**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

airflow/jobs/scheduler_job.py
"""
        Check if the process launched to process this file is done.
        :return: whether the process is finished running
        :rtype: bool
        """
        if self._process is None or self._parent_channel is None:
            raise AirflowException("Tried to see if it's done before starting!")
        if self._done:
            return True
        if self._parent_channel.poll():
            try:
                self._result = self._parent_channel.recv()
                self._done = True
                self.log.debug("Waiting for %s", self._process)
                self._process.join()
                self._parent_channel.close()
                return True
            except EOFError:
                
                
                
                
                self._done = True
                
                self._process.join(timeout=5)
                if self._process.is_alive():