**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 that ignore_first_depends_on_past doesn't affect results
        (this is the same test as
        test_dagrun_deadlock_ignore_depends_on_past_advance_ex_date except
        that start_date == execution_date so depends_on_past is irrelevant).
        """
        self.evaluate_dagrun(
            dag_id='test_dagrun_states_deadlock',
            expected_task_states={
                'test_depends_on_past': State.SUCCESS,
                'test_depends_on_past_2': State.SUCCESS,
            },
            dagrun_state=State.SUCCESS,
            run_kwargs=dict(ignore_first_depends_on_past=True),
        )
    def test_scheduler_start_date(self):
        """
        Test that the scheduler respects start_dates, even when DAGS have run
        """
        with create_session() as session:
            dag_id = 'test_start_date_scheduling'
            dag = self.dagbag.get_dag(dag_id)
            dag.clear()
            assert dag.start_date > datetime.datetime.now(timezone.utc)