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.
I wish the DATEDIFF() function would count the number of working days (mondays through fridays) between two dates for me, but until that happens, I’ve had to roll my own scalar function. I tried to think of a smart way involving perhaps a modulus calculation, but I quickly succumbed to a more down-to-earth approach.
Few things deserve the attention of a long rant as much as unneccessarily complicated syntaxes. When you want to achieve something that is clearly defined and supported, but you have to look up the the syntax. PIVOT and UNPIVOT are examples of such features, and in this case, I’ll even show you a more well-performing alternative.
It’s been absolutely ages since I last wrote a blog post, mostly because I’ve been busy getting my shiny new own consultancy up to speed, but I’ll admit that writer’s block has also been a factor.
But here’s something to write home about. This year’s annual Swedish SQL Server usergroup challenge was as interesting as ever, and it marks my third stab at this prestigious competition. In this post, I’ll go through my contribution, highlighting some of the techniques that I’ve applied to make it go really fast.
Talk to SQL Server developers or DBAs about histograms, and they’ll inevitably think of index statistics. However, a task you may encounter some day is to calculate the distribution of numbers in a table. And although there’s no quick built-in function to do this, it’s not as difficult as you may think.
I personally find the UNPIVOT syntax in T-SQL a bit unwieldy and not entirely easy to read. In this article, I’m going to show you an alternative way to perform UNPIVOT, using the CROSS APPLY operator.
You may not know that there are two different ways of writing user-defined functions that return a recordset: Table value functions and Inline functions, and they both come with a number of benefits and limitations with regard to performance and programmability.
You’ll be hard-pressed not to stumble over XML data in your daily work. Good thing then, SQL Server contains built-in XML parsing logic – there’s a native xml datatype, built-in XPath support and all the tools you need to store and transform data from or to XML data. However, this is an extensive topic, so this article will cover the basics of parsing XML data into a recordset, just to wet your apetite.
The APPLY operator can be a bit confusing, but if you master how it works, you can do great things with it. It is similar to a JOIN (hence the confusion), but differs in one key area: The JOIN defines a relation between two datasets using the ON keyword, whereas APPLY does not.