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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

Chapter 15. Partitioning Data

As databases grow, it's common to have a table or two become unmanageably large. If the table itself is much larger than the physical memory, and even its indexes stop fitting comfortably, query execution time will escalate. One way to deal with large tables is to partition them, which breaks the table into a series of smaller, related tables instead. You don't have to change your application, just keep querying the same table. But when the query can be answered by just using a subset of the data, rather than scanning the whole thing, this optimization can occur.

In this chapter we will be covering these topics:

  • Table range partitioning
  • Declarative partitioning
  • Horizontal partitioning with PL/Proxy

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