### Description

Spark-submit 
--queue thequeue option specifies the YARN queue to which the application should be submitted.


more  - https://spark.apache.org/docs/3.2.0/running-on-yarn.html

### Use case/motivation


The --queue option is particularly useful in a multi-tenant environment where different users or groups have allocated resources in specific YARN queues.

### Related issues

_No response_

### Are you willing to submit a PR?

- [X] 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)

:param total_executor_cores: (Standalone & Mesos only) Total cores for all executors
        (Default: all the available cores on the worker)
    :param executor_cores: (Standalone, YARN and Kubernetes only) Number of cores per
        executor (Default: 2)
    :param executor_memory: Memory per executor (e.g. 1000M, 2G) (Default: 1G)
    :param driver_memory: Memory allocated to the driver (e.g. 1000M, 2G) (Default: 1G)
    :param keytab: Full path to the file that contains the keytab
    :param principal: The name of the kerberos principal used for keytab
    :param proxy_user: User to impersonate when submitting the application
    :param name: Name of the job (default airflow-spark)
    :param num_executors: Number of executors to launch
    :param status_poll_interval: Seconds to wait between polls of driver status in cluster
        mode (Default: 1)
    :param application_args: Arguments for the application being submitted
    :param env_vars: Environment variables for spark-submit. It
        supports yarn and k8s mode too.
    :param verbose: Whether to pass the verbose flag to spark-submit process for debugging
    :param spark_binary: The command to use for spark submit.
                         Some distros may use spark2-submit or spark3-submit.
    :param properties_file: Path to a file from which to load extra properties. If not
                              specified, this will look for conf/spark-defaults.conf.
    :param use_krb5ccache: if True, configure spark to use ticket cache instead of relying
        on keytab for Kerberos login
    """
    conn_name_attr = "conn_id"
    default_conn_name = "spark_default"
    conn_type = "spark"
    hook_name = "Spark"
    @classmethod
    def get_ui_field_behaviour(cls) -> dict[str, Any]: