Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Learn PostgreSQL

You're reading from   Learn PostgreSQL Use, manage, and build secure and scalable databases with PostgreSQL 16

Arrow left icon
Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781837635641
Length 744 pages
Edition 2nd Edition
Languages
Arrow right icon
Authors (2):
Arrow left icon
Luca Ferrari Luca Ferrari
Author Profile Icon Luca Ferrari
Luca Ferrari
Enrico Pirozzi Enrico Pirozzi
Author Profile Icon Enrico Pirozzi
Enrico Pirozzi
Arrow right icon
View More author details
Toc

Table of Contents (22) Chapters Close

Preface 1. Introduction to PostgreSQL 2. Getting to Know Your Cluster FREE CHAPTER 3. Managing Users and Connections 4. Basic Statements 5. Advanced Statements 6. Window Functions 7. Server-Side Programming 8. Triggers and Rules 9. Partitioning 10. Users, Roles, and Database Security 11. Transactions, MVCC, WALs, and Checkpoints 12. Extending the Database – the Extension Ecosystem 13. Query Tuning, Indexes, and Performance Optimization 14. Logging and Auditing 15. Backup and Restore 16. Configuration and Monitoring 17. Physical Replication 18. Logical Replication 19. Useful Tools and Extensions 20. Other Books You May Enjoy
21. Index

Window Functions

In the previous chapter, we talked about aggregates. In this chapter, we are going to further discuss another way to make aggregates: window functions. The official documentation (https://www.postgresql.org/docs/current/tutorial-window.html) describes window functions as follows:

A window function performs a calculation across a set of table rows that are somehow related to the current row. This is comparable to the type of calculation that can be done with an aggregate function. However, window functions do not cause rows to become grouped into a single output row as non-window aggregate calls would. Instead, the rows retain their separate identities. Behind the scenes, the window function is able to access more than just the current row of the query result

In this chapter, we will talk about window functions, what they are, and how we can use them to improve the performance of our queries.

The following topics will be covered in this chapter...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime