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SQL Server Query Tuning and Optimization

SQL Server Query Tuning and Optimization

By : Benjamin Nevarez
4.9 (13)
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SQL Server Query Tuning and Optimization

SQL Server Query Tuning and Optimization

4.9 (13)
By: Benjamin Nevarez

Overview of this book

SQL Server is a relational database management system developed by Microsoft. As a database server, it is a software product with the primary function of storing and retrieving data as requested by other software applications. This book starts by describing the inner workings of the query optimizer, and will enable you to use this knowledge to write better queries and provide the query engine with all the information it needs to produce efficient execution plans. As you progress, you’ll get practical query optimization tips for troubleshooting underperforming queries. The book will also guide you through intelligent query processing and what is new in SQL Server 2022. Query performance topics such as the Query Store, In-Memory OLTP and columnstore indexes are covered as well. By the end of this book, you’ll be able to get the best possible performance for your queries and applications.
Table of Contents (14 chapters)
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Chapter 9: The Query Store

This chapter covers the Query Store, a feature introduced with SQL Server 2016 that allows you to troubleshoot queries and execution plan-related issues and monitor performance history. The Query Store collects information about queries, plans, and runtime statistics, helping you pinpoint performance differences due to changes in execution plans.

The Query Store has been improved with every release since then and, new with SQL Server 2022, allows you to enable some of the new intelligent query processing features. For example, features such as memory grant feedback, cardinality estimation feedback, and degree of parallelism feedback use the Query Store to persist their information on queries and plans.

New with SQL Server 2022, the Query Store can also be enabled on secondary replicas used by Always On availability groups. This can help in scenarios where you want to troubleshoot query performance on read-only workloads running on secondary replicas...

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