def get_state(self, duration):
'''Run any necessary calculations on the data collected from the logs
and return a list of metric objects.'''
if len(self.waits) > 0:
return [
MetricObject("wait.min", min(self.waits)),
MetricObject("wait.max", max(self.waits)),
MetricObject("wait.mean", stats_helper.find_mean(self.waits)),
MetricObject("wait.median", stats_helper.find_median(self.waits)),
MetricObject("wait.90th_percentile", stats_helper.find_percentile(self.waits, 90)),
MetricObject("wait.95th_percentile", stats_helper.find_percentile(self.waits, 95)),
MetricObject("connect.min", min(self.connects)),
MetricObject("connect.max", max(self.connects)),
MetricObject("connect.mean", stats_helper.find_mean(self.connects)),
MetricObject("connect.median", stats_helper.find_median(self.connects)),
MetricObject("connect.90th_percentile", stats_helper.find_percentile(self.connects, 90)),
MetricObject("connect.95th_percentile", stats_helper.find_percentile(self.connects, 95)),
MetricObject("service.min", min(self.services)),
MetricObject("service.max", max(self.services)),
MetricObject("service.mean", stats_helper.find_mean(self.services)),
MetricObject("service.median", stats_helper.find_median(self.services)),
MetricObject("service.90th_percentile", stats_helper.find_percentile(self.services, 90)),
MetricObject("service.95th_percentile", stats_helper.find_percentile(self.services, 95))
]
else:
return []
def get_state(self, duration):
'''Run any necessary calculations on the data collected from the logs
and return a list of metric objects.'''
self.duration = duration
metrics = []
# loop all the collected timers
for time_name in self.times:
values = self.times[time_name]['values']
unit = self.times[time_name]['unit']
# add counter
if self.duration > 0:
metrics.append(
MetricObject(time_name + '.count',
len(values) / self.duration))
# calculate statistical values
metrics.append(
MetricObject(time_name + '.mean',
stats_helper.find_mean(values), unit))
metrics.append(
MetricObject(time_name + '.median',
stats_helper.find_median(values), unit))
metrics += [
MetricObject(
'%s.%sth_percentile' % (time_name, percentile),
stats_helper.find_percentile(values, int(percentile)),
unit) for percentile in self.percentiles
]
return metrics
def get_state(self, duration):
'''Run any necessary calculations on the data collected from the logs
and return a list of metric objects.'''
duration = float(duration)
metrics = []
if duration > 0 and not self.raw_data:
metrics += [
MetricObject(counter, self.counts[counter] / duration)
for counter in self.counts
]
elif self.raw_data:
metrics += [
MetricObject(counter, self.counts[counter])
for counter in self.counts
]
for time_name in self.times:
values = self.times[time_name]['values']
unit = self.times[time_name]['unit']
metrics.append(
MetricObject(time_name + '.mean',
stats_helper.find_mean(values), unit))
metrics.append(
MetricObject(time_name + '.median',
stats_helper.find_median(values), unit))
metrics += [
MetricObject(
'%s.%sth_percentile' % (time_name, percentile),
stats_helper.find_percentile(values, int(percentile)),
unit) for percentile in self.percentiles
]
return metrics
def get_state(self, duration):
'''Run any necessary calculations on the data collected from the logs
and return a list of metric objects.'''
metrics = []
if duration > 0:
metrics += [MetricObject(counter, self.counts[counter]/duration) for counter in self.counts]
for time_name in self.times:
values = self.times[time_name]['values']
unit = self.times[time_name]['unit']
metrics.append(MetricObject(time_name+'.mean', stats_helper.find_mean(values), unit))
metrics.append(MetricObject(time_name+'.median', stats_helper.find_median(values), unit))
metrics += [MetricObject('%s.%sth_percentile' % (time_name,percentile), stats_helper.find_percentile(values,int(percentile)), unit) for percentile in self.percentiles]
return metrics
