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
:param parent_channel: the parent end of the channel to close in the child
        :type result_channel: multiprocessing.Connection
        :param file_path: the file to process
        :type file_path: str
        :param pickle_dags: whether to pickle the DAGs found in the file and
            save them to the DB
        :type pickle_dags: bool
        :param dag_ids: if specified, only examine DAG ID's that are
            in this list
        :type dag_ids: list[str]
        :param thread_name: the name to use for the process that is launched
        :type thread_name: str
        :param callback_requests: failure callback to execute
        :type callback_requests: List[airflow.utils.callback_requests.CallbackRequest]
        :return: the process that was launched
        :rtype: multiprocessing.Process
        """
        
        log: logging.Logger = logging.getLogger("airflow.processor")
        
        
        log.info("Closing parent pipe")
        parent_channel.close()
        del parent_channel
        set_context(log, file_path)
        setproctitle("airflow scheduler - DagFileProcessor {}".format(file_path))
        try:
            
            with ExitStack() as exit_stack:
                exit_stack.enter_context(redirect_stdout(StreamLogWriter(log, logging.INFO)))