### Apache Airflow version

2.4.1

### What happened

When there are large number of dag files, lets say 10K and each takes sometime to parse,  dag_parser doesnt pick any newly created files till all 10k files are finished parsing

`if not self._file_path_queue:
                self.emit_metrics()
                self.prepare_file_path_queue()`

Above logic only adds new files to queue when queue is empty

### What you think should happen instead

Every loop of dag processor should pick new files and add into file for parsing queue

### How to reproduce

_No response_

### Operating System

All

### Versions of Apache Airflow Providers

_No response_

### Deployment

Docker-Compose

### Deployment details

_No response_

### Anything else

_No response_

### Are you willing to submit PR?

- [X] 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)

DagFileProcessorManager,
    DagFileStat,
    DagParsingSignal,
    DagParsingStat,
)
from airflow.dag_processing.processor import DagFileProcessorProcess
from airflow.models import DagBag, DagModel, DbCallbackRequest, errors
from airflow.models.dagcode import DagCode
from airflow.models.serialized_dag import SerializedDagModel
from airflow.utils import timezone
from airflow.utils.net import get_hostname
from airflow.utils.session import create_session
from tests.core.test_logging_config import SETTINGS_FILE_VALID, settings_context
from tests.models import TEST_DAGS_FOLDER
from tests.test_utils.config import conf_vars
from tests.test_utils.db import clear_db_callbacks, clear_db_dags, clear_db_runs, clear_db_serialized_dags
TEST_DAG_FOLDER = pathlib.Path(__file__).parents[1].resolve() / "dags"
DEFAULT_DATE = timezone.datetime(2016, 1, 1)
class FakeDagFileProcessorRunner(DagFileProcessorProcess):
    
    
    def __init__(self, file_path, pickle_dags, dag_ids, dag_directory, callbacks):
        super().__init__(file_path, pickle_dags, dag_ids, dag_directory, callbacks)
        
        readable, writable = multiprocessing.Pipe(duplex=False)
        writable.send("abc")
        writable.close()
        self._waitable_handle = readable
        self._result = 0, 0
    def start(self):