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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

Summary


Attempts to improve database and operating system performance are best done using careful observation, not speculation, in order to determine where the system bottlenecks are. You need to start that before you have a performance problem, to record baseline information. Most production database servers should consider basic monitoring and trending setup a requirement of their early deployment.

However, it is helpful to know the low-level tools too because the longer-term views provided by most monitoring and trending tools will miss brief problems. With today's breed of database applications, even a pause lasting a few seconds could be a major response time failure, and it's one that you wouldn't even be able to see in data collected on a minute scale. Both short-term and long-term data collection has considerable value, and knowing when to switch the detail level focused to match the problem at hand is a valuable skill to hone.

Use vmstat on a very short timeframe to get a feel for...

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