SQL Server Query Performance Tuning


Автор: Grant Fritchey
Издательство: Apress

Год: 2014
Страниц: 593
Язык: Английский
Формат: PDF (Изначально электронное)
ISBN: 978-1-4302-6742-3

 


Аннотация:

Queries not running fast enough? Wondering about the in-memory database features in 2014? Tired of phone calls from frustrated users? Grant Fritchey’s book SQL Server Query Performance Tuning is the answer to your SQL Server query performance problems. The book is revised to cover the very latest in performance optimization features and techniques, especially including the newly-added, in-memory database features formerly known under the code name Project Hekaton. This book provides the tools you need to approach your queries with performance in mind.
SQL Server Query Performance Tuning leads you through understanding the causes of poor performance, how to identify them, and how to fix them. You’ll learn to be proactive in establishing performance baselines using tools like Performance Monitor and Extended Events. You’ll learn to 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, and upon heading off trouble before it occurs. Delight your users. Silence that ringing phone. Put the principles and lessons from SQL Server Query Performance Tuning into practice today.
Covers the in-memory features from Project Hekaton
Helps establish performance baselines and monitor against them
Guides in troubleshooting and eliminating of bottlenecks that frustrate users
What you’ll learn
- Establish performance baselines and monitor against them
- 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 so as to minimize performance risk
- Design in the performance that you need through careful query and index design
- Take advantage of the very latest performance optimization features in SQL Server 2014
- Understand the new, in-memory database features formerly code-named as Project Hekaton

 

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