**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.

airflow/jobs/scheduler_job.py
"""
        Reset any TaskInstance still in QUEUED or SCHEDULED states that were
        enqueued by a SchedulerJob that is no longer running.
        :return: the number of TIs reset
        :rtype: int
        """
        self.log.info("Resetting orphaned tasks for active dag runs")
        timeout = conf.getint('scheduler', 'scheduler_health_check_threshold')
        num_failed = (
            session.query(SchedulerJob)
            .filter(
                SchedulerJob.state == State.RUNNING,
                SchedulerJob.latest_heartbeat < (timezone.utcnow() - timedelta(seconds=timeout)),
            )
            .update({"state": State.FAILED})
        )
        if num_failed:
            self.log.info("Marked %d SchedulerJob instances as failed", num_failed)
            Stats.incr(self.__class__.__name__.lower() + '_end', num_failed)
        resettable_states = [State.SCHEDULED, State.QUEUED, State.RUNNING]
        query = (
            session.query(TI)
            .filter(TI.state.in_(resettable_states))
            
            
            
            
            .outerjoin(TI.queued_by_job)
            .filter(or_(TI.queued_by_job_id.is_(None), SchedulerJob.state != State.RUNNING))