### What do you see as an issue?


The [documentation for Dynamic Task Mapping](https://airflow.apache.org/docs/apache-airflow/stable/authoring-and-scheduling/dynamic-task-mapping.html#simple-mapping
) does not include an example of a "reduce" task (e.g. `sum_it` in the [examples](https://airflow.apache.org/docs/apache-airflow/stable/authoring-and-scheduling/dynamic-task-mapping.html#simple-mapping)) using the classic (or non-TaskFlow) operators. It only includes an example that uses the TaskFlow operators.

When I attempted to write a "reduce" task using classic operators for my DAG, I found that there wasn't an obvious approach.

### Solving the problem

We should add an example of a "reduce" task that uses the classic (non-TaskFlow) operators.

For example, for the given `sum_it` example:

```
"""Example DAG demonstrating the usage of dynamic task mapping reduce using classic
operators.
"""
from __future__ import annotations

from datetime import datetime

from airflow import DAG
from airflow.decorators import task
from airflow.operators.python import PythonOperator


def add_one(x: int):
    return x + 1

def sum_it(values):
    total = sum(values)
    print(f"Total was {total}")


with DAG(dag_id="example_dynamic_task_mapping_reduce", start_date=datetime(2022, 3, 4)):
    add_one_task = PythonOperator.partial(
        task_id="add_one",
        python_callable=add_one,
    ).expand(
        op_kwargs=[
            {"x": 1},
            {"x": 2},
            {"x": 3},
        ]
    )

    sum_it_task = PythonOperator(
        task_id="sum_it",
        python_callable=sum_it,
        op_kwargs={"values": add_one_task.output},
    )
```

### Anything else

_No response_

### Are you willing to submit PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

"""
        Tests serialize_operator, make sure the deps is in order
        """
        from airflow.operators.empty import EmptyOperator
        from airflow.sensors.external_task import ExternalTaskSensor
        execution_date = datetime(2020, 1, 1)
        with DAG(dag_id="test_deps_sorted", start_date=execution_date) as dag:
            task1 = ExternalTaskSensor(
                task_id="task1",
                external_dag_id="external_dag_id",
                mode="reschedule",
            )
            task2 = EmptyOperator(task_id="task2")
            task1 >> task2
        serialize_op = SerializedBaseOperator.serialize_operator(dag.task_dict["task1"])
        deps = serialize_op["deps"]
        assert deps == [
            "airflow.ti_deps.deps.not_in_retry_period_dep.NotInRetryPeriodDep",
            "airflow.ti_deps.deps.not_previously_skipped_dep.NotPreviouslySkippedDep",
            "airflow.ti_deps.deps.prev_dagrun_dep.PrevDagrunDep",
            "airflow.ti_deps.deps.ready_to_reschedule.ReadyToRescheduleDep",
            "airflow.ti_deps.deps.trigger_rule_dep.TriggerRuleDep",
        ]
    def test_error_on_unregistered_ti_dep_serialization(self):
        
        class DummyTriggerRule(BaseTIDep):