How to use the pyathena.error.DataError function in PyAthena

def _process_meta_data(self, response):
        result_set = response.get('ResultSet', None)
        if not result_set:
            raise DataError('KeyError `ResultSet`')
        meta_data = result_set.get('ResultSetMetadata', None)
        if not meta_data:
            raise DataError('KeyError `ResultSetMetadata`')
        column_info = meta_data.get('ColumnInfo', None)
        if column_info is None:
            raise DataError('KeyError `ColumnInfo`')
        self._meta_data = tuple(column_info)

query_execution_context = query_execution.get('QueryExecutionContext', {})
        self._database = query_execution_context.get('Database', None)

        self._query_id = query_execution.get('QueryExecutionId', None)
        if not self._query_id:
            raise DataError('KeyError `QueryExecutionId`')

        self._query = query_execution.get('Query', None)
        if not self._query:
            raise DataError('KeyError `Query`')
        self._statement_type = query_execution.get('StatementType', None)

        status = query_execution.get('Status', None)
        if not status:
            raise DataError('KeyError `Status`')
        self._state = status.get('State', None)
        self._state_change_reason = status.get('StateChangeReason', None)
        self._completion_date_time = status.get('CompletionDateTime', None)
        self._submission_date_time = status.get('SubmissionDateTime', None)

        statistics = query_execution.get('Statistics', {})
        self._data_scanned_in_bytes = statistics.get('DataScannedInBytes', None)
        self._execution_time_in_millis = statistics.get('EngineExecutionTimeInMillis', None)

        result_conf = query_execution.get('ResultConfiguration', {})
        self._output_location = result_conf.get('OutputLocation', None)

        encryption_conf = result_conf.get('EncryptionConfiguration', {})
        self._encryption_option = encryption_conf.get('EncryptionOption', None)
        self._kms_key = encryption_conf.get('KmsKey', None)

def _process_rows(self, response):
        result_set = response.get('ResultSet', None)
        if not result_set:
            raise DataError('KeyError `ResultSet`')
        rows = result_set.get('Rows', None)
        if rows is None:
            raise DataError('KeyError `Rows`')
        processed_rows = []
        if len(rows) > 0:
            offset = 1 if not self._next_token and self._is_first_row_column_labels(rows) else 0
            processed_rows = [
                tuple([self._converter.convert(meta.get('Type', None),
                                               row.get('VarCharValue', None))
                       for meta, row in zip(self._meta_data, rows[i].get('Data', []))])
                for i in xrange(offset, len(rows))
            ]
        self._rows.extend(processed_rows)
        self._next_token = response.get('NextToken', None)

def _process_rows(self, response):
        result_set = response.get('ResultSet', None)
        if not result_set:
            raise DataError('KeyError `ResultSet`')
        rows = result_set.get('Rows', None)
        if rows is None:
            raise DataError('KeyError `Rows`')
        processed_rows = []
        if len(rows) > 0:
            offset = 1 if not self._next_token and self._is_first_row_column_labels(rows) else 0
            processed_rows = [
                tuple([self._converter.convert(meta.get('Type', None),
                                               row.get('VarCharValue', None))
                       for meta, row in zip(self._meta_data, rows[i].get('Data', []))])
                for i in xrange(offset, len(rows))
            ]
        self._rows.extend(processed_rows)
        self._next_token = response.get('NextToken', None)

def _process_meta_data(self, response):
        result_set = response.get('ResultSet', None)
        if not result_set:
            raise DataError('KeyError `ResultSet`')
        meta_data = result_set.get('ResultSetMetadata', None)
        if not meta_data:
            raise DataError('KeyError `ResultSetMetadata`')
        column_info = meta_data.get('ColumnInfo', None)
        if column_info is None:
            raise DataError('KeyError `ColumnInfo`')
        self._meta_data = tuple(column_info)

def _parse_output_location(cls, output_location):
        match = cls._pattern_output_location.search(output_location)
        if match:
            return match.group('bucket'), match.group('key')
        else:
            raise DataError('Unknown `output_location` format.')