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https://git.anonymousland.org/anonymousland/synapse.git
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73c7112433
We change it so that each cache has an individual CacheMetric, instead of having one global CacheMetric. This means that when a cache tries to increment a counter it does not need to go through so many indirections.
156 lines
4.6 KiB
Python
156 lines
4.6 KiB
Python
# -*- coding: utf-8 -*-
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# Copyright 2015, 2016 OpenMarket Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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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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from itertools import chain
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# TODO(paul): I can't believe Python doesn't have one of these
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def map_concat(func, items):
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# flatten a list-of-lists
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return list(chain.from_iterable(map(func, items)))
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class BaseMetric(object):
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def __init__(self, name, labels=[]):
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self.name = name
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self.labels = labels # OK not to clone as we never write it
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def dimension(self):
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return len(self.labels)
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def is_scalar(self):
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return not len(self.labels)
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def _render_labelvalue(self, value):
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# TODO: some kind of value escape
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return '"%s"' % (value)
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def _render_key(self, values):
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if self.is_scalar():
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return ""
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return "{%s}" % (
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",".join(["%s=%s" % (k, self._render_labelvalue(v))
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for k, v in zip(self.labels, values)])
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)
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class CounterMetric(BaseMetric):
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"""The simplest kind of metric; one that stores a monotonically-increasing
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integer that counts events."""
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def __init__(self, *args, **kwargs):
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super(CounterMetric, self).__init__(*args, **kwargs)
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self.counts = {}
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# Scalar metrics are never empty
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if self.is_scalar():
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self.counts[()] = 0
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def inc_by(self, incr, *values):
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if len(values) != self.dimension():
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raise ValueError(
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"Expected as many values to inc() as labels (%d)" % (self.dimension())
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)
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# TODO: should assert that the tag values are all strings
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if values not in self.counts:
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self.counts[values] = incr
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else:
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self.counts[values] += incr
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def inc(self, *values):
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self.inc_by(1, *values)
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def render_item(self, k):
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return ["%s%s %d" % (self.name, self._render_key(k), self.counts[k])]
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def render(self):
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return map_concat(self.render_item, sorted(self.counts.keys()))
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class CallbackMetric(BaseMetric):
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"""A metric that returns the numeric value returned by a callback whenever
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it is rendered. Typically this is used to implement gauges that yield the
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size or other state of some in-memory object by actively querying it."""
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def __init__(self, name, callback, labels=[]):
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super(CallbackMetric, self).__init__(name, labels=labels)
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self.callback = callback
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def render(self):
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value = self.callback()
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if self.is_scalar():
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return ["%s %d" % (self.name, value)]
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return ["%s%s %d" % (self.name, self._render_key(k), value[k])
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for k in sorted(value.keys())]
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class DistributionMetric(object):
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"""A combination of an event counter and an accumulator, which counts
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both the number of events and accumulates the total value. Typically this
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could be used to keep track of method-running times, or other distributions
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of values that occur in discrete occurances.
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TODO(paul): Try to export some heatmap-style stats?
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"""
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def __init__(self, name, *args, **kwargs):
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self.counts = CounterMetric(name + ":count", **kwargs)
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self.totals = CounterMetric(name + ":total", **kwargs)
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def inc_by(self, inc, *values):
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self.counts.inc(*values)
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self.totals.inc_by(inc, *values)
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def render(self):
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return self.counts.render() + self.totals.render()
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class CacheMetric(object):
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__slots__ = ("name", "cache_name", "hits", "misses", "size_callback")
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def __init__(self, name, size_callback, cache_name):
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self.name = name
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self.cache_name = cache_name
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self.hits = 0
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self.misses = 0
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self.size_callback = size_callback
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def inc_hits(self):
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self.hits += 1
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def inc_misses(self):
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self.misses += 1
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def render(self):
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size = self.size_callback()
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hits = self.hits
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total = self.misses + self.hits
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return [
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"""%s:hits{name="%s"} %d""" % (self.name, self.cache_name, hits),
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"""%s:total{name="%s"} %d""" % (self.name, self.cache_name, total),
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"""%s:size{name="%s"} %d""" % (self.name, self.cache_name, size),
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]
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