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synced 2024-12-27 05:29:24 -05:00
Rewrite BucketCollector
This was a bit unweildy for what I wanted: in particular, I wanted to assign each measurement straight into a bucket, rather than storing an intermediate Counter which didn't do any bucketing at all. I've replaced it with something that is hopefully a bit easier to use. (I'm not entirely sure what the difference between a HistogramMetricFamily and a GaugeHistogramMetricFamily is, but given our counters can go down as well as up the latter *sounds* more accurate?)
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@ -15,6 +15,7 @@
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import functools
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import gc
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import itertools
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import logging
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import os
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import platform
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@ -27,8 +28,8 @@ from prometheus_client import Counter, Gauge, Histogram
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from prometheus_client.core import (
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REGISTRY,
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CounterMetricFamily,
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GaugeHistogramMetricFamily,
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GaugeMetricFamily,
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HistogramMetricFamily,
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)
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from twisted.internet import reactor
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@ -46,7 +47,7 @@ logger = logging.getLogger(__name__)
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METRICS_PREFIX = "/_synapse/metrics"
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running_on_pypy = platform.python_implementation() == "PyPy"
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all_gauges = {} # type: Dict[str, Union[LaterGauge, InFlightGauge, BucketCollector]]
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all_gauges = {} # type: Dict[str, Union[LaterGauge, InFlightGauge]]
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HAVE_PROC_SELF_STAT = os.path.exists("/proc/self/stat")
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@ -205,63 +206,83 @@ class InFlightGauge:
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all_gauges[self.name] = self
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@attr.s(slots=True, hash=True)
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class BucketCollector:
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"""
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Like a Histogram, but allows buckets to be point-in-time instead of
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incrementally added to.
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class GaugeBucketCollector:
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"""Like a Histogram, but the buckets are Gauges which are updated atomically.
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Args:
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name (str): Base name of metric to be exported to Prometheus.
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data_collector (callable -> dict): A synchronous callable that
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returns a dict mapping bucket to number of items in the
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bucket. If these buckets are not the same as the buckets
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given to this class, they will be remapped into them.
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buckets (list[float]): List of floats/ints of the buckets to
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give to Prometheus. +Inf is ignored, if given.
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The data is updated by calling `update_data` with an iterable of measurements.
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We assume that the data is updated less frequently than it is reported to
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Prometheus, and optimise for that case.
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"""
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name = attr.ib()
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data_collector = attr.ib()
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buckets = attr.ib()
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__slots__ = ("_name", "_documentation", "_bucket_bounds", "_metric")
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def __init__(
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self,
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name: str,
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documentation: str,
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buckets: Iterable[float],
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registry=REGISTRY,
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):
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"""
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Args:
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name: base name of metric to be exported to Prometheus. (a _bucket suffix
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will be added.)
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documentation: help text for the metric
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buckets: The top bounds of the buckets to report
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registry: metric registry to register with
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"""
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self._name = name
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self._documentation = documentation
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# the tops of the buckets
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self._bucket_bounds = [float(b) for b in buckets]
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if self._bucket_bounds != sorted(self._bucket_bounds):
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raise ValueError("Buckets not in sorted order")
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if self._bucket_bounds[-1] != float("inf"):
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self._bucket_bounds.append(float("inf"))
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self._metric = self._values_to_metric([])
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registry.register(self)
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def collect(self):
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yield self._metric
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# Fetch the data -- this must be synchronous!
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data = self.data_collector()
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def update_data(self, values: Iterable[float]):
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"""Update the data to be reported by the metric
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buckets = {} # type: Dict[float, int]
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The existing data is cleared, and each measurement in the input is assigned
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to the relevant bucket.
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"""
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self._metric = self._values_to_metric(values)
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res = []
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for x in data.keys():
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for i, bound in enumerate(self.buckets):
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if x <= bound:
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buckets[bound] = buckets.get(bound, 0) + data[x]
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def _values_to_metric(self, values: Iterable[float]) -> GaugeHistogramMetricFamily:
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total = 0.0
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bucket_values = [0 for _ in self._bucket_bounds]
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for i in self.buckets:
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res.append([str(i), buckets.get(i, 0)])
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for v in values:
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# assign each value to a bucket
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for i, bound in enumerate(self._bucket_bounds):
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if v <= bound:
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bucket_values[i] += 1
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break
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res.append(["+Inf", sum(data.values())])
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# ... and increment the sum
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total += v
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metric = HistogramMetricFamily(
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self.name, "", buckets=res, sum_value=sum(x * y for x, y in data.items())
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# now, aggregate the bucket values so that they count the number of entries in
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# that bucket or below.
