**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
pools = models.Pool.slots_stats(lock_rows=True, session=session)
        
        
        pool_slots_free = max(0, sum(pool['open'] for pool in pools.values()))
        if pool_slots_free == 0:
            self.log.debug("All pools are full!")
            return executable_tis
        max_tis = min(max_tis, pool_slots_free)
        
        
        
        query = (
            session.query(TI)
            .outerjoin(TI.dag_run)
            .filter(or_(DR.run_id.is_(None), DR.run_type != DagRunType.BACKFILL_JOB))
            .join(TI.dag_model)
            .filter(not_(DM.is_paused))
            .filter(TI.state == State.SCHEDULED)
            .options(selectinload('dag_model'))
            .limit(max_tis)
        )
        task_instances_to_examine: List[TI] = with_row_locks(
            query,
            of=TI,
            **skip_locked(session=session),
        ).all()
        
        
        if len(task_instances_to_examine) == 0:
            self.log.debug("No tasks to consider for execution.")