### Apache Airflow version

2.5.2

### What happened

when trying to delete a dag run with many tasks (>1000) the operation times out and the dag run is not deleted. 

### What you think should happen instead

_No response_

### How to reproduce

attempt to delete a dag run that contains >1000 tasks (in my case 10k) using the dagrun/list/ page results in a timeout:
![image](https://user-images.githubusercontent.com/7373236/226325567-5a87efa1-4744-417e-9995-b97dd1791401.png)


code for dag (however it fails on any dag with > 1000 tasks):
```
import json

from airflow.providers.cncf.kubernetes.operators.kubernetes_pod import KubernetesPodOperator
from datetime import datetime, timedelta
from airflow.decorators import dag, task

default_args = {
    'owner': 'airflow',
    'depends_on_past': False,
    'retries': 0,
    'retry_delay': timedelta(minutes=1),
    'start_date': datetime(2023, 2, 26),
    'is_delete_operator_pod': True,
    'get_logs': True
}


@dag('system_test', schedule=None, default_args=default_args, catchup=False, tags=['maintenance'])
def run_test_airflow():
    stress_image = 'dockerhub.prod.evogene.host/progrium/stress'  

    @task
    def create_cmds():
        commands = []
        for i in range(10000):
            commands.append(["stress --cpu 4 --io 1 --vm 2 --vm-bytes 6000M --timeout 60s"])
        return commands

    KubernetesPodOperator.partial(
        image=stress_image ,
        task_id=f'test_airflow',
        name=f'test_airflow',
        cmds=["/bin/sh", "-c"],
        log_events_on_failure=True,
        pod_template_file=f'/opt/airflow/dags/repo/templates/cpb_cpu_4_mem_16'
    ).expand(arguments=create_cmds())


run_test_airflow()

```

### Operating System

kubernetes deployment

### Versions of Apache Airflow Providers

_No response_

### Deployment

Official Apache Airflow Helm Chart

### Deployment details

_No response_

### 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)

children_states = {item["state"] for item in child_instances}
            group_state = next((state for state in wwwutils.priority if state in children_states), None)
            group_start_date = min(filter(None, children_start_dates), default=None)
            group_end_date = max(filter(None, children_end_dates), default=None)
            return {
                "task_id": task_group.group_id,
                "run_id": dag_run.run_id,
                "state": group_state,
                "start_date": group_start_date,
                "end_date": group_end_date,
            }
        def get_mapped_group_summaries():
            mapped_ti_query = (
                session.query(
                    TaskInstance.task_id, TaskInstance.state, TaskInstance.run_id, TaskInstance.map_index
                )
                .filter(
                    TaskInstance.dag_id == dag.dag_id,
                    TaskInstance.task_id.in_(child["id"] for child in children),
                    TaskInstance.run_id.in_(r.run_id for r in dag_runs),
                )
                .order_by(TaskInstance.task_id, TaskInstance.run_id)
            )
            
            mapped_tis: Mapping[str, Mapping[int, list[TaskInstance]]] = collections.defaultdict(
                lambda: collections.defaultdict(list),
            )
            for ti in mapped_ti_query:
                mapped_tis[ti.run_id][ti.map_index].append(ti)
            def get_mapped_group_summary(run_id: str, mapped_instances: Mapping[int, list[TaskInstance]]):