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Author: Kevin Feasel

The Uniqueness of Cosmos DB Unique Keys

Published 2019-08-15 by Kevin Feasel

Hasan Savran explains the scope of unique keys in Cosmos DB:

I wrote about Unique Keys and tried to explain how they work in one of my earlier post. It’s common to use SQL Server’s Primary Key or Unique Indexes to explain Unique Keys of Azure Cosmos DB. If you have a Primary Key in a table in SQL Server, the key you defined cannot be in that table more than once. By adding a unique index or unique constraint in a table, you guarantee that no duplicate values can be in your table. The key word in both of those statement is the TABLE.

Azure CosmosDB Unique Keys do not work like Primary Key or Unique Indexes/Constraints

Read on to learn how Cosmos DB differs.

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Management Studio’s Staying Power

Published 2019-08-15 by Kevin Feasel

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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Running Power BI Desktop as a Different Account

Published 2019-08-15 by Kevin Feasel

Gilbert Quevauvilliers shows how you can run Power BI Desktop as a different domain account, even when your logged-in account is not on the domain:

This is not the greatest error message.

Fortunately, I knew that I could connect to the server so the issue was not with connectivity but more around how could I authenticate against Analysis Services.

NOTE: Analysis Services can only Authenticate against domain accounts, and that is why I got the error above.

Click through for the solution.

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SQL Server Agent Security

Published 2019-08-15 by Kevin Feasel

Claudio Silva explains how you can provide secure access to manage SQL Agent jobs:

It is common having services accounts that are job owners so they can run within the proper context.

In my humble opinion, this starts to be a little strange when it comes to modifying the agent job. It means that the service account needs permissions on agent roles and someone will need to connect to SQL Server using the service account (run as) so they can manage the agent job. It works, but not practical.

It’s not trivial, but there are roles and you can add a bit of extra code to help.

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Storing Passwords in the Database

Published 2019-08-15 by Kevin Feasel

Randolph West explains the problems with storing passwords in the database and explains the best alternative:

If you are storing passwords in a database, you should stop doing that immediately. We, as software developers and data professionals, should never know what passwords our customers are using. The same goes for most sensitive data: we technical staff probably don’t need to know what’s in there. Some stuff should be hashed, and some stuff should be encrypted.

There’s good advice here.

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Power BI Icon Names

Published 2019-08-15 by Kevin Feasel

Matt Allington is on a quest to find all of the Power BI icons:

The benefit of this approach is you can leverage all the standard icons and then add you own icons as well, effectively extending the default icon set. But where can I find a list of all the names of the standard icons?

I asked this question in the Power BI Blog thread (as did some others). A list of names was provided by Francisco Mullor in the comment section of that blog post (sorry, I can’t seem to link to the exact comment). I have taken the information provided by Francisco and produced the following Power BI report.

Matt also fixes a display issue that you might run into when using these.

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Powershell Dot-Sourcing

Published 2019-08-15 by Kevin Feasel

Shane O’Neill takes us through some of the intricacies of dot-sourcing in Powershell:

The dot used to represent the location is, as I’ve said before, for the current location. Our ConvertTo-Message02 script changed it’s location as part of the script.

When we used the “dot source dot location” method, we weren’t using where our function is as a frame of reference to import the other functions. We were using what directory we are currently in.

Interesting reading.

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Local Randomness and R

Published 2019-08-14 by Kevin Feasel

Evgeni Chasnovski has a problem around generating random data:

Let’s say we have a deterministic (non-random) problem for which one of the solutions involves randomness. One very common example of such problem is a function minimization on certain interval: it can be solved non-randomly (like in most methods of optim()), or randomly (the simplest approach being to generate random set of points on interval and to choose the one with the lowest function value).

What is a “clean” way of writing a function to solve the problem? The issue with direct usage of randomness inside a function is that it affects the state of outer random number generation:

Click through for a solution which uses random numbers but doesn’t change the outside world’s random number generation after it’s done.

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The Databricks File System

Published 2019-08-14 by Kevin Feasel

Brad Llewellyn takes us through the Azure Databricks File System:

Today, we’re going to talk about the Databricks File System (DBFS) in Azure Databricks.  If you haven’t read the previous posts in this series, Introduction, Cluster Creation and Notebooks, they may provide some useful context.  You can find the files from this post in our GitHub Repository.  Let’s move on to the core of this post, DBFS.

As we mentioned in the previous post, there are three major concepts for us to understand about Azure Databricks, Clusters, Code and Data.  For this post, we’re going to talk about the storage layer underneath Azure Databricks, DBFS.  Since Azure Databricks manages Spark clusters, it requires an underlying Hadoop Distributed File System (HDFS).  This is exactly what DBFS is.  Basically, HDFS is the low cost, fault-tolerant, distributed file system that makes the entire Hadoop ecosystem work.  We may dig deeper into HDFS in a later post.  For now, you can read more about HDFS here and here.

Click through for more detail on DBFS.

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