Book Image

SQL Server 2017 Developer's Guide

Book Image

SQL Server 2017 Developer's Guide

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 (25 chapters)
Title Page
Copyright and Credits
Dedication
Packt Upsell
Contributors
Preface
Free Chapter
1
Introduction to SQL Server 2017
Index

What is Query Store?


Query Store is the answer to the challenges described previously. It was introduced in SQL Server 2016 and extended in SQL Server 2017. It collects the most relevant information about executed queries: query text, parameters, query optimization and compilation details, execution plans, execution statistics (execution time, CPU and memory usage, I/O execution details), and wait statistics; Query Store stores them in a database so that they are available after server restarts, failovers, or crashes.

You can use Query Store not only to identify performance issues, but also to fix some of them. Query Store offers a solution for issues caused by changed execution plans. By using Query Store, you can easily enforce an old plan; it is not required to rewrite the query or to write any code. You don't affect the business logic, therefore there is no need for testing; there is neither code deployment nor an application restart. By taking this approach, you can quickly implement...