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SQL Server 2017 Developer???s Guide

SQL Server 2017 Developer???s Guide

3.6 (5)
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SQL Server 2017 Developer???s Guide

SQL Server 2017 Developer???s Guide

3.6 (5)

Overview of this book

Microsoft SQL Server 2017 is a milestone in Microsoft's data platform timeline, as it brings in the power of R and Python for machine learning and containerization-based deployment on Windows and Linux. This book prepares you for advanced topics by starting with a quick introduction to SQL Server 2017's new features. Then, it introduces you to enhancements in the Transact-SQL language and new database engine capabilities before switching to a different technology: JSON support. You will take a look at the security enhancements and temporal tables. Furthermore, the book focuses on implementing advanced topics, including Query Store, columnstore indexes, and In-Memory OLTP. Toward the end of the book, you'll be introduced to R and how to use the R language with Transact-SQL for data exploration and analysis. You'll also learn to integrate Python code into SQL Server and graph database implementations as well as the deployment options on Linux and SQL Server in containers for development and testing. By the end of this book, you will be armed to design efficient, high-performance database applications without any hassle.
Table of Contents (19 chapters)
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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 to explicitly or implicitly defined formatting rules.

FOR JSON AUTO

Use FOR JSON AUTO when you want to let SQL Server...

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