### Description

In some cases the Airflow sends `SIGTERM` to the task, here to the `SparkKubernetesOperator`, it needs to send `SIGTERM` also to the corresponding pods/jobs

### Use case/motivation

_No response_

### 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)

"""
    Creates Kubernetes API connection.
    - use in cluster configuration by using extra field ``in_cluster`` in connection
    - use custom config by providing path to the file using extra field ``kube_config_path`` in connection
    - use custom configuration by providing content of kubeconfig file via
        extra field ``kube_config`` in connection
    - use default config by providing no extras
    This hook check for configuration option in the above order. Once an option is present it will
    use this configuration.
    .. seealso::
        For more information about Kubernetes connection:
        :doc:`/connections/kubernetes`
    :param conn_id: The :ref:`kubernetes connection <howto/connection:kubernetes>`
        to Kubernetes cluster.
    :param client_configuration: Optional dictionary of client configuration params.
        Passed on to kubernetes client.
    :param cluster_context: Optionally specify a context to use (e.g. if you have multiple
        in your kubeconfig.
    :param config_file: Path to kubeconfig file.
    :param in_cluster: Set to ``True`` if running from within a kubernetes cluster.
    :param disable_verify_ssl: Set to ``True`` if SSL verification should be disabled.
    :param disable_tcp_keepalive: Set to ``True`` if you want to disable keepalive logic.
    """
    conn_name_attr = "kubernetes_conn_id"
    default_conn_name = "kubernetes_default"
    conn_type = "kubernetes"
    hook_name = "Kubernetes Cluster Connection"
    DEFAULT_NAMESPACE = "default"
    @staticmethod
    def get_connection_form_widgets() -> dict[str, Any]: