def treat_metric(self, metric_name, metric_type, value, sampling):
metric_name += "|" + metric_type
if metric_type == "ms":
if sampling is not None:
raise ValueError(
"Invalid sampling for ms: `%d`, should be none"
% sampling)
self.times[metric_name] = storage.Measure(
utils.dt_in_unix_ns(utils.utcnow()), value)
elif metric_type == "g":
if sampling is not None:
raise ValueError(
"Invalid sampling for g: `%d`, should be none"
% sampling)
self.gauges[metric_name] = storage.Measure(
utils.dt_in_unix_ns(utils.utcnow()), value)
elif metric_type == "c":
sampling = 1 if sampling is None else sampling
if metric_name in self.counters:
current_value = self.counters[metric_name].value
else:
current_value = 0
self.counters[metric_name] = storage.Measure(
utils.dt_in_unix_ns(utils.utcnow()),
current_value + (value * (1 / sampling)))
# TODO(jd) Support "set" type
# elif metric_type == "s":
# pass
else:
raise ValueError("Unknown metric type `%s'" % metric_type)
def treat_metric(self, host, metric_name, metric_type,
value):
"""Collectd.
Statistics in collectd consist of a value list. A value list includes:
Values, can be one of:
Derive: used for values where a change in the value since it's last
been read is of interest. Can be used to calculate and store a rate.
Counter: similar to derive values, but take the possibility of a
counter wrap around into consideration.
Gauge: used for values that are stored as is.
Absolute: used for counters that are reset after reading.
"""
if metric_type == "absolute":
if host not in self.absolute:
self.absolute[host] = {}
self.absolute[host][metric_name] = incoming.Measure(
utils.dt_in_unix_ns(utils.utcnow()), value)
elif metric_type == "gauge":
if host not in self.gauges:
self.gauges[host] = {}
self.gauges[host][metric_name] = incoming.Measure(
utils.dt_in_unix_ns(utils.utcnow()), value)
elif metric_type == "counter" or metric_type == "derive":
if host not in self.counters:
self.counters[host] = {}
self.counters[host][metric_name] = incoming.Measure(
utils.dt_in_unix_ns(utils.utcnow()), value)
else:
raise ValueError("Unknown metric type '%s'" % metric_type)
def todo():
metric = index.create_metric(
uuid.uuid4(),
creator=conf.creator,
archive_policy_name=conf.archive_policy_name)
for _ in six.moves.range(conf.batch_of_measures):
measures = [
incoming.Measure(
utils.dt_in_unix_ns(utils.utcnow()), random.random())
for __ in six.moves.range(conf.measures_per_batch)]
instore.add_measures(metric, measures)
def on_message(self, event):
json_message = ujson.loads(event.message.body)
timestamp = utils.dt_in_unix_ns(utils.utcnow())
measures_by_host_and_name = sorted(
((message["host"], self._serialize_identifier(index,
message), value)
for message in json_message
for index, value in enumerate(message["values"])))
for (host,
name), values in itertools.groupby(measures_by_host_and_name,
key=lambda x: x[0:2]):
measures = (incoming.Measure(timestamp, v[2]) for v in values)
self.processor.add_measures(host, name, measures)
def treat_metric(self, resource_id, metric_name, metric_type, value,
sampling):
if metric_type == "absolute":
if sampling is not None:
raise ValueError(
"Invalid sampling for ms: `%d`, should be none" % sampling)
if resource_id not in self.absolute:
self.absolute[resource_id] = collections.defaultdict(list)
self.absolute[resource_id][metric_name] = storage.Measure(
utils.dt_in_unix_ns(utils.utcnow()), value)
elif metric_type == "guage":
if sampling is not None:
raise ValueError(
"Invalid sampling for g: `%d`, should be none" % sampling)
if resource_id not in self.gauges:
self.gauges[resource_id] = collections.defaultdict(list)
self.gauges[resource_id][metric_name] = storage.Measure(
utils.dt_in_unix_ns(utils.utcnow()), value)
elif metric_type == "counter":
sampling = 1 if sampling is None else sampling
if resource_id not in self.counters:
self.counters[resource_id] = collections.defaultdict(list)
if metric_name in self.counters[resource_id]:
current_value = self.counters[resource_id][metric_name].value
else:
current_value = 0
self.counters[resource_id][metric_name] = storage.Measure(
utils.dt_in_unix_ns(utils.utcnow()),
current_value + (value * (1 / sampling)))
# TODO(jd) Support "set" type
# elif metric_type == "s":
# pass
else:
raise ValueError("Unknown metric type `%s'" % metric_type)
def _test_create_metric_and_data(self, data, spacing):
metric = storage.Metric(uuid.uuid4(), self.archive_policies['medium'])
start_time = utils.datetime_utc(2014, 1, 1, 12)
incr = datetime.timedelta(seconds=spacing)
measures = [
storage.Measure(utils.dt_in_unix_ns(start_time + incr * n), val)
for n, val in enumerate(data)
]
self.index.create_metric(metric.id, str(uuid.uuid4()), 'medium')
self.storage.incoming.add_measures(metric, measures)
metrics = tests_utils.list_all_incoming_metrics(self.storage.incoming)
self.storage.process_background_tasks(self.index, metrics, sync=True)
return metric