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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

Capturing waits by Query Store in SQL Server 2017


As mentioned earlier, Query Store uses CPU time as the main criterion for execution plan comparison. Execution time often differs from CPU time, sometimes very significantly. In production environments, thousands or even hundreds of thousands of queries are running simultaneously and since most of them refer to the same database objects and SQL Server resources are limited, a query is usually not executed at once; during the execution, there are phases where instructions in the query are executed, and phases where the query waits for resources to be available to proceed with the execution. What a query is waiting for is very important information in performance troubleshooting. Unfortunately, waits were not captured by Query Store in SQL Server 2016, but SQL Server 2017 removes this limitation and increased captured data with this important information.

Since there are more than 900 wait types, in order to reduce Query Store’s impact on customer...

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