### 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)

#
#
from __future__ import annotations
import json
from typing import TYPE_CHECKING, Any, Sequence
from botocore.exceptions import ClientError
from airflow.compat.functools import cached_property
from airflow.exceptions import AirflowException
from airflow.models import BaseOperator
from airflow.providers.amazon.aws.hooks.base_aws import AwsBaseHook
from airflow.providers.amazon.aws.hooks.sagemaker import SageMakerHook
from airflow.utils.json import AirflowJsonEncoder
if TYPE_CHECKING:
    from airflow.utils.context import Context
DEFAULT_CONN_ID: str = "aws_default"
CHECK_INTERVAL_SECOND: int = 30
def serialize(result: dict) -> str:
    return json.loads(json.dumps(result, cls=AirflowJsonEncoder))
class SageMakerBaseOperator(BaseOperator):
    """This is the base operator for all SageMaker operators.
    :param config: The configuration necessary to start a training job (templated)
    """
    template_fields: Sequence[str] = ("config",)
    template_ext: Sequence[str] = ()
    template_fields_renderers: dict = {"config": "json"}
    ui_color: str = "#ededed"
    integer_fields: list[list[Any]] = []
    def __init__(self, *, config: dict, **kwargs):