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Learning PostgreSQL 10

Learning PostgreSQL 10

By : Juba, Volkov
2.3 (6)
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Learning PostgreSQL 10

Learning PostgreSQL 10

2.3 (6)
By: Juba, Volkov

Overview of this book

PostgreSQL is one of the most popular open source databases in the world, supporting the most advanced features included in SQL standards. This book will familiarize you with the latest features released in PostgreSQL 10. We’ll start with a thorough introduction to PostgreSQL and the new features introduced in PostgreSQL 10. We’ll cover the Data Definition Language (DDL) with an emphasis on PostgreSQL, and the common DDL commands supported by ANSI SQL. You’ll learn to create tables, define integrity constraints, build indexes, and set up views and other schema objects. Moving on, we’ll cover the concepts of Data Manipulation Language (DML) and PostgreSQL server-side programming capabilities using PL/pgSQL. We’ll also explore the NoSQL capabilities of PostgreSQL and connect to your PostgreSQL database to manipulate data objects. By the end of this book, you’ll have a thorough understanding of the basics of PostgreSQL 10 and will have the necessary skills to build efficient database solutions.
Table of Contents (17 chapters)
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Parallel query


PostgreSQL creates a server process for each client connection. This means that only one CPU core will be used to perform all the work. Of course, when multiple connections are active, the resources of the server machine will be used intensively. However, in the data warehouse solutions, the number of concurrent sessions is usually not very big. They tend to perform big complex queries. It makes sense to utilize multiple CPU cores to process the queries of a single client connection. 

PostgreSQL supports a feature called parallel query that makes it possible to use multiple CPUs for one query. Certain operations like table scans, joins, or aggregation can be executed in several processes concurrently. The administrator can configure the number of workers that the PostgreSQL server will create for parallel query execution. When the query optimizer can detect a benefit from parallel execution, it will request some workers, and if they are available the query (or a part of it...

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