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accumulated_values = itertools.accumulate(bucket_values)
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return GaugeHistogramMetricFamily(
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self._name,
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self._documentation,
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buckets=list(
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zip((str(b) for b in self._bucket_bounds), accumulated_values)
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),
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gsum_value=total,
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)
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yield metric
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def __attrs_post_init__(self):
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self.buckets = [float(x) for x in self.buckets if x != "+Inf"]
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if self.buckets != sorted(self.buckets):
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raise ValueError("Buckets not sorted")
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self.buckets = tuple(self.buckets)
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if self.name in all_gauges.keys():
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logger.warning("%s already registered, reregistering" % (self.name,))
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REGISTRY.unregister(all_gauges.pop(self.name))
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REGISTRY.register(self)
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all_gauges[self.name] = self
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#
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@ -12,10 +12,8 @@
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import typing
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from collections import Counter
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from synapse.metrics import BucketCollector
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from synapse.metrics import GaugeBucketCollector
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from synapse.metrics.background_process_metrics import run_as_background_process
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from synapse.storage._base import SQLBaseStore
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from synapse.storage.database import DatabasePool
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@ -23,6 +21,14 @@ from synapse.storage.databases.main.event_push_actions import (
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EventPushActionsWorkerStore,
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)
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# Collect metrics on the number of forward extremities that exist.
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_extremities_collecter = GaugeBucketCollector(
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"synapse_forward_extremities",
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"Number of rooms on the server with the given number of forward extremities"
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" or fewer",
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buckets=[1, 2, 3, 5, 7, 10, 15, 20, 50, 100, 200, 500],
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)
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class ServerMetricsStore(EventPushActionsWorkerStore, SQLBaseStore):
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"""Functions to pull various metrics from the DB, for e.g. phone home
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@ -32,18 +38,6 @@ class ServerMetricsStore(EventPushActionsWorkerStore, SQLBaseStore):
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def __init__(self, database: DatabasePool, db_conn, hs):
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super().__init__(database, db_conn, hs)
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# Collect metrics on the number of forward extremities that exist.
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# Counter of number of extremities to count
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self._current_forward_extremities_amount = (
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Counter()
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) # type: typing.Counter[int]
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BucketCollector(
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"synapse_forward_extremities",
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lambda: self._current_forward_extremities_amount,
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buckets=[1, 2, 3, 5, 7, 10, 15, 20, 50, 100, 200, 500, "+Inf"],
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)
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# Read the extrems every 60 minutes
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def read_forward_extremities():
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# run as a background process to make sure that the database transactions
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@ -65,7 +59,7 @@ class ServerMetricsStore(EventPushActionsWorkerStore, SQLBaseStore):
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return txn.fetchall()
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res = await self.db_pool.runInteraction("read_forward_extremities", fetch)
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self._current_forward_extremities_amount = Counter([x[0] for x in res])
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_extremities_collecter.update_data(x[0] for x in res)
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async def count_daily_messages(self):
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"""
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@ -52,14 +52,14 @@ class ExtremStatisticsTestCase(HomeserverTestCase):
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self.reactor.advance(60 * 60 * 1000)
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self.pump(1)
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items = set(
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items = list(
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filter(
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lambda x: b"synapse_forward_extremities_" in x,
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generate_latest(REGISTRY).split(b"\n"),
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generate_latest(REGISTRY, emit_help=False).split(b"\n"),
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)
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)
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expected = {
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expected = [
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b'synapse_forward_extremities_bucket{le="1.0"} 0.0',
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b'synapse_forward_extremities_bucket{le="2.0"} 2.0',
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b'synapse_forward_extremities_bucket{le="3.0"} 2.0',
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@ -72,9 +72,12 @@ class ExtremStatisticsTestCase(HomeserverTestCase):
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b'synapse_forward_extremities_bucket{le="100.0"} 3.0',
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b'synapse_forward_extremities_bucket{le="200.0"} 3.0',
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b'synapse_forward_extremities_bucket{le="500.0"} 3.0',
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b'synapse_forward_extremities_bucket{le="+Inf"} 3.0',
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b"synapse_forward_extremities_count 3.0",
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b"synapse_forward_extremities_sum 10.0",
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}
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# per https://docs.google.com/document/d/1KwV0mAXwwbvvifBvDKH_LU1YjyXE_wxCkHNoCGq1GX0/edit#heading=h.wghdjzzh72j9,
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# "inf" is valid: "this includes variants such as inf"
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b'synapse_forward_extremities_bucket{le="inf"} 3.0',
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b"# TYPE synapse_forward_extremities_gcount gauge",
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b"synapse_forward_extremities_gcount 3.0",
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b"# TYPE synapse_forward_extremities_gsum gauge",
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b"synapse_forward_extremities_gsum 10.0",
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]
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self.assertEqual(items, expected)
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