Creating an index is one of the most intensive operations you can do on a database. When populating a database using tools such as pg_restore, the time spent building indexes can be the longest part of the data loading. And you can't necessarily just ignore them afterwards. Index rebuilding can be an expected part of regular database maintenance, particularly in the case where many rows (but not all of them) are being deleted from a section of an index. There's more information about that topic back in Chapter 7, Routine Maintenance.

PostgreSQL 10 High Performance
By :

PostgreSQL 10 High Performance
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
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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