ChunPo's avatar
ChunPo
New Member
6 months ago
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Need Clarification

Enable Dataflow Gen2 to Dynamically Adjust Schema Mapping & Resource Paths Using Pipeline Parameters

Please consider enabling Dataflow Gen2 to:

  1. Dynamically adjust schema mapping at runtime based on the resolved parameter value.
  2. Allow resource paths (such as Lakehouse table names) to be fully driven by public parameters from pipelines.
  3. Support end‑to‑end dynamic data ingestion patterns commonly used in modern data engineering.

@https://learn.microsoft.com/en-us/fabric/data-factory/dataflow-parameters#considerations-and-limitations

7 Comments

  • miguel's avatar
    miguel
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    Hi! 

    Could you tell us a bit more about the scenario for #1 and #3?

     

    For #2, and specifically for your case with Lakehouse destinations, changing the name of your table is completely supported for Dataflow public parameters. You can follow the tutorial below for more information on how to make that happen:

    Parameterized Dataflow Gen2 - Microsoft Fabric | Microsoft Learn

  • I have contacted the support team and here is their response: Please review the document below, which outlines that using public parameters is limited when parameters change the resource path for either the source or destination. Additionally, parameters cannot be used to modify schema mapping. @https://learn.microsoft.com/en-us/fabric/data-factory/dataflow-parameters#considerations-and-limitations
  • miguel's avatar
    miguel
    Icon for Community Admin rankCommunity Admin

    That is correct information. However, changing the LakehouseId, WorkspaceId or TableName when using the Lakehouse connector (point #2) do not impact the resource path. By resource path we are referring to the connection component as described in the Dataflow item definition from the link below:

    Dataflow definition - Microsoft Fabric REST APIs | Microsoft Learn

     

    If you could tell us a bit more about your scenario for #1 and #3, perhaps with an example, that would help tremendously.

  • AMladenov's avatar
    AMladenov
    Regular Visitor
    miguel I have the following use-case for #1/#3 - Metadata driven dataflow which ingest X number of excel files from a Sharepoint, the parameters (sourcepath, filename, column mapping, column datatypes, destination schema, destination tablename, filters on columns and etc.) are read from a JSON files with a ForEach loop and fed to the dataflow. Currently I cannot manage to parametrize the data destination table schema, it does not follow the set schema in the dataflow for the current ingested file (at runtime), the one set at the time of dataflow creation through the UI persists.
  • AMladenov's avatar
    AMladenov
    Regular Visitor
    miguel the columns of the table during output. "Data destination" column mapping does not update on run even on "Use automatic setting", dataflow needs to be republished.

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