**Apache Airflow version**:

1.10.12

**What happened**:

I created dag with dagrun_timeout=2 minutes. 

After 2 minutes dagrun is marked as failed and the next one is started, but task keeps going.

**What you expected to happen**:

Task is killed with dag run as it is done when you mark dagrun failed manually.

**How to reproduce it**:
```
dag = DAG(dag_id='platform.airflow-test',
          description='',
          schedule_interval="0 0 * * *",
          start_date=datetime(2020, 7, 1),
          max_active_runs=1,
          catchup=True,
          dagrun_timeout=timedelta(minutes=2))

run_this = BashOperator(
    task_id='run_after_loop',
    bash_command=' for((i=1;i<=600;i+=1)); do echo "Welcome $i times"; sleep 1;  done',
    dag=dag,
)
```
airflow/jobs/scheduler_job.py
"""
    Process a Python file containing Airflow DAGs.
    This includes:
    1. Execute the file and look for DAG objects in the namespace.
    2. Execute any Callbacks if passed to DagFileProcessor.process_file
    3. Serialize the DAGs and save it to DB (or update existing record in the DB).
    4. Pickle the DAG and save it to the DB (if necessary).
    5. Record any errors importing the file into ORM
    Returns a tuple of 'number of dags found' and 'the count of import errors'
    :param dag_ids: If specified, only look at these DAG ID's
    :type dag_ids: List[str]
    :param log: Logger to save the processing process
    :type log: logging.Logger
    """
    UNIT_TEST_MODE: bool = conf.getboolean('core', 'UNIT_TEST_MODE')
    def __init__(self, dag_ids: Optional[List[str]], log: logging.Logger):