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Category: T-SQL

Refreshing a View in SQL Server

Published 2024-03-25 by Kevin Feasel

Chad Callihan hits the reset button:

I recently encountered a question related to views: what happens when you make a change to the table that a view is based on? For example, if you change a column from VARCHAR(8) to VARCHAR(20), how does the view handle that change? You might expect the view to update, but it won’t do it on its own. You have to refresh the view.

Let’s look at a mocked up example.

Click through for that example. You’d think it could do so on its own, but nope. I suppose the reason you can’t is probably related to linked server and external object references in views, where that remote resource can change schema and SQL Server wouldn’t know about it. Perhaps also the idea that a person may be authorized to change a table in one database or schema but shouldn’t be authorized to modify (even to refresh?) a particular view that references the table.

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Calculating Percentages in T-SQL

Published 2024-03-21 by Kevin Feasel

Edwin Sanchez shows a variety of methods to calculate percentages of the whole in T-SQL:

Calculating percentages in SQL Server is like slicing a pie. You need to know the total size (the denominator) and the size of the slice you want (the numerator). To get a percentage, you divide the slice size by the total size and multiply by 100. 

Read on for a variety of methods to calculate this. I wouldn’t use all of the methods myself, as I have certain predilections against subqueries in the SELECT clause, but they do get the job done.

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The Proper Use of Views and Inline UDFs

Published 2024-03-20 by Kevin Feasel

Erik Darling plays tic-tac-toe:

The problem is really the stuff that people stick into views. They’re sort of like a junk drawer for data. Someone builds a view that returns a correct set of results, which becomes a source of truth. Then someone else comes along and uses that view in another view, because they know it returns the correct results, and so on and so on. Worse, views tend to do a bunch of data massaging, left joining and coalescing and substringing and replacing and case expressioning and converting things to other things. The bottom line is that views are as bad as you make them.

The end result is a trash monster with a query plan that can only be viewed in full from deep space.

Read on to learn the use cases for views and inline UDFs, as well as a few important notes regarding performance of each. Views are like mogwai: they’re fine as long as you never get them wet and never let them eat after midnight. The problem is, far too many companies are apparently the business equivalent of all-you-can-eat buffets at water parks.

Inline user-defined functions are like patenting a device that lets you shoot yourself in both feet with one pull of the trigger. Which, if I understand things correctly, means you’ll need a Form 4 for each inline UDF.

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Dropping Objects in SQL Server and Snowflake

Published 2024-03-20 by Kevin Feasel

Kevin Wilkie gets the drop on us:

When you’re working between SQL Server and Snowflake, there can be a lot of crossover that may make you forget what system you’re working in. Sometimes it’s close, but not close enough.

Today, let’s go over something that should be rather simple – removing old objects that we shouldn’t need any longer.

Read on to see how the two data platform technologies differ in this regard.

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Thoughts on Common Table Expressions

Published 2024-03-19 by Kevin Feasel

Erik Darling has opinions:

Much like joins and Venn diagrams, anyone who thinks they have some advanced hoodoo to teach you about common table expressions is a charlatan or a simpleton. They are one of the least advanced constructs in T-SQL, and are no better or worse than any other abstraction layer, with the minor exception that common table expressions can be used to build recursive queries.

As I read through the post, I kept wanting to disagree with Erik more than I do. My short form is, I aesthetically prefer common table expressions to subqueries. But that doesn’t make CTEs faster.

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Using IN and NOT IN in SQL Server

Published 2024-03-18 by Kevin Feasel

Erik Darling shares some advice:

I’ll be brief here, and let you know exactly when I’ll use IN and NOT IN rather than anything else:

  • When I have a list of literal values

That’s it. That’s all. If I have to go looking in another table for anything, I use either EXISTS or NOT EXISTS. The syntax just feels better to me, and I don’t have to worry about getting stupid errors about subqueries returning more than one value.

I’m typically a lot more flexible about using IN, though I do agree with NOT IN: that clause is usually more trouble than it’s worth.

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Using the APPLY Operator

Published 2024-03-14 by Kevin Feasel

Erik Darling gets an auto-link for talking about my favorite operator:

I end up converting a lot of derived joins, particularly those that use windowing functions, to use the apply syntax. Sometimes good indexes are in place to support that, other times they need to be created to avoid an Eager Index Spool.

One of the most common questions I get is when developers should consider using apply over other join syntax.

The short answer is that I start mentally picturing the apply syntax being useful when:

To learn when, you’re going to have to read the whole thing. And, if you want to learn even more about it, I have a talk on the topic that might be of interest.

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Comparing TOP(1) + ORDER BY vs MAX() Performance in SQL Server

Published 2024-03-06 by Kevin Feasel

Andy Brownsword breaks out the stopwatch:

The TOP clause limits the number of results which are returned from a query, in this instance we’re focussing on a single result. In contrast, when using MAX we’re applying a function to our data to select the largest value from our data.

Let’s dive into some examples with the StackOverflow data, specifically the Votes table.

Read on for several scenarios and how the two perform. Things get a bit more complicated as you introduce other tables in joins and similar additional factors, but this gives you a good foundation for comparison.

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