### Body

There are some use cases where users want to trigger new DAG run as soon as one finished. This is a request I've seen several times with some variations (for example like this [Stackoverflow question](https://stackoverflow.com/q/75623153/14624409)) but the basic request is the same.

The workaround users do to get such functionality is place `TriggerDagRunOperator` as last task of their DAG invoking the same DAG:

```
from datetime import datetime

from airflow import DAG
from airflow.operators.empty import EmptyOperator
from airflow.operators.trigger_dagrun import TriggerDagRunOperator

with DAG(
    dag_id="example",
    start_date=datetime(2023, 1, 1,),
    catchup=False,
    schedule=None,
) as dag:
    task = EmptyOperator(task_id="first")
    trigger = TriggerDagRunOperator(
        task_id="trigger",
        trigger_dag_id="example",
    )

    task >> trigger

```

As you can see this works nicely:
![Screenshot 2023-03-03 at 14 20 51](https://user-images.githubusercontent.com/45845474/222718862-dfde8a41-24b6-4991-b318-b7f9784514f6.png)

My suggestion is to add first class support for this use case, so the above example will be changed to:

```

from datetime import datetime

from airflow import DAG
from airflow.operators.empty import EmptyOperator
from airflow.operators.trigger_dagrun import TriggerDagRunOperator

with DAG(
    dag_id="example",
    start_date=datetime(2023, 1, 1,),
    catchup=False,
    schedule="@continues",
) as dag:
    task = EmptyOperator(task_id="first")
```

I guess it won't exactly be `"@continues"` but more likely new [ScheduleArg](https://github.com/apache/airflow/blob/8b8552f5c4111fe0732067d7af06aa5285498a79/airflow/models/dag.py#L127) type but I show it like that just for simplification of the idea.

### Committer

- [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.
"""
        Returns the number of task instances in the given DAG.
        :param session: ORM session
        :param dag_id: ID of the DAG to get the task concurrency of
        :param task_ids: A list of valid task IDs for the given DAG
        :param states: A list of states to filter by if supplied
        :return: The number of running tasks
        """
        qry = session.query(func.count(TaskInstance.task_id)).filter(
            TaskInstance.dag_id == dag_id,
        )
        if task_ids:
            qry = qry.filter(
                TaskInstance.task_id.in_(task_ids),
            )
        if states:
            if None in states:
                if all(x is None for x in states):
                    qry = qry.filter(TaskInstance.state.is_(None))
                else:
                    not_none_states = [state for state in states if state]
                    qry = qry.filter(
                        or_(TaskInstance.state.in_(not_none_states), TaskInstance.state.is_(None))
                    )
            else:
                qry = qry.filter(TaskInstance.state.in_(states))
        return qry.scalar()
    @classmethod
    def get_serialized_fields(cls):