Optimizing a string split and search

We’re no strangers to doing things in T-SQL that would perhaps be more efficient in a procedural language. Love it or hate it, a T-SQL solution is easier in some situations, like my sp_ctrl3 procedure that I use as a drop-in replacement for the standard sp_help procedure to display object information in a way that simplifies copying and pasting.

One of the things that sp_ctrl3 does is plaintext database search. If you pass a string to the procedure that does not match an existing object, it’ll just perform a plaintext search of all SQL modules (procedure, views, triggers, etc) for that string. The search result includes line numbers for each result, so it needs to split each module into lines.

I’ve found that this takes a very long time to run in a database with large stored procedures, so here’s how I tuned it to run faster.

How to run your CTE just once, and re-use the output

You may already know that common table expressions, like views, don’t behave like regular tables. They’re a way to make your query more readable by allowing you to write a complex SQL expression just once, rather than repeating it all over your statement or view. This makes reading, understanding and future refactoring of your code a little less painful.

But they’re no magic bullet, and you may end up with some unexpected execution plans.

An alternative to data masking

Dynamic data masking is a neat new feature in recent SQL Server versions that allows you to protect sensitive information from non-privileged users by masking it. But using a brute-force guessing attack, even a non-privileged user can guess the contents of a masked column. And if you’re on SQL Server 2014 or earlier, you won’t have the option of using data masking at all.

Read on to see how you can bypass dynamic data masking, and for an alternative approach that uses SQL Server column-level security instead.

Catching circular references in parent-child structures

A popular form of organizing dimensions is in parent-child structures, also known as “unbalanced” or “ragged” dimensions, because any branch can have an arbitrary number of child levels. There are many advantages to this type of representation, but their recursive nature also brings some challenges. In this post, we’re going to look at circular references, and how you can trap them before they run out of control.

Joining two SCD2 tables

A number of OLTP systems store dimension data in SCD2-like tables in order to retain all the revisions whenever the dimension information changes. In certain situations, you may come across a need to join two or more SCD tables, while keeping all the versions information intact. Sound tricky? Not really.

An indented representation of a parent-child hierarchy

When you’re designing reports, they can often be based on hiearchies represented by “nodes” in a parent-child setup. To the end-user, the parent-child representation doesn’t provide very much readability, so you need to output this information in a human-readable form, for instance in a table where the names/titles are indented.

Splitting a range string into a table

This week’s post is a requirement that I see very regularly as a developer. You get a plaintext string containing one or more ranges. Each range is comma delimited, and the start and end values of the range are separated by a dash. The string could look something like this, for example: 100-120,121-499,510,520,790-999.

Wouldn’t it be practical if we could construct a table value function that returns one row for each range, with columns for the start and end of each range?

Calculating median using the NTILE function

A while back, I was shown an absolutely gorgeous median calculation, using the new OFFSET/FETCH functionality introduced in SQL Server 2012. But this got me thinking. How can you calculate the median in an older SQL Server? Here’s an idea of how to do it using the NTILE() function.