Category: T-SQL

Eric Blinn probably exists:

I’ve seen the EXISTS keyword in Microsoft SQL Server T-SQL code and don’t understand it well. What does it do? How do I use it? Are there best practices around SQL EXISTS?

This SQL tutorial will explain what the keyword EXISTS does and show several different use cases.

Read on to see how you can use EXISTS and its complement, NOT EXISTS, in a variety of use cases. One important part of why EXISTS can be useful compared to other ways of writing a particular query is that the performance profile of an EXISTS clause is a semi-join: we proceed until we find the first result matching our clause. If that happens to be in the first row, we can stop there as we’ve fulfilled the requirement. By contrast, an alternative using IN or something else like using SELECT COUNT(*) would likely need to read more pages of data than EXISTS.

Kevin Wilkie has fun with an unexpected character:

The query ran just fine so I happily completed my work for the day. I sent it to my QA team and had them check it out before pushing it to Production. They sent it back with a note saying “We expect a lot more “Insert Garbage Data Here” to show.

Being a good data developer – or someone who just wants to show QA up (take your pick) – decided to dig deep into what FieldName really shows. I found a lot of the following:

In Kevin’s case, he tried to use TRIM() and it didn’t fix anything. That’s because TRIM(), by default, only removes the space character (up to the first non-space character), not all whitespace and not the null character CHAR(0) that Kevin found.

An alternative version of TRIM() that would have worked in this case, plus adding in tabstops as well, would be:

SELECT
    TRIM(' '+char(0)+char(9) FROM FieldName) AS TrimmedFieldName
FROM dbo.SomeTable;
GO

And you could also extend that to include newlines, line feeds, vertical tabs, the line separator character, and whatever else you need.

Andy Brownsword is looking for a discount:

Performing a wildcard search by throwing a % into a LIKE expression is bread and butter. How do we handle this when we actually want to search for the wildcard though?

This was an issue I first saw early in my career before I was even building database solutions. The business had a back office solution where you could search through offers on the UI. Unfortunately it threw up some strange results.

Searching for ‘30%’ offers would return more than expected.

Read on for an example of the problem, as well as how you can resolve it.