A Fine Slice Of SQL Server
Federico Campoli deals with a lot of RAM:
Nowadays it’s not uncommon to deal with machines with hundreds of GB of RAM.
Abundant memory can give PostgreSQL a massive performance boost. However things work slightly different than you may expect.
Let’s find out!
Click through for a dive into how PostgreSQL handles memory management.
Comments closedReza Rad does a bit of a match:
Have you ever wanted to match two tables together but not on exact matches, but also on a threshold of similarity? if your answer to this question is yes, then this feature is built for you. Let’s explore in details how the fuzzy matching works in Power BI. To learn more about Power BI, read Power BI from Rookie to Rock Star.
As always, Reza has a video and a blog post for us, explaining how the fuzzy matching process works and some of the knobs you can control. In the comments, Reza even digs up the specific algorithm that Microsoft uses for fuzzy matching.
Comments closedMarco Russo and Alberto Ferrari show that tracking weekdays is like an onion:
Computing time intelligence calculations in DAX is rather simple. However, as soon as the requirements are not trivial, the complexity of formulas skyrockets, and it is necessary to have a very good understanding of several details about DAX to obtain a good formula. In this article, we show a simple requirement: the need to maintain a filter on weekdays while computing time intelligence. As you are about to read, it will require several complex steps despite being a simple requirement; but let us start by clarifying what we want to obtain and what a filter-preserving column is.
Click through for the full article.
Comments closedThere is a SET command in SQL Server that changes how much data is returned from some fields. This short post shows what I learned about the SET TEXTSIZE command.
I’m pretty sure that, if I’ve ever used this command before, it was by accident. It’s kind of a neat concept in how it can limit the result size of larger blocks of text, but I think it’s too limiting to be a good solution save for some very specific circumstances.
Comments closedAli Oghabian shares some hard-earned advice:
The aggregate function can be very useful in R, allowing one to run a function (e.g. mean) within groups of rows, in each column in a matrix/data-frame and organize the results in an easy-to-read table. However, the function takes long to run for very wide matrices and data frames, where the number of the columns are large. I this post I demonstrate the issue and show a couple of nice solutions that at least for the example cuts down the time to 15% and even less, compared to the run-time of the aggregate function.
Click through for a demo. Granted, this is a matrix with 10,000 columns, so I’m not sure how this applies to narrower matrices. H/T R-Bloggers.
Comments closedThom Brown shares some advice:
As you may have heard, there are reportedly over 1,500 PostgreSQL servers that have been exploited to mine Bitcoin. And your server could be next if you haven’t taken precautions. Firstly, you need to update to the latest minor release, just so no known exploitable bugs exist on your system. But regardless of whether you update, your PostgreSQL instance could still be misconfigured in a way that would allow unwelcome visitors access, so you need to make sure you shore up your defenses. Here are some steps you should take.
Click through for some solid guidance.
Comments closedYichao Wu makes an announcement:
Workspace folders are an easy way for you to efficiently organize and manage items in the workspace. We’re pleased to share that Folder Rest API is now in preview. Create and manage folders in automation scenarios and seamlessly integrate with other systems and tools.
I’m hoping this means source control for folders is also forthcoming.
Comments closedMarco Russo summarizes the announcements:
I usually do not write about announcements and new features until we have had time to try and test them in the real world. However, there are always exceptions, and some of the announcements at the Microsoft Fabric Conference 2025 fall into this category because I have worked with them enough to provide hands-on feedback.
In short, these are the topics I am covering in this blog post:
- Direct Lake and Import mode
- Calendars in DAX
- User-Defined Functions (UDF) in DAX
These weren’t the headline-grabbers of the conference, but Marco explains the importance behind each of them.
Comments closedKoen Verbeeck runs into a problem:
I recently had a new pipeline fail. It was actually a copy of an old pipeline where I had made some adjustments into as part of a database migration. When triggered during an execution run, it failed saying some expression could not be parsed. When I went into the pipeline and triggered a debug, it immediately failed with the following helpful error message:
Click through for the error message and how Koen was able to fix the issue.
Comments closedRadim Marek clocks in for the day:
The next possible source of confusion when working with time in PostgreSQL is presence of two distinct data types:
timestamp(ortimestamp without time zone)timestamptz(ortimestamp with time zone) Despite what the names suggest, the key difference isn’t whether they store timezone information, but rather how they handle it during storage and retrieval.
Click through for quite a bit of detail and plenty of examples on how to handle date and time data in PostgreSQL. And I’m still jealous about support for intervals, especially in window functions.
Comments closed