theis188 opened a new issue, #44793:
URL: https://github.com/apache/airflow/issues/44793

   ### Apache Airflow version
   
   2.10.3
   
   ### If "Other Airflow 2 version" selected, which one?
   
   _No response_
   
   ### What happened?
   
   The Airflow scheduler does not choose consistently between 
`sql_alchemy_conn` and `sql_alchemy_conn_secret`. If both are set and point to 
different databases, this can cause errors.
   
   For example, DAGs populated into the `sql_alchemy_conn` connection, but when 
trying to run a TriggerDagRunOperator, it would run into a bug because it would 
apparently connect through `sql_alchemy_conn_secret` and run into database 
errors (DAG not found etc).
   
   These settings were misconfigured on my side, but there a consistent 
resolution order would help to surface these misconfigurations.
   
   ### What you think should happen instead?
   
   There should be a consistent resolution order. Probably `sql_alchemy_conn` 
should be preferred, then the other options `_cmd`, then `_secret`, but the 
exact order would be less important than having it be consistent.
   
   ### How to reproduce
   
   Set `sql_alchemy_conn` and `sql_alchemy_conn_secret` to point to different 
databases.
   
   In my case, `sql_alchemy_conn_secret` database was upgraded to a lower 
version (`2.8.1`) and the schema difference caused errors.
   
   Try to trigger a DAG through `TriggerDagRunOperator`, eg:
   
   ```
   import datetime
   from airflow import DAG
   from airflow.operators.trigger_dagrun import TriggerDagRunOperator
   from airflow.operators.empty import EmptyOperator
   
   with DAG(
       "my_automation_dag",
       start_date=datetime.datetime(year=2024, day=1, month=1),
   ) as dag:
       task = TriggerDagRunOperator(
           task_id="trigger_new_task",
           trigger_dag_id="my_task_dag",
       )
   
   with DAG(
       "my_task_dag",
       start_date=datetime.datetime(year=2024, day=1, month=1),
   ) as task_dag:
       empty_task = EmptyOperator(
           task_id="my_empty_task"
       )
   ```
   
   The DAGs will populate to the `sql_alchemy_conn` database but 
TriggerDagRunOperator should fail.
   
   You might get the same error as I did, about a missing column, 
`task_instance.task_display_name`.
   
   
   
   
   
   
   ### Operating System
   
   Debian GNU/Linux 12 (bookworm)
   
   ### Versions of Apache Airflow Providers
   
   ```
   apache-airflow-providers-amazon==8.23.0
   apache-airflow-providers-cncf-kubernetes==7.14.0
   apache-airflow-providers-common-compat==1.2.2
   apache-airflow-providers-common-io==1.4.2
   apache-airflow-providers-common-sql==1.20.0
   apache-airflow-providers-fab==1.5.1
   apache-airflow-providers-ftp==3.11.1
   apache-airflow-providers-http==4.13.3
   apache-airflow-providers-imap==3.7.0
   apache-airflow-providers-postgres==5.14.0
   apache-airflow-providers-slack==8.9.2
   apache-airflow-providers-smtp==1.8.1
   apache-airflow-providers-sqlite==3.9.1
   ```
   
   ### Deployment
   
   Virtualenv installation
   
   ### Deployment details
   
   _No response_
   
   ### Anything else?
   
   _No response_
   
   ### Are you willing to submit PR?
   
   - [ ] Yes I am willing to submit a PR!
   
   ### Code of Conduct
   
   - [X] I agree to follow this project's [Code of 
Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)
   


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