

**Description**

We are using a 3rd party executor which has the ability to use multiple queues, however the `default_queue` is defined under the `celery` heading and is used regardless of the executor that you are using.

See: https://github.com/apache/airflow/blob/2.0.1/airflow/models/baseoperator.py#L366

It would be nice to decouple the default_queue configuration argument away from the celery section to allow other executors to utilise this functionality with less confusion.

**Are you willing to submit a PR?**

Yep! Will open a pull request shortly


**Related Issues**

Not that I'm aware of.

airflow/models/baseoperator.py
t4.set_downstream(t6)
        t5.set_downstream(t6)
    :param tasks: List of tasks or List[airflow.models.BaseOperator] to set dependencies
    :type tasks: List[airflow.models.BaseOperator] or airflow.models.BaseOperator
    """
    for index, up_task in enumerate(tasks[:-1]):
        down_task = tasks[index + 1]
        if isinstance(up_task, BaseOperator):
            up_task.set_downstream(down_task)
            continue
        if isinstance(down_task, BaseOperator):
            down_task.set_upstream(up_task)
            continue
        if not isinstance(up_task, Sequence) or not isinstance(down_task, Sequence):
            raise TypeError(
                'Chain not supported between instances of {up_type} and {down_type}'.format(
                    up_type=type(up_task), down_type=type(down_task)
                )
            )
        up_task_list = up_task
        down_task_list = down_task
        if len(up_task_list) != len(down_task_list):
            raise AirflowException(
                f'Chain not supported different length Iterable '
                f'but get {len(up_task_list)} and {len(down_task_list)}'
            )
        for up_t, down_t in zip(up_task_list, down_task_list):
            up_t.set_downstream(down_t)
def cross_downstream(
    from_tasks: Sequence[BaseOperator], to_tasks: Union[BaseOperator, Sequence[BaseOperator]]