### Apache Airflow version

2.0.2

### Operating System

Linux (AWS MWAA)

### Versions of Apache Airflow Providers

Version 2.0.2

### Deployment

MWAA

### Deployment details

_No response_

### What happened

While running an Airflow step using the AWSGlueJobOperator to run a glue script using Airflow, these were the job args given: 
```
"GlueVersion": "3.0",
"WorkerType": "G.2X",
"NumberOfWorkers": 60,
```

At this point, this is the error encountered:

```
Traceback (most recent call last):
  File "/usr/local/lib/python3.7/site-packages/airflow/models/taskinstance.py", line 1138, in _run_raw_task
    self._prepare_and_execute_task_with_callbacks(context, task)
  File "/usr/local/lib/python3.7/site-packages/airflow/models/taskinstance.py", line 1311, in _prepare_and_execute_task_with_callbacks
    result = self._execute_task(context, task_copy)
  File "/usr/local/lib/python3.7/site-packages/airflow/models/taskinstance.py", line 1341, in _execute_task
    result = task_copy.execute(context=context)
  File "/usr/local/lib/python3.7/site-packages/airflow/providers/amazon/aws/operators/glue.py", line 121, in execute
    glue_job_run = glue_job.initialize_job(self.script_args)
  File "/usr/local/lib/python3.7/site-packages/airflow/providers/amazon/aws/hooks/glue.py", line 108, in initialize_job
    job_name = self.get_or_create_glue_job()
  File "/usr/local/lib/python3.7/site-packages/airflow/providers/amazon/aws/hooks/glue.py", line 186, in get_or_create_glue_job
    **self.create_job_kwargs,
  File "/usr/local/lib/python3.7/site-packages/botocore/client.py", line 357, in _api_call
    return self._make_api_call(operation_name, kwargs)
  File "/usr/local/lib/python3.7/site-packages/botocore/client.py", line 676, in _make_api_call
    raise error_class(parsed_response, operation_name)
botocore.errorfactory.InvalidInputException: An error occurred (InvalidInputException) when calling the CreateJob operation: Please do not set Allocated Capacity if using Worker Type and Number of Workers.

```

This issue is because AWSGlueJobHook (when called by AWSGlueJobOperator) assigns num_of_dpus (defaulted to 6 by the init method) to the AllocatedCapacity variable as shown in the screenshot below (taken from the AWSGlueJobHook class)
![image](https://user-images.githubusercontent.com/36181425/138749154-d0c715c6-5f8c-426d-ae56-0aae684b04f3.png)

The links to the source code are: 
https://airflow.apache.org/docs/apache-airflow-providers-amazon/stable/_modules/airflow/providers/amazon/aws/hooks/glue.html#AwsGlueJobHook.initialize_job
https://airflow.apache.org/docs/apache-airflow-providers-amazon/stable/_modules/airflow/providers/amazon/aws/operators/glue.html#AwsGlueJobOperator.template_fields

So, there is no way for the user to proceed forward by specifying the 'WorkerType' and 'NumberOfWorkers' and not encountering the error above. 

This is because AWS Glue API does not allow to use "AllocatedCapacity" or "MaxCapacity" parameters when the 'WorkerType' and 'NumberOfWorkers' are being assigned. Here is the link to the AWS documentation for the same: https://docs.aws.amazon.com/en_us/glue/latest/dg/aws-glue-api-jobs-job.html

### What you expected to happen

The expected outcome is that Airflow runs the Glue job by taking "WorkerType" and "NumberOfWorkers" as the parameter for Glue version 3.0.

### How to reproduce

This issue can be reproduced by the following steps:

1. Set the job args dict to include the following keys and values.

`  "GlueVersion": "3.0",
    "WorkerType": "G.2X",
    "NumberOfWorkers": 60,`

2. Create a dag with one step using AwsGlueJobOperator and assign the job_args dict to the `create_job_kwargs` parameter.
3. Run the dag and this issue will be encoutered.

### 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)

airflow/providers/amazon/aws/hooks/glue.py
"""
        Get state of the Glue job. The job state can be
        running, finished, failed, stopped or timeout.
        :param job_name: unique job name per AWS account
        :type job_name: str
        :param run_id: The job-run ID of the predecessor job run
        :type run_id: str
        :return: State of the Glue job
        """
        glue_client = self.get_conn()
        job_run = glue_client.get_job_run(JobName=job_name, RunId=run_id, PredecessorsIncluded=True)
        job_run_state = job_run['JobRun']['JobRunState']
        return job_run_state
    def job_completion(self, job_name: str, run_id: str) -> Dict[str, str]: