Connecting Power BI to Azure Databricks

I work a lot with Azure Databricks and a topic that always comes up is reporting on top of the data that is processed with Databricks. Even though notebooks offer some great ways to visualize data for analysts and power users, it is usually not the kind of report the top-management would expect. For those scenarios, you still need to use a proper reporting tool, which usually is Power BI when you are already using Azure and other Microsoft tools.

So, I am very happy that there is finally an official connector in PowerBI to access data from Azure Databricks! Previously you had to use the generic Spark connector (docs) which was rather difficult to configure and did only support authentication using a Databricks Personal Access Token.

With the new connector you can simply click on “Get Data” and then either search for “Azure Databricks” or go the “Azure” and scroll down until you see the new connector:

The next dialog that pops up will ask you for the hostname and HTTP path – this is very similar to the Spark connector. You find all the necessary information via the Databricks Web UI. As this connection is always bound to an existing cluster you need to go the clusters details page and check the Advanced Tab “JDBC/ODBC” as described here:
(NOTE: you can simply copy the Server Hostname and the HTTP Path from the cluster page)

The last part is then the authentication. As mentioned earlier the new connector now also supports Azure Active Directory authentication which allows you to use the same user that you use to connect to the Databricks Web UI!
Personal Access Tokens are also still supported and there is also Basic authentication using username/password.

Once you are connected, you can choose the tables that you want to import/connect and start building your report!

Here is also a quick overview which features are supported by the Spark and the Azure Databricks connector as there are some minor but important differences:

Feature ComparisonSpark ConnectorDatabricks Connector
Power BI DesktopYESYES
Power BI ServiceYESYES *
Direct Query (Desktop)YESYES
Direct Query (Service)YESYES *
Import ModeYESYES
Manual Refresh (Service)YESYES *
Scheduled Refresh (Service)YESYES *
Azure Active Directory (AAD) AuthenticationNOYES
Personal Access Token AuthenticationYESYES
Username/Password AuthenticationYESYES
General AvailableYESYES
Performacne Improvements with Spark 3.xNO *YES *
Supports On-Premises data gatewayYESNO
Features supported by Spark and Databricks Connector for PowerBI

*) Updated 2020-10-06: the new Databricks Connector for PowerBI now supports all features also in the PowerBI service!

Update 2020-10-06: So from the current point of view the new Databricks Connector is a superset of old Spark Connector with additional options for authentication and better performance with the latest Spark versions. So it is highly recommended to use the new Databricks Connector unless you have very specific reasons to use the Spark connector! Actually the only reason why I would still use the Spark connector is the support for the On-Premises data gateway in case your Spark or Databricks cluster is hosted in a private VNet.

So currently the generic Spark connector still looks superior simply for the support in the Power BI Service. However, I am quite sure that it will be fully supported also by the Power BI Service in the near future. I will update this post accordingly!
On the other hand, Azure Active Directory authentication is a huge plus for the native Azure Databricks connector as you do not have to mess around with Databricks Personal Access Tokens (PAT) anymore!

Another thing that I have not yet tested but would be very interesting is whether Pass-Through security works with this new connector. So you log in with your AAD credentials in Power BI, they get passed on to Databricks and from there to the Data Lake Store. For Databricks Table Access Control I assume this will just work as it does for PAT as it is not related to AAD authentication.

Upgrading your reports from PowerBI to Azure Analysis Services

Since April 2017 it is possible to build reports on top of datasets that are hosted in the PowerBI service. This was announced and described here and here in more detail. This might not seem like a big deal at first sight, but it can have a huge impact on how you work with PowerBI. By separating the data model from the report, you can have two or more independent people working with the same dataset. Also, the people who build the reports in the end most not necessarily have the knowledge to build a data model – the just need to use it. So, there are some clear advantages when you split up your workbook:

  • separation of duty (data modeler vs. report builder)´
  • any number of reports on top of the same model
  • easy control over reports as the files are quite small (they only contain the definition of the report)

This is all pretty cool and, from my point of view, the way to go once you want to use the reports in production and/or have several people working on/with the same reports.

But lets go a step further. After some time, as your data model grows, you realize that the reports get slow and also the processing takes a considerable amount of time to finish. The official upgrade path will then guide you to Azure Analysis Services and you will migrate your data model to deal with the larger data volumes and make use of the flexibility in processing you gained by your upgrade. This migration process is very well described here.

So far so good, but what happens to your reports? Last week I was in exactly the position described above and we had to migrate the existing reports (which were base on a dataset hosted in PowerBI) to Azure Analysis Services. As of now, there is now simple way to simply change the connection string from PowerBI to Azure Analysis Services neither in PBI Desktop nor in the Service. But we could think of some options how it might work:

  • rebuild all reports
  • use the REST API to update the connection string of the existing reports
  • modify the .pbix file manually (NOT OFFICIALLY SUPPORTED)

As you can imagine, rebuilding all reports was not really an option.

The next option, the PowerBI REST API looked pretty promising at first sight. It allows you to retrieve and set the dataset that is used by your report. So the idea is to simply create a new dataset which points to Azure Analysis Services in Live Query mode, take the existing report and use the Rebind API call to bind it to the new AAS dataset. Even though this is supposed to work, I could not make it work in my environment. I tried all things that I could think of but nothing work and I also gave up on this.

So I was stuck there but knew that the information of the data source has to be somewhere in the .pbix file. In the past I already did something similar with Excel/PowerPivot files (“Restoring a SSAS Tabular model to PowerPivot”) so I thought I would also give it a try for .pbix files. And it turns out that they are quite similar. For those of you who are new to this, most (if not all) of the files that are associated with a Microsoft tool and end with “x” (e.g. .xlsx/docx/…) are just ZIP-files in the end. To unzip them, simply rename them to .zip and use your favorite zip-tool to open them. You will see a file-structure similar to the one below:
pbix zip file content

(If your file contains a data model, you see a file called “DataModelSchema” instead of “Connections”. The next steps will not work in this case!). However, in our case, as the report is linked to a dataset hosted in the PowerBI service, our file does not contain any data itself but only the connection information to our data source. As you can guess, this information is stored in the “Connections” file.

To see what a connection to an Azure Analysis Services dataset looks like, I simply created a new PowerBI desktop model and established a Live Connection. Saved it and opened it again as zip file. The Connection file itself is just a JSON but the details are not really relevant here. I simply replaced the Connections file from my original report with the one from my new workbook linked to AAS. Renamed it back to pbix, opened it and voilà, my report was connected to AAS!

This saved us a lot of time and we could move all of our reports within a couple of hours!

Please keep in mind, that this is not officially supported and might break your model. So make sure to always create a backup before you modify the contents of a pbix file manually!
I do not take any responsibility for any broken models or anything else that might happen!