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Mastering PostgreSQL 9.6

You're reading from   Mastering PostgreSQL 9.6 A comprehensive guide for PostgreSQL 9.6 developers and administrators

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Product type Paperback
Published in May 2017
Publisher
ISBN-13 9781783555352
Length 416 pages
Edition 1st Edition
Languages
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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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Toc

Table of Contents (14) Chapters Close

Preface 1. PostgreSQL Overview FREE CHAPTER 2. Understanding Transactions and Locking 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

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 there? 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 provided by PostgreSQL is rank. It tells us:

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)

If somebody produced 9000 barrels per day, it would be the 27 best year in North America and 21 in the Middle East.

Note that in my example, I used NULLS LAST. When data is sorted, nulls are usually at the end. However, if sort order...
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