**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
"""
    Process a Python file containing Airflow DAGs.
    This includes:
    1. Execute the file and look for DAG objects in the namespace.
    2. Execute any Callbacks if passed to DagFileProcessor.process_file
    3. Serialize the DAGs and save it to DB (or update existing record in the DB).
    4. Pickle the DAG and save it to the DB (if necessary).
    5. Record any errors importing the file into ORM
    Returns a tuple of 'number of dags found' and 'the count of import errors'
    :param dag_ids: If specified, only look at these DAG ID's
    :type dag_ids: List[str]
    :param log: Logger to save the processing process
    :type log: logging.Logger
    """
    UNIT_TEST_MODE: bool = conf.getboolean('core', 'UNIT_TEST_MODE')
    def __init__(self, dag_ids: Optional[List[str]], log: logging.Logger):