Book Image

Mastering PostgreSQL 13 - Fourth Edition

By : Hans-Jürgen Schönig
Book Image

Mastering PostgreSQL 13 - Fourth Edition

By: Hans-Jürgen Schönig

Overview of this book

Thanks to its reliability, robustness, and high performance, PostgreSQL has become one of the most advanced open source databases on the market. This updated fourth edition will help you understand PostgreSQL administration and how to build dynamic database solutions for enterprise apps with the latest release of PostgreSQL, including designing both physical and technical aspects of the system architecture with ease. Starting with an introduction to the new features in PostgreSQL 13, this book will guide you in building efficient and fault-tolerant PostgreSQL apps. You’ll explore advanced PostgreSQL features, such as logical replication, database clusters, performance tuning, advanced indexing, monitoring, and user management, to manage and maintain your database. You’ll then work with the PostgreSQL optimizer, configure PostgreSQL for high speed, and move from Oracle to PostgreSQL. The book also covers transactions, locking, and indexes, and shows you how to improve performance with query optimization. You’ll also focus on how to manage network security and work with backups and replication while exploring useful PostgreSQL extensions that optimize 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 executing advanced administrative tasks.
Table of Contents (15 chapters)

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, something can go 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
------------------------------------------------------------------------------------
Hash Join (cost=2.25..4.63 rows=100 width=8)
Hash Cond: (a.a = b.b)
-> Function Scan on generate_series a (cost=0.00..1.00 rows=100 width=4)
-> Hash (cost=1.00..1.00 rows=100...