A Fine Slice Of SQL Server
Alex Lin makes an announcement:
We’re excited to announce the General Availability of Managed Private Endpoints (MPE) in Fabric Eventstream. This network security feature allows you to stream data from Azure resources to Fabric over a private and secure network without the complexity of manual network configurations.
Read on to see what private endpoints give you and what’s new for general availability.
Leave a CommentBrent Ozar shares the numbers:
In this quarter’s update of our SQL ConstantCare® population report, showing how quickly (or slowly) folks adopt new versions of SQL Server, the data is very similar to last quarter. SQL Server 2019 still rules the market:
Click through to see where people are at in Brent’s sample of the market. Alan Cranfield has some numbers for SQL Server on AWS and those come pretty close to what Brent’s sample shows as well.
Leave a CommentGilbert Quevauvilliers finds some UUIDs:
When completing the Power BI performance load testing, you will need to get details from your Power BI report and App Workspace, which will later be used in the PBIReport.JSON file.
In this blog post I will show you how to find those details, so that when it comes time to add it to the PBIReport.JSON file, it will be easy to plug the values in.
The reason for a separate blog post is because you will have to find the GUIDs that are used, which takes a bit of time and knowledge to find the correct GUID for the right value.
Click through for the most unsatisfying Easter egg hunt you could imagine. Gilbert then continues to pull out slider and filter data values.
Leave a CommentArun Sirpal explains what zone redundancy is in Azure:
Do you know what happens when you enable zonal redundancy for your SQL managed instance?
Lets define it first (in the context of Business-Critical tier) – zonal redundancy is achieved by placing compute and storage replicas in different availability zones (3) and then using underlying Always On availability group to replicate data changes from the primary instance to standby replicas in other availability zones.
Availability zones are in the same Azure region, so it works well for high availability but isn’t as good for disaster recovery: if an entire region goes down, zone redundancy won’t help you very much. Also, be aware that you’re paying for what’s running in those three zones because TANSTAAFL.
Leave a CommentHans-Jürgen Schönig compares data sizes:
In this case study, we’ll delve into each of PostgreSQL’s main storage options, their characteristics, and the factors that influence their choice, enabling you to make informed decisions about your database’s storage strategy. You will also learn how you can archive data in a hybrid environment for long term storage.
Click through for a comparison of two common file formats, plus two PostgreSQL-specific mechanisms for data storage. The comparison here is mostly one of final file size, though common query performance would be interesting to include as well, especially because the columnar data file types (Parquet and Citus-based columnstore) have a very different performance profile versus row-store data.
Leave a CommentMarco Russo and Alberto Ferrari take us through a complicated function:
ALLSELECTED is among the most complex functions in the whole DAX language. ALLSELECTED is the only DAX function that leverages shadow filter contexts. Moreover, ALLSELECTED has a slightly different behavior when used in SUMMARIZECOLUMNS or inside an iterator. Using ALLSELECTED with SUMMARIZECOLUMNS mostly produces the expected result, whereas using ALLSELECTED inside an iterator can produce weird results. Mixing the two techniques is the perfect recipe for a problematic report!
In this article, we briefly describe ALLSELECTED features in both scenarios (SUMMARIZECOLUMNS and iterators), and then we provide the best practices about the function, showing an example where mixing the two behaviors produces an unexpected result.
Read on to learn more.
Leave a CommentJon Vöge continues a series on write-back in Microsoft Fabric:
In my pursuit of testing out Translytical Task Flows and User Data Functions as a write-back alternative to Power Apps, I’ve come to spent a good amount of time trying to debug those features as well. Especially since they have a tendency to throw pretty non-descriptive error messages your way.
For this week’s blog post, I’ve made a small write-up of tips and tricks for troubleshooting and debugging translytical task flows, as this was something I struggled a little with myself.
Read on for several tips around better testing and error handling within these functions.
Leave a CommentSimon Frazer shares some tips:
At some point, every SQL developer or DBA will need to debug T-SQL scripts, either to verify that they behave as expected or to track down the root cause of a problem. Whether you’re building something new or investigating a production issue, debugging is an essential part of the process.
There are several techniques available for troubleshooting, and it’s important to approach this differently depending on whether you’re working in a production or non-production environment. Each environment has its own risks and constraints.
Click through for Simon’s process. I also echo Simon’s sentiments at the end regarding the SSMS debugger—I know people who are passionate about it and mourn its passing, but I was never one of those people. It was far too easy to get in trouble with it, especially in shared environments.
Leave a CommentJohn Sterrett recaps the most recent SQL Saturday:
Earlier this month, we hosted T-SQL Tuesday and chose the topic of Growing the Younger Data Community and Speakers. Today, I bring you a summary recap of everyone who shared their thoughts on this subject with links to their full content.
Click through for a review of the entrants for this month.
Leave a CommentBrian Kernan announces a change:
In August 2025, Microsoft Fabric will introduce workspace access limits to improve service quality, reliability, and to encourage workspace access control hygiene. This limit will be permanent once it is rolled out – each Fabric & Power BI workspace will be limited to a maximum of 1,000 users or groups in workspaces roles (Admin, Member, Contributor, Viewer). A workspace with a group over 1,000 individuals will not be impacted by this change, the number of users within a group is not impacted. Additionally, workspaces that are overlimit at the time of access limit enforcement will remain overlimit, but no additional users or groups can be added until the workspace is under-limit.
I read this and I say “Hmm…” I’m not in a position where I could say that 1000+ users in a workspace is a bad idea that they’re protecting us from, or if it’s an implicit acknowledgement of failure to scale.
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