Note that the x-axis is percentage of all waits, not wait count. You’ll see that PREEMPTIVE_OS_FLUSHFILEBUFFERS is the top wait on my Linux instance – that’s by design and I’ll blog about that next. I’ve also submitted a GitHub change to add that wait to the list of waits filtered out by script the extension uses.
Anyway, you can drill in to the details by clicking the ellipsis at the top-right of the graph and selecting ‘Show Details’. That’ll give all the waits and by selecting each one you can see the usual output from my waits script. To get more information on what each wait means, select the bottom cell, right-click on the URL to copy it, and paste into your favorite browser to go to my waits library. And of course, you can refresh the results via the ellipsis as well.
I like how Azure Data Studio is coming together as a full product. There’s a ways to go yet, but it’s getting there.
This is a contrived example but I was given a script that got the “Discipline”, “DocumentVersion”, “DocumentNumber”, “SectionNumber”, and “SectionName” out of the above.
And while it works, I hate that formatting. Everything is all squashed and shoved together.
No, thanks. Let’s see if we can make this more presentable.
Shane has a regular expression. Now Shane has two problems.
In all seriousness, regular expressions are extremely powerful in the right scenario. Shane mentions being okay with it not in the database engine and I’m usually alright with that, but there are cases when it’s really helpful like figuring out if a particular input is valid. One example I have on a project is finding legitimate codes (like ISBN) where you can solve the problem easily with a regex but my source data is abysmal. I can use the SQL# regular expression functions to drop into CLR and figure out whether that value is any good, something I would have a lot more trouble with in T-SQL alone.
A great thing about these snippets is that you can add your own and they can be exactly how you want them.
To get started with this open the Command Pallet with Ctrl+Shift+P and type in ‘snippets’.
Scroll down and find the SQL option. Open it and it will bring you to the SQL.json file in which we’ll be storing our SQL Snippets.
I had to migrate a bunch of SSMS snippets to Azure Data Studio and was not that happy with the experience, especially for some of the more complicated snippets.
H2O provides popular open source software for data science and machine learning on big data, including Apache SparkTM integration. It provides two open source python AutoML classes: h2o.automl.H2OAutoML and pysparkling.ml.H2OAutoML. Both APIs use the same underlying algorithm implementations, however, the latter follows the conventions of Apache Spark’s MLlib library and allows you to build machine learning pipelines that include MLlib transformers. We will focus on the latter API in this post.
H2OAutoML supports classification and regression. The ML models built and tuned by H2OAutoML include Random Forests, Gradient Boosting Machines, Deep Neural Nets, Generalized Linear Models, and Stacked Ensembles.
The post only has a few lines of code but there are a lot of working parts under the surface.
There are a lot of source control applications and software, everyone has its pros and cons, but personally, I like to use GitHub, since it is free to use and since it was recently acquired by Microsoft, support for other products is easier (SQL Server for this case).
On this post, I will show you how to implement a source control for a database using GitHub and Azure Data Studio (ADS).
Click through for the step-by-step instructions.
In previous versions of Azure Data Studio, when a user ran large queries, no results would appear in the results grid until the query could show all of the results. This was not a great experience for our users, thus we did some investigating to improve this experience. In the latest build of Azure Data Studio, users can now see results streamed in the results grid. This makes it a better experience since users can see the results quicker and interact with their data instead of being in a waiting state.
There are several enhancements this month, including Azure Active Directory support.
One thing about Azure Data Studio I’m not too keen about, though, is that many of the keyboard shortcuts are different. One keyboard shortcut that’s particularly helpful to me is using Ctrl + E to execute queries. I realize that F5 is the most common key to execute a query, however on most laptop keyboards you now need to hold an additional key to make the function keys behave like function keys. For this reason, Ctrl+ E is a wonderful and quick alternative, but it doesn’t work in Azure Data Studio. Or didn’t, until now.
Fortunately, Azure Data Studio is designed to be expanded upon with extensions from both Microsoft and the community. In the case of keyboard shortcuts, a particularly helpful one is called SSMS Keymap, which ports many popular SSMS keyboard shortcuts into Azure Data Studio. With this extension, Ctrl + E is once again an option, and I no longer have to click “Execute” with a mouse, or fumble to find my laptop’s F5 equivalent.
Click through for the demo and grab that extension.
We recently released a VS Code extension that lets you highlight terms and search dbatools.io, Microsoft Docs, Google, StackOverflow, DuckDuckGo or Technet or Thwack right from your code! It’s called dbatools simple search and you can find it in the Extension Marketplace.
I’ve also confirmed that it does work with Azure Data Studio; you just need to download the vsix extension from the Extension Marketplace and install and get context menu search support.
Azure Data Studio (ADS) is getting all sorts of love and attention these days. So much so that they have finally gotten around to adding Extended Events (XE) to the tool – sort of. Now we have the power to run traces on SQL Server via ADS.
The presence of XE in ADS comes via an extension and comes with a few other caveats. I will explore the extension for XE available in ADS in this article and discuss some of the caveats. As you read the article, it might be helpful to go ahead and download ADS if you do not already have it.
Jason points out the name of SQL Server Profiler and I’d like to add my own bit of irritation here. “Don’t use Profiler, except the one good Profiler but not the Profiler you think you’re using unless you know not to use Profiler and use Profiler instead.” Yeah, that’s pretty clear.
In November’s version of the monthly release blog, the emphasis was on fixing customer issues and adding and improving existing extensions.
Introducing the Paste the Plan extension
Introducing the High Color Queries extension
Improved Logging support
Read on for the details. This product is getting closer and closer to a state where it can be a daily driver.