Microsoft SQL Server 2017 Automatic Tuning
Microsoft launched the SQL Servers to facilitate users for the management and prevention of data, keeping in mind the data management issues nowadays.
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Every new version of Microsoft SQL Server comes with powerful new features. Among all the best features of SQL Server, we will discuss the most important and basic feature, Automatic tuning. It is very important to know about the old ways of tuning so that you can easily understand how automatic tuning works and how is it different from the old method of tuning.
Whenever your database is having any issue regarding its performance, you try to apply a scientific method to find out what is going on. The traditional method involves a few actions such as: observe, ask questions, generate a theory, perform the experiment, get to the conclusion and gather results.
A good example could be a slow report. You observe the behavior of the report, note down how long the duration is and try to compare with old performance baselines so you get a good idea of how big is the issue that you are facing and why there is a lack in performance.
Then you ask questions such as:
Was a patch applied lately?
Did we change code or table structures?
After that, you try to generate a hypothesis. One theory can be that you have something missing in the index. To accomplish an experiment, you have to review the implementation plan of the particular query, check if you have bad operators, and examine how to fix them. You then create a conclusion that a new index is required and finally, share the new index script with the application management team.
After that, you can compare two performance plans. The previous plan without the index having bad performance versus the new plan with the index running faster.
SQL Server can track down Query Store data in the form of historical statistics of transactions with automatic tuning. After that auto-tuning will be able to tell if a query is unexpectedly under-performing. If a new stat breaks the average of a given stored procedure, it will be marked as a regressed query, meaning a TSQL that just started to present a bad behavior compared to old performance data.
SQL Server 2017 auto tuning will compare the old plan vs. the new plan and identify if the difference is significant enough. If it is important, then auto-tuning will proceed and implement the best plan possible.
We just skipped the scientific method as it was automatic, and a solution moved to production without human interference.
If you are willing to using automatic tuning, make sure to track down programs that are being executed by feature. You have to go deeper to fix an issue with the help of the scientific method finally. You can see the involuntary plan as a temporary Band-Aid. It is important that you take care of the issue. You do not want to end up with a web of compulsory plans which are tough to navigate. You have to keep these things in mind while dealing with an auto tuner.
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