This is a real-world problem that I came across the other day. In a reporting scenario, I wanted to output a number of values in an easy, human-readable way for a report. But just making a long, comma-separated string of numbers doesn’t really make it very readable. This is particularly true when there are hundreds of values.
So here’s a powerful pattern to solve that task.
For windowed functions, SQL Server introduces two new operators in the execution plan; Segment and Sequence Project. If you’ve tried looking them up in the documentation, you’ll know that it’s not exactly perfectly obvious how they work. Here’s my stab at clarifying what they actually do.
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.
In datawarehousing, a common scenario you may have encountered is the phenomenon of late-arriving dimension members. Imagine a situation where you get dimension members and fact data from two entirely different data sources, which may or may not provide data at the same time. Some fact data will probably be ready to load before its corresponding dimension member(s) arrive. How do you tag your fact data, and what consequence does that have for the integrity of your data warehouse?
A common scenario you may have encountered is the need to calculate the first business day after a given date. There are quite a few ugly ways to solve this, including cursors, but there are also some pretty neat ways to approach the problem, and as a bonus, you’ll learn about recursion and the new LEAD(), LAG() functions and accumulation in T-SQL.
Windowed functions are a powerful feature of T-SQL, allowing you to perform advanced aggregates. They provide a very efficient way of doing this as soon as you just get the hang of the OVER() clause.
sqlsunday.com 