Book Image

Mastering SQL Server 2017

By : Miloš Radivojević, Dejan Sarka, William Durkin, Christian Cote, Matija Lah
Book Image

Mastering SQL Server 2017

By: Miloš Radivojević, Dejan Sarka, William Durkin, Christian Cote, Matija Lah

Overview of this book

Microsoft SQL Server 2017 uses the power of R and Python for machine learning and containerization-based deployment on Windows and Linux. By learning how to use the features of SQL Server 2017 effectively, you can build scalable apps and easily perform data integration and transformation. You’ll start by brushing up on the features of SQL Server 2017. This Learning Path will then demonstrate how you can use Query Store, columnstore indexes, and In-Memory OLTP in your apps. You'll also learn to integrate Python code in SQL Server and graph database implementations for development and testing. Next, you'll get up to speed with designing and building SQL Server Integration Services (SSIS) data warehouse packages using SQL server data tools. Toward the concluding chapters, you’ll discover how to develop SSIS packages designed to maintain a data warehouse using the data flow and other control flow tasks. By the end of this Learning Path, you'll be equipped with the skills you need to design efficient, high-performance database applications with confidence. This Learning Path includes content from the following Packt books: SQL Server 2017 Developer's Guide by Miloš Radivojevi?, Dejan Sarka, et. al SQL Server 2017 Integration Services Cookbook by Christian Cote, Dejan Sarka, et. al
Table of Contents (20 chapters)
Title Page
Free Chapter
1
Introduction to SQL Server 2017

Retrieving SQL Server data in JSON format

This section explores JSON support in SQL Server with a very common action: formatting tabular data as JSON. In SQL Server 2017, the clause FOR JSON can be used with the SELECT statement to accomplish this. It is analogous to formatting relational data as XML by using the FOR XML extension.

When you use the FOR JSON clause, you can choose between two modes:

  • FOR JSON AUTO: The JSON output will be formatted by the structure of the SELECT statement automatically.
  • FOR JSON PATH: The JSON output will be formatted by the structure explicitly defined by you. With JSON PATH, you can create a more complex output (nested objects and properties).

In both modes, SQL Server extracts relational data defined by the SELECT statement, converts SQL Server data types to appropriate JSON types, implements escaping rules, and finally formats the output according...