**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/models/serialized_dag.py
last_updated = Column(UtcDateTime, nullable=False)
    dag_hash = Column(String(32), nullable=False)
    __table_args__ = (Index('idx_fileloc_hash', fileloc_hash, unique=False),)
    dag_runs = relationship(
        DagRun,
        primaryjoin=dag_id == foreign(DagRun.dag_id),
        backref=backref('serialized_dag', uselist=False, innerjoin=True),
    )
    dag_model = relationship(
        DagModel,
        primaryjoin=dag_id == DagModel.dag_id,  
        foreign_keys=dag_id,
        uselist=False,
        innerjoin=True,
        backref=backref('serialized_dag', uselist=False, innerjoin=True),
    )
    def __init__(self, dag: DAG):
        self.dag_id = dag.dag_id
        self.fileloc = dag.full_filepath
        self.fileloc_hash = DagCode.dag_fileloc_hash(self.fileloc)
        self.data = SerializedDAG.to_dict(dag)
        self.last_updated = timezone.utcnow()
        self.dag_hash = hashlib.md5(json.dumps(self.data, sort_keys=True).encode("utf-8")).hexdigest()
    def __repr__(self):
        return f"<SerializedDag: {self.dag_id}>"
    @classmethod
    @provide_session
    def write_dag(cls, dag: DAG, min_update_interval: Optional[int] = None, session: Session = None):
        """Serializes a DAG and writes it into database.
        If the record already exists, it checks if the Serialized DAG changed or not. If it is