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'])