
**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.



tests/dag_processing/test_manager.py
self, mock_processor
    ):
        """
        Check that the same set of failure callback with zombies are passed to the dag
        file processors until the next zombie detection logic is invoked.
        """
        test_dag_path = TEST_DAG_FOLDER / 'test_example_bash_operator.py'
        with conf_vars({('scheduler', 'parsing_processes'): '1', ('core', 'load_examples'): 'False'}):
            dagbag = DagBag(test_dag_path, read_dags_from_db=False)
            with create_session() as session:
                session.query(LJ).delete()
                dag = dagbag.get_dag('test_example_bash_operator')
                dag.sync_to_db()
                task = dag.get_task(task_id='run_this_last')
                ti = TI(task, DEFAULT_DATE, State.RUNNING)
                local_job = LJ(ti)
                local_job.state = State.SHUTDOWN
                session.add(local_job)
                session.commit()
                
                
                session.add(ti)
                ti.job_id = local_job.id
                session.commit()
                expected_failure_callback_requests = [
                    TaskCallbackRequest(