### Description

A count of datasets that are currently registered/declared in an Airflow deployment.

### Use case/motivation

Would be nice to see how deployments are adopting datasets.

### Related issues

_No response_

### Are you willing to submit a PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

if not _is_parent_process():
            
            return
        try:
            sig_name = signal.Signals(signum).name
        except Exception:
            sig_name = str(signum)
        self.log.info("%s\n%s received, printing debug\n%s", "-" * 80, sig_name, "-" * 80)
        self.executor.debug_dump()
        self.log.info("-" * 80)
    def is_alive(self, grace_multiplier: float | None = None) -> bool:
        """
        Whether the SchedulerJob is alive.
        We define alive as in a state of running and a heartbeat within the
        threshold defined in the ``scheduler_health_check_threshold`` config
        setting.
        ``grace_multiplier`` is accepted for compatibility with the parent class.
        """
        if grace_multiplier is not None:
            
            return super().is_alive(grace_multiplier=grace_multiplier)
        scheduler_health_check_threshold: int = conf.getint("scheduler", "scheduler_health_check_threshold")
        return (
            self.state == State.RUNNING
            and (timezone.utcnow() - self.latest_heartbeat).total_seconds() < scheduler_health_check_threshold
        )
    def __get_concurrency_maps(