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**Apache Airflow version**:
2.0.1

**Environment**:

- **Cloud provider or hardware configuration**:
- **OS** (e.g. from /etc/os-release):  "18.04.1 LTS (Bionic Beaver)"

- **Kernel** (e.g. `uname -a`): 4.15.0-130-generic #134-Ubuntu 
- **Install tools**:
- **Others**:

**What happened**:

I observe the following exception,  in the scheduler intermittently:

```
[2021-02-10 03:51:26,651] {scheduler_job.py:1298} ERROR - Exception when executing SchedulerJob._run_scheduler_loop
Traceback (most recent call last):
  File "/home/foo/bar/.env38/lib/python3.8/site-packages/airflow/jobs/scheduler_job.py", line 1280, in _execute
    self._run_scheduler_loop()
  File "/home/foo/bar/.env38/lib/python3.8/site-packages/airflow/jobs/scheduler_job.py", line 1354, in _run_scheduler_loop
    self.adopt_or_reset_orphaned_tasks()
  File "/home/foo/bar/.env38/lib/python3.8/site-packages/airflow/utils/session.py", line 65, in wrapper
    return func(*args, session=session, **kwargs)
  File "/home/foo/bar/.env38/lib/python3.8/site-packages/airflow/jobs/scheduler_job.py", line 1837, in adopt_or_reset_orphaned_tasks
    for attempt in run_with_db_retries(logger=self.log):
  File "/home/foo/bar/.env38/lib/python3.8/site-packages/tenacity/__init__.py", line 390, in __iter__
    do = self.iter(retry_state=retry_state)
  File "/home/foo/bar/.env38/lib/python3.8/site-packages/tenacity/__init__.py", line 356, in iter
    return fut.result()
  File "/home/foo/py_src/lib/python3.8/concurrent/futures/_base.py", line 432, in result
    return self.__get_result()
  File "/home/foo/py_src/lib/python3.8/concurrent/futures/_base.py", line 388, in __get_result
    raise self._exception
  File "/home/foo/bar/.env38/lib/python3.8/site-packages/airflow/jobs/scheduler_job.py", line 1882, in adopt_or_reset_orphaned_tasks
    to_reset = self.executor.try_adopt_task_instances(tis_to_reset_or_adopt)
  File "/home/foo/bar/.env38/lib/python3.8/site-packages/airflow/executors/celery_executor.py", line 478, in try_adopt_task_instances
    states_by_celery_task_id = self.bulk_state_fetcher.get_many(
  File "/home/foo/bar/.env38/lib/python3.8/site-packages/airflow/executors/celery_executor.py", line 554, in get_many
    result = self._get_many_using_multiprocessing(async_results)
  File "/home/foo/bar/.env38/lib/python3.8/site-packages/airflow/executors/celery_executor.py", line 595, in _get_many_using_multiprocessing
    num_process = min(len(async_results), self._sync_parallelism)
TypeError: object of type 'map' has no len()
```

**What you expected to happen**:

I think the `len` should not be called on the `async_results`, or `map` should not be used in `try_adopt_task_instances`.

**How to reproduce it**:

Not sure how I can reproduce it. But, here are the offending lines:

https://github.com/apache/airflow/blob/90ab60bba877c65cb93871b97db13a179820d28b/airflow/executors/celery_executor.py#L479

Then, this branch gets hit:

https://github.com/apache/airflow/blob/90ab60bba877c65cb93871b97db13a179820d28b/airflow/executors/celery_executor.py#L554

The, we see the failure, here:
https://github.com/apache/airflow/blob/90ab60bba877c65cb93871b97db13a179820d28b/airflow/executors/celery_executor.py#L595


airflow/executors/celery_executor.py
"""
    Gets status for many Celery tasks using the best method available
    If BaseKeyValueStoreBackend is used as result backend, the mget method is used.
    If DatabaseBackend is used as result backend, the SELECT ...WHERE task_id IN (...) query is used
    Otherwise, multiprocessing.Pool will be used. Each task status will be downloaded individually.
    """
    def __init__(self, sync_parallelism=None):
        super().__init__()
        self._sync_parallelism = sync_parallelism
    def get_many(self, async_results) -> Mapping[str, EventBufferValueType]:
        """Gets status for many Celery tasks using the best method available."""
        if isinstance(app.backend, BaseKeyValueStoreBackend):
            result = self._get_many_from_kv_backend(async_results)
            return result
        if isinstance(app.backend, DatabaseBackend):
            result = self._get_many_from_db_backend(async_results)
            return result
        result = self._get_many_using_multiprocessing(async_results)
        self.log.debug("Fetched %d states for %d task", len(result), len(async_results))
        return result
    def _get_many_from_kv_backend(self, async_tasks) -> Mapping[str, EventBufferValueType]:
        task_ids = _tasks_list_to_task_ids(async_tasks)
        keys = [app.backend.get_key_for_task(k) for k in task_ids]
        values = app.backend.mget(keys)
        task_results = [app.backend.decode_result(v) for v in values if v]
        task_results_by_task_id = {task_result["task_id"]: task_result for task_result in task_results}
        return self._prepare_state_and_info_by_task_dict(task_ids, task_results_by_task_id)
    def _get_many_from_db_backend(self, async_tasks) -> Mapping[str, EventBufferValueType]: