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Mastering PostgreSQL 13

You're reading from   Mastering PostgreSQL 13 Build, administer, and maintain database applications efficiently with PostgreSQL 13

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Product type Paperback
Published in Nov 2020
Publisher Packt
ISBN-13 9781800567498
Length 476 pages
Edition 4th Edition
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Author (1):
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Hans-Jürgen Schönig Hans-Jürgen Schönig
Author Profile Icon Hans-Jürgen Schönig
Hans-Jürgen Schönig
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Table of Contents (15) Chapters Close

Preface 1. PostgreSQL 13 Overview 2. Understanding Transactions and Locking FREE CHAPTER 3. Making Use of Indexes 4. Handling Advanced SQL 5. Log Files and System Statistics 6. Optimizing Queries for Good Performance 7. Writing Stored Procedures 8. Managing PostgreSQL Security 9. Handling Backup and Recovery 10. Making Sense of Backups and Replication 11. Deciding on Useful Extensions 12. Troubleshooting PostgreSQL 13. Migrating to PostgreSQL 14. Other Books You May Enjoy

Understanding hypothetical aggregates

Hypothetical aggregates are pretty similar to standard ordered sets. However, they help to answer a different kind of question: what would be the result if a value was in the data? As you can see, this is not about values inside the database, but about the result if a certain value was actually there.

The only hypothetical function that's provided by PostgreSQL is rank, as shown in the following code:

test=# SELECT region, 
rank(9000) WITHIN GROUP
(ORDER BY production DESC NULLS LAST)
FROM t_oil
GROUP BY ROLLUP (1);
region | rank
---------------+------
Middle East | 21
North America | 27
| 47
(3 rows)

The preceding code tells us this: if somebody produced 9,000 barrels of oil per day, it would be ranked the 27th best year in North America and the 21st best year in Middle East.

In this example, I used NULLS LAST. When data is sorted, nulls are usually at the end. However, if the...
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