### Apache Airflow Provider(s)

google

### Versions of Apache Airflow Providers

apache-airflow-providers-google==7.0.0

But the problem exists in all newer versions.

### Apache Airflow version

apache-airflow==2.3.2

### Operating System

Ubuntu 20.04.4 LTS

### Deployment

Official Apache Airflow Helm Chart

### Deployment details

_No response_

### What happened

The `list_rows` method in the BigQuery Hook does not return the page_token value, which is necessary for paginating query results. Same problem with `get_datasets_list` method. 

The documentation for the `get_datasets_list` method even states that the page_token parameter can be accessed:
```
            :param page_token:  Token representing a cursor into the datasets. If not passed,
            the API will return the first page of datasets. The token marks the beginning of the
            iterator to be returned and the value of the ``page_token`` can be accessed at
            ``next_page_token`` of the :class:`~google.api_core.page_iterator.HTTPIterator`.
```
but it doesn't return HTTPIterator. Instead, it converts the `HTTPIterator` to `list[DatasetListItem]` using `list(datasets)`, making it impossible to retrieve the original `HTTPIterator` and thus impossible to obtain the `next_page_token`.

### What you think should happen instead

`list_rows` \ `get_datasets_list` methods should return `Iterator` OR both the list of rows\datasets and the page_token value to allow users to retrieve multiple results pages. For backward compatibility, we can have a parameter like `return_iterator=True` or smth like that. 

### How to reproduce

_No response_

### 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)

encryption_configuration: dict | None = None,
    ) -> str:
        """
        Executes a BigQuery SQL query. Optionally persists results in a BigQuery
        table. See here:
        https://cloud.google.com/bigquery/docs/reference/v2/jobs
        For more details about these parameters.
        :param sql: The BigQuery SQL to execute.
        :param destination_dataset_table: The dotted ``<dataset>.<table>``
            BigQuery table to save the query results.
        :param write_disposition: What to do if the table already exists in
            BigQuery.
        :param allow_large_results: Whether to allow large results.
        :param flatten_results: If true and query uses legacy SQL dialect, flattens
            all nested and repeated fields in the query results. ``allowLargeResults``
            must be true if this is set to false. For standard SQL queries, this
            flag is ignored and results are never flattened.
        :param udf_config: The User Defined Function configuration for the query.
            See https://cloud.google.com/bigquery/user-defined-functions for details.
        :param use_legacy_sql: Whether to use legacy SQL (true) or standard SQL (false).
            If `None`, defaults to `self.use_legacy_sql`.
        :param api_resource_configs: a dictionary that contain params
            'configuration' applied for Google BigQuery Jobs API:
            https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs
            for example, {'query': {'useQueryCache': False}}. You could use it
            if you need to provide some params that are not supported by the
            BigQueryHook like args.
        :param maximum_billing_tier: Positive integer that serves as a
            multiplier of the basic price.
        :param maximum_bytes_billed: Limits the bytes billed for this job.