In order to detect, troubleshoot, and prevent parameter sniffing issues, we’re going to need: Metrics about how queries are performing Different versions of the query plans that caused those metrics To collect them, we’re going to go from the lowest-overhead, least-data solutions first, and then gradually progress to the collection methods that have the highest…
2.1 Spotting Wild Variations in the Plan Cache
In order to detect, troubleshoot, and prevent parameter sniffing issues, we’re going to need: Metrics about how queries are performing Different versions of the query plans that caused those metrics To collect them, we’re going to go from the lowest-overhead, least-data solutions first, and then gradually progress to the collection methods that have the highest...
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- 0.1 Prerequisites Before the Class
- 0.2 Download the Slides and Scripts
- 1.1 How Index Tuning Reduces the Stench
- 1.2 How Query Hints Reduce the Stench
- 1.3 The Drawbacks of Using Recompile Hints
- 1.4 Lab 1: Get One Plan to Work Well Enough for Most
- 1.5 Bad Branching Causes Sniffing, Good Branching Reduces It
- 1.6 Lab 2: Reducing Sniffing by Caching Multiple Plans
- 2.2 How Freeing the Plan Cache Reduces the Blast Radius: usp_PlanCacheAutopilot
- 2.3 Tracking Even More Plan Cache Details with Query Store
- 2.4 Lab 3: Track Down Plans & Parameters
- 3.1 How Memory Grant Feedback Multiplies Parameter Sniffing
- 3.2 How Adaptive Joins Help, and How to Get Them
- 3.3 How Automatic Tuning Mitigates Parameter Sniffing
- 4.1 Lab 4 Setup: Fixing the Problems You’ve Been Tracking Down
- 4.2 Tuning usp_SearchPostsByPostType
- 4.3 Tuning usp_RptFastestAnswers
- 4.4 Tuning usp_SearchPostsByLocation
- 4.5 Tuning usp_RptQuestionsAnsweredForUser
- 4.6 Tuning usp_SearchUsers
- 4.7 Tuning usp_RptPostLeaderboard
- 4.8 Tuning usp_RptAvgAnswerTimeByTag
- Bonus Lab: Seeing the Effects of SQL Server 2019 Compat Mode
- Bonus: Storytelling Time