I recently released a Pluralsight Course Analyzing SQL Server Query Plans, and it is really doing great in terms of viewership and I have received some really great comments and feedback about this course. This week, I will be discussing different aspects of Analyzing SQL Server Query Plans. Today we will discuss Create Efficient Query Plans Using Query Store.
When the query store was a new product I was really not sure how to actually the product until I implemented it in the real world for the first time. Query store is an amazing feature if we know how to use it and how to translate the feature to success. Till today, I see lots of users who have enabled query stores for their database but have no idea how to use it efficiently. Many people just use it as a query repository and that is just an extremely limited use of this product.
There can be many different usages of the Query Store but I have been using it for three major things.
- After SQL Server upgrade tracking Query regressions
- Fixing parameter spoofing issues
- Tracking wait statistics for specific queries
Query Store Reports
Though the query store may look complicated the easiest part of the query store is actually query store reports. There are few readymade reports which you can use it identify the troublesome queries and also remedy their fixes.
- Regressed Queries
- Overall Resource Consumption
- Top Resource Consuming Queries
- Queries With Forced Plans
- Queries With High Variation
- Queries With Wait Statistics
- Tracked Queries
Pluralsight Course Analyzing SQL Server Query Plans
In the Pluralsight Course Analyzing SQL Server Query Plans, I discuss how to Create Efficient Query Plans Using Query Store. I explain to you how you can implement your query store and use it later on to identify the troublemaking query plans. The course is of only 2 hours and 30 minutes and if you have a Pluralsight subscription, you can watch it for free. If you do not have a Pluralsight subscription, you can still watch the course for FREE by signing up for a trial account.
Reference: Pinal Dave (https://blog.sqlauthority.com)