### Apache Airflow version

Other Airflow 2 version (please specify below)

### What happened

Airflow 2.3.4 (but actual code seems to have same behaviour).

I have mapped task with xcom value.

I want to get xcom value of particular instance or xcom values of all task instances.

I am using standard REST API method /dags/{dag_id}/dagRuns/{dag_run_id}/taskInstances/{task_id}/xcomEntries/{xcom_key}

And it throws an error
`
  File &#34;/home/airflow/.local/lib/python3.9/site-packages/sqlalchemy/orm/query.py&#34;, line 2850, in one_or_none
    return self._iter().one_or_none()
  File &#34;/home/airflow/.local/lib/python3.9/site-packages/sqlalchemy/engine/result.py&#34;, line 1510, in one_or_none
    return self._only_one_row(
  File &#34;/home/airflow/.local/lib/python3.9/site-packages/sqlalchemy/engine/result.py&#34;, line 614, in _only_one_row
    raise exc.MultipleResultsFound(
sqlalchemy.exc.MultipleResultsFound: Multiple rows were found when one or none was required
`

Is it any way of getting xcom of mapped tasks via API?

### What you think should happen instead

_No response_

### How to reproduce

Make dag with mapped task. Return xcom value in every task. Try to get xcom value via API.

### Operating System

ubuntu 20.04

### Versions of Apache Airflow Providers

_No response_

### Deployment

Other

### Deployment details

Standard

### 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)

"""Create a `DAG` with a single `EmptyOperator` task.
    DagRun and DagModel is also created.
    Apart from the already existing arguments, any other argument in kwargs
    is passed to the DAG and not to the EmptyOperator task.
    If you have an argument that you want to pass to the EmptyOperator that
    is not here, please use `default_args` so that the DAG will pass it to the
    Task::
        dag, task = create_dummy_dag(default_args={'start_date':timezone.datetime(2016, 1, 1)})
    You cannot be able to alter the created DagRun or DagModel, use `dag_maker` fixture instead.
    """
    from airflow.operators.empty import EmptyOperator
    from airflow.utils.types import DagRunType
    def create_dag(
        dag_id="dag",
        task_id="op1",
        max_active_tis_per_dag=16,
        max_active_tis_per_dagrun=None,
        pool="default_pool",
        executor_config={},
        trigger_rule="all_done",
        on_success_callback=None,
        on_execute_callback=None,