### 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.
recursion_depth: int = 0,
        max_recursion_depth: int | None = None,
        dag_bag: DagBag | None = None,
        exclude_task_ids: frozenset[str] | frozenset[tuple[str, int]] | None = frozenset(),
    ) -> int | Iterable[TaskInstance]:
        """
        Clears a set of task instances associated with the current dag for
        a specified date range.
        :param task_ids: List of task ids or (``task_id``, ``map_index``) tuples to clear
        :param start_date: The minimum execution_date to clear
        :param end_date: The maximum execution_date to clear
        :param only_failed: Only clear failed tasks
        :param only_running: Only clear running tasks.
        :param confirm_prompt: Ask for confirmation
        :param include_subdags: Clear tasks in subdags and clear external tasks
            indicated by ExternalTaskMarker
        :param include_parentdag: Clear tasks in the parent dag of the subdag.
        :param dag_run_state: state to set DagRun to. If set to False, dagrun state will not
            be changed.
        :param dry_run: Find the tasks to clear but don't clear them.
        :param session: The sqlalchemy session to use
        :param dag_bag: The DagBag used to find the dags subdags (Optional)
        :param exclude_task_ids: A set of ``task_id`` or (``task_id``, ``map_index``)
            tuples that should not be cleared
        """
        if get_tis:
            warnings.warn(
                "Passing `get_tis` to dag.clear() is deprecated. Use `dry_run` parameter instead.",
                RemovedInAirflow3Warning,
                stacklevel=2,