**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 the given file.
        :param result_channel: the connection to use for passing back the result
        :type result_channel: multiprocessing.Connection
        :param parent_channel: the parent end of the channel to close in the child
        :type parent_channel: multiprocessing.Connection
        :param file_path: the file to process
        :type file_path: str
        :param pickle_dags: whether to pickle the DAGs found in the file and
            save them to the DB
        :type pickle_dags: bool
        :param dag_ids: if specified, only examine DAG ID's that are
            in this list
        :type dag_ids: list[str]
        :param thread_name: the name to use for the process that is launched
        :type thread_name: str
        :param callback_requests: failure callback to execute
        :type callback_requests: List[airflow.utils.callback_requests.CallbackRequest]
        :return: the process that was launched
        :rtype: multiprocessing.Process
        """
        
        log: logging.Logger = logging.getLogger("airflow.processor")
        
        
        log.info("Closing parent pipe")
        parent_channel.close()
        del parent_channel
        set_context(log, file_path)
        setproctitle(f"airflow scheduler - DagFileProcessor {file_path}")