
Pro SQL Server Wait Statistics
Description
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Pro SQL Server Wait Statistics is a practical guide for analyzing and troubleshooting SQL Server performance using wait statistics. Whether you are new to wait statistics, or already familiar with them, this book will help you gain a deeper understanding on how wait statistics are generated and what they can mean for your SQL Server's performance.
Besides the most common wait types, Pro SQL Server Wait Statistics goes further into the more complex and performance threatening wait types. The different wait types are categorized by their area of impact, and include CPU, IO, Lock, and many more different wait type categories. Filled with clear examples, Pro SQL Server Wait Statistics helps you gain practical knowledge of why and how specific wait times increase or decrease, and how they impact your SQL Server's performance.
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Person
Enrico van de Laar is a SQL Server professional who specializes in performance tuning and analysis. Enrico is a Microsoft MVP for SQL Server, and a speaker at various SQL Server events around the world. He works for an IT company which focuses on the Dutch healthcare sector, from where he manages, troubleshoots, and optimizes the databases of some of the largest hospitals in The Netherlands.
Content
Introduction
Part I: Foundations of Wait Statistics Analysis
1. How Wait Statistics are Generated
2. Querying Wait Statistics
3. Building a Solid Baseline
Part II: Wait Types
4. CPU Wait Types
5. I/O Wait Types
6. Backup Wait Types
7. Lock Wait Types
8. Latch Wait Types
9. High-Availability and Disaster Recovery Wait Types
10: Preemptive Wait Types
11: Background and Miscellaneous Wait Types
12. Chapter 12
13: Appendix A
14. Appendix B
15. Appendix C
System requirements
File format: PDF
Copy protection: Watermark-DRM (Digital Rights Management)
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This eBook uses Watermark-DRM, a „soft” copy protection. This means that there are no technical restrictions to prevent illegal distribution. However, there is a personalised watermark embedded in the eBook that can be used to identify the purchaser of the eBook in the event of misuse and to provide evidence for legal purposes.
For more information, see our eBook Help page.