However while learning basics of Airflow I was relying on manual triggering of DAGs ( schedule_interval=None). Therefore the behaviour I'm observing is understandable.ĮxternalTaskSensor is the obvious way out. By default, it is not supposed to wait for completion of DAG. Looking at the implementation, it becomes clear that the job of TriggerDagRunOperator is just to trigger external DAG and that's about it. How to force TriggerDagRunOperators to await completion of DAG? Extending SubDagOperator to remove this check might work but I decided to steer clear of it How to overcome limitation of parent_id prefix in dag_id of SubDags?Īs told there's no straight way of achieving this. I'm hereby posting my (partial) answer will update as and when things become clear. Taking hints from Parekh's answer, I was able to make TriggerDagRunOperator work in the intended fashion. So there isn't just one TriggerDagRunOperator that I could put at last, there are many (here 3, but would be upto 15 in production) I have to chain several similar (differing only in arguments) DAGs together in a workflow that triggers them one-by-one. Would it be possible to just have the TriggerDagRunOperator be the NOTE: In this example, the top-level DAGs are named as importer_child_v1_db_X and their corresponding task_ids (for TriggerDagRunOperator) are named as importer_v1_db_X Actually the logs indicate that while they are fired one-after another, the execution moves onto next DAG ( TriggerDagRunOperator) before the previous one has finished. When I trigger the import_parent_v1 DAG, all the 3 external DAGs that it is supposed to fire using TriggerDagRunOperator start running parallely even when I chain them sequentially. Is there a workaround for my approach of creating separate files (for DAGs that differ only in input) for each top-level DAG?Ĭan you give some more detail on what you mean by awaiting completion.Any alternate / better way to wire-up independent (top-level) DAGs together?.How to force TriggerDagRunOperators to await completion of DAG?.How to overcome limitation of parent_id prefix in dag_id of SubDags?.ExternalTaskSensor might help overcome above limitation but it would make things very messy.Works in my demo but runs in parallel (not sequentially) as it doesn't wait for triggered DAG to finish before moving onto next one.SubDag's dag_id must be prefixed by it's parent's, that would force absurd IDs on top-level DAGs that are supposed to be functional independently too.Can lead to deadlocks but there are easy solutions still there's a lot of haze around using them.I have identified two ways this could be done: So I created one file for each DAG in my dags directory and now I must wire them up for sequential execution. Currently they must be run together in series in future they may require parallel triggering.Irrespective of whether a DAG fails or succeeds, the chain of triggering must not break.Order and number of DAGs in series is fixed (known ahead of writing code) and changes rarely (once in a few months).The series of DAGs, however, needs to run daily.Individual top-level DAGs will have schedule_interval=None as they will only need occasional manual triggering.I need to have several identical (differing only in arguments) top-level DAGs that can also be triggered together with following constraints / assumptions: 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. ![]() See the License for the # specific language governing permissions and limitations # under the License. You may obtain a copy of the License at # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. ![]() The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License") you may not use this file except in compliance # with the License. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements.
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