BigQuery supports clustering for both partitioned and non-partitioned tables.

Reference: [https://cloud.google.com/bigquery/docs/clustered-tables](https://cloud.google.com/bigquery/docs/clustered-tables)
airflow/providers/google/cloud/hooks/bigquery.py
"""Helper method that escapes parameters to a SQL query"""
    e = s
    e = e.replace('\\', '\\\\')
    e = e.replace('\n', '\\n')
    e = e.replace('\r', '\\r')
    e = e.replace("'", "\\'")
    e = e.replace('"', '\\"')
    return e
def _bq_cast(string_field: str, bq_type: str) -> Union[None, int, float, bool, str]:
    """
    Helper method that casts a BigQuery row to the appropriate data types.
    This is useful because BigQuery returns all fields as strings.
    """
    if string_field is None:
        return None
    elif bq_type == 'INTEGER':
        return int(string_field)
    elif bq_type in ('FLOAT', 'TIMESTAMP'):
        return float(string_field)
    elif bq_type == 'BOOLEAN':
        if string_field not in ['true', 'false']:
            raise ValueError("{} must have value 'true' or 'false'".format(string_field))
        return string_field == 'true'
    else:
        return string_field
def _split_tablename(