### 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)

next_info = self.dag.next_dagrun_info(self.dag.get_run_data_interval(dagrun))
            if next_info is None:
                raise ValueError(f"cannot create run after {dagrun}")
            return self.create_dagrun(
                execution_date=next_info.logical_date,
                data_interval=next_info.data_interval,
                **kwargs,
            )
        def __call__(
            self,
            dag_id="test_dag",
            serialized=want_serialized,
            fileloc=None,
            processor_subdir=None,
            session=None,
            **kwargs,
        ):
            from airflow import settings
            from airflow.models import DAG
            from airflow.utils import timezone
            if session is None:
                self._own_session = True
                session = settings.Session()
            self.kwargs = kwargs
            self.session = session
            self.start_date = self.kwargs.get("start_date", None)
            default_args = kwargs.get("default_args", None)
            if default_args and not self.start_date: