Category: Query Tuning

Itzik Ben-Gan has some solutions to show:

This month, I’m going to start exploring the submitted solutions, roughly, going from the worse performing to the best performing ones. Why even bother with the bad performing ones? Because you can still learn a lot from them; for example, by identifying anti-patterns. Indeed, the first attempt at solving this challenge for many people, including myself and Peter, is based on an interval intersection concept. It so happens that the classic predicate-based technique for identifying interval intersection has poor performance since there’s no good indexing scheme to support it. This article is dedicated to this poor performing approach. Despite the poor performance, working on the solution is an interesting exercise. It requires practicing the skill of modeling the problem in a way that lends itself to set-based treatment. It is also interesting to identify the reason for the bad performance, making it easier to avoid the anti-pattern in the future. Keep in mind, this solution is just the starting point.

Click through for a solution which is straightforward but slow.

Joe Obbish has a solution:

Itzik Ben-Gan posted an interesting T-SQL challenge on SQL performance dot com. I’m writing up my solution in my own blog post because I have a lot to say and getting code formatting right can be tricky in blog post comments. For reference, my test machine is using SQL Server 2019 CU14 with an i7-9700K CPU @ 3.60 GHz processor. The baseline cursor solution completes in 8465 ms on my machine.

Click through for a bit of formal logic and a lot of tuning.

Erik Darling has a recommendation:

When working with ORMs, care has to be taken to strongly type your parameters to match the data type, length, precision, and scale of the columns those parameters will be compared to. Time and time again, I see the same patterns with string parameters:

– They’re unnecessarily typed as Unicode/nvarchar

– They’re not defined with an appropriate length

– They’re used as catch-all parameters for temporal types (dates, etc.)

Spoiler: these aren’t benefits.

Brent Ozar just says no:

When you put NOLOCK in your query, SQL Server will:

– Read rows twice

– Skip rows altogether

– Show you changes that never actually got committed

– Let your query fail with an error

This is not a bug. This is by design. 

There are reasons why you might want to use NOLOCK, but start with no and you’ll be in better shape.

Also, remember that NOLOCK really means “No, lock!”