Book Image

Learning PostgreSQL 11 - Third Edition

By : Salahaldin Juba, Andrey Volkov
Book Image

Learning PostgreSQL 11 - Third Edition

By: Salahaldin Juba, Andrey Volkov

Overview of this book

PostgreSQL is one of the most popular open source database management systems in the world, and it supports advanced features included in SQL standards. This book will familiarize you with the latest features in PostgreSQL 11, and get you up and running with building efficient PostgreSQL database solutions from scratch. Learning PostgreSQL, 11 begins by covering the concepts of relational databases and their core principles. You’ll explore the Data Definition Language (DDL) and commonly used DDL commands supported by ANSI SQL. You’ll also learn how to create tables, define integrity constraints, build indexes, and set up views and other schema objects. As you advance, you’ll come to understand Data Manipulation Language (DML) and server-side programming capabilities using PL/pgSQL, giving you a robust background to develop, tune, test, and troubleshoot your database application. The book will guide you in exploring NoSQL capabilities and connecting to your database to manipulate data objects. You’ll get to grips with using data warehousing in analytical solutions and reports, and scaling the database for high availability and performance. By the end of this book, you’ll have gained a thorough understanding of PostgreSQL 11 and developed the necessary skills to build efficient database solutions.
Table of Contents (18 chapters)

Partitioning

Data is constantly or periodically loaded into a data warehouse. The database can grow very big. The bigger it gets, the slower it works. The size of the database is limited by the capacity of the disk storage, so part of it needs to be deleted from time to time. Deletion from a very big table can also be quite slow.

The data that is newer is usually queried more often. Business users could check the reports of the last day every morning, of the last week every Monday, and of the last month at the beginning of the next month. It's common to compare the results of a time period with a corresponding previous period; for example, the current month as compared to the previous month, or to the respective month one year ago. It's unlikely that somebody would query ten-year-old data.

It would be nice to keep the newer, more-queried data in one relatively small...