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Learning PostgreSQL 10

You're reading from   Learning PostgreSQL 10 A beginner's guide to building high-performance PostgreSQL database solutions

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Product type Paperback
Published in Dec 2017
Publisher
ISBN-13 9781788392013
Length 488 pages
Edition 2nd Edition
Languages
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Authors (2):
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Andrey Volkov Andrey Volkov
Author Profile Icon Andrey Volkov
Andrey Volkov
Salahaldin Juba Salahaldin Juba
Author Profile Icon Salahaldin Juba
Salahaldin Juba
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Toc

Table of Contents (17) Chapters Close

Preface 1. Relational Databases FREE CHAPTER 2. PostgreSQL in Action 3. PostgreSQL Basic Building Blocks 4. PostgreSQL Advanced Building Blocks 5. SQL Language 6. Advanced Query Writing 7. Server-Side Programming with PL/pgSQL 8. OLAP and Data Warehousing 9. Beyond Conventional Data Types 10. Transactions and Concurrency Control 11. PostgreSQL Security 12. The PostgreSQL Catalog 13. Optimizing Database Performance 14. Testing 15. Using PostgreSQL in Python Applications 16. Scalability

Parallel query


PostgreSQL creates a server process for each client connection. This means that only one CPU core will be used to perform all the work. Of course, when multiple connections are active, the resources of the server machine will be used intensively. However, in the data warehouse solutions, the number of concurrent sessions is usually not very big. They tend to perform big complex queries. It makes sense to utilize multiple CPU cores to process the queries of a single client connection. 

PostgreSQL supports a feature called parallel query that makes it possible to use multiple CPUs for one query. Certain operations like table scans, joins, or aggregation can be executed in several processes concurrently. The administrator can configure the number of workers that the PostgreSQL server will create for parallel query execution. When the query optimizer can detect a benefit from parallel execution, it will request some workers, and if they are available the query (or a part of it...

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