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anawast
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fabric.evaluate_dax() when run in context of SPN fails
We have been running a notebook which leverages fabric.evaluate_dax() through a pipeline. When the pipeline was created in the context of a user (that is my alias) everything runs smoothly. However the moment the pipeline is created by a SPN- we face a 401 unauthorised error. It says that it is unauthorised for the url: https://api.powerbi.com/powerbi/globalservice/v201606/clusterdetails, which the fabric.evaluate_dax() function is probably using internally. On the semantic model on which we want to run the dax query the permission that I have as a user and that of the SPN are identical. Does anyone have any inisghts into this?Solved860Views0likes4CommentsDynamically get notebook snapshot link when using mssparkutils.notebook.run()
When I use mssparkutils.notebook.run() to a run a notebook from a parent notebook, it generates a snapshot link of the notebook in the output window of the parent notebook- clicking on which I can view the execution of each cell of the notebook in question. I would like to dynamically get this snapshot link. Could you plese help with how one can do that?Solved1.2KViews0likes4CommentsAlias Semantic Model Links
Hi. For AAS servers we had the option of aliasing the server names like here: https://learn.microsoft.com/en-us/azure/analysis-services/analysis-services-server-alias Is there a process via which we could do the same for Semantic Model links? Replacing the AAS server link with the semantic model link in the web app does not work.Solved1.2KViews1like6CommentsRe: Awaiting Futures not blocking when present in loops or functions
Can you suggest what you would use instead of the below code, in that case? def parallelNotebooks(notebookMetadata):Future[Seq[String]]= { //runs notebooks in parallel } breakable { while (true) { val now: LocalDateTime = LocalDateTime.now() println(now) val duration = java.time.Duration.between(start, now) val executedMinutes = duration.toHours * 60 + duration.toMinutes if (executedMinutes > threshold_executionMinutes) { break() } val df = // Get data from metadata if (df.count() == 0) { break() } val notebookMetadata = //get seq from df val res = parallelNotebooks(notebookMetadata) Await.result(res, scala.concurrent.duration.Duration.Inf) } }1.1KViews0likes4CommentsAwaiting Futures not blocking when present in loops or functions
As per this documentation: https://docs.scala-lang.org/overviews/core/futures.html Await.results() should block until all futures have completed. This works as expected when called in an individual cell in a Fabric Notebook. However, when called within a loop or if present in a function and called through the function- the same doesn't work. As you can see below things work fine if called within a cell: However if called within a function (or in a loop)- the same doesn't work.Solved1.2KViews0likes6CommentsHigh Concurrency Notebook- run by separate data pipelines
Hi, when we tested high concurrency in the past for Fabric we faced two main blockers: 1. The notebooks needed to have the same default lake house 2. The notebooks couldn't be run by multiple pipelines. That is for 2 notebooks to run in high concurrency- and scheduled through pipelines- they needed to be run by 1 data pipeline. Wanted to check- if there have been any changes here and these restrictions have been relaxed. can I now run 2 notebooks in high concurrency running each notebook through a different data pipeline? Will high concurrency work even if the notebooks do not share the same default lakehouse? If not- is there any plan to relax these requirements in the future?Solved1.5KViews0likes5CommentsCold Start when Semantic Model is in direct lake mode
Hi Team, we do know that when a semantic model is in direct lake mode, it suffers from a cold start until the cache is warmed up through usage. Is there any plan to warm up the semantic model proactively (through telemtry usage or loading a subset/full-set of attributes into the cache)?Solved1.5KViews0likes3CommentsRe: High Concurrency Pipelines doesn't seem to be working as expected
No, I mean across Pipelines. Within the same workspace, I can create multiple pipelines. So if I create 2 pipelines, each with a notebook activity, these 2 notebooks don't share a single session, i.e., they do not run as high concurrency would expect.1.9KViews0likes1Comment
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