In the previous post we looked at the functions TRY_CAST, TRY_CONVERT, and TRY_PARSE and how they compared. I wrapped up and said that my preference for new developments would be to use TRY_PARSE due to the tighter control which it provides us. As with everything in SQL Server however, there is no ‘best’ approach, it depends. I therefore wanted […]
We’re on quite a roll with window functions these past few weeks. Last week we looked at the operators we’d see in execution plans when using a window function. This week I wanted to tackle one of the more troublesome ones specifically: the Sort operator. We know that sort operators are expensive in our queries. To use […]
Our SQL Server environments are home to many workloads. In these situations one size doesn’t always fit all when it comes to configuration. Let’s take an example. On one hand we want small, high performance, transactional processing during the day. Through the evening this could change to larger, batch processing tasks. I’ve seen the configuration […]
We’ve recently looked at how single threaded concurrency was handled in SQL Server and followed up last time by diving into multithreaded concurrency. This time we’re going to go a bit further with the multithreading to look more into how the contention is handled when the number of cores available doesn’t line up with our workload. We’ll also […]
Recently we looked at single threaded concurrency in SQL Server for workloads which only need a single core to execute. We saw how they ran at the same time with the queries effectively being round-robined on the CPU. This time out I wanted to look at how the concurrency looks when we’re working with multithreaded workloads. Setting […]
The question for today: if we have three queries – one which takes 1 second to run, one which takes 2 seconds to run, and one which takes 3 seconds to run – how long will it take to return data for the first and last query if they all start at the same time? […]
Whilst we have front-end code which requires faster response times, there are also times we build code with the purpose of running for extended periods of time. Examples of this could be maintenance routine, or custom built queuing mechanisms. The way in which we design longer running processes like this can be key when it […]
We’ve previously looked at how to implement vertical partitioning and the benefits it can bring within our data. Here I’d like to dive a little further into improving the performance even further with a couple of modifications to our schema. We’ll use the same setup as we had previously to create the table, populate it and partition it. This results in […]
We recently looked at implementing vertical partitioning on a set of data. In an earlier introduction post we also mentioned the benefits which can be seen as a result of the partitioning in both our maintenance and querying of the data. Here we’ll take a look at those benefits with a little more evidence. We’ll be using the data […]
We previously looked at an introduction to Vertical Partitioning where we covered what it is and the potential benefits and drawbacks of using it. Here I wanted to build up some data and show how we may vertically partition it to help make it more manageable for us. So that we’ve got some relevant data to use […]
Andy Brownsword 