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##### SUMMARY
The vmware_cluster_ha module should support advanced configuration parameters in a generic way. 

##### ISSUE TYPE
- Feature Idea

##### COMPONENT NAME
vmware_cluster_ha

##### ADDITIONAL INFORMATION
The feature would allow advanced configurations like isolation address handling.

<!--- Paste example playbooks or commands between quotes below -->
```yaml
name: Enable HA with multiple custom isolation addresses for stretched vSAN
  vmware_cluster_ha:
    hostname: '{{ vcenter_hostname }}'
    username: '{{ vcenter_username }}'
    password: '{{ vcenter_password }}'
    datacenter_name: datacenter
    cluster_name: cluster
    enable_ha: yes
    configuration_parameters:
      das.usedefaultisolationaddress: false
      das.isolationaddress0: '{{ primary_isolation_address }}'
      das.isolationaddress1: '{{ secondary_isolation_address }}'
  delegate_to: localhost
```

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search_spec = vim.host.DatastoreBrowser.SearchSpec(
            details=detail_query,
            matchPattern=[vmdk_filename],
            searchCaseInsensitive=True,
        )
        search_res = browser.SearchSubFolders(
            datastorePath=datastore_name_sq,
            searchSpec=search_spec
        )
        changed = False
        vmdk_path = datastore_name_sq + " " + vmdk_fullpath
        try:
            changed, result = wait_for_task(search_res)
        except TaskError as task_e:
            self.module.fail_json(msg=to_native(task_e))
        if not changed:
            self.module.fail_json(msg="No valid disk vmdk image found for path %s" % vmdk_path)
        target_folder_paths = [
            datastore_name_sq + " " + vmdk_folder + '/',
            datastore_name_sq + " " + vmdk_folder,
        ]
        for file_result in search_res.info.result:
            for f in getattr(file_result, 'file'):
                if f.path == vmdk_filename and file_result.folderPath in target_folder_paths:
                    return f
        self.module.fail_json(msg="No vmdk file found for path specified [%s]" % vmdk_path)
    #
    
    #
    def _deepmerge(self, d, u):