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PostgreSQL High Performance Cookbook

You're reading from   PostgreSQL High Performance Cookbook Mastering query optimization, database monitoring, and performance-tuning for PostgreSQL

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781785284335
Length 360 pages
Edition 1st Edition
Languages
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Authors (2):
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Chitij Chauhan Chitij Chauhan
Author Profile Icon Chitij Chauhan
Chitij Chauhan
Dinesh Kumar Dinesh Kumar
Author Profile Icon Dinesh Kumar
Dinesh Kumar
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Toc

Table of Contents (13) Chapters Close

Preface 1. Database Benchmarking FREE CHAPTER 2. Server Configuration and Control 3. Device Optimization 4. Monitoring Server Performance 5. Connection Pooling and Database Partitioning 6. High Availability and Replication 7. Working with Third-Party Replication Management Utilities 8. Database Monitoring and Performance 9. Vacuum Internals 10. Data Migration from Other Databases to PostgreSQL and Upgrading the PostgreSQL Cluster 11. Query Optimization 12. Database Indexing

Working with set operations

In this recipe, we will be discussing various PostgreSQL set operations.

Getting ready

PostgreSQL provides various set operations, which deal with multiple independent data sets. The supported set operators are UNION/ALL, INTERSECT/ALL, and EXCEPT/ALL. In general, we use the set operations in SQL when we need to either join or merge operations among independent datasets. To process these independent datasets, PostgreSQL will evaluate each dataset operation independently, and then it applies the given set operation on the final datasets.

How to do it…

  1. To demonstrate these set operations, let's query the benchmarsql to get all the customer IDs, that have not placed any online order:
    benchmarksql=# EXPLAIN SELECT c_id FROM bmsql_customer
    EXCEPT
    SELECT h_c_id FROM bmsql_history;
                                                           QUERY PLAN                                                        
    ----------------------------------------------...
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