def execute(self, query, rid=None):
# Request data given a simple target expression.
data = BaseStatsHandler(rid).get_stats(metric=query.target,
start=self.start,
stop=self.stop)
# If response is empty, then data is absent for the given interval.
if not len(data):
log.warning('No datapoints for %s.%s', rid, query.target)
return None, None
# Check whether the query to InfluxDB returned multiple series.
if len(data) > 1:
log.error('Got multiple series for %s.%s', rid, query.target)
raise methods.MultipleSeriesReturnedError()
# Ensure requested and returned measurements/columns match.
data = data.values()[0]
target = query.target.split('.')
if data['measurement'] != target[0] or data['column'] != target[-1]:
log.error('Got %s while expecting %s', data['name'], query.target)
raise methods.RequestedTargetMismatchError()
# Sanitize datapoints.
datapoints = [val for val, _ in data['datapoints'] if val is not None]
# Compare against the threshold and compute retval.
return methods.compute(query.operator, query.aggregation, datapoints,
query.threshold)
def execute(self, query, rid=None):
# Request data given a simple target expression.
data = hrs.MultiHandler(rid).get_data(query.target, start=self.window)
# No data ever reached Graphite? Is the whisper file missing?
if not len(data):
log.warning('Empty response for %s.%s', rid, query.target)
raise methods.EmptyResponseReturnedError()
# Check whether the query to Graphite returned multiple series. This
# should never occur actually, since the query's target belongs to a
# pre-defined list of allowed targets which are quaranteed to return
# a single series.
if len(data) > 1:
log.warning('Got multiple series for %s.%s', rid, query.target)
raise methods.MultipleSeriesReturnedError()
# Ensure requested and returned targets match.
data = data[0]
target = data['_requested_target']
if target != query.target:
log.warning('Got %s while expecting %s', target, query.target)
raise methods.RequestedTargetMismatchError()
# Clean datapoints of None values.
datapoints = [val for val, _ in data['datapoints'] if val is not None]
if not datapoints:
log.warning('No datapoints for %s.%s', rid, query.target)
return None, None
# Compare against the threshold and compute retval.
triggered, retval = methods.compute(query.operator, query.aggregation,
datapoints, query.threshold)
return triggered, retval
def execute(self, query, rid=None):
# Request data given a simple target expression.
from mist.api.models import Machine
m = Machine.objects.get(id=rid)
data = fdb_methods.get_stats(machine=m,
start=self.start,
stop=self.stop,
metrics=[
"fetch(\"{id}." + query.target +
"\", start=\"{start}\"" +
", stop=\"{stop}\"" +
", step=\"{step}\")"])
# No data ever reached Graphite? Is the whisper file missing?
if not len(data):
log.warning('Empty response for %s.%s', rid, query.target)
raise methods.EmptyResponseReturnedError()
# Check whether the query to Graphite returned multiple series. This
# should never occur actually, since the query's target belongs to a
# pre-defined list of allowed targets which are quaranteed to return
# a single series.
if len(data) > 1:
log.warning('Got multiple series for %s.%s', rid, query.target)
raise methods.MultipleSeriesReturnedError()
# Ensure requested and returned targets match.
target = list(data.keys())[0]
data = list(data.values())[0]
if target != query.target:
log.warning('Got %s while expecting %s', target, query.target)
raise methods.RequestedTargetMismatchError()
# Clean datapoints of None values.
datapoints = [val for val, _ in data['datapoints'] if val is not None]
if not datapoints:
log.warning('No datapoints for %s.%s', rid, query.target)
return None, None
# Compare against the threshold and compute retval.
return methods.compute(query.operator, query.aggregation, datapoints,
query.threshold)