**Apache Airflow version**: 2.0.0rc3

**Kubernetes version (if you are using kubernetes)** (use `kubectl version`):

**Environment**:

- **Cloud provider or hardware configuration**: Linux
- **OS** (e.g. from /etc/os-release): Ubuntu
- **Kernel** (e.g. `uname -a`): 
- **Install tools**:
- **Others**:

**What happened**:

After shutting down the scheduler, while tasks were in running state, trying to restart the scheduler results in pk violations..

```[2020-12-15 22:43:29,673] {scheduler_job.py:1293} ERROR - Exception when executing SchedulerJob._run_scheduler_loop
Traceback (most recent call last):
  File "/home/jcoder/git/airflow_2.0/pyenv/lib/python3.7/site-packages/sqlalchemy/engine/base.py", line 1277, in _execute_context
    cursor, statement, parameters, context
  File "/home/jcoder/git/airflow_2.0/pyenv/lib/python3.7/site-packages/sqlalchemy/engine/default.py", line 593, in do_execute
    cursor.execute(statement, parameters)
psycopg2.errors.UniqueViolation: duplicate key value violates unique constraint "dag_run_dag_id_run_id_key"
DETAIL:  Key (dag_id, run_id)=(example_task_group, scheduled__2020-12-14T04:31:00+00:00) already exists.
```


**What you expected to happen**:

Scheduler restarts and picks up where it left off.

**How to reproduce it**:

Set example dag ( I used task_group) to schedule_interval `* * * * *` and start the scheduler and let it run for a few minutes. 
Shut down the scheduler
Attempt to restart the scheduler

**Anything else we need to know**:
I came across this doing testing using the LocalExecutor in a virtual env. If no else is able to reproduce it, I'll try again in a clean virtual env.

tests/jobs/test_scheduler_job.py
"""
        Test to check that a DAG returns its active runs
        """
        now = timezone.utcnow()
        six_hours_ago_to_the_hour = (now - datetime.timedelta(hours=6)).replace(
            minute=0, second=0, microsecond=0
        )
        start_date = six_hours_ago_to_the_hour
        dag_name1 = 'get_active_runs_test'
        default_args = {'owner': 'airflow', 'depends_on_past': False, 'start_date': start_date}
        dag1 = DAG(dag_name1, schedule_interval='* * * * *', max_active_runs=1, default_args=default_args)
        run_this_1 = DummyOperator(task_id='run_this_1', dag=dag1)
        run_this_2 = DummyOperator(task_id='run_this_2', dag=dag1)
        run_this_2.set_upstream(run_this_1)
        run_this_3 = DummyOperator(task_id='run_this_3', dag=dag1)
        run_this_3.set_upstream(run_this_2)
        session = settings.Session()
        orm_dag = DagModel(dag_id=dag1.dag_id)
        session.merge(orm_dag)
        session.commit()
        session.close()
        dag1.clear()
        dr = dag1.create_dagrun(
            run_type=DagRunType.SCHEDULED,
            execution_date=start_date,