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Day: January 22, 2019

Azure Databricks And Active Directory

Tristan Robinson wraps up a two-parter on Azure Databricks security:

With the addition of Databricks runtime 5.1 which was released December 2018, comes the ability to use Azure AD credential pass-through. This is a huge step forward since there is no longer a need to control user permissions through Databricks Groups / Bash and then assigning these groups access to secrets to access Data Lake at runtime. As mentioned previously – with the lack of support for AAD within Databricks currently, ACL activities were done on an individual basis which was not ideal. By using this feature, you can now pass the authentication onto Data Lake, and as we know one of the advantages of Data Lake is the tight integration into Active Directory so this simplifies things. Its worth noting that this feature is currently in public preview but having tested it thoroughly, am happy with the implementation/limitations. The feature also requires a premium workspace and only works with high concurrency clusters – both of which you’d expect to use in this scenario.

It looks like this is the way to go forward with securing Azure Databricks. Read the whole thing.

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Using Plotly In Power BI

Kara Annanie shows how you can R integration in Power BI to push Plotly visuals to users:

In the example, above, we’ve created a line chart visualization using Plotly and we’ve decided to put labels on the graph, but only on the first and last points of the line graph. This graph would be particularly useful to show 13 months of data overtime, where the left-most label shows January of last year, for example, and the right-most label shows January of this year, for example. The user could still view the trend across the year between both January data points.

Click through for a pair of videos and some notes on how to get started.

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Power BI “Is Nullable” Property

Chris Webb notices a new column property in Power BI Desktop:

I was, naturally, curious about what it did and I couldn’t find any documentation so I did a bit of investigation of my own and asked a few people at Microsoft.
It turns out that it is primarily intended for validation purposes, so that if you know a column should never contain a null value and then, at a later date, a null value does appear in that column then you’ll get the following error when you try to refresh a table in Import mode:

Column ‘MyColumn’ in Table ‘TestTable’ contains blank values and this is not allowed for columns on the one side of a many-to-one relationship or for columns that are used as the primary key of a table

Read on for more information. It looks like it works just as you’d expect.

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Common DAX Error Messages

Marco Russo takes us through some of the more common Power BI error messages around writing DAX:

The message should help the author fix the code, but sometimes the text suggests a possible action without describing the underlying issue. The goal of this article is to explain the more common DAX error messages by providing a more detailed explanation and by including links to additional material. If some terms are not clear, look at the linked articles or consider some free self-paced training such as Introducing DAX.

Click through for several examples.

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Recreating Dropped Azure SQL Managed Instance DBs

Jovan Popovic has a script to re-create an Azure SQL Managed Instance database which you might accidentally have dropped:

Azure SQL Database – Managed Instance is fully-managed PaaS service that provides advanced disaster-recovery capabilities. Even if you accidentally drop the database or someone drops your database as part of security attack, Managed Instance will enable you to easily recover the dropped database.
Azure SQL Managed Instance performs automatic backups of you database every 5-10 minutes. If anything happens with your database and even if someone drops it, your data is not lost. Managed Instance enables you to easily re-create the dropped database from the automatic backups.

Click through for the Powershell script.

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SQL Server Versions: Choose Your Own Adventure

Brent Ozar has a guide to help you choose which version of SQL Server to install:

Wait! Before you install that next SQL Server, hold up. Are you sure you’re using the right version?
I know, management wants you to stay on an older build, and the vendor says they’ll only support older versions, but now’s your chance to make your case for a newer version – and I’m gonna help you do it.
I’m going to go from the dark ages forward, making a sales pitch for each newer version.

My branch logic is easier: if you need the data today, SQL Server 2017. If you need the data later this year, SQL Server 2019. If you hate your company and yourself, SQL Server 6.5.

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Resource Semaphore Waits

Arthur Daniels explains what the RESOURCE_SEMAPHORE wait type is with an example:

So according to this DMV, there’s only 3 queries with memory grants, while the remaining 5 queries have to wait for space in this semaphore. This is where the wait type comes in. When a query is sitting as a waiter, it will display the wait type RESOURCE_SEMAPHORE.

This is one of the biggest performance-killing waits you can find, and there are several ways to tackle it in SQL Server, as well as adding more hardware.

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SQL Server Data File Size Limit: 16 TB

Dave Mason learned the hard way that data files max out at 16 TB in SQL Server:

I could see that most of the stored proc execution calls were coming from the same server, which was a processing server running a web service. The customer decided to shut down the service and have a quick discussion with his dev team to see if there had been any recent changes deployed. We called it a night. I got a text the next morning. The server was rebooted, and performance had improved noticeably. None to my surprise, I got another call later that day: performance had deteriorated again.
I got back online and looked at all the same things I’d looked at before and still was puzzled.

I think this is a case where Swart’s Ten Percent Rule is easier to violate than most: terabyte-sized databases are fairly common these days, though most of them probably have multiple data files to help with piecemeal recovery.

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