🧟 Slow Zombie query causes scheduler heartbeat failures without errors

### Apache Airflow version

2.6.3

### What happened

Due to an error with our postgres database (the stats on the tables were stale) this query:

https://github.com/apache/airflow/blob/1e20ef215ab8e688dc4331513fc5df34db443e84/airflow/jobs/scheduler_job_runner.py#L1686-L1698

took a very long time to return. During this time, heartbeats were not written, which caused health check failures (including k8s start / liveness check failures).

It took several days of debugging to track down the cause because airflow does not log any errors in this case. We resolved it by running `ANALYZE`.

### What you think should happen instead

Airflow should log warnings/errors if queries that are expected to return quickly take a long time to return.

### How to reproduce

1. Make your postgres database slow (either don't analyze statistics, or just change the query to something like `SELECT pg_sleep(2400);` for testing)
2. Try to run the airflow scheduler
3. Notice that heartbeats are not written frequently and no warnings or errors are logged

### Operating System

Debian GNU/Linux 11 (bullseye)

### Versions of Apache Airflow Providers

n/a

### Deployment

Docker-Compose

### 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)

Start in airflow/jobs/scheduler_job_runner.py at the linked lines 1686-1698 and inspect the scheduler query involved in heartbeat updates. Reproduce the delay with a slow PostgreSQL query such as SELECT pg_sleep(2400), then determine the expected warning or error behavior. Done means a slow query produces useful scheduler logs instead of failing silently.

Written by the indexing model from the issue text.