**Apache Airflow version**:
2.1.0

**What happened**:
There are several hooks that still use optional parameters from the classic `Extra` field.  However, when creating the connection the `Extra` field is overwritten with values from the custom fields that are included in the form.  Because the `Extra` field is overwritten, these optional parameters cannot be used by the hook.

For example, in the `AzureDataFactoryHook`, If `resource_group_name` or `factory_name` are not provided when initializing the hook, it defaults to the value specified in the connection extras. Using the Azure Data Factory connection form, here is the initial connection submission:
![image](https://user-images.githubusercontent.com/48934154/127029091-a8b1c979-f238-4bac-9d3a-f94b6cd92a2b.png)

After saving the connection, the `Extra` field is overwritten with the custom fields that use "extras" under the hood:
![image](https://user-images.githubusercontent.com/48934154/127029242-79c990f0-b9cf-43bb-9a6b-28b4e9c6d4e1.png)


**What you expected to happen**:

Wavering slightly but I would have initially expected that the `Extra` field wasn't overwritten but updated with both the custom field "extras" plus the originally configured values in the `Extra` field.  However, a better UX would be that the values used in the `Extra` field should be separate custom fields for these hooks and the `Extra` field is hidden.  Perhaps it's even both?

**How to reproduce it**:
Install either the Microsoft Azure or Snowflake providers, attempt to create a connection for either the Snowflake, Azure Data Factory, Azure Container Volume, or Azure types with the `Extra` field populated prior to saving the form.


**Anything else we need to know**:
Happy to submit PRs to fix this issue. 🚀 


airflow/www/views.py
"""Mark task as success."""
        args = request.form
        dag_id = args.get('dag_id')
        task_id = args.get('task_id')
        origin = get_safe_url(args.get('origin'))
        execution_date = args.get('execution_date')
        upstream = to_boolean(args.get('upstream'))
        downstream = to_boolean(args.get('downstream'))
        future = to_boolean(args.get('future'))
        past = to_boolean(args.get('past'))
        return self._mark_task_instance_state(
            dag_id,
            task_id,
            origin,
            execution_date,
            upstream,
            downstream,
            future,
            past,
            State.SUCCESS,
        )
    def _get_tree_data(self, dag_runs: Iterable[DagRun], dag: DAG, base_date: DateTime):