def save_sample(self, metric, value, timestamp=None,
dimensions=None, hostname=None, device_name=None):
"""Save a simple sample, evict old values if needed.
"""
if timestamp is None:
timestamp = time.time()
if metric not in self._sample_store:
raise exceptions.CheckException("Saving a sample for an undefined metric: %s" % metric)
try:
value = util.cast_metric_val(value)
except ValueError as ve:
raise exceptions.NaN(ve)
# Data eviction rules
key = (tuple(sorted(dimensions.items())), device_name)
if self.is_gauge(metric):
self._sample_store[metric][key] = ((timestamp, value, hostname, device_name), )
elif self.is_counter(metric):
if self._sample_store[metric].get(key) is None:
self._sample_store[metric][key] = [(timestamp, value, hostname, device_name)]
else:
self._sample_store[metric][key] = self._sample_store[metric][key][-1:] + \
[(timestamp, value, hostname, device_name)]
else:
raise exceptions.CheckException("%s must be either gauge or counter, skipping sample at %s" %
(metric, time.ctime(timestamp)))
if self.is_gauge(metric):
# store[metric][dimensions] = (ts, val) - only 1 value allowed
assert len(self._sample_store[metric][key]) == 1, self._sample_store[metric]
elif self.is_counter(metric):
assert len(self._sample_store[metric][key]) in (1, 2), self._sample_store[metric]
def __init__(self, check, prefix=None, default_mapping=None):
"""C'tor
:param check: Target check instance
"""
self._check = check
self._prefix = prefix
self._groups = {}
self._metric_map = {}
self._dimension_map = {}
self._metric_cache = {}
self._grp_metric_map = {}
self._grp_dimension_map = {}
self._grp_metric_cache = {}
self._metric_to_group = {}
for inst in self._check.instances:
iname = inst['name']
mappings = inst.get('mapping', default_mapping)
if mappings:
# build global name filter and rate/gauge assignment
self._metric_map[iname] = mappings
self._metric_cache[iname] = {}
# build global dimension map
self._dimension_map[
iname] = DynamicCheckHelper._build_dimension_map(mappings)
# check if groups are used
groups = mappings.get('groups')
self._metric_to_group[iname] = {}
self._groups[iname] = []
if groups:
self._groups[iname] = groups.keys()
self._grp_metric_map[iname] = {}
self._grp_metric_cache[iname] = {}
self._grp_dimension_map[iname] = {}
for grp, gspec in groups.items():
self._grp_metric_map[iname][grp] = gspec
self._grp_metric_cache[iname][grp] = {}
self._grp_dimension_map[iname][
grp] = DynamicCheckHelper._build_dimension_map(
gspec)
# add the global mappings as pseudo group, so that it is considered when searching for metrics
self._groups[iname].append(
DynamicCheckHelper.DEFAULT_GROUP)
self._grp_metric_map[iname][
DynamicCheckHelper.
DEFAULT_GROUP] = self._metric_map[iname]
self._grp_metric_cache[iname][
DynamicCheckHelper.
DEFAULT_GROUP] = self._metric_cache[iname]
self._grp_dimension_map[iname][
DynamicCheckHelper.
DEFAULT_GROUP] = self._dimension_map[iname]
else:
raise exceptions.CheckException(
'instance %s is not supported: no element "mapping" found!',
iname)