SQL Server Query Performance Tuning by Grant FritcheyQueries not running fast enough? Wondering about the in-memory database features in 2014? Tired of phone calls from frustrated users? Grant Fritcheys 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. Youll learn to be proactive in establishing performance baselines using tools like Performance Monitor and Extended Events. Youll learn to recognize bottlenecks and defuse them before the phone rings. Youll 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
How To Troubleshoot a Slow Running Query in SQL Server Extended Events & Wait Stats (by Amit Bansal)
Interview questions for SQL Server Performance Tuning Specialists
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Q2: Explain how the SQL Server Engine uses an Index Allocation Map (IAM)?
Now these functions can be user defined or inbuilt. These functions normally provide functionality which would be very difficult to get without these functions. Now when these functions are used improperly in the WHERE clause these functions can cause major performance issues. Now what is SARgable? It is Search Argument able. Add actual execution plan and statistics IO ON for better understanding. Both the above queries are working fine and we got rows in both the case.
Tables incur extra index maintenance overhead. Generally, OLTP database designs should keep the number of indexes to a functional minimum , again due to the high volumes of similar transactions combined with the cost of index maintenance. Unused indexes should be eliminated. Any index that has been used by select, update or delete operations will appear in sys. Always choose the smallest appropriate data type. Keep the code in your triggers to the very minimum to reduce overhead. See sys.