SQLskills' Joe Sack (@josephsack) walks us through an interesting scenario where we might blame a query performance issue on parameter sniffing or bad statistics, when it actually turns out that a check constraint is the best solution to keep the optimizer honest.
Jonathan Kehayias (@SQLPoolBoy) demonstrates column-side implicit conversions and the impact they can have on a workload. He concludes that you can only throw hardware at this problem for so long; a design or code change will be necessary to solve the performance issue long-term.
In many SQL Server workloads, especially OLTP, the database’s transaction log can be a bottleneck that adds to the time it takes a transaction to complete. Most people assume that the I/O subsystem is the real bottleneck, with it not being able to keep up with the amount of transaction log being generated by the workload.
One of the things that's simultaneously great and horrible about the Internet is that, once something gets posted out in the ether, it basically never goes away. (Some day, politicians will realize this. We can easily fact check their consistency.) Because of longevity of content posted to the Internet, a lot of performance tuning topics become "zombies." We shoot 'em dead, but they keep coming back!
Hit-highlighting is a feature that many people wish SQL Server's Full-Text Search would support natively. This is where you can return the entire document (or an excerpt) and point out the words or phrases that helped match that document to the search. Doing so in an efficient and accurate manner is no easy task, as I found out first hand.
I've long been a proponent of choosing the correct data type. I've talked about some examples in a previous "Bad Habits" blog post, but this weekend at SQL Saturday #162 (Cambridge, UK), the topic of using DATETIME by default came up. In a conversation after my T-SQL : Bad Habits and Best Practices presentation, a user stated that they just use DATETIME even if they only need granularity to the minute or day, this way the date/time columns across their enterprise are always the same data type. I suggested that this might be wasteful, and that the consistency might not be worth it, but today I decided to set out to prove my theory.