### 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)

from airflow.models import DagModel
            from airflow.models.serialized_dag import SerializedDagModel
            dag = self.dag
            dag.__exit__(type, value, traceback)
            if type is not None:
                return
            dag.clear(session=self.session)
            dag.sync_to_db(processor_subdir=self.processor_subdir, session=self.session)
            self.dag_model = self.session.get(DagModel, dag.dag_id)
            if self.want_serialized:
                self.serialized_model = SerializedDagModel(
                    dag, processor_subdir=self.dag_model.processor_subdir
                )
                self.session.merge(self.serialized_model)
                serialized_dag = self._serialized_dag()
                self.dagbag.bag_dag(serialized_dag, root_dag=serialized_dag)
                self.session.flush()
            else:
                self.dagbag.bag_dag(self.dag, self.dag)
        def create_dagrun(self, **kwargs):
            from airflow.utils import timezone
            from airflow.utils.state import State
            from airflow.utils.types import DagRunType