### Apache Airflow version

2.2.0b2 (beta snapshot)

### Operating System

Debian GNU/Linux 11 (bullseye)

### Versions of Apache Airflow Providers

```
apache-airflow-providers-amazon @ file:///root/.cache/pypoetry/artifacts/c9/69/16/ffa2eb7a2e6e850a7048eaf66b6c40c990ef7c58149f20d3d3f333a2e9/apache_airflow_providers_amazon-2.2.0-py3-none-any.whl
apache-airflow-providers-celery @ file:///root/.cache/pypoetry/artifacts/6e/1b/2f/f968318a7474e979af4dc53893ecafe8cd11a98a94077a9c3c27304eb7/apache_airflow_providers_celery-2.1.0-py3-none-any.whl
apache-airflow-providers-ftp @ file:///root/.cache/pypoetry/artifacts/8b/9a/dd/79a36c62bc7f37f98d0ea33652570e19272e8a7a2297db13a6785698d1/apache_airflow_providers_ftp-2.0.1-py3-none-any.whl
apache-airflow-providers-http @ file:///root/.cache/pypoetry/artifacts/52/28/81/03a89147daf7daceb55f1218189d1c4af01c33c45849b568769ca6765f/apache_airflow_providers_http-2.0.1-py3-none-any.whl
apache-airflow-providers-imap @ file:///root/.cache/pypoetry/artifacts/1c/5d/c5/269e8a8098e7017a26a2a376eb3020e1a864775b7ff310ed39e1bd503d/apache_airflow_providers_imap-2.0.1-py3-none-any.whl
apache-airflow-providers-postgres @ file:///root/.cache/pypoetry/artifacts/fb/69/ac/e8e25a0f6a4b0daf162c81c9cfdbb164a93bef6bd652c1c00eee6e0815/apache_airflow_providers_postgres-2.3.0-py3-none-any.whl
apache-airflow-providers-redis @ file:///root/.cache/pypoetry/artifacts/cf/2b/56/75563b6058fe45b70f93886dd92541e8349918eeea9d70c703816f2639/apache_airflow_providers_redis-2.0.1-py3-none-any.whl
apache-airflow-providers-sqlite @ file:///root/.cache/pypoetry/artifacts/61/ba/e9/c0b4b7ef2599dbd902b32afc99f2620d8a616b3072122e90f591de4807/apache_airflow_providers_sqlite-2.0.1-py3-none-any.whl
```

### Deployment

Other Docker-based deployment

### Deployment details

AWS ECS + Fargate, RabbitMQ, Celery executor, Postgres 13 backend

### What happened

Hey so we just hit an issue with the 2.2.0b2 migration `airflow/migrations/versions/7b2661a43ba3_taskinstance_keyed_to_dagrun.py`
 . We have dag_runs without a run_id (as it is still nullable) on the dag_run table. This caused the FK constraint on TI not to apply.
Noticeably this wasn't caught by https://github.com/apache/airflow/blob/ca93ff4ef05e68369b4fd42fcda3b40f63682d4a/airflow/utils/db.py#L700 before the migrations apply. Is it worth adding an additional check here and making dag_run.run_id NOT NULL?

### What you expected to happen

The data check before applying migrations should have spotted the NULL run_ids on the dag_run table. Going forward perhaps we can make this column NOT NULL?

### How to reproduce

NULL some run_id columns on the dag_run table. As to how this occurs I am not sure.

### 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)

airflow/models/dagrun.py
running_drs = (
                session.query(DagRun.dag_id, func.count(DagRun.state).label('num_running'))
                .filter(DagRun.state == DagRunState.RUNNING)
                .group_by(DagRun.dag_id)
                .subquery()
            )
            query = query.outerjoin(running_drs, running_drs.c.dag_id == DagRun.dag_id).filter(
                func.coalesce(running_drs.c.num_running, 0) < DagModel.max_active_runs
            )
        query = query.order_by(
            nulls_first(cls.last_scheduling_decision, session=session),
            cls.execution_date,
        )
        if not settings.ALLOW_FUTURE_EXEC_DATES:
            query = query.filter(DagRun.execution_date <= func.now())
        return with_row_locks(
            query.limit(max_number), of=cls, session=session, **skip_locked(session=session)
        )
    @staticmethod
    @provide_session
    def find(
        dag_id: Optional[Union[str, List[str]]] = None,
        run_id: Optional[str] = None,
        execution_date: Optional[datetime] = None,
        state: Optional[DagRunState] = None,
        external_trigger: Optional[bool] = None,
        no_backfills: bool = False,
        run_type: Optional[DagRunType] = None,
        session: Session = None,