### 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)

mock_pid.return_value = 1234
        manager = DagFileProcessorManager(
            dag_directory=TEST_DAG_FOLDER,
            max_runs=1,
            processor_timeout=timedelta(seconds=5),
            signal_conn=MagicMock(),
            dag_ids=[],
            pickle_dags=False,
            async_mode=True,
        )
        processor = DagFileProcessorProcess(
            file_path="abc.txt",
            pickle_dags=False,
            dag_ids=[],
            dag_directory=str(TEST_DAG_FOLDER),
            callback_requests=[],
        )
        processor._start_time = timezone.make_aware(datetime.max)
        manager._processors = {"abc.txt": processor}
        manager._kill_timed_out_processors()
        mock_dag_file_processor.kill.assert_not_called()
    @conf_vars({("core", "load_examples"): "False"})
    @pytest.mark.execution_timeout(10)
    def test_dag_with_system_exit(self):