Sample more frequently, and always record unexpected cache misses
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@@ -41,9 +41,10 @@ class Tagger(object):
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An object used by :class:`QueryTimer` to allow timed code blocks
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to add measurements and tags to the timer.
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"""
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def __init__(self):
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def __init__(self, default_sample_rate):
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self.added_tags = []
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self.measures = []
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self.sample_rate = default_sample_rate
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def measure(self, name, size):
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"""
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@@ -108,7 +109,7 @@ class QueryTimer(object):
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metric_name: The name used to aggregate all of these metrics.
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course_context: The course which the query is being made for.
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"""
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tagger = Tagger()
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tagger = Tagger(self._sample_rate)
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metric_name = "{}.{}".format(self._metric_base, metric_name)
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start = time()
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@@ -124,24 +125,24 @@ class QueryTimer(object):
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size,
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timestamp=end,
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tags=[tag for tag in tags if not tag.startswith('{}:'.format(metric_name))],
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sample_rate=self._sample_rate,
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sample_rate=tagger.sample_rate,
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)
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dog_stats_api.histogram(
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'{}.duration'.format(metric_name),
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end - start,
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timestamp=end,
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tags=tags,
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sample_rate=self._sample_rate,
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sample_rate=tagger.sample_rate,
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)
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dog_stats_api.increment(
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metric_name,
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timestamp=end,
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tags=tags,
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sample_rate=self._sample_rate,
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sample_rate=tagger.sample_rate,
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)
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TIMER = QueryTimer(__name__, 0.001)
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TIMER = QueryTimer(__name__, 0.01)
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def structure_from_mongo(structure, course_context=None):
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@@ -231,6 +232,8 @@ class CourseStructureCache(object):
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tagger.tag(from_cache=str(compressed_pickled_data is not None).lower())
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if compressed_pickled_data is None:
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# Always log cache misses, because they are unexpected
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tagger.sample_rate = 1
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return None
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tagger.measure('compressed_size', len(compressed_pickled_data))
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@@ -320,10 +323,15 @@ class MongoConnection(object):
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structure = cache.get(key, course_context)
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tagger_get_structure.tag(from_cache=str(bool(structure)).lower())
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if not structure:
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# Always log cache misses, because they are unexpected
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tagger_get_structure.sample_rate = 1
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with TIMER.timer("get_structure.find_one", course_context) as tagger_find_one:
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doc = self.structures.find_one({'_id': key})
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tagger_find_one.measure("blocks", len(doc['blocks']))
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structure = structure_from_mongo(doc, course_context)
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tagger_find_one.sample_rate = 1
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cache.set(key, structure, course_context)
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return structure
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