**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/serialization/serialized_objects.py
"""Serializes a DAG into a JSON object."""
        try:
            serialize_dag = cls.serialize_to_json(dag, cls._decorated_fields)
            serialize_dag["tasks"] = [cls._serialize(task) for _, task in dag.task_dict.items()]
            serialize_dag['_task_group'] = SerializedTaskGroup.serialize_task_group(dag.task_group)
            
            if dag.has_on_success_callback:
                serialize_dag['has_on_success_callback'] = True
            if dag.has_on_failure_callback:
                serialize_dag['has_on_failure_callback'] = True
            return serialize_dag
        except SerializationError:
            raise
        except Exception:
            raise SerializationError(f'Failed to serialize dag {dag.dag_id!r}')
    @classmethod
    def deserialize_dag(cls, encoded_dag: Dict[str, Any]) -> 'SerializedDAG':