**Apache Airflow version**: 2.1.0

**What happened**:

We use a python script that reads JSON configs from db to dynamically generate DAGs. Sometimes, when JSON Configs is updated, we expect DAGs to be removed in Airflow.  This doesn't always happen. From my observation, one of the following happens:
1) DAG is removed because the python script no longer generates it.
2) DAG still exists but run history is empty. When trigger the DAG, first task is stuck in `queued` status indefinitely.

**What you expected to happen**:
I expect the right behavior should be 
>1) DAG is removed because the python script no longer generates it.

**How to reproduce it**:
* Create a python script in DAG folder that dynamically generates multiple DAGs
* Execute these dynamically generated DAGs a few times
* Use Airflow Variable to toggle (reduce) the # of DAGs generated
* Examine if number of dynamically generated DAGs in the web UI


airflow/dag_processing/processor.py
super().__init__()
        self.dag_ids = dag_ids
        self._log = log
    @provide_session
    def manage_slas(self, dag: DAG, session: Session = None) -> None:
        """
        Finding all tasks that have SLAs defined, and sending alert emails
        where needed. New SLA misses are also recorded in the database.
        We are assuming that the scheduler runs often, so we only check for
        tasks that should have succeeded in the past hour.
        """
        self.log.info("Running SLA Checks for %s", dag.dag_id)
        if not any(isinstance(ti.sla, timedelta) for ti in dag.tasks):
            self.log.info("Skipping SLA check for %s because no tasks in DAG have SLAs", dag)
            return
        qry = (
            session.query(TI.task_id, func.max(DR.execution_date).label('max_ti'))
            .join(TI.dag_run)