diff options
Diffstat (limited to 'synapse/metrics/__init__.py')
-rw-r--r-- | synapse/metrics/__init__.py | 115 |
1 files changed, 68 insertions, 47 deletions
diff --git a/synapse/metrics/__init__.py b/synapse/metrics/__init__.py index a1f7ca3449..b8d2a8e8a9 100644 --- a/synapse/metrics/__init__.py +++ b/synapse/metrics/__init__.py @@ -15,6 +15,7 @@ import functools import gc +import itertools import logging import os import platform @@ -27,8 +28,8 @@ from prometheus_client import Counter, Gauge, Histogram from prometheus_client.core import ( REGISTRY, CounterMetricFamily, + GaugeHistogramMetricFamily, GaugeMetricFamily, - HistogramMetricFamily, ) from twisted.internet import reactor @@ -46,7 +47,7 @@ logger = logging.getLogger(__name__) METRICS_PREFIX = "/_synapse/metrics" running_on_pypy = platform.python_implementation() == "PyPy" -all_gauges = {} # type: Dict[str, Union[LaterGauge, InFlightGauge, BucketCollector]] +all_gauges = {} # type: Dict[str, Union[LaterGauge, InFlightGauge]] HAVE_PROC_SELF_STAT = os.path.exists("/proc/self/stat") @@ -205,63 +206,83 @@ class InFlightGauge: all_gauges[self.name] = self -@attr.s(slots=True, hash=True) -class BucketCollector: - """ - Like a Histogram, but allows buckets to be point-in-time instead of - incrementally added to. +class GaugeBucketCollector: + """Like a Histogram, but the buckets are Gauges which are updated atomically. - Args: - name (str): Base name of metric to be exported to Prometheus. - data_collector (callable -> dict): A synchronous callable that - returns a dict mapping bucket to number of items in the - bucket. If these buckets are not the same as the buckets - given to this class, they will be remapped into them. - buckets (list[float]): List of floats/ints of the buckets to - give to Prometheus. +Inf is ignored, if given. + The data is updated by calling `update_data` with an iterable of measurements. + We assume that the data is updated less frequently than it is reported to + Prometheus, and optimise for that case. """ - name = attr.ib() - data_collector = attr.ib() - buckets = attr.ib() + __slots__ = ("_name", "_documentation", "_bucket_bounds", "_metric") - def collect(self): + def __init__( + self, + name: str, + documentation: str, + buckets: Iterable[float], + registry=REGISTRY, + ): + """ + Args: + name: base name of metric to be exported to Prometheus. (a _bucket suffix + will be added.) + documentation: help text for the metric + buckets: The top bounds of the buckets to report + registry: metric registry to register with + """ + self._name = name + self._documentation = documentation - # Fetch the data -- this must be synchronous! - data = self.data_collector() + # the tops of the buckets + self._bucket_bounds = [float(b) for b in buckets] + if self._bucket_bounds != sorted(self._bucket_bounds): + raise ValueError("Buckets not in sorted order") - buckets = {} # type: Dict[float, int] + if self._bucket_bounds[-1] != float("inf"): + self._bucket_bounds.append(float("inf")) - res = [] - for x in data.keys(): - for i, bound in enumerate(self.buckets): - if x <= bound: - buckets[bound] = buckets.get(bound, 0) + data[x] + self._metric = self._values_to_metric([]) + registry.register(self) - for i in self.buckets: - res.append([str(i), buckets.get(i, 0)]) + def collect(self): + yield self._metric - res.append(["+Inf", sum(data.values())]) + def update_data(self, values: Iterable[float]): + """Update the data to be reported by the metric - metric = HistogramMetricFamily( - self.name, "", buckets=res, sum_value=sum(x * y for x, y in data.items()) + The existing data is cleared, and each measurement in the input is assigned + to the relevant bucket. + """ + self._metric = self._values_to_metric(values) + + def _values_to_metric(self, values: Iterable[float]) -> GaugeHistogramMetricFamily: + total = 0.0 + bucket_values = [0 for _ in self._bucket_bounds] + + for v in values: + # assign each value to a bucket + for i, bound in enumerate(self._bucket_bounds): + if v <= bound: + bucket_values[i] += 1 + break + + # ... and increment the sum + total += v + + # now, aggregate the bucket values so that they count the number of entries in + # that bucket or below. + accumulated_values = itertools.accumulate(bucket_values) + + return GaugeHistogramMetricFamily( + self._name, + self._documentation, + buckets=list( + zip((str(b) for b in self._bucket_bounds), accumulated_values) + ), + gsum_value=total, ) - yield metric - - def __attrs_post_init__(self): - self.buckets = [float(x) for x in self.buckets if x != "+Inf"] - if self.buckets != sorted(self.buckets): - raise ValueError("Buckets not sorted") - - self.buckets = tuple(self.buckets) - - if self.name in all_gauges.keys(): - logger.warning("%s already registered, reregistering" % (self.name,)) - REGISTRY.unregister(all_gauges.pop(self.name)) - - REGISTRY.register(self) - all_gauges[self.name] = self # |