**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
from airflow.utils.module_loading import import_string
from airflow.utils.task_group import TaskGroup
try:
    
    from kubernetes.client import models as k8s
    from airflow.kubernetes.pod_generator import PodGenerator
    
    HAS_KUBERNETES = True
except ImportError:
    HAS_KUBERNETES = False
if TYPE_CHECKING:
    from airflow.ti_deps.deps.base_ti_dep import BaseTIDep
log = logging.getLogger(__name__)
_OPERATOR_EXTRA_LINKS: Set[str] = {
    "airflow.operators.trigger_dagrun.TriggerDagRunLink",
    "airflow.sensors.external_task.ExternalTaskSensorLink",
    
    "airflow.operators.dagrun_operator.TriggerDagRunLink",
    "airflow.sensors.external_task_sensor.ExternalTaskSensorLink",
}
@cache
def get_operator_extra_links():
    """
    Returns operator extra links - both the ones that are built in and the ones that come from
    the providers.
    :return: set of extra links
    """
    _OPERATOR_EXTRA_LINKS.update(ProvidersManager().extra_links_class_names)
    return _OPERATOR_EXTRA_LINKS
class BaseSerialization: