**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
:return: A map from (dag_id, task_id) to # of task instances and
         a map from (dag_id, task_id) to # of task instances in the given state list
        :rtype: tuple[dict[str, int], dict[tuple[str, str], int]]
        """
        ti_concurrency_query: List[Tuple[str, str, int]] = (
            session.query(TI.task_id, TI.dag_id, func.count('*'))
            .filter(TI.state.in_(states))
            .group_by(TI.task_id, TI.dag_id)
        ).all()
        dag_map: DefaultDict[str, int] = defaultdict(int)
        task_map: DefaultDict[Tuple[str, str], int] = defaultdict(int)
        for result in ti_concurrency_query:
            task_id, dag_id, count = result
            dag_map[dag_id] += count
            task_map[(dag_id, task_id)] = count
        return dag_map, task_map
    
    @provide_session
    def _executable_task_instances_to_queued(self, max_tis: int, session: Session = None) -> List[TI]:
        """
        Finds TIs that are ready for execution with respect to pool limits,
        dag concurrency, executor state, and priority.
        :param max_tis: Maximum number of TIs to queue in this loop.
        :type max_tis: int
        :return: list[airflow.models.TaskInstance]
        """
        executable_tis: List[TI] = []
        
        
        pools = models.Pool.slots_stats(lock_rows=True, session=session)