PostgreSQL has become an increasingly viable database platform to serve as storage for applications, from classic corporate database use to the latest web apps. But getting the best performance from it is not an easy subject to learn. You need just the right combination of thumb rule to get started, solid monitoring, and maintenance to keep your system running as well as suggestions for troubleshooting, and add-on tools to add the features the core database doesn't try to handle on its own. This book is an update of the book PostgreSQL 9.6 High Performance.
PostgreSQL 10 High Performance - Third Edition
By :
PostgreSQL 10 High Performance - Third Edition
By:
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 (18 chapters)
Preface
Free Chapter
PostgreSQL Versions
Database Hardware
Database Hardware Benchmarking
Disk Setup
Memory for Database Caching
Server Configuration Tuning
Routine Maintenance
Database Benchmarking
Database Indexing
Query Optimization
Database Activity and Statistics
Monitoring and Trending
Pooling and Caching
Scaling with Replication
Partitioning Data
Avoiding Common Problems
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