**Description**
The Airflow logs generated by the Livy operator currently only state the status of the submitted batch. To view the logs from the job itself, one must go separately to the session logs. I think that Airflow should have the option (possibly on by default) that retrieves the session logs after the batch reaches a terminal state if a `polling_interval` has been set.

**Use case / motivation**
When debugging a task submitted via Livy, the session logs are the first place to check. For most other tasks, including SparkSubmitOperator, viewing the first-check logs can be done in the Airflow UI, but for Livy you must go externally or write a separate task to retrieve them. 

**Are you willing to submit a PR?**

I don't yet have a good sense of how challenging this will be to set up and test. I can try but if anyone else wants to go for it, don't let my attempt stop you.

**Related Issues**

None I could find

airflow/providers/apache/livy/hooks/livy.py
:type jars: Sequence[str]
        :param py_files: Python files to be used in this session.
        :type py_files: Sequence[str]
        :param files: files to be used in this session.
        :type files: Sequence[str]
        :param driver_memory: Amount of memory to use for the driver process  string.
        :type driver_memory: str
        :param driver_cores: Number of cores to use for the driver process int.
        :type driver_cores: Union[str, int]
        :param executor_memory: Amount of memory to use per executor process  string.
        :type executor_memory: str
        :param executor_cores: Number of cores to use for each executor  int.
        :type executor_cores: Union[int, str]
        :param num_executors: Number of executors to launch for this session  int.
        :type num_executors: Union[str, int]
        :param archives: Archives to be used in this session.
        :type archives: Sequence[str]
        :param queue: The name of the YARN queue to which submitted string.
        :type queue: str
        :param name: The name of this session string.
        :type name: str
        :param conf: Spark configuration properties.
        :type conf: dict
        :return: request body
        :rtype: dict
        """
        body: Dict[str, Any] = {'file': file}
        if proxy_user:
            body['proxyUser'] = proxy_user
        if class_name: