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Author Fritchey, Grant.

Title SQL Server 2022 Query performance tuning : troubleshoot and optimize Query performance / Grant Fritchey. [O'Reilly electronic resource]

Edition 6th edition
Publication Info. New York : Apress, 2022.
©2022
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Description 1 online resource (xxv, 720 pages : illustrations)
Series ITpro collection
Note Description based upon print version of record.
Includes index.
Contents Query Performance Tuning -- Execution Plan Generation and the Query Optimizer -- Methods for Capturing Query Performance Metrics -- Analyzing Query Behavior Using Execution Plans -- Statistics, Data Distribution, and Cardinality -- Using query store for query performance and execution plans -- Execution plan cache behavior -- Query recompilation -- Index architecture -- Index behaviors -- Key lookups and solutions -- Dealing with index fragmentation -- Parameter-sensitive queries: causes and solutions -- Query design analysis -- Reduce query resource use -- Blocking and blocked processes -- Causes and solutions for deadlocks -- Row-by-row processing from cursors and other causes -- Memory-optimized OLTP tables and procedures -- Graph databases -- Intelligent query processing -- Automated turning in Azure and SQL server -- A query tuning methodology.
Summary Troubleshoot slow-performing queries and make them run faster. Database administrators and SQL developers are constantly under pressure to provide more speed. This new edition has been redesigned and rewritten from scratch based on the last 15 years of learning, knowledge, and experience accumulated by the author. The book Includes expanded information on using extended events, automatic execution plan correction, and other advanced features now available in SQL Server. These modern features are covered while still providing the necessary fundamentals to better understand how statistics and indexes affect query performance. The book gives you knowledge and tools to help you identify poorly performing queries and understand the possible causes of that poor performance. The book also provides mechanisms for resolving the issues identified, whether on-premises, in containers, or on cloud platform providers. You'll learn about key fundamentals, such as statistics, data distribution, cardinality, and parameter sniffing. You'll learn to analyze and design your indexes and your queries using best practices that ward off performance problems before they occur. You'll also learn to use important modern features, such as Query Store to manage and control execution plans, the automated performance tuning feature set, and memory-optimized OLTP tables and procedures. You will be able to troubleshoot in a systematic way. Query tuning doesn't have to be difficult. This book helps you to make it much easier. What You Will Learn Use Query Store to understand and easily change query performance Recognize and eliminate bottlenecks leading to slow performance Tune queries whether on-premises, in containers, or on cloud platform providers Implement best practices in T-SQL to minimize performance risk Design in the performance that you need through careful query and index design Understand how built-in, automatic tuning can assist your performance enhancement efforts Protect query performance during upgrades to the newer versions of SQL Server Who This Book Is For Developers and database administrators with responsibility for query performance in SQL Server environments, and anyone responsible for writing or creating T-SQL queries and in need of insight into bottlenecks (including how to identify them, understand them, and eliminate them).
Bibliography Includes bibliographical references.
Subject SQL server.
SQL server
Querying (Computer science)
Query languages (Computer science)
Bases de données -- Interrogation.
Langages d'interrogation.
online searching.
Query languages (Computer science)
Querying (Computer science)
Other Form: Print version: Fritchey, Grant SQL Server 2022 Query Performance Tuning Berkeley, CA : Apress L. P.,c2022 9781484288900
ISBN 9781484288917 (electronic bk.)
1484288912 (electronic bk.)
Standard No. 10.1007/978-1-4842-8891-7 doi
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