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

Converting JSON data in a tabular format

Nowadays, JSON is a recognized format for data representation and exchange. However, most of the existing data still resides in relational databases and you need to combine them to process and manipulate them together. In order to combine JSON with relational data or to import it in relational tables, you need to map JSON data to tabular data, that is, convert it into a tabular format. In SQL Server 2016, you can use the OPENJSON function to accomplish this:

  • OPENJSON is a newly added rowset function. A rowset function is a table-valued function and returns an object that can be used as if it were a table or a view. Just as OPENXML provides a rowset view over an XML document, OPENJSON gives a rowset view over JSON data. The OPENJSON function converts JSON objects and properties to table rows and columns respectively.
  • It accepts two...