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Curated SQL Posts

Thoughts on a Decline in SQL Server Quality

Published 2025-03-11 by Kevin Feasel

Kendra Little shares her opinion:

“Is it just me, or is SQL Server quality slipping?”

I asked myself that question for couple/few years until I faced up to it: SQL Server is well into a period where Microsoft investment is waning, and Microsoft regularly isn’t able to deliver the features they promise.

Read on for Kendra’s take. I’m not in total agreement with this, though part of that is because my stance is closer to (if you’ll allow me the misappropriation of a famous quotation), there is a great deal of ruin in a data platform product.

But if I had a single line of demarcation to Kendra’s point, I’d probably make it when SQL Server QA shifted to “We’ll find all of the bugs in Azure SQL DB first, so we don’t need this redundancy” several years back. That doesn’t explain everything, but it does provide a relevant timeframe for all of this.

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Retrieving Microsoft Fabric Items using a Python-Only Notebook

Published 2025-03-11 by Kevin Feasel

Gilbert Quevauvilliers doesn’t need Spark for this:

This blog below explains how to use a Python only notebook to get all the Fabric items using the Fabric REST API.

NOTE: At the time of this blog post Feb 2025, Dataflow Gen2 is not included in the Fabric items, I am sure it will be there in the future.

NOTE II: This only gets the Fabric Items, which does not include the Power BI Items.

Despite the notes, Gilbert leads off with the main reason why you might want to use this: it takes up approximately 5% of the capacity units that a Spark-based notebook does to perform the same operation.

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An Introduction to pgNow

Published 2025-03-11 by Kevin Feasel

Ryan Booz introduces a new free tool from Redgate:

pgNow is a free, cross-platform desktop tool created by Redgate that helps you identify key performance metrics and configuration optimizations in your running Postgres instance. Available now as a public preview application, it’s designed to help when you’re in a pinch and don’t have the Postgres experience or monitoring solution already in place to help identify why your server or database is experiencing a degradation in performance. Even in its current preview offering, pgNow is a helpful front-line tool for troubleshooting your Postgres cluster. And I couldn’t be more excited to share it with you.

Click through to see what’s in the preview. Ryan has mentioned that the tool will remain free even when it’s in a stable release.

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Conditional Formatting via Power BI Visual Calculation

Published 2025-03-11 by Kevin Feasel

Marco Russo and Alberto Ferrari talk highlighting:

However, visual calculations are incredibly convenient when it comes to calculations that are specifically tied to a visual. Let us face it: every semantic model contains measures with intricate ISINSCOPE, HASONEVALUE, and SELECTEDVALUE function calls whose only goal is to determine the color of a font or the background of a cell. An example of the intricacy of those measures is in one of our most viewed articles here: https://www.sqlbi.com/articles/filtering-the-top-products-alongside-the-other-products-in-power-bi/.

Visual calculations can be used to control conditional formatting starting with the February 2025 version of Power BI. Several small details must be known to use them, but they are definitely worth learning.

Read on to see how it works. Conditional formatting has always seemed to be oddly difficult to do in Power BI. If you were in the happy path for conditional formatting, it’s a few mouse clicks. But if not, then good luck.

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ETL Orchestration and Air Traffic Control

Published 2025-03-11 by Kevin Feasel

Jens Vestergaard extends a metaphor:

We have been working getting an enterprise grade event driven orchestration of our ETL system to operate like an airport control tower, managing a fleet of flights (data processes) as they progress through various stages of take-off, transit, and landing. All of this, because Microsoft Fabric has a core-based limit to the number of Notebook executions that a capacity can execute and have queued up in line for execution when invoking them using the REST API. Read the details here: limits (you know, it’s funny that there is no stated limits for Azure Service Bus Queues on number of messages in queue, but there is for Microsoft Fabric, which uses a Service Bus queue underneath…)

That limitation is a bit annoying, but read on to see how Jens uses this metaphor to explain the various parts of an ETL orchestration engine.

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Refreshing Power BI Semantic Model Hidden Tables via Fabric Data Pipelines

Published 2025-03-11 by Kevin Feasel

Chris Webb digs into the dark underbelly of a semantic model:

Following on from my recent post about refreshing semantic models with Fabric Data Pipelines and the semantic model refresh activity, a few people asked me how to refresh hidden tables because they are not displayed in the Pipeline configuration UI. I got the answer from my colleague Alex Powers (aka reddit celebrity u/itsnotaboutthecell) who kindly allowed me to blog about it.

Click through for the demonstration.

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Local Text Summarization via DistilBart

Published 2025-03-10 by Kevin Feasel

Muhammad Asad Iqbal Khan summarizes a document:

Text summarization represents a sophisticated evolution of text generation, requiring a deep understanding of content and context. With encoder-decoder transformer models like DistilBart, you can now create summaries that capture the essence of longer text while maintaining coherence and relevance.

In this tutorial, you’ll discover how to implement text summarization using DistilBart. You’ll learn through practical, executable examples, and by the end of this guide, you’ll understand both the theoretical foundations and hands-on implementation details. After completing this tutorial, you will know:

Click through for the article.

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Serving Databricks Models via API Management Endpoints

Published 2025-03-10 by Kevin Feasel

Drew Furgiuele makes available a model:

When it comes to generative AI projects I’d argue that the hardest and most tedious part has moved into a new area: hosting and serving your models. Whether you’re working with CPU intensive models, or models that require GPU horsepower, sourcing the hardware, building out deployment pipelines, configuring monitoring, and then securing everything is real, serious work that requires everyone to lean in to get it right.

And then, there’s the real question of how you’re going to use those models: will you be setting up automation and doing batch processing using your models and infrastructure? Or do you want to get really serious and offer up real-time inference? If the latter, you can add one more thing to solve for: managing your front-end APIs that you will have to build to support that use case.

Click through to see how you can use an API management tool (like Azure API Management) to assist in these things.

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Publishing a Fabric SQL Database

Published 2025-03-10 by Kevin Feasel

Koen Verbeeck deploys a database:

When a SQL Database is in Microsoft Fabric, you can develop it locally in a database project. As part of the development process, you want to deploy this project to the online Fabric SQL Database. The database project also contains pre- and/or post-deployment scripts that need to be executed as part of the deployment process. How can this goal be achieved?

Click through for the answer.

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Load Testing Azure SQL Databases

Published 2025-03-10 by Kevin Feasel

Reitse Eskens sets the stage:

Some time ago, I wrote a number of blogposts comparing the different Azure SQL options to give you some idea about performance, differences between tiers and differences between the Stock Keeping Units (SKU’s). This was done by creating data in the database itself and review the metrics. This works fine and gave a good overview of the different tiers and SKU’s. For reference, you can find those blogs here.

For the new series, I’ve thought of a new process that aligns more with my regular line of work, data warehousing. This means ingesting a lot of data and modelling it.

Click through for the summary of method and initial notes.

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