نام کتاب
SQL Server 2017 Query Performance Tuning

Troubleshoot and Optimize Query Performance

Grant Fritchey

Paperback947 Pages
PublisherApress
Edition5
LanguageEnglish
Year2018
ISBN9781484238875
902
A3487
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توضیحات


Identify and fix causes of poor performance. You will learn Query Store, adaptive execution plans, and automated tuning on the Microsoft Azure SQL Database platform. Anyone responsible for writing or creating T-SQL queries will find valuable the insight into bottlenecks, including how to recognize them and eliminate them.


This book covers the latest in performance optimization features and techniques and is current with SQL Server 2017. If your queries are not running fast enough and you’re tired of phone calls from frustrated users, then this book is the answer to your performance problems. 


SQL Server 2017 Query Performance Tuning is about more than quick tips and fixes. You’ll learn to be proactive in establishing performance baselines using tools such as Performance Monitor and Extended Events. You’ll recognize bottlenecks and defuse them before the phone rings. You’ll learn some quick solutions too, but emphasis is on designing for performance and getting it right. The goal is to head off trouble before it occurs.


What You'll Learn

  • Use Query Store to understand and easily change query performance
  • Recognize and eliminate bottlenecks leading to slow performance
  • Deploy quick fixes when needed, following up with long-term solutions
  • Implement best practices in T-SQL to minimize performance risk
  • Design in the performance that you need through careful query and index design
  • Utilize the latest performance optimization features in SQL Server 2017
  • Protect query performance during upgrades to the newer versions of SQL Server


Who This Book Is For

Developers and database administrators with responsibility for application performance in SQL Server environments. Anyone responsible for writing or creating T-SQL queries will find valuable the insight into bottlenecks, including how to recognize them and eliminate them.


Table of Contents

Chapter 1: SQL Query Performance Tuning

Chapter 2: Memory Performance Analysis

Chapter 3: Disk Performance Analysis

Chapter 4: CPU Performance Analysis

Chapter 5: Creating a Baseline 

Chapter 6: Query Performance Metrics

Chapter 7: Analyzing Query Performance

Chapter 8: Index Architecture and Behavior

Chapter 9: Index Analysis 

Chapter 10: Database Engine Tuning Advisor

Chapter 11: Query Store 

Chapter 12: Key Lookups and Solutions 

Chapter 13: Statistics, Data Distribution, and Cardinality 

Chapter 14: Index Fragmentation 

Chapter 15: Execution Plan Generation 

Chapter 16: Execution Plan Cache Behavior

Chapter 17: Parameter Sniffing 

Chapter 18: Query Recompilation 

Chapter 19: Query Design Analysis 

Chapter 20: Reduce Query Resource Use 

Chapter 21: Blocking and Blocked Processes 

Chapter 22: Causes and Solutions for Deadlocks 

Chapter 23: Row-by-Row Processing 

Chapter 24: Memory-Optimized OLTP Tables and Procedures 

Chapter 25: Automated Tuning in Azure SQL Database and SQL Server 

Chapter 26: Database Performance Testing 

Chapter 27: Database Workload Optimization 

Chapter 28: SQL Server Optimization Checklist 


About the Author

Grant Fritchey, Microsoft Data Platform MVP, has more than 20 years of experience in IT. That time was spent in technical support, development, and database administration. He currently works as Product Evangelist at Red Gate Software. Grant writes articles for publication at SQL Server Central and Simple-Talk. He has published books, including SQL Server Execution Plans and SQL Server 2012 Query Performance Tuning (Apress). He has written chapters for Beginning SQL Server 2012 Administration (Apress), SQL Server Team-based Development, SQL Server MVP Deep Dives Volume 2, Pro SQL Server 2012 Practices (Apress), and Expert Performance Indexing in SQL Server (Apress). Grant currently serves as President on the Board of Directors of the PASS organization, the leading source of educational content and training on the Microsoft Data Platform. --This text refers to an out of print or unavailable edition of this title.

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