Azure datafactory Error

Ahmed ELHOULA 11 Reputation points
2021-02-22T04:57:53.797+00:00

I have this error in my pipe:
There are substantial concurrent MappingDataflow executions which is causing failures due to throttling under Integration Runtime

Azure Data Factory
Azure Data Factory
An Azure service for ingesting, preparing, and transforming data at scale.
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  1. PRADEEPCHEEKATLA-MSFT 77,751 Reputation points Microsoft Employee
    2021-02-22T08:53:27.073+00:00

    Hello @Ahmed ELHOULA ,

    Welcome to the Microsoft Q&A platform.

    You may experience this error message when you've reached the integration runtime's capacity limit.

    Error message:

    Type=Microsoft.DataTransfer.Execution.Core.ExecutionException,Message=There are substantial concurrent MappingDataflow executions which is causing failures due to throttling under Integration Runtime 'AutoResolveIntegrationRuntime'.  
    

    Cause: You've reached the integration runtime's capacity limit. You might be running a large amount of data flow by using the same integration runtime at the same time. See Azure subscription and service limits, quotas, and constraints for details.

    Resolution:

    • Run your pipelines at different trigger times.
    • Create a new integration runtime, and split your pipelines across multiple integration runtimes.

    Reference: A pipeline run fails when you reach the capacity limit of the integration runtime

    Hope this helps. Do let us know if you any further queries.

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  2. Ahmed ELHOULA 11 Reputation points
    2021-03-04T16:41:26.803+00:00

    Hello

    Soryy for my late answer
    yes it hlped me .

    Thank you


  3. Kelvin 1 Reputation point
    2022-09-19T23:31:58.58+00:00

    Hello,

    we got the same error even run only one pipeline. any idea? how to checking how many MappingDataflow is running ? Thanks a lot

    Operation on target DF_Upsert_Wind_D_Sensor failed: There are substantial concurrent MappingDataflow executions which is causing failures due to throttling under Integration Runtime 'ir-mvn', ActivityId: '4e9dc4a4-b41f-418d-92d8-7418427be66f'.

    Cheers,
    Kelvin

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