### 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.
job_id = 42
        dag = DAG(dag_id="test_create_dagrun_job_id_is_set")
        dr = dag.create_dagrun(
            run_id="test_create_dagrun_job_id_is_set", state=State.NONE, creating_job_id=job_id
        )
        assert dr.creating_job_id == job_id
    def test_dag_add_task_sets_default_task_group(self):
        dag = DAG(dag_id="test_dag_add_task_sets_default_task_group", start_date=DEFAULT_DATE)
        task_without_task_group = EmptyOperator(task_id="task_without_group_id")
        default_task_group = TaskGroupContext.get_current_task_group(dag)
        dag.add_task(task_without_task_group)
        assert default_task_group.get_child_by_label("task_without_group_id") == task_without_task_group
        task_group = TaskGroup(group_id="task_group", dag=dag)
        task_with_task_group = EmptyOperator(task_id="task_with_task_group", task_group=task_group)
        dag.add_task(task_with_task_group)
        assert task_group.get_child_by_label("task_with_task_group") == task_with_task_group
        assert dag.get_task("task_group.task_with_task_group") == task_with_task_group
    @pytest.mark.parametrize("dag_run_state", [DagRunState.QUEUED, DagRunState.RUNNING])
    def test_clear_set_dagrun_state(self, dag_run_state):
        dag_id = "test_clear_set_dagrun_state"
        self._clean_up(dag_id)
        task_id = "t1"
        dag = DAG(dag_id, start_date=DEFAULT_DATE, max_active_runs=1)
        t_1 = EmptyOperator(task_id=task_id, dag=dag)
        session = settings.Session()
        dagrun_1 = dag.create_dagrun(
            run_type=DagRunType.BACKFILL_JOB,