is the most advanced open source database in the world. It is easy to install, configure, and maintain by following the documentation; however, it’s difficult to develop applications using programming languages and design databases accordingly. This book is what you need to get the most out of PostgreSQL You will begin with advanced SQL topics such as views, materialized views, and cursors, and learn about performing data type conversions. You will then perform trigger operations and use trigger functions in PostgreSQL. Next we walk through data modeling, normalization concepts, and the effect of transactions and locking on the database. The next half of the book covers the types of indexes, constrains, and the concepts of table partitioning, as well as the different mechanisms and approaches available to write efficient queries or code. Later, we explore PostgreSQL Extensions and Large Object Support in PostgreSQL. Finally, you will perform database operations in PostgreSQL using PHP and Java. By the end of this book, you will have mastered all the aspects of PostgreSQL development. You will be able to build efficient enterprise-grade applications with PostgreSQL by making use of these concepts
Table of Contents (17 chapters)
PostgreSQL Development Essentials
About the Authors
About the Reviewers

Table partitioning

Partitioning is a feature in DBMS which segregates large amounts of data into multiple segments based on an attribute of a relation. Using this as a feature, we can perform operations effectively on large datasets. We can also go without partitioning the large datasets, but eventually we'll need to pay for performance as a result. The query response time and the amount of data it processes are inversely proportional. So, in short, the more data we have, the less performance we get (where performance is the actual time of query execution).

For example, consider we have a global business where we store all our global customers' information in our local database as follows:

CREATE TABLE customers
(id integer,
name varchar(126),
countrycode varchar(3),
contactnum text);

In the preceding table, we will store all our global customer details along with the countrycode. For demonstration purposes, I am going to use three-character country names, which are generated randomly from...