### Apache Airflow version

2.6.0

### What happened

When marking an EMR Serverless job as failed, the job continues to run.

### What you think should happen instead

The job should be cancelled. Looking at the [EMR Serverless Operator](https://github.com/apache/airflow/blob/a6be96d92828a86e982b53646a9e2eeca00a5463/airflow/providers/amazon/aws/operators/emr.py#L939), I don't see an `on_kill` method, so assuming we just need to add that. 

I'm not sure how to handle the `EmrServerlessCreateApplicationOperator` operator, though - if the workflow has a corresponding `EmrServerlessDeleteApplicationOperator`, we'd probably want to delete the application if the job is cancelled.

### How to reproduce

- Start an EMR Serverless DAG
- Mark the job as failed in the Airflow UI
- See that the EMR Serverless job continues to run

### Operating System

n/a

### Versions of Apache Airflow Providers

`apache-airflow-providers-amazon==8.0.0`

### Deployment

Amazon (AWS) MWAA

### Deployment details

_No response_

### Anything else

_No response_

### Are you willing to submit 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)

"""
    An operator that modifies an existing EMR cluster.
    .. seealso::
        For more information on how to use this operator, take a look at the guide:
        :ref:`howto/operator:EmrModifyClusterOperator`
    :param cluster_id: cluster identifier
    :param step_concurrency_level: Concurrency of the cluster
    :param aws_conn_id: aws connection to uses
    :param do_xcom_push: if True, cluster_id is pushed to XCom with key cluster_id.
    """
    template_fields: Sequence[str] = ("cluster_id", "step_concurrency_level")
    template_ext: Sequence[str] = ()
    ui_color = "#f9c915"
    operator_extra_links = (
        EmrClusterLink(),
        EmrLogsLink(),
    )
    def __init__(
        self, *, cluster_id: str, step_concurrency_level: int, aws_conn_id: str = "aws_default", **kwargs
    ):
        super().__init__(**kwargs)
        self.aws_conn_id = aws_conn_id
        self.cluster_id = cluster_id
        self.step_concurrency_level = step_concurrency_level
    def execute(self, context: Context) -> int: