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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

Bulk loading


There are two slightly different types of bulk data loads you might want to do. The first type, and the main focus of this section, is when you're initially populating an empty database. Sometimes you also need to do later bulk loads into tables that are already populated. In that case, some of the techniques here, such as dropping indexes and constraints, will no longer be applicable. And you may not be able to get quite as aggressive in tuning the server for better loading speed when doing incremental loading. In particular, options that decrease the integrity of the whole server, such as disabling fsync, only make sense when starting with a blank system.

Loading methods

The preferred path to get a lot of data into the database is by using the COPY command. This is the fastest way to insert a set of rows. If that's not practical and you have to use INSERT instead, you should try to include as many records as possible per commit, wrapping several into a BEGIN/COMMIT block. Most...

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