### Apache Airflow Provider(s)

amazon

### Versions of Apache Airflow Providers



apache-airflow-providers-amazon | 2.4.0

### Apache Airflow version

2.2.3 (latest released)

### Operating System

Amazon Linux 2

### Deployment

MWAA

### Deployment details

_No response_

### What happened

Sagemaker Processing Operator no longer honors the `action_if_job_exists` param and always fails creation of a new processing job is a job with the name already exists. 

This happens because in a recent change, the function responsible for executing the job no longer honors the increment setting:

Change that breaks the increment: https://github.com/apache/airflow/commit/96dd70348ad7e31cfeae6d21af70671b41551fe9

New code: https://github.com/apache/airflow/blob/6734eb1d09a99dc519e89a59e2086cef09a87098/airflow/providers/amazon/aws/operators/sagemaker.py#L167

  

### What you expected to happen

When Sagemaker Processing operator is called with a job-name that already exists, the job creation should succeed with a name that is incremented by 1.   

### How to reproduce

invoke SageMakerProcessingOperator twice with the same job name while keeping action_if_job_exists as 'increment'.   

### 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)

return ""
    prev_transitions_num = 0
    if prev_description is not None:
        if prev_description.get("SecondaryStatusTransitions") is not None:
            prev_transitions_num = len(prev_description["SecondaryStatusTransitions"])
    transitions_to_print = (
        current_transitions[-1:]
        if len(current_transitions) == prev_transitions_num
        else current_transitions[prev_transitions_num - len(current_transitions) :]
    )
    status_strs = []
    for transition in transitions_to_print:
        message = transition["StatusMessage"]
        time_str = timezone.convert_to_utc(cast(datetime, job_description["LastModifiedTime"])).strftime(
            "%Y-%m-%d %H:%M:%S"
        )
        status_strs.append(f"{time_str} {transition['Status']} - {message}")
    return "\n".join(status_strs)
class SageMakerHook(AwsBaseHook):
    """
    Interact with Amazon SageMaker.
    Additional arguments (such as ``aws_conn_id``) may be specified and
    are passed down to the underlying AwsBaseHook.
    .. seealso::
        :class:`~airflow.providers.amazon.aws.hooks.base_aws.AwsBaseHook`
    """
    non_terminal_states = {"InProgress", "Stopping"}
    endpoint_non_terminal_states = {"Creating", "Updating", "SystemUpdating", "RollingBack", "Deleting"}
    failed_states = {"Failed"}
    def __init__(self, *args, **kwargs):