forked from MirrorHub/synapse
Create the concept of a cachecounter metric; generating two counters specific to caches
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@ -13,7 +13,7 @@
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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 .metric import CounterMetric
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from .metric import CounterMetric, CacheCounterMetric
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# We'll keep all the available metrics in a single toplevel dict, one shared
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@ -43,6 +43,15 @@ class Metrics(object):
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return metric
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def register_cachecounter(self, name, *args, **kwargs):
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full_name = "%s.%s" % (self.name_prefix, name)
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metric = CacheCounterMetric(full_name, *args, **kwargs)
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self._register(metric)
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return metric
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def counted(self, func):
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""" A method decorator that registers a counter, to count invocations
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of this method. """
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@ -14,16 +14,28 @@
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# limitations under the License.
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class CounterMetric(object):
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class BaseMetric(object):
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def __init__(self, name, keys=[]):
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self.name = name
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self.keys = keys # OK not to clone as we never write it
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def _render_key(self, values):
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# TODO: some kind of value escape
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return ",".join(["%s=%s" % kv for kv in zip(self.keys, values)])
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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 not len(keys):
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if not len(self.keys):
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self.counts[()] = 0
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def inc(self, *values):
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@ -42,13 +54,32 @@ class CounterMetric(object):
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def fetch(self):
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return dict(self.counts)
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def _render_key(self, values):
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# TODO: some kind of value escape
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return ",".join(["%s=%s" % kv for kv in zip(self.keys, values)])
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def render(self):
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if not len(self.keys):
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return ["%s %d" % (self.name, self.counts[()])]
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return ["%s{%s} %d" % (self.name, self._render_key(k), self.counts[k])
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for k in sorted(self.counts.keys())]
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class CacheCounterMetric(object):
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"""A combination of two CounterMetrics, one to count cache hits and one to
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count misses.
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This metric generates standard metric name pairs, so that monitoring rules
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can easily be applied to measure hit ratio."""
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def __init__(self, name, keys=[]):
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self.name = name
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self.hits = CounterMetric(name + ":hits", keys=keys)
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self.misses = CounterMetric(name + ":misses", keys=keys)
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def inc_hits(self, *values):
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self.hits.inc(*values)
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def inc_misses(self, *values):
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self.misses.inc(*values)
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def render(self):
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return self.hits.render() + self.misses.render()
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@ -15,7 +15,7 @@
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from tests import unittest
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from synapse.metrics.metric import CounterMetric
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from synapse.metrics.metric import CounterMetric, CacheCounterMetric
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class CounterMetricTestCase(unittest.TestCase):
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@ -59,3 +59,28 @@ class CounterMetricTestCase(unittest.TestCase):
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"vector{method=GET} 2",
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"vector{method=PUT} 1",
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])
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class CacheCounterMetricTestCase(unittest.TestCase):
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def test_cachecounter(self):
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counter = CacheCounterMetric("cache")
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self.assertEquals(counter.render(), [
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"cache:hits 0",
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"cache:misses 0",
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])
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counter.inc_misses()
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self.assertEquals(counter.render(), [
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"cache:hits 0",
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"cache:misses 1",
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])
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counter.inc_hits()
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self.assertEquals(counter.render(), [
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"cache:hits 1",
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"cache:misses 1",
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])
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