Press "Enter" to skip to content

Author: Kevin Feasel

The Building Blocks of Extended Events

Ed Pollack takes us through the basics of extended events in SQL Server:

Extended Events are an excellent way to collect data about a SQL Server that provides a vast array of events that can be used for performance monitoring, troubleshooting, or auditing a server. In this article, I’ll explain the building blocks of Extended Events data collection.

While using Extended Events is not overly complex, building a reliable system to collect, parse, and store events over time without any data loss can be challenging.

This article walks through the steps to create, configure, and implement Extended Events in SQL Server, providing the prerequisite code and concepts to build an automated collection process.

Read the whole thing.

Comments closed

Azure DevOps Templates for Data Platform Deployments

Kevin Chant has some toys for us:

For my T-SQL Tuesday contribution this month is I want to introduce my Azure DevOps templates for Data Platform deployments.

This months T-SQL Tuesday is hosted by Frank Geisler. Frank has invited us to write about deploying SQL components through descriptive methods and build some new cool templates for them.

Which is good timing for me, because I co-presented a session on the day this post is published. I showed how to use YAML in Azure DevOps for Data Platform deployments at Data Platform Virtual Summit. .

Click through to learn more and see Kevin’s repos, as well as more information on the topic.

Comments closed

A Trace Flag (Generally) to Avoid

Erik Darling takes us through trace flag 3608:

According to the docs:

Prevents SQL Server from automatically starting and recovering any database except the master database. If activities that require TempDB are initiated, then model is recovered and TempDB is created. Other databases will be started and recovered when accessed. Some features, such as snapshot isolation and read committed snapshot, might not work. Use for Move System Databases and Move User Databases.

Note: Do not use during normal operation.

Scope: global only

But it turns out it can do quite a bit of harm. It seems that many things stop working when it’s in use, though, including statistics getting automatically created.

Click through to see what kinds of things fail to work as a result of this trace flag.

Comments closed

Testing Stock Market Efficiency with Compression Algorithms

Holger von Jouanne-Diedrich has a clever test:

One of the most fiercely fought debates in quantitative finance is whether the stock market (or financial markets in general) is (are) efficient, i.e. whether you can find patterns in them that can be profitably used.

If you want to learn about an ingenious method (that is already present in anyone’s computer) to approach that question, read on!

As soon as I saw the post, my Eugene Fama senses were tingling. The results are not surprising (at least, to anyone who got my reference in the prior sentence), but I did enjoy the rather clever approach to the question.

Comments closed

Environments in Azure ML

Luis Valencia explains what environments are in Azure ML:

An Environment defines Python packages, environment variables, and Docker settings that are used in machine learning experiments, including in data preparation, training, and deployment to a web service. An Environment is managed and versioned in an Azure Machine Learning Workspace. You can update an existing environment and retrieve a version to reuse. Environments are exclusive to the workspace they are created in and can’t be used across different workspaces.

In basic terms for a developer, it’s basically a Docker Image with all the needed dependencies (conda/pip packages) to run your experiment.

A friendly word of advice from some bad experiences: stick with the curated environments as much as you can. Those are easy and rarely fail. Building your own environments from Conda files is a possibility, but it’s an, err, probabilistic exercise as to whether your compute target will actually work or not.

Comments closed

Tools and Tips for Accessibility

Daron Yöndem shares insights:

Last week, as a new employee, I went through Microsoft’s internal employee learning portal and found the Accessibility 101 online course. To my surprise, the course did have a good amount of practical information and connected the concept of accessibility nicely to inclusion and diversity. In this post, I want to share a couple of the practical steps to help you step up your accessibility game. If you are where I was, I’m sure you will love these.

Click through for some easy ways to improve presentations and webpages. Most of this is a few minutes’ worth of effort but can pay dividends. On a side note, congrats to Daron for the Microsoft gig. I enjoyed working with him in the past and know he’ll do great there.

Comments closed

Pipelined Functions in Powershell

Robert Cain continues a series on functions in Powershell:

In my previous post, I covered the use of PowerShell Advanced Functions. I highly suggest you read it if you haven’t, it provides some foundational knowledge that will be important to understand for this post.

In this post, we’ll see how to pipeline enable your functions. Just like a cmdlet, you’ll be able to take input from the pipeline, work with it, then send it out your function back into the pipeline.

Making your code pipeline-friendly is especially important if you want others to use your functions, as that’s one of the biggest benefits of Powershell as a language.

Comments closed

Measure Filters in Power BI

Marco Russo and Alberto Ferrari dive into a topic:

The first paragraph of this article needs to be a warning: the article itself is here for DAX and Power BI enthusiasts only. We are going to show a report that does not work, and then we explore how to fix the problem by performing a deep analysis of the queries generated by Power BI, finding the problem, and finally fixing it. The article contains a lot of references to advanced DAX concepts and the final solution is NOT a best practice. The value of the article is not in the specific solution. Rather, the important part is that a deep understanding of DAX and Power BI can help you obtain the right results, specifically when you have the feeling that you are faced with a bug because Power BI is acting strange. If you do not like DAX before reading this article, you will like it even less at the end. But if you love DAX, then chances are you will really enjoy the reading, even though it requires quite a lot of brain bandwidth. For sure, it took all of mine when I first encountered this behavior.

Break out the propeller hats before you dive in.

Comments closed