def test_valid_metrics_by_components(self): metrics = [{ "name": "name1", "dimensions": { "key1": "value1", "key2": "value2" }, "timestamp": 1405630174123, "value": 1.0 }, { "name": "name2", "dimensions": { "key1": "value1", "key2": "value2" }, "value_meta": { "key1": "value1", "key2": "value2" }, "timestamp": 1405630174123, "value": 2.0 }] for i in six.moves.range(len(metrics)): metric_validator.validate_name(metrics[i]['name']) metric_validator.validate_value(metrics[i]['value']) metric_validator.validate_timestamp(metrics[i]['timestamp']) if 'dimensions' in metrics[i]: metric_validator.validate_dimensions(metrics[i]['dimensions']) if 'value_meta' in metrics[i]: metric_validator.validate_value_meta(metrics[i]['value_meta'])
def submit_metric(self, name, value, metric_class, dimensions=None, delegated_tenant=None, hostname=None, device_name=None, value_meta=None, timestamp=None, sample_rate=1): # validate dimensions, name, value and value meta if dimensions: metric_validator.validate_dimensions(dimensions) metric_validator.validate_name(name) metric_validator.validate_value(value) if value_meta: metric_validator.validate_value_meta(value_meta) hostname_to_post = self.get_hostname_to_post(hostname) tenant_to_post = delegated_tenant or self.global_delegated_tenant dimensions_copy = dimensions.copy() if 'hostname' not in dimensions_copy and hostname_to_post: dimensions_copy.update({'hostname': hostname_to_post}) # TODO(joe): Shouldn't device_name be added to dimensions in the check # plugin? Why is it special cased through so many layers? if device_name: dimensions_copy.update({'device': device_name}) # TODO(joe): Decide if hostname_to_post and device_name are necessary # for the context tuple context = (name, tuple(dimensions_copy.items()), tenant_to_post, hostname_to_post, device_name) if context not in self.metrics: self.metrics[context] = metric_class(name, dimensions_copy, tenant=tenant_to_post) cur_time = time() if timestamp is not None: if cur_time - int(timestamp) > self.recent_point_threshold: log.debug( "Discarding {0} - ts = {1}, current ts = {2} ".format( name, timestamp, cur_time)) self.num_discarded_old_points += 1 return else: timestamp = cur_time self.metrics[context].value_meta = value_meta self.metrics[context].sample(value, sample_rate, timestamp)
def submit_metric(self, name, value, metric_class, dimensions=None, delegated_tenant=None, hostname=None, device_name=None, value_meta=None, timestamp=None, sample_rate=1): # validate dimensions, name, value and value meta if dimensions: metric_validator.validate_dimensions(dimensions) metric_validator.validate_name(name) metric_validator.validate_value(value) if value_meta: metric_validator.validate_value_meta(value_meta) hostname_to_post = self.get_hostname_to_post(hostname) tenant_to_post = delegated_tenant or self.global_delegated_tenant dimensions_copy = dimensions.copy() if 'hostname' not in dimensions_copy and hostname_to_post: dimensions_copy.update({'hostname': hostname_to_post}) # TODO(joe): Shouldn't device_name be added to dimensions in the check # plugin? Why is it special cased through so many layers? if device_name: dimensions_copy.update({'device': device_name}) # TODO(joe): Decide if hostname_to_post and device_name are necessary # for the context tuple context = (name, tuple(dimensions_copy.items()), tenant_to_post, hostname_to_post, device_name) if context not in self.metrics: self.metrics[context] = metric_class(name, dimensions_copy, tenant=tenant_to_post) cur_time = time() if timestamp is not None: if cur_time - int(timestamp) > self.recent_point_threshold: log.debug( "Discarding {0} - ts = {1}, current ts = {2} ".format(name, timestamp, cur_time)) self.num_discarded_old_points += 1 return else: timestamp = cur_time self.metrics[context].value_meta = value_meta self.metrics[context].sample(value, sample_rate, timestamp)
def test_valid_metrics_by_components(self): metrics = [ {"name": "name1", "dimensions": {"key1": "value1", "key2": "value2"}, "timestamp": 1405630174123, "value": 1.0}, {"name": "name2", "dimensions": {"key1": "value1", "key2": "value2"}, "value_meta": {"key1": "value1", "key2": "value2"}, "timestamp": 1405630174123, "value": 2.0} ] for i in six.moves.range(len(metrics)): metric_validator.validate_name(metrics[i]['name']) metric_validator.validate_value(metrics[i]['value']) metric_validator.validate_timestamp(metrics[i]['timestamp']) if 'dimensions' in metrics[i]: metric_validator.validate_dimensions(metrics[i]['dimensions']) if 'value_meta' in metrics[i]: metric_validator.validate_value_meta(metrics[i]['value_meta'])