airflow.providers.microsoft.azure.triggers.data_factory
¶
Module Contents¶
Classes¶
Trigger with params to run the task when the ADF Pipeline is running. |
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Trigger when the Azure data factory pipeline job finishes. |
- class airflow.providers.microsoft.azure.triggers.data_factory.ADFPipelineRunStatusSensorTrigger(run_id, azure_data_factory_conn_id, poke_interval, resource_group_name, factory_name)[source]¶
Bases:
airflow.triggers.base.BaseTrigger
Trigger with params to run the task when the ADF Pipeline is running.
- Parameters
run_id (str) – The pipeline run identifier.
azure_data_factory_conn_id (str) – The connection identifier for connecting to Azure Data Factory.
poke_interval (float) – polling period in seconds to check for the status
resource_group_name (str) – The resource group name.
factory_name (str) – The data factory name.
- class airflow.providers.microsoft.azure.triggers.data_factory.AzureDataFactoryTrigger(run_id, azure_data_factory_conn_id, end_time, resource_group_name, factory_name, wait_for_termination=True, check_interval=60)[source]¶
Bases:
airflow.triggers.base.BaseTrigger
Trigger when the Azure data factory pipeline job finishes.
When wait_for_termination is set to False, it triggers immediately with success status.
- Parameters
run_id (str) – Run id of a Azure data pipeline run job.
azure_data_factory_conn_id (str) – The connection identifier for connecting to Azure Data Factory.
end_time (float) – Time in seconds when triggers will timeout.
resource_group_name (str) – The resource group name.
factory_name (str) – The data factory name.
wait_for_termination (bool) – Flag to wait on a pipeline run’s termination.
check_interval (int) – Time in seconds to check on a pipeline run’s status.