Create a custom sensor based on airflow metadatabase? Is it a good practice?

I’m developing a data pipeline that contains two DAGs, one for each filetype. Theses DAGs are triggered via API call. There is a cloud function that controles a batch_id (stored in an cloud SQL). Each batch can contains the two files (filetype_1 and filetype_2). There is a main DAG where the API call is made to. This main DAG trigger the DAG 1 or DAG 2 (or both) based on the filetype information that is passed via Conf in the API call. In the case that the batch contains both filetypes, one API call is made for each filetype (one dag_run per filetype). At some point, I will need to check if the DAG for filetype_2 was triggered before continuing the DAG for filetype_2. But considering that are two different dag_run_ids, I was wondering if is it a good practice to modify the dag_run_id pattern, and then create a SQL sensor for airflow metadatabase to check if a dag_run_id was created for DAG filetype_2 and wait for succes in case if it exists. For illustrate this scenario, image that the batch_id would be

  • batch_id: tenant1_20221120123323
  • The default dag_run_id: manual__2022-11-19T00:00:00+00:00
  • The new dag_run_id: manual__tenant1_20221120123323_filetype2__2022-11-19T00:00:00+00:00, manual__tenant1_20221120123323_filetype1__2022-11-19T00:00:00+00:00

Then I could check in airflow metadatabase if a dag_run_id containing batch_id (tenant1_20221120123323) and filetype_2 was created to identify if filetype_2 was present in batch. In true case, then DAG_1 waits for dag_run_id for filetype_2 succeed.