### 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)

ti_queued = ti.try_number == buffer_key.try_number and ti.state == TaskInstanceState.QUEUED
            ti_requeued = ti.queued_by_job_id != self.id or self.executor.has_task(ti)
            if ti_queued and not ti_requeued:
                Stats.incr("scheduler.tasks.killed_externally")
                msg = (
                    "Executor reports task instance %s finished (%s) although the "
                    "task says its %s. (Info: %s) Was the task killed externally?"
                )
                self.log.error(msg, ti, state, ti.state, info)
                
                try:
                    dag = self.dagbag.get_dag(ti.dag_id)
                    task = dag.get_task(ti.task_id)
                except Exception:
                    self.log.exception("Marking task instance %s as %s", ti, state)
                    ti.set_state(state)
                    continue
                ti.task = task
                if task.on_retry_callback or task.on_failure_callback:
                    request = TaskCallbackRequest(
                        full_filepath=ti.dag_model.fileloc,
                        simple_task_instance=SimpleTaskInstance.from_ti(ti),
                        msg=msg % (ti, state, ti.state, info),
                        processor_subdir=ti.dag_model.processor_subdir,
                    )
                    self.executor.send_callback(request)
                else:
                    ti.handle_failure(error=msg % (ti, state, ti.state, info), session=session)
        return len(event_buffer)
    def _execute(self) -> None: