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Category: Azure Data Studio

Azure Data Studio August 2020 Release

Alan Yu announces the most recent set of changes around Azure Data Studio:

The notebooks viewlet in Azure Data Studio now includes a dynamic search experience. When you are dealing with hundreds of notebooks, it can be tricky navigating and finding the notebook you need. With this experience, we make it faster to search through notebook content.

Once notebooks are listed in the Notebooks viewlet, users can easily search for content across all notebooks and see how many instances the search term appears in a certain notebook. You can then interact with the notebook.

It’s a notebook-heavy month.

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Creating a Database Project with Azure Data Studio

Wolfgang Strasser takes the database project extension for a spin:

There is currently one requirement to start your database project development in ADS, it is that you need the Insider build of ADS (that you can download here). After the installation, you’ll need to install the extension. Please search for it in the list of extensions and install it in your ADS instance.

Tom Norman and I talked about it in detail on last night’s episode of Shop Talk (to be posted later today). It’s a good start, but there are still some rough edges and missing functionality. I’d expect that to improve over time, though.

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Quality Azure Data Studio Extensions

Randolph West vouches for some Azure Data Studio extensions:

It’s worth mentioning that for the most part Azure Data Studio extensions are extremely lightweight, both in download size and memory usage. Installing this many on SQL Server Management Studio (SSMS) would slow it down dramatically.

Note: not all extensions can be installed from the Extensions pane. For many of them you must visit a website, download the VSIX file and install it manually using the File > Install Extension from VSIX Package menu option. In most cases you can trust extensions from reputable publishers, but always take care.

Randolph has quite a few more extensions than I do, but I can’t say any of those are a bad choice.

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Azure Data Studio June 2020 Release

Alan Yu announces a new release of Azure Data Studio:

The Data Virtualization extension for Azure Data Studio is now updated with more functionality and a new logo. This update allows you to use the data virtualization wizard to virtualize MongoDB and Teradata data sources into your SQL Server. This new functionality is available for SQL Server 2019 instances running CU5 or later.

To install the extension, search for Data Virtualization in the extension viewlet in Azure Data Studio and click install.

Of course I’m going to clip the bit about PolyBase.

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Installing Azure Data Studio on CentOS

Sreekanth Bandarla walks us through installation and usage of Azure Data Studio on CentOS:

Okay…now what? Where to locate the executable and how do I open Azure data studio in CentOS? GUI in CentOS is not as user friendly as you can see in some other Linux OSs (Mint for eg or few other Ubuntu flavors of Linux). In windows you can locate the program in start menu or even in few desktop experience Linux distributions it’s extremely easy to just search in application center, but that was not the case for me in CentOS 7.

Click through to see how to install and open ADS on a Red Hat-based system.

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SQL Server on a Windows Container

Kevin Chant lives dangerously:

In this post I want to cover an interesting Windows Container with SQL Server installed experiment that I did. Because it was fairly involved, and it took a while.

In fact, this is the experiment I was talking about in my recent post about recent Azure Data Studio updates. Which you can read about in detail here.

My general philosophy is to avoid Windows containers at all costs, though I’m glad that there are some more adventurous than I.

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May 2020 Release of Azure Data Studio

Alan Yu has some goodies for us:

The key highlights to cover this month include:

– Announcing Redgate SQL Prompt extension
– Announcing the new machine learning extension
– Added new Python dependencies wizard
– Added support for parameterization for Always Encrypted
– Improvements to the notebook markdown toolbar
– Bug fixes

For a list of complete updates, refer to the Azure Data Studio release notes.

I’ll have to check out the ML extension.

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Creating Charts with Azure Data Studio

Rajendra Gupta walks us through chart creation with Azure Data Studio:

Usually, we use to extract the data from a SQL database, copy it in Microsoft excel and creates the required Chart from it. We can also use various tools such as SQL Server Reporting Service ( SSRS), Power BI to import data and create charts, visuals from it directly. These tools work fine; however, it requires additional steps to install these tools, have intermediate knowledge of it. You might require to do this with different data set, and every time, you cannot create a separate visual using Power BI or SSRS. In this type of requirement, the most common useful tool is Microsoft Excel. You can also use PowerShell, but it again requires you to have PowerShell script knowledge. You can go through the article How to create charts from SQL Server data using PowerShell to create charts from PowerShell.

In this article, we will explore creating charts from SQL Server data without exporting it to separate tools Microsoft Excel, SSRS or Power BI.

There is some nice functionality available for quick analysis, though I’m disappointed that I can’t choose which column(s) to include in the visual—it looks like it simply includes them all. SandDance does, though its style precludes certain types of visuals like line charts.

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Azure Data Studio April 2020 Release

Alan Yu announces the April 2020 release of Azure Data Studio:

KQL magic extension support is now available in Azure Data Studio Notebooks. It allows you to connect, query and explore Azure Data Explorer (Kusto), ApplicationInsights and LogAnalytics data using kql (Kusto Query Language). If you are using Log Analytics today for your Azure SQL DB as described here, you can now do log metric analysis using KQL magic in Azure Data Studio Notebooks. 

KQL magic package can be downloaded from Manage Packages in Python Notebook or using pip install. In a Python Notebook in Azure Data Studio, load KQL magic using (%reload_ext Kqlmagic). Start connecting, querying, and exploring using %kql or %%kql for multi-lines.   

KQL magic allows you to see tabular results similar to SQL Notebook, where you can also have the benefits of exporting outputs to other formats (csv, Excel, JSON, XML) and using the Charting functionality. You can also take advantage of rendering charts directly with plotly for richer interactivity. 

There are several fairly big changes in here, so check them all out.

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