
**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
elif list_mode == "random_seeded_by_host":
            
            
            random.Random(get_hostname()).shuffle(file_paths)
        files_paths_at_run_limit = [
            file_path for file_path, stat in self._file_stats.items() if stat.run_count == self._max_runs
        ]
        file_paths_to_exclude = set(file_paths_in_progress).union(
            file_paths_recently_processed, files_paths_at_run_limit
        )
        
        
        files_paths_to_queue = [
            file_path for file_path in file_paths if file_path not in file_paths_to_exclude
        ]
        for file_path, processor in self._processors.items():
            self.log.debug(
                "File path %s is still being processed (started: %s)",
                processor.file_path,
                processor.start_time.isoformat(),
            )
        self.log.debug("Queuing the following files for processing:\n\t%s", "\n\t".join(files_paths_to_queue))
        for file_path in files_paths_to_queue:
            if file_path not in self._file_stats:
                self._file_stats[file_path] = DagFileStat(
                    num_dags=0, import_errors=0, last_finish_time=None, last_duration=None, run_count=0
                )
        self._file_path_queue.extend(files_paths_to_queue)
    @provide_session
    def _find_zombies(self, session):