Book Image

Learning PostgreSQL 11 - Third Edition

By : Salahaldin Juba, Andrey Volkov
Book Image

Learning PostgreSQL 11 - Third Edition

By: Salahaldin Juba, Andrey Volkov

Overview of this book

PostgreSQL is one of the most popular open source database management systems in the world, and it supports advanced features included in SQL standards. This book will familiarize you with the latest features in PostgreSQL 11, and get you up and running with building efficient PostgreSQL database solutions from scratch. Learning PostgreSQL, 11 begins by covering the concepts of relational databases and their core principles. You’ll explore the Data Definition Language (DDL) and commonly used DDL commands supported by ANSI SQL. You’ll also learn how to create tables, define integrity constraints, build indexes, and set up views and other schema objects. As you advance, you’ll come to understand Data Manipulation Language (DML) and server-side programming capabilities using PL/pgSQL, giving you a robust background to develop, tune, test, and troubleshoot your database application. The book will guide you in exploring NoSQL capabilities and connecting to your database to manipulate data objects. You’ll get to grips with using data warehousing in analytical solutions and reports, and scaling the database for high availability and performance. By the end of this book, you’ll have gained a thorough understanding of PostgreSQL 11 and developed the necessary skills to build efficient database solutions.
Table of Contents (18 chapters)

Common mistakes in writing queries

There are some common mistakes and bad practices that developers may fall into. For example, a relational database is based on set theory; new developers tend to think in the scope of row-level manipulation instead of set manipulation. In addition, a lot of people create poor physical designs because they aren't familiar with relational-database modeling. In this section, we'll cover common mistakes in writing queries. For modelling issues, it's recommended to have a look at normalization because normalization also can boost performance by reducing data size and enhance statistics. In general, there are several issues that might lead to bad performance:

  • Incorrect statistics: This might happen if there are cross-correlations among predicates, or if the predicates have an immutable function.
  • Unnecessary data retrieval: When there...