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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

Using sample data sets

There are enough sample data sets that are available for PostgreSQL, and most of the data sets are implemented by considering real-time business cases.

Note

Find the list of sample data sets that are available for postgres at this URL: https://wiki.postgresql.org/wiki/Sample_Databases.

Benchmarking tools such as pgBench and BenchmarkSQL will initiate a sample data set, on which they generate a real-time database load and do the benchmarking. In this chapter, to demonstrate a few aspects of the optimizer, let's choose the BenchmarkSQL's catalog tables, which will generate enough data load for this chapter's demonstrations.

Getting ready

BenchmarkSQL is an open source implementation of the popular TPC/C OLTP database benchmark, which supports Firebird, Oracle, and PostgreSQL and captures detailed benchmark results in CSV files, which can later be turned into an HTML report. BenchmarkSQL also captures the OS metrics, such as CPU and memory usages...

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