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1. Triggerdagrunoperator airflow 2.0 example how to#
2. Triggerdagrunoperator airflow 2.0 example software#
3. Triggerdagrunoperator airflow 2.0 example code#
4. Triggerdagrunoperator airflow 2.0 example license#

PythonOperator ( dag = dag_b, task_id = 'some_task_id', python_callable = call_with_desired_context, provide_context = True, )įinally, as an aside, note that in the case of passing through the ds from context, it is also an option to use execution date. # which will now be the same as the one from dag_a conf # trigger lambda, do whatever you want with this ds from airflow import DAG dag_a = DAG ( 'dag_a_id', default_args =, schedule_interval = None, catchup = False, ) def call_with_desired_context ( ** context ): ds = context. With this set, one can initialize the DAG as shown below. One pattern is to use the on_success_callback key on the default_args that get passed into the DAG class that initializes dag_a. Now, the question is where to fire the trigger for dag_b. execute ( context ) Triggering a DAG run from another TriggerDagRunOperator ( task_id = 'unique_dag_run_operator_id', trigger_dag_id = 'dag_b_id' ). This can then be used from within dag_a to call for a run of dag_b. This will be triggered in TriggerDagRunOperator during its initialization step in the following line: super(TriggerDagRunOperator, self)._init_(*args, **kwargs).Īt a bare minimum, we might represent a trigger of dag_b as the following.

Triggerdagrunoperator airflow 2.0 example code#

If you review the source code, it won’t be immediately obvious that this parameter is required.īut, if you review the source code for BaseOperator the abstract base class for TriggerDagRunOperator, you will see that a task_id is required for initialization. execution_date: this is an optional date time objectĪ gotcha is that, in addition to those three parameters, it also requires a unique task_id as well.python_callable: an optional python method that receives the current context object and is also passed the dag_run object.Airflow documentation as of 1.10.10 states that this TriggerDagRunOperator requires the following parameters: This can be achieved through the DAG run operator TriggerDagRunOperator. Triggering a DAG can be accomplished from any other DAG so long as you have the other DAG that you want to trigger’s task ID. This is undesirable - as we would want the backfill date string being provided to dag_a to also be propagated through to the second DAG, dag_b. Instead, a new context is generated for dag_b, and, as a result, dag_b has a context which has the current date, 06-01. But, when the first DAG triggers the second DAG, dag_b, dag_b does not receive the same context. When the backfill DAG job is triggered in Airflow, dag_a receives a context which includes the date for the backfill job (in this case, the 04-13 date). The backfill date is going to be for 04-13-2020. Let’s say the current date is 06-01-2020. In this example, you might have one DAG and a second, let’s call them dag_a and dag_b. Why would you want to pass the context from the first DAG to the second? For example, let’s say you want to trigger a backfill or rerun a DAG for a prior date.

Triggerdagrunoperator airflow 2.0 example how to#

Second, I demonstrate how to pass through the context from the first DAG to the second. First, I document how to trigger a DAG from within another Airflow DAG, without the trigger being attached to either DAG. The intent of this post is to demonstrate how to accomplish two tasks. External DAG triggers in Airflow May 31, 2020 2nd DAG (example_trigger_target_dag) which will be triggered by the TriggerDagRunOperator in the 1st DAG """ import pendulum from airflow import DAG from _dagrun import TriggerDagRunOperator with DAG ( dag_id = "example_trigger_controller_dag", start_date = pendulum. 1st DAG (example_trigger_controller_dag) holds a TriggerDagRunOperator, which will trigger the 2nd DAG 2.

""" Example usage of the TriggerDagRunOperator.

Triggerdagrunoperator airflow 2.0 example license#

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Triggerdagrunoperator airflow 2.0 example software#

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