**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
command,
                priority=priority,
                queue=queue,
            )
    def _critical_section_execute_task_instances(self, session: Session) -> int:
        """
        Attempts to execute TaskInstances that should be executed by the scheduler.
        There are three steps:
        1. Pick TIs by priority with the constraint that they are in the expected states
        and that we do exceed max_active_runs or pool limits.
        2. Change the state for the TIs above atomically.
        3. Enqueue the TIs in the executor.
        HA note: This function is a "critical section" meaning that only a single executor process can execute
        this function at the same time. This is achieved by doing ``SELECT ... from pool FOR UPDATE``. For DBs
        that support NOWAIT, a "blocked" scheduler will skip this and continue on with other tasks (creating
        new DAG runs, progressing TIs from None to SCHEDULED etc.); DBs that don't support this (such as
        MariaDB or MySQL 5.x) the other schedulers will wait for the lock before continuing.
        :param session:
        :type session: sqlalchemy.orm.Session
        :return: Number of task instance with state changed.
        """
        if self.max_tis_per_query == 0:
            max_tis = self.executor.slots_available
        else:
            max_tis = min(self.max_tis_per_query, self.executor.slots_available)
        queued_tis = self._executable_task_instances_to_queued(max_tis, session=session)
        self._enqueue_task_instances_with_queued_state(queued_tis)
        return len(queued_tis)
    @provide_session
    def _change_state_for_tasks_failed_to_execute(self, session: Session = None):