**Apache Airflow version**: 2.0.0


**Kubernetes version (if you are using kubernetes)** (use `kubectl version`):

**Environment**:

- **Cloud provider or hardware configuration**:
- **OS** (e.g. from /etc/os-release):
- **Kernel** (e.g. `uname -a`):
- **Install tools**:
- **Others**:

**What happened**:

I have the following DAG:

```py
from datetime import datetime, timedelta

from airflow import DAG
from airflow.operators.bash_operator import BashOperator

with DAG(
    dag_id="sla_trigger",
    schedule_interval="* * * * *",
    start_date=datetime(2020, 2, 3),
) as dag:
    BashOperator(
        task_id="bash_task",
        bash_command="sleep 30",
        sla=timedelta(seconds=2),
    )

```

And in my understanding this dag should result in SLA miss every time it is triggered (every minute). However, after few minutes of running I don't see any SLA misses...

**What you expected to happen**:

I expect to see SLA if task takes longer than expected.

**How to reproduce it**:

Use the dag from above.

**Anything else we need to know**:

N/A

tests/jobs/test_scheduler_job.py
"""
        Test that the scheduler respects task start dates that are different from DAG start dates
        """
        dagbag = DagBag(dag_folder=os.path.join(settings.DAGS_FOLDER, "no_dags.py"), include_examples=False)
        dag_id = 'test_task_start_date_scheduling'
        dag = self.dagbag.get_dag(dag_id)
        dag.is_paused_upon_creation = False
        dagbag.bag_dag(dag=dag, root_dag=dag)
        
        other_dag = self.dagbag.get_dag('test_start_date_scheduling')
        other_dag.is_paused_upon_creation = True
        dagbag.bag_dag(dag=other_dag, root_dag=other_dag)
        dagbag.sync_to_db()
        scheduler = SchedulerJob(executor=self.null_exec, subdir=dag.fileloc, num_runs=2)
        scheduler.run()
        session = settings.Session()
        tiq = session.query(TaskInstance).filter(TaskInstance.dag_id == dag_id)
        ti1s = tiq.filter(TaskInstance.task_id == 'dummy1').all()
        ti2s = tiq.filter(TaskInstance.task_id == 'dummy2').all()
        assert len(ti1s) == 0
        assert len(ti2s) == 2
        for task in ti2s:
            assert task.state == State.SUCCESS
    def test_scheduler_multiprocessing(self):