**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
dagbag = DagBag(dag_folder=ELASTIC_DAG_FILE, include_examples=False, read_dags_from_db=False)
            dagbag.sync_to_db()
            dag_ids = dagbag.dag_ids
            dagbag = DagBag(read_dags_from_db=True)
            for i, dag_id in enumerate(dag_ids):
                dag = dagbag.get_dag(dag_id)
                dr = dag.create_dagrun(
                    state=State.RUNNING,
                    run_id=f"{DagRunType.MANUAL.value}__{i}",
                    dag_hash=dagbag.dags_hash[dag.dag_id],
                )
                dagruns.append(dr)
                for ti in dr.get_task_instances():
                    ti.set_state(state=State.SCHEDULED)
            mock_agent = mock.MagicMock()
            job = SchedulerJob(subdir=PERF_DAGS_FOLDER, num_runs=1)
            job.executor = MockExecutor(do_update=False)
            job.heartbeat = mock.MagicMock()
            job.processor_agent = mock_agent
            with assert_queries_count(expected_query_count):
                with mock.patch.object(DagRun, 'next_dagruns_to_examine') as mock_dagruns:
                    mock_dagruns.return_value = dagruns
                    job._run_scheduler_loop()
    @parameterized.expand(
        [
            
            
            ([8, 8, 8, 8], 1, 1, "1d", "None", "no_structure"),  
            ([8, 8, 8, 8], 1, 1, "1d", "None", "linear"),  
            ([20, 11, 11, 11], 1, 1, "1d", "@once", "no_structure"),