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Learning PostgreSQL 11

Learning PostgreSQL 11

By : Christopher Travers, Volkov
2.7 (6)
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Learning PostgreSQL 11

Learning PostgreSQL 11

2.7 (6)
By: Christopher Travers, 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)
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Cleaning up the database

Often, a database can contain several unused objects or very old data. Cleaning up these objects helps administrators perform a backup of images more quickly. From a development point of view, unused objects are noise because they affect the refactoring process.

In database applications, you need to keep the database clean, since unused database objects might hinder quick development due to those objects' dependencies. To clean the database, you need to identify the unused database objects, including tables, views, indexes, and functions.

Table statistics, such as the number of live rows, index scans, and sequential scans, can help identify empty and unused tables. Note that the following queries are based on statistics, so the results need to be validated. The pg_stat_user_tables table provides this information, and the following query shows empty...

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