**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
"""Validate serialized_obj satisfies JSON schema."""
        if cls._json_schema is None:
            raise AirflowException(f'JSON schema of {cls.__name__:s} is not set.')
        if isinstance(serialized_obj, dict):
            cls._json_schema.validate(serialized_obj)
        elif isinstance(serialized_obj, str):
            cls._json_schema.validate(json.loads(serialized_obj))
        else:
            raise TypeError("Invalid type: Only dict and str are supported.")
    @staticmethod
    def _encode(x: Any, type_: Any) -> Dict[Encoding, Any]:
        """Encode data by a JSON dict."""
        return {Encoding.VAR: x, Encoding.TYPE: type_}
    @classmethod
    def _is_primitive(cls, var: Any) -> bool:
        """Primitive types."""
        return var is None or isinstance(var, cls._primitive_types)
    @classmethod
    def _is_excluded(cls, var: Any, attrname: str, instance: Any) -> bool:
        """Types excluded from serialization."""
        if var is None:
            if not cls._is_constructor_param(attrname, instance):
                
                return True
            return cls._value_is_hardcoded_default(attrname, var, instance)
        return isinstance(var, cls._excluded_types) or cls._value_is_hardcoded_default(
            attrname, var, instance
        )
    @classmethod
    def serialize_to_json(