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Category: Azure Data Studio

Azure Data Studio Auto-Save

Dave Bland takes us through one nice feature of Azure Data Studio:

Azure Data Studio has many great features and even more if you add all the extensions that are available.  Many extensions are very useful now, even though they are still in preview.  These features are naturally compared to SQL Server Management Studio.  One feature I like that sort of exists I SSMS is the auto save feature.  This feature will automatically save your files when you close Azure Data Studio and will be there the next time you use ADS.  SSMS has the auto recovery option, but is works a bit differently so it isn’t quite the same. ADS has a setting named “Files: Hot Exit”.

Read on to see how it works.

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Automating Azure Data Studio Notebooks

Aaron Nelson has two separate ways of scheduling Azure Data Studio notebooks for us:

There are two new options for automating your SQL Notebooks with your SQL Servers. Earlier this month, the Insiders build of Azure Data Studio received the ability to add SQL Notebooks in SQL Agent. This past Friday (September 20th, 2019) a new version of the SqlServer PowerShell module was posted to the Gallery, with a new Invoke-SqlNotebook cmdlet.

Read on for demos of both.

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Creating Big Data Clusters with Azure Data Studio

Niels Berglund takes us through the creation of a Big Data Cluster by using Azure Data Studio to generate a notebook:

I wrote a blog post back in November 2018, about how to install and deploy SQL Server 2019 Big Data Cluster on Azure Kubernetes Service. Back then SQL Server 2019 Big Data Cluster was in private preview, (CTP 2.1 I believe), and you had to sign up, to get access to the “bits”. Well, you did not really get any “bits”; what you did get was access to Python deployment scripts.

Now, September 2019, the BDC is in public preview (you do not have to sign up), and it has reached Release Candidate (RC) status, RC 1. The install method has changed, or rather, in addition to installing via deployment scripts, you can now also install using Azure Data Studio deployment notebooks, and that is what this blog post is about.

Having gone through this myself, there’s quite a bit of reading involved in the setup, but they make the process pretty smooth. This also shows off one of the key benefits of notebooks: documentation and code together.

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Azure Data Studio September Release

Alan Yu announces the September release of Azure Data Studio:

As we continue to bring over key features from SQL Server Management Studio, one highly requested feature was enabling SQL Server command line (SQLCMD) mode in our Query Editor. SQLCMD mode allows users to write and edit queries as SQLCMD scripts. In addition, users can also execute the SQLCMD scripts.

This feature is now possible in Azure Data Studio.

Looks like there were several good improvements this month.

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Azure Data Studio Server Groups

Dave Bland explains how we can get different tab colors in Azure Data Studio:

Have you ever been in an environment where you worked with both DEV\QA servers and Production servers?  Of course you have, we all have.  However, being in such an environment brings a certain level of risk.  We all try to be very careful to run any code we are asked to run on the correct server and in the correct environment.  Despite all of our checks and our Due diligence, we are still human and do make a mistake from time to time.  Azure Data Studio has a nice feature that will allows us to change the color of tabs based on the environment the server is in.  The image below is an example of what it would look like.

I really like this functionality because it gives you one additional warning that you’re about to run a dev script against a production server on accident.

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Estimated Execution Plans in Azure Data Studio

Dave Bland walks us through the “Explain” button in Azure Data Studio:

At first I was thinking maybe it is a short cut to help.  Nope, it is actually an easy way to get the estimated execution plan. The key is estimated execution plan. While in SQL Server Management Studio we have been able to easily get both the estimated or actual execution plan.

Just as a reminder, the actual execution plan requires the query to actually run. While the estimated plan will use statistics to generate the plan.  Generally, if the actual and estimated are capture very close to each other, you are more than likely not going to see a difference between the tow.

Now let’s talk about the Explain button.  It will return two things, the XML of the execution plan and a graphical representation of the execution plan.

There are a few differences between Azure Data Studio’s implementation of execution plans and SQL Server Management Studio’s.

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Azure Data Studio August Release

Alan Yu announces a new version of Azure Data Studio:

The key highlights to cover this month include:
– SandDance integration—A new way to interact with data
– Notebook improvements
– SQL Server Dacpac extension can support Azure Active Directory
– SQL Server 2019 extension
– Visual Studio Code merge 1.37
– Bug fixes

Being able to add a new cell inline is nice, especially when you’re dealing with larger notebooks.

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Management Studio’s Staying Power

Kendra Little explains why SQL Server Management Studio isn’t going away anytime soon:

After all, SSMS is no longer the cool new kid on the block: Microsoft has shown consistent effort to develop their new tool, Azure Data Studio (the artist formerly known as SQL Operations Studio), since November 2017. Azure Data Studio is built on the modern foundation of Microsoft’s VS Code, whereas SQL Server Managed Studio is related to the legacy Visual Studio Shell.

Based on this overview, it might seem like a new SQL Server DBA or developer should primarily learn Azure Data Studio, not SSMS. And it might similarly seem like vendors should focus on developing new tooling only for Azure Data Studio.

But when you look into the details of how Azure Data Studio is being developed, it becomes clear that SSMS is still just as relevant than ever:

User base inertia is another reason, one that Kendra doesn’t mention directly. I like where Azure Data Studio is going and try to use it at least half-time. But there are a lot of people with a specific workflow they’ve developed and don’t want to change. As long as that’s a large percentage of the SQL Server population, SSMS isn’t going anywhere.

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Deploying a Big Data Cluster

Mohammad Darab takes us through the Big Data Cluster deployment process using Azure Data Studio:

I’ve been “playing around” with Big Data Clusters for some time now and CTP 3.2 is way ahead when it comes to streamlining the BDC deployment process. You can check out my 4-part series on deploying BDC on AKS to see how cumbersome the process used to be. New in CTP 3.2, you can deploy a BDC on AKS (an existing cluster OR a new cluster) using an Azure Data Studio notebook. Let’s see how.

Click through for instructions. It was rather smart of Microsoft to release the instructions as a notebook.

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The SQL Notebook Experience, Featuring Powershell

Rob Sewell takes a break from book-writing and talks about using Powershell in SQL Notebooks:

Yes, it’s funny but also it carries a serious warning. Without understanding what it is doing, please don’t enable PowerShell to be run in a SQL Notebook that someone sent you in an email or you find on a GitHub. In the same way as you don’t open the word document attachment which will get a thousand million trillion pounddollars into your bank account or run code you copy from the internet on production without understanding what it does, this could be a very dangerous thing to do.

With that warning out of the way, there are loads of really useful and fantastic use cases for this. SQL Notebooks make great run-books or incident response recorders and PowerShell is an obvious tool for this. (If only we could save the PowerShell output in a SQL Notebook, this would be even better)

“It’s a bit hacky” is a generous statement, but it’s really cool that Rob figured out a way to do this. There is a Powershell kernel for Jupyter, but I’ve not had the best experience adding new kernels to Azure Data Studio (at least not F#’s kernel, which I tried).

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