**Apache Airflow version**: 2.0.2


**Kubernetes version (if you are using kubernetes)** (use `kubectl version`): NA

**Environment**: MWAA and Locally

- **Cloud provider or hardware configuration**: AWS
- **OS** (e.g. from /etc/os-release): NA
- **Kernel** (e.g. `uname -a`): NA
- **Install tools**: NA
- **Others**: NA

**What happened**:

When calling the SagemakerProcessingOperator sometimes get: "botocore.exceptions.ClientError: An error occurred (ThrottlingException)" due to excessive ListProcessingJobs operations.

**What you expected to happen**:

The job should have started without timing out. I believe one fix would be to use the `NameContains` functionality of boto3 [list_processing_jobs](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html#SageMaker.Client.list_processing_jobs) so you don't have to paginate as is occurring [here](https://github.com/apache/airflow/blob/main/airflow/providers/amazon/aws/hooks/sagemaker.py#L916). 

**How to reproduce it**:

If you incrementally create Sagemaker Processing jobs you will eventually see the Throttling as the pagination increases.

**Anything else we need to know**:

This looks like it is happening when the account already has a lot of former Sagemaker Processing jobs.
airflow/providers/amazon/aws/hooks/sagemaker.py
"""
        Check if a tuning configuration is valid
        :param tuning_config: tuning_config
        :type tuning_config: dict
        :return: None
        """
        for channel in tuning_config['TrainingJobDefinition']['InputDataConfig']:
            if "S3DataSource" in channel['DataSource']:
                self.check_s3_url(channel['DataSource']['S3DataSource']['S3Uri'])
    def get_log_conn(self):
        """
        This method is deprecated.
        Please use :py:meth:`airflow.providers.amazon.aws.hooks.logs.AwsLogsHook.get_conn` instead.
        """
        warnings.warn(
            "Method `get_log_conn` has been deprecated. "
            "Please use `airflow.providers.amazon.aws.hooks.logs.AwsLogsHook.get_conn` instead.",
            category=DeprecationWarning,
            stacklevel=2,
        )
        return self.logs_hook.get_conn()
    def log_stream(self, log_group, stream_name, start_time=0, skip=0):