Syntax – Page 2 – Curated SQL

Learning RegEx with Louis Davidson

Published 2025-08-04 by Kevin Feasel

Louis Davidson has a few blog posts for us to catch up on. So far, this is a four-part series on regular expressions and SQL Server.

Part 1 covers simple pattern matching:

I have never once written an regular expression prior to a couple of articles on this blog. And truth be told, when I published those blogs, I got the expression wrong because it seemed to work, and it was what Copilot told me would work. If you are new like me and/or your code is important, test with lots of cases. I obviously fixed that code (thankfully the conclusions were right).

So no, I have never. LIKE does 99% of what I need in a simple manner, and .8% of the time in a complex way, so I never really thought about it too much. I suspect that will be the case even now in SQL, but like any good student, it is time to change my knowledge of regular expressions.

Part 2 covers repeating patterns:

In this blog, I want to look for strings that have 1 or more instances of a repeating pattern. For example, say you want to look for something like the following:
LIKE'%FredFredFred%'

--(or any fixed or unlimited length of a, and only a)
LIKE'%aaaaaaaaaaaaaaa%'or'%aaaaaaa%'

Part 3 looks at matching sets of characters:

In this article, we are going to take an initial look at what are referred to as “character classes” or “character sets” in Regular Expressions. They are commonly used when looking for data to be in a certain format. For example:

We are going to look at how to set a filter for 'lll-ll-lln' and/or 'lll-ll-lll' (where l is letter and n is numeric).

And part 4 deals with negation:

In Part 3, I covered some of the basics of using character classes/sets. (I do tend to say sets.) This allowed us to do things like find words that start with a, b, c, d or e. This is done using: ^[a-e] or ^[abcde]. Now I want to look at two new things (one of which looks really similar to the previous classes but does things very differently.:

Negated character classes – Look for strings that don’t have a particular character in them

Perl character classes – shorthand for certain types of characters

Regular expressions can be very challenging to learn and even more challenging to troubleshoot and ensure there are no missing corner cases. But they offer an enormous amount of power and that makes it all worthwhile.

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Common Table Expressions in SQL Server and Materialization

Published 2025-07-28 by Kevin Feasel

Vlad Drumea is back to following Betteridge’s Law of Headlines and the people rejoice:

There’s this weird misconception floating around LinkedIn and reddit that SQL Server CTEs somehow store results in either memory or tempdb.

This is wrong and whoever states that CTEs store results either have no idea what they’re talking about or are intentionally trying to mislead people for engagement farming.

Click through for the proof of this.

As a quick note, you can materialize common table expressions in some relational database platforms like PostgreSQL, but SQL Server does not have that option.

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A Deep Dive into IDENTITY Columns

Published 2025-07-24 by Kevin Feasel

Vlad Drumea performs a deep dive:

In SQL Server, IDENTITY is a column-level property that is used to provide an auto-incremented value for every new row inserted.

All you have to do is provide a seed value and an increment value when defining said column, and SQL Server will handle it from there.

Unlike sequences, identity columns do not require additional objects like default constraints or triggers to ensure the column is populated.

I’m glad that Vlad made a demo showing how @@IDENTITY works and how it can give you unexpected outputs if you’re not aware of a trigger working with a separate identity column. That one tends to get people.

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The PRODUCT() Function in SQL Server 2025

Published 2025-07-22 by Kevin Feasel

Ed Pollack points out a new function:

With each version of SQL Server, there are always a few new features introduced that we applaud as we finally have access to a useful function that is already available elsewhere.

Introduced in SQL Server 2025 CTP 1.3, the PRODUCT() function acts similarly to SUM(), but multiplies values rather than adds them. It is an aggregate function in SQL Server and therefore operates on a data set, rather than on scalar values.

Ed notes that there are aggregate and window function versions of PRODUCT() and shows examples of how it works.

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Grouping Sets in T-SQL

Published 2025-07-21 by Kevin Feasel

Erik Darling has a new video.

Erik mentions that he doesn’t often see GROUPING SETS in the wild. I’ve used them several times. And the use of the term “several times” probably gives you exactly the feeling that I intended. I really like grouping sets for very specific analytical system purposes (at least for moderate-sized datasets), so I’m glad that syntax is there. But outside of reporting queries, it’s a really uncommon bit of syntax.

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Percentage Splits with Window Functions

Published 2025-07-21 by Kevin Feasel

Andy Brownsword breaks things up:

Sometimes you want to segment records. It may be splitting a customer base for marketing purposes, or segmenting a user base for a new feature. Good segmentation makes clean divisions in the data.

In this post we’ll see a way to achieve that with a great deal of help from Window Functions.

Click through for Andy’s motivation, which is a way that absolutely will not work the way you want it to.

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Result Set Chaining in Snowflake

Published 2025-07-17 by Kevin Feasel

Kevin Wilkie tries out a new operator:

In a recent Snowflake release, a slick new operator quietly entered the scene: ->>. This little guy can make certain query workflows both more readable and more efficient—especially when you’re dealing with multi-step commands like SHOW, LIST, or DESCRIBE.

Click through to see how it works. Seems that this operator has some pretty strict limitations, but for certain use cases, it’s quite nice.

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Regular Expressions in SQL Server 2025

Published 2025-07-15 by Kevin Feasel

Ed Pollack digs into some new functionality:

String-searching in SQL Server has always been a mighty hassle. Balancing performance and horribly-complex queries is a compromise that no one enjoys.

Generally speaking, a relational database is not an ideal place to search large amounts of text. Even when leveraging features such as Full-Text Indexing, the ability for an application to leverage speedy text-searching decreases as data becomes larger. If a service optimized for text-search can be used, such as Elasticsearch or Azure AI Search, then it will be far easier to deliver accurate results quickly.

Ed focuses on the mechanisms available rather than performance, and that’s the current sticking point. Whether regular expression queries will get faster in subsequent CTPs or SQL Server 2025 RTM, we’ll see.

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DISTINCT vs VALUES in DAX

Published 2025-07-02 by Kevin Feasel

Marco Russo and Alberto Ferrari compare two keywords:

When you begin modelling in DAX, DISTINCT and VALUES often appear interchangeable: both return the list of unique values for a column in the current filter context. In a clean development model, they behave the same, so it is easy to pick one at random – or worse, swap between them without thinking.

However, they are not identical. The subtle difference is crucial in production models that may one day contain invalid relationships or bad data.

Read on to see how each works and how they differ in practice.

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Reshaping Data with the APPLY Operator

Published 2025-06-11 by Kevin Feasel

I have a new video:

In this video, I show how we can use the APPLY operator to reshape datasets, allowing us to unpivot tables and also calculate the greatest and least values for a row.

If you look closely at the scripts, you’ll see 08 and 10. In the source control repo, I also have a script 09 that covers splitting strings. Using APPLY to split strings has always been a bit of a niche case, but prior to SQL Server 2016’s introduction of STRING_SPLIT() and SQL Server 2022’s improvement of the function, I could make the case that it sometimes made sense to know how to split strings via APPLY. Today, not so much, which is why I tossed that demo from the video.

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Category: Syntax