Book Image

Mastering PostgreSQL 12 - Third Edition

By : Hans-Jürgen Schönig
Book Image

Mastering PostgreSQL 12 - Third Edition

By: Hans-Jürgen Schönig

Overview of this book

Thanks to its reliability, robustness, and high performance, PostgreSQL has become the most advanced open source database on the market. This third edition of Mastering PostgreSQL helps you build dynamic database solutions for enterprise applications using the latest release of PostgreSQL, which enables database analysts to design both physical and technical aspects of system architecture with ease. Starting with an introduction to the newly released features in PostgreSQL 12, this book will help you build efficient and fault-tolerant PostgreSQL applications. You’ll thoroughly examine the advanced features of PostgreSQL, including logical replication, database clusters, performance tuning, monitoring, and user management. You’ll also work with the PostgreSQL optimizer, configure PostgreSQL for high speed, and understand how to move from Oracle to PostgreSQL. As you progress through the chapters, you’ll cover transactions, locking, indexes, and how to optimize queries for improved performance. Additionally, you’ll learn how to manage network security and explore backups and replications while understanding useful PostgreSQL extensions to help you in optimizing the performance of large databases. By the end of this PostgreSQL book, you’ll be able to get the most out of your database by implementing advanced administrative tasks effortlessly.
Table of Contents (18 chapters)
Free Chapter
1
Section 1: Basic Overview
4
Section 2: Advanced Concepts

Making use of parallel queries

Starting with version 9.6, PostgreSQL supports parallel queries. This support for parallelism has been improved gradually over time, and version 11 has added even more functionality to this important feature. In this section, we will take a look at how parallelism works and what can be done to speed up things.

Before digging into the details, it is necessary to create some sample data, as follows:

test=# CREATE TABLE t_parallel AS 
SELECT * FROM generate_series(1, 25000000) AS id;
SELECT 25000000

After loading the initial data, we can run our first parallel query. A simple count will show what a parallel query looks like in general:

test=# explain SELECT count(*) FROM t_parallel;
QUERY PLAN
------------------------------------------------------------------------------------
Finalize Aggregate (cost=258537.40..258537.41 rows=1 width=8)
-> Gather...