# (C) Copyright 2015-2016 Hewlett Packard Enterprise Development LP # (C) Copyright 2017-2018 SUSE LLC # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import time import six.moves.urllib.parse as urlparse from monasca_tempest_tests.tests.api import base from monasca_tempest_tests.tests.api import constants from monasca_tempest_tests.tests.api import helpers from tempest.lib.common.utils import data_utils from tempest.lib import decorators from tempest.lib import exceptions from urllib import urlencode NUM_MEASUREMENTS = 100 MIN_REQUIRED_MEASUREMENTS = 2 WAIT_TIME = 30 class TestStatistics(base.BaseMonascaTest): @classmethod def resource_setup(cls): super(TestStatistics, cls).resource_setup() name = data_utils.rand_name('name') key = data_utils.rand_name('key') value1 = data_utils.rand_name('value1') value2 = data_utils.rand_name('value2') cls._test_name = name cls._test_key = key cls._test_value1 = value1 cls._start_timestamp = int(time.time() * 1000) metrics = [ helpers.create_metric(name=name, dimensions={key: value1}, timestamp=cls._start_timestamp, value=1.23), helpers.create_metric(name=name, dimensions={key: value2}, timestamp=cls._start_timestamp + 1000, value=4.56) ] cls.metric_values = [m['value'] for m in metrics] cls.monasca_client.create_metrics(metrics) start_time_iso = helpers.timestamp_to_iso(cls._start_timestamp) query_param = '?name=' + str(name) + '&start_time=' + \ start_time_iso + '&merge_metrics=true' + '&end_time=' + \ helpers.timestamp_to_iso(cls._start_timestamp + 1000 * 2) start_time_iso = helpers.timestamp_to_iso(cls._start_timestamp) cls._start_time_iso = start_time_iso num_measurements = 0 for i in range(constants.MAX_RETRIES): resp, response_body = cls.monasca_client.\ list_measurements(query_param) elements = response_body['elements'] if len(elements) > 0: num_measurements = len(elements[0]['measurements']) if num_measurements >= MIN_REQUIRED_MEASUREMENTS: break time.sleep(constants.RETRY_WAIT_SECS) if num_measurements < MIN_REQUIRED_MEASUREMENTS: assert False, "Required {} measurements, found {}".format(MIN_REQUIRED_MEASUREMENTS, num_measurements) cls._end_timestamp = cls._start_timestamp + 3000 cls._end_time_iso = helpers.timestamp_to_iso(cls._end_timestamp) name2 = data_utils.rand_name("group-by") cls._group_by_metric_name = name2 cls._group_by_end_time_iso = helpers.timestamp_to_iso(cls._start_timestamp + 4000) group_by_metrics = [ helpers.create_metric(name=name2, dimensions={'key1': 'value1', 'key2': 'value5', 'key3': 'value7'}, timestamp=cls._start_timestamp + 1, value=2), helpers.create_metric(name=name2, dimensions={'key1': 'value2', 'key2': 'value5', 'key3': 'value7'}, timestamp=cls._start_timestamp + 1001, value=3), helpers.create_metric(name=name2, dimensions={'key1': 'value3', 'key2': 'value6', 'key3': 'value7'}, timestamp=cls._start_timestamp + 2001, value=5), helpers.create_metric(name=name2, dimensions={'key1': 'value4', 'key2': 'value6', 'key3': 'value8'}, timestamp=cls._start_timestamp + 3001, value=7), ] cls.monasca_client.create_metrics(group_by_metrics) query_param = '?name=' + str(name2) + \ '&start_time=' + start_time_iso + \ '&merge_metrics=true' + \ '&end_time=' + cls._group_by_end_time_iso num_measurements = 0 for i in range(constants.MAX_RETRIES): resp, response_body = cls.monasca_client. \ list_measurements(query_param) elements = response_body['elements'] if len(elements) > 0: num_measurements = len(elements[0]['measurements']) if num_measurements >= len(group_by_metrics): break time.sleep(constants.RETRY_WAIT_SECS) if num_measurements < len(group_by_metrics): assert False, "Required {} measurements, found {}".format(len(group_by_metrics), response_body) @classmethod def resource_cleanup(cls): super(TestStatistics, cls).resource_cleanup() @decorators.attr(type="gate") def test_list_statistics(self): self._test_list_statistic(with_end_time=True) @decorators.attr(type="gate") def test_list_statistics_with_no_end_time(self): self._test_list_statistic(with_end_time=False) def _test_list_statistic(self, with_end_time=True): query_parms = '?name=' + str(self._test_name) + \ '&statistics=' + urlparse.quote('avg,sum,min,max,count') + \ '&start_time=' + str(self._start_time_iso) + \ '&merge_metrics=true' + '&period=100000' if with_end_time is True: query_parms += '&end_time=' + str(self._end_time_iso) resp, response_body = self.monasca_client.list_statistics( query_parms) self.assertEqual(200, resp.status) self.assertTrue(set(['links', 'elements']) == set(response_body)) element = response_body['elements'][0] self._verify_element(element) column = element['columns'] num_statistics_method = 5 statistics = element['statistics'][0] self._verify_column_and_statistics( column, num_statistics_method, statistics, self.metric_values) @decorators.attr(type="gate") @decorators.attr(type=['negative']) def test_list_statistics_with_no_name(self): query_parms = '?merge_metrics=true&statistics=avg&start_time=' + \ str(self._start_time_iso) + '&end_time=' + \ str(self._end_time_iso) self.assertRaises(exceptions.UnprocessableEntity, self.monasca_client.list_statistics, query_parms) @decorators.attr(type="gate") @decorators.attr(type=['negative']) def test_list_statistics_with_no_statistics(self): query_parms = '?name=' + str(self._test_name) + '&start_time=' + str( self._start_time_iso) + '&end_time=' + str(self._end_time_iso) self.assertRaises(exceptions.UnprocessableEntity, self.monasca_client.list_statistics, query_parms) @decorators.attr(type="gate") @decorators.attr(type=['negative']) def test_list_statistics_with_no_start_time(self): query_parms = '?name=' + str(self._test_name) + '&statistics=avg' self.assertRaises(exceptions.UnprocessableEntity, self.monasca_client.list_statistics, query_parms) @decorators.attr(type="gate") @decorators.attr(type=['negative']) def test_list_statistics_with_invalid_statistics(self): query_parms = '?name=' + str(self._test_name) + '&statistics=abc' + \ '&start_time=' + str(self._start_time_iso) + \ '&end_time=' + str(self._end_time_iso) self.assertRaises(exceptions.UnprocessableEntity, self.monasca_client.list_statistics, query_parms) @decorators.attr(type="gate") def test_list_statistics_with_dimensions(self): query_parms = '?name=' + str(self._test_name) + '&statistics=avg' \ '&start_time=' + str(self._start_time_iso) + \ '&end_time=' + str(self._end_time_iso) + \ '&dimensions=' + str(self._test_key) + ':' + \ str(self._test_value1) + '&period=100000' resp, response_body = self.monasca_client.list_statistics( query_parms) self.assertEqual(200, resp.status) dimensions = response_body['elements'][0]['dimensions'] self.assertEqual(dimensions[self._test_key], self._test_value1) @decorators.attr(type="gate") @decorators.attr(type=['negative']) def test_list_statistics_with_end_time_equals_start_time(self): query_parms = '?name=' + str(self._test_name) + \ '&merge_metrics=true&statistics=avg&' \ 'start_time=' + str(self._start_time_iso) + \ '&end_time=' + str(self._start_time_iso) + \ '&period=100000' self.assertRaises(exceptions.BadRequest, self.monasca_client.list_statistics, query_parms) @decorators.attr(type="gate") def test_list_statistics_with_period(self): query_parms = '?name=' + str(self._test_name) + \ '&merge_metrics=true&statistics=avg&' \ 'start_time=' + str(self._start_time_iso) + \ '&end_time=' + str(self._end_time_iso) + \ '&period=1' resp, response_body = self.monasca_client.list_statistics( query_parms) self.assertEqual(200, resp.status) time_diff = self._end_timestamp - self._start_timestamp len_statistics = len(response_body['elements'][0]['statistics']) self.assertEqual(time_diff / 1000, len_statistics) @decorators.attr(type="gate") def test_list_statistics_with_offset_limit(self): start_timestamp = int(time.time() * 1000) name = data_utils.rand_name() metric = [ helpers.create_metric(name=name, timestamp=start_timestamp + 1, dimensions={'key1': 'value-1', 'key2': 'value-1'}, value=1), helpers.create_metric(name=name, timestamp=start_timestamp + 1001, dimensions={'key1': 'value-2', 'key2': 'value-2'}, value=2), helpers.create_metric(name=name, timestamp=start_timestamp + 2001, dimensions={'key1': 'value-3', 'key2': 'value-3'}, value=3), helpers.create_metric(name=name, timestamp=start_timestamp + 3001, dimensions={'key1': 'value-4', 'key2': 'value-4'}, value=4) ] num_metrics = len(metric) self.monasca_client.create_metrics(metric) query_parms = '?name=' + name for i in range(constants.MAX_RETRIES): resp, response_body = self.monasca_client.list_metrics(query_parms) self.assertEqual(200, resp.status) elements = response_body['elements'] if elements and len(elements) == num_metrics: break else: time.sleep(constants.RETRY_WAIT_SECS) self._check_timeout(i, constants.MAX_RETRIES, elements, num_metrics) start_time = helpers.timestamp_to_iso(start_timestamp) end_timestamp = start_timestamp + 4001 end_time = helpers.timestamp_to_iso(end_timestamp) query_parms = '?name=' + name + '&merge_metrics=true&statistics=avg' \ + '&start_time=' + str(start_time) + '&end_time=' + \ str(end_time) + '&period=1' resp, body = self.monasca_client.list_statistics(query_parms) self.assertEqual(200, resp.status) elements = body['elements'][0]['statistics'] first_element = elements[0] query_parms = '?name=' + name + '&merge_metrics=true&statistics=avg'\ + '&start_time=' + str(start_time) + '&end_time=' + \ str(end_time) + '&period=1' + '&limit=' + str(num_metrics) resp, response_body = self.monasca_client.list_statistics( query_parms) self.assertEqual(200, resp.status) elements = response_body['elements'][0]['statistics'] self.assertEqual(num_metrics, len(elements)) self.assertEqual(first_element, elements[0]) for limit in range(1, num_metrics): start_index = 0 params = [('name', name), ('merge_metrics', 'true'), ('statistics', 'avg'), ('start_time', str(start_time)), ('end_time', str(end_time)), ('period', 1), ('limit', limit)] offset = None while True: num_expected_elements = limit if (num_expected_elements + start_index) > num_metrics: num_expected_elements = num_metrics - start_index these_params = list(params) # If not the first call, use the offset returned by the last call if offset: these_params.extend([('offset', str(offset))]) query_parms = '?' + urlencode(these_params) resp, response_body = self.monasca_client.list_statistics(query_parms) self.assertEqual(200, resp.status) if not response_body['elements']: self.fail("No metrics returned") if not response_body['elements'][0]['statistics']: self.fail("No statistics returned") new_elements = response_body['elements'][0]['statistics'] self.assertEqual(num_expected_elements, len(new_elements)) expected_elements = elements[start_index:start_index + limit] self.assertEqual(expected_elements, new_elements) start_index += num_expected_elements if start_index >= num_metrics: break # Get the next set offset = self._get_offset(response_body) @decorators.attr(type="gate") def test_list_statistics_with_group_by_one(self): query_parms = '?name=' + self._group_by_metric_name + \ '&group_by=key2' + \ '&statistics=max,avg,min' + \ '&start_time=' + str(self._start_time_iso) + \ '&end_time=' + str(self._group_by_end_time_iso) resp, response_body = self.monasca_client.list_statistics( query_parms) self.assertEqual(200, resp.status) elements = response_body['elements'] self.assertEqual(len(elements), 2) for statistics in elements: self.assertEqual(1, len(statistics['dimensions'].keys())) self.assertEqual([u'key2'], statistics['dimensions'].keys()) @decorators.attr(type="gate") def test_list_statistics_with_group_by_multiple(self): query_parms = '?name=' + self._group_by_metric_name + \ '&group_by=key2,key3' + \ '&statistics=max,avg,min' + \ '&start_time=' + str(self._start_time_iso) + \ '&end_time=' + str(self._group_by_end_time_iso) resp, response_body = self.monasca_client.list_statistics( query_parms) self.assertEqual(200, resp.status) elements = response_body['elements'] self.assertEqual(len(elements), 3) for statistics in elements: self.assertEqual(2, len(statistics['dimensions'].keys())) self.assertEqual({u'key2', u'key3'}, set(statistics['dimensions'].keys())) @decorators.attr(type="gate") def test_list_statistics_with_group_by_all(self): query_parms = '?name=' + self._group_by_metric_name + \ '&group_by=*' + \ '&statistics=max,avg,min' + \ '&start_time=' + str(self._start_time_iso) + \ '&end_time=' + str(self._group_by_end_time_iso) resp, response_body = self.monasca_client.list_statistics( query_parms) self.assertEqual(200, resp.status) elements = response_body['elements'] self.assertEqual(len(elements), 4) @decorators.attr(type="gate") def test_list_statistics_with_group_by_offset_limit(self): query_parms = '?name=' + str(self._group_by_metric_name) + \ '&group_by=key2' + \ '&statistics=avg,max' + \ '&start_time=' + str(self._start_time_iso) + \ '&end_time=' + str(self._group_by_end_time_iso) + \ '&period=1' resp, response_body = self.monasca_client.list_statistics(query_parms) self.assertEqual(200, resp.status) all_expected_elements = response_body['elements'] for limit in range(1, 4): offset = None for i in range(4 - limit): query_parms = '?name=' + str(self._group_by_metric_name) + \ '&group_by=key2' + \ '&statistics=avg,max' + \ '&start_time=' + str(self._start_time_iso) + \ '&end_time=' + str(self._group_by_end_time_iso) + \ '&period=1' + \ '&limit=' + str(limit) if i > 0: offset = self._get_offset(response_body) query_parms += "&offset=" + offset expected_elements = helpers.get_expected_elements_inner_offset_limit( all_expected_elements, offset, limit, 'statistics') resp, response_body = self.monasca_client.list_statistics(query_parms) self.assertEqual(200, resp.status) self.assertEqual(expected_elements, response_body['elements']) @decorators.attr(type="gate") def test_list_statistics_with_long_start_time(self): query_parms = '?name=' + str(self._test_name) + \ '&statistics=' + urlparse.quote('avg,sum,min,max,count') + \ '&start_time=' + "2017-01-01T00:00:00.00Z" + \ '&end_time=' + str(self._end_time_iso) + \ '&merge_metrics=true' + '&period=100000' resp, response_body = self.monasca_client.list_statistics( query_parms) self.assertEqual(200, resp.status) self.assertTrue(set(['links', 'elements']) == set(response_body)) element = response_body['elements'][0] self._verify_element(element) column = element['columns'] num_statistics_method = 5 statistics = element['statistics'][0] self._verify_column_and_statistics( column, num_statistics_method, statistics, self.metric_values) @decorators.attr(type="gate") @decorators.attr(type=['negative']) def test_list_statistics_with_no_merge_metrics(self): key = data_utils.rand_name('key') value = data_utils.rand_name('value') metric3 = helpers.create_metric( name=self._test_name, dimensions={key: value}, timestamp=self._start_timestamp + 2000) self.monasca_client.create_metrics(metric3) query_param = '?name=' + str(self._test_name) + '&start_time=' + \ self._start_time_iso + '&end_time=' + helpers.