
**Apache Airflow version**: 2.1.2

**Apache Airflow Provider versions** (please include all providers that are relevant to your bug): 2.0

apache-airflow-providers-apache-hive==2.0.0
apache-airflow-providers-celery==2.0.0
apache-airflow-providers-cncf-kubernetes==1.2.0
apache-airflow-providers-docker==2.0.0
apache-airflow-providers-elasticsearch==1.0.4
apache-airflow-providers-ftp==2.0.0
apache-airflow-providers-imap==2.0.0
apache-airflow-providers-jdbc==2.0.0
apache-airflow-providers-microsoft-mssql==2.0.0
apache-airflow-providers-mysql==2.0.0
apache-airflow-providers-oracle==2.0.0
apache-airflow-providers-postgres==2.0.0
apache-airflow-providers-sqlite==2.0.0
apache-airflow-providers-ssh==2.0.0

**Kubernetes version (if you are using kubernetes)** (use `kubectl version`): 1.17

**Environment**:

- **Install tools**: https://github.com/prometheus/statsd_exporter

**What happened**:

We are using an [statsd_exporter](https://github.com/prometheus/statsd_exporter) to store statsd metrics in prometheus. And we came across strange behavior, the metric dag_processing.last_duration. <dag_file> for different dags is drawn with holes at random intervals.

![image](https://user-images.githubusercontent.com/3032319/128734876-800ab58e-50d5-4c81-af4a-79c8660c2f0a.png)

![image](https://user-images.githubusercontent.com/3032319/128734946-27381da5-40cc-4c83-9bcc-60d8264d26a3.png)

![image](https://user-images.githubusercontent.com/3032319/128735019-a523e58c-5751-466d-abb7-1888fa79b9e1.png)


**What you expected to happen**:

Metrics should be sent with the frequency specified in the config in the AIRFLOV__SHEDULER__PRINT_STATS_INTERVAL parameter and the default value is 30, and this happens in the[ _log_file_processing_stats method](https://github.com/apache/airflow/blob/2fea4cdceaa12b3ac13f24eeb383af624aacb2e7/airflow/dag_processing/manager.py#L696), the problem is that the initial time is taken using the [get_start_time](https://github.com/apache/airflow/blob/2fea4cdceaa12b3ac13f24eeb383af624aacb2e7/airflow/dag_processing/manager.py#L827) function which looks only at the probability of active processes that some of the dags will have time to be processed in 30 seconds and removed from self._processors [file_path] and thus the metrics for them will not be sent to the statsd. While for outputting to the log,  [lasttime](https://github.com/apache/airflow/blob/2fea4cdceaa12b3ac13f24eeb383af624aacb2e7/airflow/dag_processing/manager.py#L783) is used in which information on the last processing is stored and from which it would be nice to send metrics to the statistics.



airflow/dag_processing/manager.py
"""
        :param file_path: the path to the file that's being processed
        :type file_path: unicode
        :return: the number of times the given file has been parsed
        :rtype: int
        """
        stat = self._file_stats.get(file_path)
        return stat.run_count if stat else 0
    def set_file_paths(self, new_file_paths):
        """
        Update this with a new set of paths to DAG definition files.
        :param new_file_paths: list of paths to DAG definition files
        :type new_file_paths: list[unicode]
        :return: None
        """
        self._file_paths = new_file_paths
        self._file_path_queue = [x for x in self._file_path_queue if x in new_file_paths]
        
        filtered_processors = {}
        for file_path, processor in self._processors.items():
            if file_path in new_file_paths:
                filtered_processors[file_path] = processor
            else:
                self.log.warning("Stopping processor for %s", file_path)
                Stats.decr('dag_processing.processes')
                processor.terminate()
                self._file_stats.pop(file_path)
        self._processors = filtered_processors
    def wait_until_finished(self):