A Fine Slice Of SQL Server
Koen Verbeeck speeds things up:
We are building a large warehouse in Microsoft Fabric using the warehouse. Our biggest fact tables have some performance issues when we are running our analytical queries, and it seems we cannot use indexes in the Fabric Warehouse. Is there some way to improve performance?
Click through to see how you can use clustering to improve the performance of warehousing queries, as well as some of the pre-requisites to make it work.
Leave a CommentMarco Russo and Alberto Ferrari talk about type systems:
In a previous article, Introducing user-defined functions in DAX, we described the syntax for creating user-defined functions, including the two passing modes (VAL and EXPR) and the fundamental parameter types SCALAR and TABLE. In this article, we build on that foundation and focus on the complete type system, with particular attention to the reference types introduced in March 2026 that provide better documentation, stronger validation, and improved IntelliSense support.
Before diving into the new types, let us briefly recap the full picture of parameter types and passing modes available in DAX user-defined functions.
Click through for a classic deep dive from Marco and Alberto.
Leave a CommentPostgres table partitioning is one of those features that feels like a superpower right up until it isn’t. Just define a partition key, carve up data into manageable chunks, and everything hums along beautifully. And what’s not to love? Partition pruning in query plans, smaller tables, faster maintenance, easy archiving of old data; it’s a smorgasbord of convenience.
Then you try to enforce a unique constraint without including the partition key, and Postgres behaves as if you just asked it to divide by zero. Well… about that.
Click through for an explanation, some workarounds that might work in specific circumstances, and a few closing remarks.
As for SQL Server, the same rule applies. If you want a unique index (which is what a unique key constraint uses under the covers), you must include the partitioning column. If you don’t include it, SQL Server will include it for you rather than giving a hard error.
Leave a CommentJamal Hansen provides an overview of window functions:
So let’s dive in. What problem do window functions solve? They seem to do aggregation-type activities, can’t
GROUP BYdo this?The short answer is, not very well.
Window functions allow you to do things like calculate running totals, rankings, and moving averages, which tend to be very difficult to do otherwise because it requires a ‘window’ into a subset of the data.
Click through for the explanation, a primer on some of the types of window functions that are available, and several examples. I noticed that the code is impossible to read in light mode on the website, so either highlight it or go into dark mode, I guess.
Leave a CommentWhen you provision a Microsoft Fabric trial, it spins up at F64 by default. That’s the equivalent of 64 Capacity Units — a solid chunk of compute. For most trial users, this is just the number they see and never think twice about.
But here’s what I just discovered: you can change it.
Click through to see how.
Leave a CommentRebecca Lewis takes a look at a few more vulnerabilities Microsoft has patched in SQL Server:
This week’s Patch Tuesday landed three new SQL Server CVEs. Two are elevation-of-privilege bugs — familiar territory, we had three of those last month. The third one is different. CVE-2026-33120 is a remote code execution flaw in SQL Server 2022. CVSS 8.8. An authenticated, low-privileged login on the network can execute arbitrary code on your SQL Server.
Go. Patch. Now.
Click through for more information and be sure to get these patched.
Leave a CommentNikola Ilic asks, what’s in a name?
My dear Microsoft Fabric friends – if you’ve ever opened a workspace and seen “Lakehouse”, “Lakehouse 1”, “lh_test_v2”, and “NewLakehouse_DELETE_ME” all sitting next to each other, this post is for you
Three weeks into a fresh Fabric tenant, things look great. Twelve weeks in, you’re staring at 47 workspaces, three of them called something like “Test – DO NOT USE”, and nobody on the team can remember which Lakehouse holds the actual production sales data.
I don’t know how Nikola has figured out my naming strategy so well. Click through for a systematic attempt to standardize naming for Fabric objects.
Leave a CommentSteve Hughes learns something new:
Thanks to everyone who joined the blog party this month. I noticed three themes in the responses. Every response had one or more of these themes woven into their response.
- I learned something.
- I discovered ways to improve my presentations.
- I get more value in the hallway conversations.
Click through for this month’s participants and what they’ve learned.
Leave a CommentAnthony Nocentino runs a test:
When building the sql-on-k8s-operator, I wanted to make sure it could handle both planned and unplanned failovers. The easy case is a planned failover, where you deliberately move the primary role to another replica. The harder case is an unplanned failover, where the primary pod just disappears. The operator needs to handle both.
I recently ran a full planned failover rotation on a three-replica SQL Server Availability Group managed by sql-on-k8s-operator, and I want to show you exactly what happens inside SQL Server and the operator during each hop. If you’ve been following my Introducing the SQL Server on Kubernetes Operator post, this is the logical next step: what does the error log actually look like during a planned failover, what does the operator do in response, and how long does the whole thing take?
I ran the same three-hop rotation twice: once with an idle 5GB database to establish a baseline, and once under a sustained TPC-C workload with HammerDB. In this post, I’ll walk through the SQL Server error log entries, the operator’s reconcile behavior, and the timing data for both runs. In the next blog post, I’ll show what happens during an unplanned failover. Let’s go.
Click through to see how it all works.
Leave a CommentChris Webb tells us don’t panic:
Since March 2026, Power BI semantic models have started showing warnings in their Refresh History in the Service. This has scared a few people but in fact all that is happening is that errors which were there all along and which don’t prevent refreshes from completing are now being flagged. Documentation on this feature can be found here but let’s see an example of the type of errors that can cause these warnings.
Click through for that example.
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