### Apache Airflow version

2.5.3

### What happened

I upgraded my airflow cluster from 2.5.2 to 2.5.3 , after which strange things started happening.
I'm currently using a standalone dagProcessor, and the parsing time that used to take about 2 seconds has suddenly increased to about 10 seconds.
I'm thinking it's weird because I haven't made any changes other than a version up, but is there something I can look into? Thanks in advance! 🙇🏼 
![image](https://user-images.githubusercontent.com/16011260/231323427-e0d95506-c752-4a2b-93fc-9880b18814f3.png)


### What you think should happen instead

I believe that the time it takes to parse a Dag should be constant, or at least have some variability, but shouldn't take as long as it does now.

### How to reproduce

If you cherrypick [this commit](https://github.com/apache/airflow/pull/30079) into 2.5.2 stable code, the issue will recur.

### Operating System

Debian GNU/Linux 11 (bullseye)

### Versions of Apache Airflow Providers

_No response_

### Deployment

Official Apache Airflow Helm Chart

### Deployment details

- Kubernetes 1.21 Cluster
- 1.7.0 helm chart
- standalone dag processor
- using kubernetes executor
- using mysql database

### Anything else

This issue still persists, and restarting the Dag Processor has not resolved the issue.

### 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)

pass
class DagProcessorJobRunner(BaseJobRunner, LoggingMixin):
    """
    DagProcessorJobRunner is a job runner that runs a DagFileProcessorManager processor.
    :param job: Job instance to use
    :param processor: DagFileProcessorManager instance to use
    """
    job_type = "DagProcessorJob"
    def __init__(
        self,
        job: Job,
        processor: DagFileProcessorManager,
        *args,
        **kwargs,
    ):
        super().__init__(*args, **kwargs)
        self.job = job
        if job.job_type and job.job_type != self.job_type:
            raise Exception(
                f"The job is already assigned a different job_type: {job.job_type}."
                f"This is a bug and should be reported."
            )
        self.processor = processor
        self.processor.heartbeat = lambda: perform_heartbeat(
            job=self.job,
            heartbeat_callback=empty_callback,
            only_if_necessary=False,
        )
    def _execute(self) -> int | None: