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Category: Microsoft Fabric

Visualizing a Spark Execution Plan

Published 2024-05-01 by Kevin Feasel

Gerhard Brueckl builds a very helpful tool:

I recently found myself in a situation where I had to optimize a Spark query. Coming from a SQL world originally I knew how valuable a visual representation of an execution plan can be when it comes to performance tuning. Soon I realized that there is no easy-to-use tool or snippet which would allow me to do that. Though, there are tools like DataFlint, the ubiquitous Spark monitoring UI or the Spark explain() function but they are either hard to use or hard to get up running especially as I was looking for something that works in both of my two favorite Spark engines being Databricks and Microsoft Fabric.

Read on for Gerhard’s answer, including an example of it in action.

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Understanding the Delta Lake Format

Published 2024-04-30 by Kevin Feasel

Reza Rad has a new post and video combo:

Please don’t get lost in the terminology pit regarding analytics. You have probably heard of Lake Structure, Data Lake, Lakehouse, Delta Tables, and Delta Lake. They all sound the same! Of course, I am not here to talk about all of them; I am here to explain what Delta Lake is.

Delta Lake is an open-source standard for Apache Spark workloads (and a few others). It is not specific to Microsoft; other vendors are using it, too. This open-source standard format stores table data in a way that can be beneficial for many purposes.

In other words, when you create a table in a Lakehouse in Fabric, the underlying structure of files and folders for that table is stored in a structure (or we can call it format) called Delta Lake.

Read on to learn more about this open standard and how it all fits together with Microsoft Fabric.

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Exporting and Sharing Power BI Reports in Fabric

Published 2024-04-25 by Kevin Feasel

Sandeep Pawar distributes PDFs like candy:

With the proposed solution below, you will be able to :

  • Export a Power BI report, or a page of a report or a specific visual from any page as a PDF, PNG, PPTX or other supported file formats
  • Apply report level filters before exporting
  • Automate the extracts on a schedule
  • Save the exported reports to specific folders
  • Grant access to individual folders in the Lakehouse

Click through for the solution.

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Searching for Tenant Settings in Microsoft Fabric

Published 2024-04-23 by Kevin Feasel

Nicky van Vroenhoven performs a search:

You probably also use the same method as I did to search through the Admin portal and tenant settings: CTRL + F from your browser. It does the trick, but not very well. 

For example, it only searches the titles of the settings, not the descriptions.

Next to that, you also can get a lof matches that you have to scroll or loop through, which makes it not very clear because more often than not, you don’t know in what section of the tenant settings you ended up.

Read on for an alternative method of searching. Or, I guess, two of them because without Nicky’s post, it can be easy to confuse the two search boxes.

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Enterprise Agreements and Transitioning from Power BI P SKUs to Fabric F SKUs

Published 2024-04-22 by Kevin Feasel

David Eldersveld talks licensing:

To facilitate a smooth transition from Power BI to Fabric (new capabilities), Microsoft ensured customers could access these new Fabric workloads as well as Copilot for Power BI on their existing Power BI Premium capacity P SKUs.

However, with the introduction of Azure-billed pay-as-you-go and annual reservation F SKUs for Microsoft Fabric, Microsoft recently announced the eventual retirement of the Power BI Premium per capacity SKUs that needs to consider an organization’s Enterprise Agreement (EA) timing.

Read on to learn more, especially if you currently have a Power BI Premium P1 (or higher) SKU.

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Refreshing a Power BI Semantic Model via Fabric Pipelines

Published 2024-04-18 by Kevin Feasel

Marc Lelijveld builds a pipeline:

Recently, Microsoft released a new activity type to trigger Power BI Semantic Model refreshes. A great step forward to have a native pipeline activity and no longer need to setup complex steps with APIs and authentication manually. Or is there still a case?

In this blog I will elaborate on what this new Pipeline activity exactly is, various scenarios in which it can be applied and finally some edge cases and shortcomings.

Click through to see how it works.

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Mirroring Snowflake to Microsoft Fabric

Published 2024-04-16 by Kevin Feasel

Reza Rad hogs the photocopier:

Microsoft Fabric offers an end-to-end SaaS analytics solution; however, the world is using all kinds of data sources in its implementation. Mirroring is a new functionality in Fabric that allows customers to keep their data wherever they are, but then they can use Fabric analytics solutions with the same speed and performance as if their data were in Fabric. Best of all, this won’t cost extra. If you wonder what it is and how it works, read this article.

Click through for the video and article.

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A Scaffolding Design Pattern for Microsoft Fabric Pipelines

Published 2024-04-15 by Kevin Feasel

Andy Leonard shares some thoughts on design:

When assigned a project, it’s tempting – and dangerous – to Just Start Coding. If you suffer from the urge to develop first and design later, you are not alone (there’s at least one other developer like you and he’s typing this post). Do yourself a favor and…

Read on for more information on Andy’s design-first mentality and a sample of how you might lay out that initial design.

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Mirroring Azure SQL DB into Microsoft Fabric

Published 2024-04-12 by Kevin Feasel

Dennes Torres holds up a mirror:

You need to read data from production to build a single source of truth. If you create pipelines reading directly from production, you will create additional load over the production environment. The mirror allows you to do much of the production reporting from the mirror, leaving the production environment to serve other users. Keep in mind, production report, but not analytics report.

Mirroring a production database to Fabric is one method to ensure the load over production will be as low as possible and the data will be transferred fabric to complete the transformations from this point.

Only this? What about avoiding pipeline creation? Not really, you still need to create pipelines, as I will explain ahead.

Click through for the demo and explanation. This is an important thing for people to note: mirroring doesn’t eliminate ELT. You still have the data lake process to work through, as your transactional system does not and should not look like your reporting system.

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