Curated SQL Posts

Andy Levy has a bone to pick:

Here’s the thing – these types are really just aliases for native types in SQL Server, but more constrained. Constrain yourself to UDTs and you’ll have trouble right-sizing your fields. Let’s say you’ve got three data types for text data:

– myShortString (varchar(10))
– myString (varchar(256))
– myBigString (varchar(8000))

These lengths are not helping anyone. You can’t store email addresses or names in myShortString. But myString is probably way too much for that data. You’re going to waste memory because of how SQL Server estimates memory grants and your indexes will be bloated. Maybe you just need to create more UDTs to cover these situations. But that just compounds the other problems, doesn’t it?

Pushes glasses up the bridge of his nose. Teeeeechnically, an e-mail address may be up to 256 characters long, including a username of up to 64 characters (and maybe two angle brackets, depending on the host). So myString would actually be perfect. Steve Jones has a comment about 300, but that was probably the original standard of 320. Regardless, I realize how far beside the point that is, and Andy’s point is a good one, as well as the several others he makes in the post.

One quick note on defined types: they really do make a lot of sense in a domain-driven design, especially when working with functional programming languages. Defining a CustomerID as an int is fine, but if I know my customer IDs are natural numbers (1, 2, 3, …), 9 digits long, and do not contain the sequence 2345 (because my company considers this an unlucky number sequence), creating a CustomerID type which provides this sort of type checking is great because you keep the rules as close to the data as possible and ensure consistency. It’s also more restrictive than int, so you can cast back down to an int when you’re ready to interact with some remote system. So short answer, do this all day in F#, but not in the database.

Hugo Kornelis levies a defense of floating point data types:

Let’s return to the database. Let’s figure out a way to store these numbers appropriately.

Could we use decimal (or its synonym numeric)? Well, yes. We can. We need 25 digits after the decimal place for 0.0000000000000000000004052, and 9 digits before the decimal place for 299900000, so that would fit in a decimal(34,25). But if you try to compute c² so you can then multiply that to the m, you’ll run into an overflow error.

Hugo does a good job of defending the float data type.

Deepthi Goguri has a complaint about VARCHAR(MAX):

Though VARCHAR(MAX) is suitable in situations with large strings of data, it has its own complications that we need to consider. In my career as a DBA, I at least saw couple of times SQL developers using VARCHAR(MAX) when they should not. Fixing the datatypes once in production is painful and causes risks.

I think Deepthi’s advice is sound: use VARCHAR(MAX) when necessary but not as a starting point. I don’t shy away from VARCHAR(MAX) on principle (except with columnstore indexes—get that noise right out of here) and I don’t think you should either, as long as you understand the ramifications.