**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
elif type_ == DAT.POD:
            if not HAS_KUBERNETES:
                raise RuntimeError("Cannot deserialize POD objects without kubernetes libraries installed!")
            pod = PodGenerator.deserialize_model_dict(var)
            return pod
        elif type_ == DAT.TIMEDELTA:
            return datetime.timedelta(seconds=var)
        elif type_ == DAT.TIMEZONE:
            return Timezone(var)
        elif type_ == DAT.RELATIVEDELTA:
            if 'weekday' in var:
                var['weekday'] = relativedelta.weekday(*var['weekday'])  
            return relativedelta.relativedelta(**var)
        elif type_ == DAT.SET:
            return {cls._deserialize(v) for v in var}
        elif type_ == DAT.TUPLE:
            return tuple([cls._deserialize(v) for v in var])
        else:
            raise TypeError(f'Invalid type {type_!s} in deserialization.')
    _deserialize_datetime = pendulum.from_timestamp
    _deserialize_timezone = pendulum.tz.timezone
    @classmethod
    def _deserialize_timedelta(cls, seconds: int) -> datetime.timedelta:
        return datetime.timedelta(seconds=seconds)
    @classmethod
    def _is_constructor_param(cls, attrname: str, instance: Any) -> bool:
        
        return attrname in cls._CONSTRUCTOR_PARAMS
    @classmethod
    def _value_is_hardcoded_default(cls, attrname: str, value: Any, instance: Any) -> bool: