Learning PostgreSQL 11: A beginner’s guide to building high-performance PostgreSQL database solutions, 3rd Edition
By 作者: Salahaldin Juba – Andrey Volkov
ISBN-10 书号: 1789535468
ISBN-13 书号: 9781789535464
Release Finelybook 出版日期: 2019-01-31
pages 页数: (556 )
Book Description to Finelybook sorting
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.
Copyright and Credits
PostgreSQL in Action
PostgreSQL Basic Building Blocks
PostgreSQL Advanced Building Blocks
Advanced Query Writing
Server-Side Programming with PL/pgSQL
OLAP and Data Warehousing
Beyond Conventional Data Types
Transactions and Concurrency Control
The PostgresQL Catalog
Optimizing Database Performance
Using PostgreSQL in Python Applications
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What You Will Learn
Understand the basics of relational databases, relational algebra, and data modeling
Install a PostgreSQL server, create a database, and implement your data model
Create tables and views, define indexes and stored procedures, and implement triggers
Make use of advanced data types such as Arrays, hstore, and JSONB
Connect your Python applications to PostgreSQL and work with data efficiently
Identify bottlenecks to enhance reliability and performance of database applications
Salahaldin Juba has over than a decade of experience in the industry and academia, with a focus on database development for large-scale and enterprise applications. He holds a master’s degree of science in environmental management with a distinction, and a bachelor’s degree of engineering in computer systems. He is also a Microsoft Certified Solution Developer (MCSD).
He has worked mainly with SQL server, PostgreSQL, and Greenplum databases. As a software engineer, he works mainly with defining ETL processes with external parties, promoting SQL best practices, designing OLTP and OLAP applications, and providing training and consultation services.
Andrey Volkov studied information systems in banking, and started his career as a financial analyst at a commercial bank. He joined a data warehouse team, and after some time, he lead the team by taking the position of the data warehouse architect.
There he worked mainly with Oracle database stack and used it to develop logical and physical models of financial and accounting data, implement them in the database, develop ETL processes, and perform analytical tasks.
Now Andrey works as a senior database developer at a telecommunication provider. There, he works mainly with PostgreSQL databases, being responsible for data modeling, developing a data warehouse, reporting, and billing systems.