Alaeddine22 opened a new issue, #27329:
URL: https://github.com/apache/airflow/issues/27329
### Apache Airflow version
Other Airflow 2 version (please specify below)
### What happened
Hello,
I installed the stable version 2.4.1 with sqlAlchemy configured for an
Oracle database.
when running airflow standalone i'm having the following error :
`sqlalchemy.exc.DatabaseError: (cx_Oracle.DatabaseError) ORA-00972:
identifier is too long
[SQL: SELECT dag.dag_id AS dag_dag_id, dag.root_dag_id AS dag_root_dag_id,
dag.is_paused AS dag_is_paused, dag.is_subdag AS dag_is_subdag, dag.is_active
AS dag_is_active, dag.last_parsed_time AS dag_last_parsed_time,
dag.last_pickled AS dag_last_pickled, dag.last_expired AS dag_last_expired,
dag.scheduler_lock AS dag_scheduler_lock, dag.pickle_id AS dag_pickle_id,
dag.fileloc AS dag_fileloc, dag.processor_subdir AS dag_processor_subdir,
dag.owners AS dag_owners, dag.description AS dag_description, dag.default_view
AS dag_default_view, dag.schedule_interval AS dag_schedule_interval,
dag.timetable_description AS dag_timetable_descriptio_1, dag.max_active_tasks
AS dag_max_active_tasks, dag.max_active_runs AS dag_max_active_runs,
dag.has_task_concurrency_limits AS dag_has_task_concurrency_2,
dag.has_import_errors AS dag_has_import_errors, dag.next_dagrun AS
dag_next_dagrun, dag.next_dagrun_data_interval_start AS
dag_next_dagrun_data_int_3, dag.next_dagrun_data_interval_end AS dag_next
_dagrun_data_int_4, dag.next_dagrun_create_after AS
dag_next_dagrun_create_a_5, dag_tag_1.name AS dag_tag_1_name, dag_tag_1.dag_id
AS dag_tag_1_dag_id, dag_schedule_dataset_ref_1.dataset_id AS
dag_schedule_dataset_ref_6, dag_schedule_dataset_ref_1.dag_id AS
dag_schedule_dataset_ref_7, dag_schedule_dataset_ref_1.created_at AS
dag_schedule_dataset_ref_8, dag_schedule_dataset_ref_1.updated_at AS
dag_schedule_dataset_ref_9, task_outlet_dataset_refe_2.dataset_id AS
task_outlet_dataset_refe_a, task_outlet_dataset_refe_2.dag_id AS
task_outlet_dataset_refe_b, task_outlet_dataset_refe_2.task_id AS
task_outlet_dataset_refe_c, task_outlet_dataset_refe_2.created_at AS
task_outlet_dataset_refe_d, task_outlet_dataset_refe_2.updated_at AS
task_outlet_dataset_refe_e
FROM dag LEFT OUTER JOIN dag_tag dag_tag_1 ON dag.dag_id = dag_tag_1.dag_id
LEFT OUTER JOIN dag_schedule_dataset_reference dag_schedule_dataset_ref_1 ON
dag.dag_id = dag_schedule_dataset_ref_1.dag_id LEFT OUTER JOIN
task_outlet_dataset_reference task_outlet_dataset_refe_2 ON dag.dag_id =
task_outlet_dataset_refe_2.dag_id
WHERE dag.dag_id IN (:dag_id_1_1, :dag_id_1_2, :dag_id_1_3, :dag_id_1_4,
:dag_id_1_5, :dag_id_1_6, :dag_id_1_7, :dag_id_1_8, :dag_id_1_9, :dag_id_1_10,
:dag_id_1_11, :dag_id_1_12, :dag_id_1_13, :dag_id_1_14, :dag_id_1_15,
:dag_id_1_16, :dag_id_1_17, :dag_id_1_18, :dag_id_1_19, :dag_id_1_20,
:dag_id_1_21, :dag_id_1_22, :dag_id_1_23, :dag_id_1_24, :dag_id_1_25,
:dag_id_1_26, :dag_id_1_27, :dag_id_1_28, :dag_id_1_29, :dag_id_1_30,
:dag_id_1_31, :dag_id_1_32, :dag_id_1_33, :dag_id_1_34, :dag_id_1_35,
:dag_id_1_36, :dag_id_1_37, :dag_id_1_38, :dag_id_1_39, :dag_id_1_40,
:dag_id_1_41, :dag_id_1_42) FOR UPDATE OF ]
[parameters: {'dag_id_1_1': 'latest_only', 'dag_id_1_2':
'example_short_circuit_operator', 'dag_id_1_3':
'example_branch_python_operator_decorator', 'dag_id_1_4':
'example_weekday_branch_operator', 'dag_id_1_5':
'example_short_circuit_decorator', 'dag_id_1_6':
'example_external_task_marker_child', 'dag_id_1_7':
'dataset_consumes_1_never_scheduled', 'dag_id_1_8':
'example_branch_datetime_operator_3', 'dag_id_1_9':
'example_trigger_controller_dag', 'dag_id_1_10':
'example_subdag_operator.section-2', 'dag_id_1_11': 'example_bash_operator',
'dag_id_1_12': 'dataset_consumes_1_and_2', 'dag_id_1_13': 'example_complex',
'dag_id_1_14': 'dataset_produces_2', 'dag_id_1_15':
'example_xcom_args_with_operators', 'dag_id_1_16': 'tutorial_taskflow_api',
'dag_id_1_17': 'example_branch_datetime_operator_2', 'dag_id_1_18':
'example_branch_datetime_operator', 'dag_id_1_19':
'example_branch_dop_operator_v3', 'dag_id_1_20': 'latest_only_with_trigger',
'dag_id_1_21': 'dataset_produces_1', 'dag_id_1_22':
'example_subdag_operator.section-1', 'dag_id_1_23': 'example_skip_dag',
'dag_id_1_24': 'tutorial_dag', 'dag_id_1_25': 'example_branch_operator',
'dag_id_1_26': 'example_external_task_marker_parent', 'dag_id_1_27':
'example_xcom_args', 'dag_id_1_28': 'example_trigger_target_dag',
'dag_id_1_29': 'dataset_consumes_unknown_never_scheduled', 'dag_id_1_30':
'dataset_consumes_1', 'dag_id_1_31': 'example_subdag_operator', 'dag_id_1_32':
'example_nested_branch_dag', 'dag_id_1_33': 'example_dag_decorator',
'dag_id_1_34': 'example_python_operator', 'dag_id_1_35': 'tutorial',
'dag_id_1_36': 'example_sla_dag', 'dag_id_1_37':
'example_task_group_decorator', 'dag_id_1_38':
'example_passing_params_via_test_command', 'dag_id_1_39':
'example_branch_labels', 'dag_id_1_40': 'example_task_group', 'dag_id_1_41':
'example_time_delta_sensor_async', 'dag_id_1_42': 'example_xcom'}]
(Background on this error at: https://sqlalche.me/e/14/4xp6)`
Any solutions for this problem ?
Would you consider the limit of 30 characters for the fields of tables ?
Thank you in advance.
### What you think should happen instead
The table DAG is having a field (next_dagrun_data_interval_start) with more
than 30 characters
### How to reproduce
_No response_
### Operating System
ubuntu
### Versions of Apache Airflow Providers
_No response_
### Deployment
Official Apache Airflow Helm Chart
### 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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