**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
except SerializedDagNotFound:
                    self.log.exception("DAG '%s' not found in serialized_dag table", dag_run.dag_id)
                    continue
            guard.commit()
            
            session.expunge_all()
            
            try:
                if self.executor.slots_available <= 0:
                    
                    self.log.debug("Executor full, skipping critical section")
                    return 0
                timer = Stats.timer('scheduler.critical_section_duration')
                timer.start()
                
                num_queued_tis = self._critical_section_execute_task_instances(session=session)
                
                
                timer.stop(send=True)
            except OperationalError as e:
                timer.stop(send=False)
                if is_lock_not_available_error(error=e):
                    self.log.debug("Critical section lock held by another Scheduler")
                    Stats.incr('scheduler.critical_section_busy')
                    session.rollback()
                    return 0
                raise
            guard.commit()
            return num_queued_tis
    def _create_dag_runs(self, dag_models: Iterable[DagModel], session: Session) -> None: