If you have a DAG with `max_active_runs=1` and it is running some tasks, and then you manually trigger another run of this DAG, both runs end up not scheduling anything and you see this message over and over in the logs:

```
[2020-10-16 14:00:34,118]  2437572 {{airflow.jobs.scheduler_job.SchedulerJob scheduler_job.py:1657}} INFO - DAG scenario1_case2_01_1 already has 1 active runs, not queuing any more tasks
```

A longer term fix for this would be to introduce a "queued" state for DagRuns, and then when manually creating dag runs set it to queued, and only have the scheduler set DagRuns to running.

That may or may not be less work than fixing the current mechanism.
airflow/jobs/scheduler_job.py
"""
        For the DAGs in the given DagBag, record any associated import errors and clears
        errors for files that no longer have them. These are usually displayed through the
        Airflow UI so that users know that there are issues parsing DAGs.
        :param session: session for ORM operations
        :type session: sqlalchemy.orm.session.Session
        :param dagbag: DagBag containing DAGs with import errors
        :type dagbag: airflow.DagBag
        """
        
        for dagbag_file in dagbag.file_last_changed:
            session.query(errors.ImportError).filter(
                errors.ImportError.filename == dagbag_file
            ).delete()
        
        for filename, stacktrace in dagbag.import_errors.items():
            session.add(errors.ImportError(
                filename=filename,
                timestamp=timezone.utcnow(),
                stacktrace=stacktrace))
        session.commit()
    @provide_session
    def execute_callbacks(