Book Image

Learn PostgreSQL

By : Luca Ferrari, Enrico Pirozzi
Book Image

Learn PostgreSQL

By: Luca Ferrari, Enrico Pirozzi

Overview of this book

PostgreSQL is one of the fastest-growing open source object-relational database management systems (DBMS) in the world. As well as being easy to use, it’s scalable and highly efficient. In this book, you’ll explore PostgreSQL 12 and 13 and learn how to build database solutions using it. Complete with hands-on tutorials, this guide will teach you how to achieve the right database design required for a reliable environment. You'll learn how to install and configure a PostgreSQL server and even manage users and connections. The book then progresses to key concepts of relational databases, before taking you through the Data Definition Language (DDL) and commonly used DDL commands. To build on your skills, you’ll understand how to interact with the live cluster, create database objects, and use tools to connect to the live cluster. You’ll then get to grips with creating tables, building indexes, and designing your database schema. Later, you'll explore the Data Manipulation Language (DML) and server-side programming capabilities of PostgreSQL using PL/pgSQL, before learning how to monitor, test, and troubleshoot your database application to ensure high-performance and reliability. By the end of this book, you'll be well-versed with the Postgres database and be able to set up your own PostgreSQL instance and use it to build robust solutions.
Table of Contents (27 chapters)
1
Section 1: Getting Started
5
Section 2: Interacting with the Database
12
Section 3: Administering the Cluster
20
Section 4: Replication
23
Section 5: The PostegreSQL Ecosystem

ANALYZE and how to update statistics

PostgreSQL exploits a statistical approach to evaluate different execution plans. This means that PostgreSQL does not know how many tuples there are in a table, but has a good approximation that allows the planner to compute the cost of the execution plan.

Statistics are not only related to the quantity (how many tuples) but also to the quality of the underlying data – for example, how many distinct values, which values are more frequent in a column, and so on. Thanks to the combination of all of this data, PostgreSQL is able to make a good decision.

There are times, however, when the quality of the statistical data is not good enough for PostgreSQL to choose the best plan, a problem commonly known as "out-of-date statistics." In fact, statistics are not updated in real time; rather, PostgreSQL keeps track of what is ongoing in every table in every database and summarizes the number of new tuples, updated ones, and deleted ones, as...