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PostgreSQL 10 High Performance

PostgreSQL 10 High Performance

By : Enrico Pirozzi
2.5 (2)
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PostgreSQL 10 High Performance

PostgreSQL 10 High Performance

2.5 (2)
By: Enrico Pirozzi

Overview of this book

PostgreSQL database servers have a common set of problems that they encounter as their usage gets heavier and requirements get more demanding. Peek into the future of your PostgreSQL 10 database's problems today. Know the warning signs to look for and how to avoid the most common issues before they even happen. Surprisingly, most PostgreSQL database applications evolve in the same way—choose the right hardware, tune the operating system and server memory use, optimize queries against the database and CPUs with the right indexes, and monitor every layer, from hardware to queries, using tools from inside and outside PostgreSQL. Also, using monitoring insight, PostgreSQL database applications continuously rework the design and configuration. On reaching the limits of a single server, they break things up; connection pooling, caching, partitioning, replication, and parallel queries can all help handle increasing database workloads. By the end of this book, you will have all the knowledge you need to design, run, and manage your PostgreSQL solution while ensuring high performance and high availability
Table of Contents (23 chapters)
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Title Page
Dedication
Packt Upsell
Contributors
Preface
Index

Common performance issues


Many performance issues come from bad designs or implementations that just don't fundamentally work well with PostgreSQL. There are a few areas where the problem is not so bad; it's more of a quirk with known workarounds. This section covers some of the more common problems new PostgreSQL users run into from this category.

Counting rows

It's not unusual to find an application that does the following to determine how many rows there are in a table:

SELECT count(*) FROM t;

In some databases other than PostgreSQL, this executes very quickly, usually because that information is kept handy in an index or similar structure. Unfortunately, because PostgreSQL keeps its row visibility information in the row data pages, you cannot determine a true row count without looking at every row in the table, one at a time, to determine whether they are visible or not. That's a sequential scan of the full table, and it's pretty slow; it even turns out to be an effective way to benchmark...

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