\ timestamp_to_iso(self._start_timestamp + 1000 * 4) + \ '&merge_metrics=True' for i in range(constants.MAX_RETRIES): resp, response_body = self.monasca_client.\ list_measurements(query_param) elements = response_body['elements'] for element in elements: if str(element['name']) == self._test_name and len( element['measurements']) == 3: end_time_iso = helpers.timestamp_to_iso( self._start_timestamp + 1000 * 4) query_parms = '?name=' + str(self._test_name) + \ '&statistics=avg' + '&start_time=' + \ str(self._start_time_iso) + '&end_time=' +\ str(end_time_iso) + '&period=100000' self.assertRaises(exceptions.Conflict, self.monasca_client.list_statistics, query_parms) return time.sleep(constants.RETRY_WAIT_SECS) self._check_timeout(i, constants.MAX_RETRIES, elements, 3) @decorators.attr(type="gate") @decorators.attr(type=['negative']) def test_list_statistics_with_name_exceeds_max_length(self): long_name = "x" * (constants.MAX_LIST_STATISTICS_NAME_LENGTH + 1) query_parms = '?name=' + str(long_name) + '&merge_metrics=true' + \ '&start_time=' + str(self._start_time_iso) + \ '&end_time=' + str(self._end_time_iso) self.assertRaises(exceptions.UnprocessableEntity, self.monasca_client.list_statistics, query_parms) @decorators.attr(type="gate") def test_list_statistics_response_body_statistic_result_type(self): query_parms = '?name=' + str(self._test_name) + '&period=100000' + \ '&statistics=avg' + '&merge_metrics=true' + \ '&start_time=' + str(self._start_time_iso) + \ '&end_time=' + str(self._end_time_iso) resp, response_body = self.monasca_client.list_statistics( query_parms) self.assertEqual(200, resp.status) element = response_body['elements'][0] statistic = element['statistics'] statistic_result_type = type(statistic[0][1]) self.assertEqual(statistic_result_type, float) def _verify_element(self, element): self.assertTrue(set(['id', 'name', 'dimensions', 'columns', 'statistics']) == set(element)) self.assertTrue(type(element['id']) is unicode) self.assertTrue(element['id'] is not None) self.assertTrue(type(element['name']) is unicode) self.assertTrue(type(element['dimensions']) is dict) self.assertEqual(len(element['dimensions']), 0) self.assertTrue(type(element['columns']) is list) self.assertTrue(type(element['statistics']) is list) self.assertEqual(element['name'], self._test_name) def _verify_column_and_statistics( self, column, num_statistics_method, statistics, values): self.assertTrue(type(column) is list) self.assertTrue(type(statistics) is list) self.assertEqual(len(column), num_statistics_method + 1) self.assertEqual(column[0], 'timestamp') for i, method in enumerate(column): if method == 'avg': self.assertAlmostEqual(statistics[i], float(sum(values) / len(values))) elif method == 'max': self.assertEqual(statistics[i], max(values)) elif method == 'min': self.assertEqual(statistics[i], min(values)) elif method == 'sum': self.assertAlmostEqual(statistics[i], sum(values)) elif method == 'count': self.assertEqual(statistics[i], len(values)) def _check_timeout(self, timer, max_retries, elements, expect_num_elements): if timer == max_retries - 1: error_msg = ("Failed: timeout on waiting for metrics: {} elements " "are needed. Current number of elements = {}").\ format(expect_num_elements, len(elements)) raise self.fail(error_msg)