### Apache Airflow version

2.5.0

### What happened

Very simple dag:

```python3
from airflow import DAG
from airflow.operators.bash import BashOperator
from datetime import datetime, timedelta

with DAG(dag_id="hello_world", schedule=timedelta(days=30 * 365), start_date=datetime(1970, 1, 1)) as dag:
    (
        BashOperator(task_id="hello", bash_command="echo hello")
        >> BashOperator(task_id="world", bash_command="echo world")
    )
```

Run it like `airflow dags test hello_world $(date +%Y-%m-%d)`

End of output:
```
[2022-12-04 21:24:02,993] {dagrun.py:606} INFO - Marking run <DagRun hello_world @ 2022-12-04T00:00:00+00:00: manual__2022-12-04T00:00:00+00:00, state:running, queued_at: None. externally triggered: False> successful
[2022-12-04 21:24:03,003] {dagrun.py:657} INFO - DagRun Finished: dag_id=hello_world, execution_date=2022-12-04T00:00:00+00:00, run_id=manual__2022-12-04T00:00:00+00:00, run_start_date=2022-12-04T00:00:00+00:00, run_end_date=2022-12-05 04:24:02.995279+00:00, run_duration=102242.995279, state=success, external_trigger=False, run_type=manual, data_interval_start=2022-12-04T00:00:00+00:00, data_interval_end=2052-11-26T00:00:00+00:00, dag_hash=None
[2022-12-04 21:24:03,004] {dagrun.py:878} WARNING - Failed to record first_task_scheduling_delay metric:
Traceback (most recent call last):
  File "/home/matt/2022/12/04/venv/lib/python3.9/site-packages/airflow/models/dagrun.py", line 866, in _emit_true_scheduling_delay_stats_for_finished_state
    first_start_date = ordered_tis_by_start_date[0].start_date
IndexError: list index out of range
```

### What you think should happen instead

No warning (or, an explanation of what I can do address whatever it's warning about).

### How to reproduce

_No response_

### Operating System

NixOS 22.11 (gnu/linux)

### Versions of Apache Airflow Providers

n/a

### 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)

"""Get the number of active dag runs for each dag."""
        query = session.query(cls.dag_id, func.count("*"))
        if dag_ids is not None:
            
            
            query = query.filter(cls.dag_id.in_(list(set(dag_ids))))
        if only_running:
            query = query.filter(cls.state == State.RUNNING)
        else:
            query = query.filter(cls.state.in_([State.RUNNING, State.QUEUED]))
        query = query.group_by(cls.dag_id)
        return {dag_id: count for dag_id, count in query.all()}
    @classmethod
    def next_dagruns_to_examine(
        cls,
        state: DagRunState,
        session: Session,
        max_number: int | None = None,
    ) -> list[DagRun]:
        """
        Return the next DagRuns that the scheduler should attempt to schedule.
        This will return zero or more DagRun rows that are row-level-locked with a "SELECT ... FOR UPDATE"
        query, you should ensure that any scheduling decisions are made in a single transaction -- as soon as
        the transaction is committed it will be unlocked.
        """
        from airflow.models.dag import DagModel
        if max_number is None:
            max_number = cls.DEFAULT_DAGRUNS_TO_EXAMINE
        
        query = (