**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
state=State.FAILED,
            execution_date=DEFAULT_DATE + timedelta(days=1),
            start_date=DEFAULT_DATE + timedelta(days=1),
            session=session,
        )
        ti = dr.get_task_instance(task_id=op1.task_id, session=session)
        ti.state = initial_task_state
        session.commit()
        
        
        scheduler = SchedulerJob(num_runs=2, processor_poll_interval=30)
        scheduler.dagbag = dagbag
        executor = MockExecutor(do_update=False)
        executor.queued_tasks
        scheduler.executor = executor
        processor = mock.MagicMock()
        processor.done = False
        scheduler.processor_agent = processor
        with mock.patch.object(settings, "USE_JOB_SCHEDULE", False), conf_vars(
            {('scheduler', 'clean_tis_without_dagrun_interval'): '0.001'}
        ):
            scheduler._run_scheduler_loop()
        ti = dr.get_task_instance(task_id=op1.task_id, session=session)
        assert ti.state == expected_task_state
        assert ti.start_date is not None
        if expected_task_state in State.finished:
            assert ti.end_date is not None
            assert ti.start_date == ti.end_date
            assert ti.duration is not None
    def test_dagrun_timeout_verify_max_active_runs(self):