### Apache Airflow version

2.2.2 (latest released)

### What happened

After upgrading from Airflow 2.1.4 to 2.2.2, every DAG gives this error upon execution:

> [2021-12-17, 15:01:12 UTC] {taskinstance.py:1259} INFO - Executing <Task(_PythonDecoratedOperator): print_the_context> on 2021-12-17 15:01:08.943254+00:00
[2021-12-17, 15:01:12 UTC] {standard_task_runner.py:52} INFO - Started process 873 to run task
[2021-12-17, 15:01:12 UTC] {standard_task_runner.py:76} INFO - Running: ['airflow', 'tasks', 'run', 'example_python_operator', 'print_the_context', 'manual__2021-12-17T15:01:08.943254+00:00', '--job-id', '326', '--raw', '--subdir', 'DAGS_FOLDER/test.py', '--cfg-path', '/tmp/tmpej1imvkr', '--error-file', '/tmp/tmpqn9ad7em']
[2021-12-17, 15:01:12 UTC] {standard_task_runner.py:77} INFO - Job 326: Subtask print_the_context
[2021-12-17, 15:01:12 UTC] {standard_task_runner.py:92} ERROR - Failed to execute job 326 for task print_the_context
Traceback (most recent call last):
  File "/home/ec2-user/venv/lib/python3.7/site-packages/airflow/task/task_runner/standard_task_runner.py", line 85, in _start_by_fork
    args.func(args, dag=self.dag)
  File "/home/ec2-user/venv/lib/python3.7/site-packages/airflow/cli/cli_parser.py", line 48, in command
    return func(*args, **kwargs)
  File "/home/ec2-user/venv/lib/python3.7/site-packages/airflow/utils/cli.py", line 92, in wrapper
    return f(*args, **kwargs)
  File "/home/ec2-user/venv/lib/python3.7/site-packages/airflow/cli/commands/task_command.py", line 287, in task_run
    ti = _get_ti(task, args.execution_date_or_run_id)
  File "/home/ec2-user/venv/lib/python3.7/site-packages/airflow/utils/session.py", line 70, in wrapper
    return func(*args, session=session, **kwargs)
  File "/home/ec2-user/venv/lib/python3.7/site-packages/airflow/cli/commands/task_command.py", line 86, in _get_ti
    dag_run = _get_dag_run(task.dag, exec_date_or_run_id, create_if_necssary, session)
  File "/home/ec2-user/venv/lib/python3.7/site-packages/airflow/cli/commands/task_command.py", line 80, in _get_dag_run
    ) from None
airflow.exceptions.DagRunNotFound: DagRun for example_python_operator with run_id or execution_date of 'manual__2021-12-17T15:01:08.943254+00:00' not found

Both tables `airflowdb.task_instance` and `airflowdb.dag_run` have rows with `run_id` equal to "manual__2021-12-17T15:01:08.943254+00:00".

The issue seems to arise in the `_get_dag_run()` function from [airflow/cli/commands/task_command.py](https://github.com/apache/airflow/blob/bb82cc0fbb7a6630eac1155d0c3b445dff13ceb6/airflow/cli/commands/task_command.py#L61-L72):

``` 
    execution_date = None
    with suppress(ParserError, TypeError):
        execution_date = timezone.parse(exec_date_or_run_id)

    if create_if_necessary and not execution_date:
        return DagRun(dag_id=dag.dag_id, run_id=exec_date_or_run_id)
    try:
        return (
            session.query(DagRun)
            .filter(
                DagRun.dag_id == dag.dag_id,
                DagRun.execution_date == execution_date,
            )
            .one()
        )
```
Here, `exec_date_or_run_id == 'manual__2021-12-17T15:01:08.943254+00:00'` and `timezone.parse(exec_date_or_run_id)` fails, meaning `execution_date` stays as `None` and the session query returns no results.

### What you expected to happen

Expect DAGs to run without the above error.

### How to reproduce

Upgraded from 2.1.4 to 2.2.2 and manually ran a few DAGs. The above log is from the [example_python_operator](https://github.com/apache/airflow/blob/main/airflow/example_dags/example_python_operator.py) DAG provided on the Airflow repo.

### Operating System

Amazon Linux 2

### Versions of Apache Airflow Providers

_No response_

### Deployment

Virtualenv installation

### Deployment details

_No response_

### Anything else

Tried `airflow db upgrade` and `airflow db reset`  without any luck. The same issue appears on 2.2.3rc2.

Using MySQL 8.0.23.

### Are you willing to submit 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)

airflow/cli/commands/task_command.py
"""
    Returns the unmet dependencies for a task instance from the perspective of the
    scheduler (i.e. why a task instance doesn't get scheduled and then queued by the
    scheduler, and then run by an executor).
    >>> airflow tasks failed-deps tutorial sleep 2015-01-01
    Task instance dependencies not met:
    Dagrun Running: Task instance's dagrun did not exist: Unknown reason
    Trigger Rule: Task's trigger rule 'all_success' requires all upstream tasks
    to have succeeded, but found 1 non-success(es).
    """
    dag = get_dag(args.subdir, args.dag_id)
    task = dag.get_task(task_id=args.task_id)
    ti = _get_ti(task, args.execution_date_or_run_id)
    dep_context = DepContext(deps=SCHEDULER_QUEUED_DEPS)
    failed_deps = list(ti.get_failed_dep_statuses(dep_context=dep_context))
    
    if failed_deps:
        print("Task instance dependencies not met:")
        for dep in failed_deps:
            print(f"{dep.dep_name}: {dep.reason}")
    else:
        print("Task instance dependencies are all met.")
@cli_utils.action_cli(check_db=False)
@suppress_logs_and_warning
def task_state(args):