If Fabric pipelines support array and object parameters without issue and a Spark Notebook within the pipeline can leverage the pipeline parameters for configurable notebook execution than it would be nice for both to support the same range of data types for their parameters.
This would be a QOL adjustment instead of having to pass strings that are parsed into json objects in the notebook. It would also allow, in a more complex workflow, the ability to cleanly use an array in a forEach loop in the pipeline and potentially handle it in a seperate fashion in a notebook.
miguel
on:
Enable CI/CD for Dataflow Gen2 across all Fabric S...
on:
Need more details on Average utilization% in Capac...
lbendlin
on:
Increase the 1,000 Item Limit per Fabric Workspace
on:
Power BI Reports with GIS data
NaamaTsafrir
on:
Rename "Domain Admin" to "Domain Owner" to match P...