def _buffered_plaintext_send_metric(self, base_name, name, value, t, force=False):
self.batch_count += 1
self.batch_buffer += "{0}.{1} {2} {3}\n".format(
base_name, name, value, now())
# Check if we reach batch size and send
if self.batch_count >= self.batch_size:
self._send_plaintext()
def _buffered_plaintext_send_metric(self, base_name, name, value, t, force=False):
self.batch_count += 1
self.batch_buffer += "{0}.{1} {2} {3}\n".format(
base_name, name, value, now())
# Check if we reach batch size and send
if self.batch_count >= self.batch_size:
self._send_plaintext()
def prepare_metric(self, name, type, metric, keys, snapshot_keys=[]):
base_name = re.sub(r"\s+", "_", name)
if self.prefix:
base_name = "{0}.{1}".format(self.prefix, base_name)
time = now()
type = "gauge" if type != "counter" else "counter"
if self.filters:
keys = filter(lambda key: key in self.filters, keys)
snapshot_keys = filter(lambda key: key in self.filters, snapshot_keys)
if self.excludes:
keys = filter(lambda key: key not in self.excludes, keys)
snapshot_keys = filter(lambda key: key in self.excludes, snapshot_keys)
for name in keys:
value = getattr(metric, name)
yield type, {
"name": "{0}.{1}".format(base_name, name),
"source": self.source,
"time": time,
"value": value
}
if hasattr(metric, 'snapshot'):
snapshot = metric.snapshot
for name in snapshot_keys:
value = getattr(snapshot, name)
yield type, {
"name": "{0}.{1}".format(base_name, name),
"source": self.source,
"time": time,
"value": value
}
def __init__(self, average_class=EWMA):
self.counter = AtomicLong(0)
self.start_time = now()
self.last_tick = AtomicLong(self.start_time)
self.interval = EWMA.INTERVAL
self.m1_rate = EWMA.m1()
self.m5_rate = EWMA.m5()
self.m15_rate = EWMA.m15()
def send_metric(self, name, type, metric, keys, snapshot_keys=None):
if snapshot_keys is None:
snapshot_keys = []
base_name = re.sub(r"\s+", "_", name)
if self.prefix:
base_name = "{0}.{1}".format(self.prefix, base_name)
for name in keys:
value = True
value = getattr(metric, name)
self._buffered_send_metric(base_name, name, value, now())
if hasattr(metric, 'snapshot'):
snapshot = metric.snapshot
for name in snapshot_keys:
value = True
value = getattr(snapshot, name)
self._buffered_send_metric(base_name, name, value, now())
def __init__(self, average_class=EWMA):
self.counter = AtomicLong(0)
self.start_time = now()
self.last_tick = AtomicLong(self.start_time)
self.interval = EWMA.INTERVAL
self.m1_rate = EWMA.m1()
self.m5_rate = EWMA.m5()
self.m15_rate = EWMA.m15()
def send_metric(self, name, type, metric, keys, snapshot_keys=None):
if snapshot_keys is None:
snapshot_keys = []
base_name = re.sub(r"\s+", "_", name)
if self.prefix:
base_name = "{0}.{1}".format(self.prefix, base_name)
for name in keys:
value = True
value = getattr(metric, name)
self._buffered_send_metric(base_name, name, value, now())
if hasattr(metric, 'snapshot'):
snapshot = metric.snapshot
for name in snapshot_keys:
value = True
value = getattr(snapshot, name)
self._buffered_send_metric(base_name, name, value, now())
def update(self, value, timestamp=None):
if timestamp is None:
timestamp = now()
self.rescale_if_necessary()
with self.lock:
try:
priority = self.weight(timestamp) / random.random()
except (OverflowError, ZeroDivisionError):
priority = sys.float_info.max
if len(self.values) < self.reservoir_size:
heapq.heappush(self.values, (priority, value))
else:
heapq.heappushpop(self.values, (priority, value))
def update(self, value, timestamp=None):
if timestamp is None:
timestamp = now()
self.rescale_if_necessary()
with self.lock:
try:
priority = self.weight(timestamp) / random.random()
except (OverflowError, ZeroDivisionError):
priority = sys.float_info.max
if len(self.values) < self.reservoir_size:
heapq.heappush(self.values, (priority, value))
else:
heapq.heappushpop(self.values, (priority, value))
def rescale_if_necessary(self):
time = now()
next_time = self.next_scale_time.value
if time > next_time:
self.rescale(time, next_time)
def clear(self):
with self.lock:
self.values = []
self.start_time = now()
self.next_scale_time.value = \
self.start_time + self.rescale_threshold
def rescale_if_necessary(self):
time = now()
next_time = self.next_scale_time.value
if time > next_time:
self.rescale(time, next_time)
def clear(self):
with self.lock:
self.values = []
self.start_time = now()
self.next_scale_time.value = self.start_time + self.rescale_threshold