Book Image

Mastering PostgreSQL 11 - Second Edition

By : Hans-Jürgen Schönig
Book Image

Mastering PostgreSQL 11 - Second Edition

By: Hans-Jürgen Schönig

Overview of this book

This second edition of Mastering PostgreSQL 11 helps you build dynamic database solutions for enterprise applications using the latest release of PostgreSQL, which enables database analysts to design both the physical and technical aspects of the system architecture with ease. This book begins with an introduction to the newly released features in PostgreSQL 11 to help you build efficient and fault-tolerant PostgreSQL applications. You’ll examine all of the advanced aspects of PostgreSQL in detail, including logical replication, database clusters, performance tuning, monitoring, and user management. You will also work with the PostgreSQL optimizer, configuring PostgreSQL for high speed, and see how to move from Oracle to PostgreSQL. As you progress through the chapters, you will cover transactions, locking, indexes, and optimizing queries to improve performance. Additionally, you’ll learn to manage network security and explore backups and replications, while understanding the useful extensions of PostgreSQL so that you can optimize the speed and performance of large databases. By the end of this book, you will be able to use your database to its utmost capacity by implementing advanced administrative tasks with ease.
Table of Contents (15 chapters)
Free Chapter
1
PostgreSQL Overview

Enabling and disabling optimizer settings

So far, the most important optimizations that are performed by the planner have been discussed in detail. PostgreSQL has improved a lot over the years. Still, it can happen that something goes south and users have to convince the planner to do the right thing.

To modify plans, PostgreSQL offers a couple of runtime variables that will have a significant impact on planning. The idea is to give the end user the chance to make certain types of nodes in the plan more expensive than others. What does that mean in practice? Here is a simple plan:

test=# explain SELECT * 
FROM generate_series(1, 100) AS a,
generate_series(1, 100) AS b
WHERE a = b;
QUERY PLAN
-----------------------------------------------------------------
Merge Join (cost=119.66..199.66 rows=5000 width=8)
Merge Cond: (a.a = b.b)...