is the datastore only support AzureBlob? could you call out of that?

[ccyjava]

I try to create a change-based schedule but got the failure if I am using ADLS as the datastore.

datastore = Datastore(workspace=ws, name="adls_segrel11") reactive_schedule = Schedule.create(ws, name="MyReactiveSchedule", description="Based on input file change.", pipeline_id=pipeline_id, experiment_name=experiment_name, datastore=datastore, datapath parameter_name="local/AML_Temp/TTLShort/Trigger/data2")

Schedule.create(workspace, name, pipeline_id, experiment_name, recurrence, description, pipeline_parameters, wait_for_provisioning, wait_timeout, datastore, polling_interval, data_path_parameter_name, continue_on_step_failure, path_on_datastore, _workflow_provider, _service_endpoint) 374 if datastore is not None: 375 if datastore.datastore_type != 'AzureBlob': --> 376 raise ValueError('Datastore must be of type AzureBlobDatastore') 377 datastore_name = datastore.name 379 from azureml.pipeline.core._graph_context import _GraphContext

ValueError: Datastore must be of type AzureBlobDatastore

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Document Details

⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

• ID: e60dd174-3b79-db95-a665-991bcf3b9579
• Version Independent ID: 70221e45-7afe-7f3c-1fcd-373d7e92eb6b
• Content: Trigger Azure Machine Learning pipelines - Azure Machine Learning
• Content Source: articles/machine-learning/how-to-trigger-published-pipeline.md
• Service: machine-learning
• Sub-service: mlops
• GitHub Login: @Blackmist
• Microsoft Alias: larryfr

[YutongTie-MSFT]

Thanks for the feedback! We are currently investigating and will update you shortly.

[Blackmist]

@ccyjava Thanks for the feedback!

@lgayhardt - Can you confirm the behavior with the pipelines PM and update the document as needed?

reassign:lgayhardt

[likebupt]

Sorry for the inconvenience. Currently v1 schedule only supports AzureBlobStorage. We will call out in document.

[lgayhardt]

The doc has been update with a note. Thanks!

please-close