def test_sets_flush_during_bucket(self):
ag_interval = self.interval
stats = MetricsBucketAggregator('myhost', interval=ag_interval)
self.wait_for_bucket_boundary(ag_interval)
stats.submit_packets('my.set:10|s')
stats.submit_packets('my.set:20|s')
stats.submit_packets('my.set:20|s')
stats.submit_packets('my.set:30|s')
stats.submit_packets('my.set:30|s')
stats.submit_packets('my.set:30|s')
self.sleep_for_interval_length(ag_interval)
stats.submit_packets('my.set:40|s')
# Assert that it's treated normally.
metrics = stats.flush()
assert len(metrics) == 1
m = metrics[0]
assert m['metric'] == 'my.set'
assert m['points'][0][1] == 3
self.sleep_for_interval_length(ag_interval)
metrics = stats.flush()
m = metrics[0]
assert m['metric'] == 'my.set'
assert m['points'][0][1] == 1
# Assert there are no more sets
assert not stats.flush()
def test_sdstatsd_aggregation_perf(self):
ma = MetricsBucketAggregator('my.host')
for _ in xrange(self.FLUSH_COUNT):
for i in xrange(self.LOOPS_PER_FLUSH):
for j in xrange(self.METRIC_COUNT):
# metrics
ma.submit_packets('counter.%s:%s|c' % (j, i))
ma.submit_packets('gauge.%s:%s|g' % (j, i))
ma.submit_packets('histogram.%s:%s|h' % (j, i))
ma.submit_packets('set.%s:%s|s' % (j, 1.0))
# tagged metrics
ma.submit_packets('counter.%s:%s|c|#tag1,tag2' % (j, i))
ma.submit_packets('gauge.%s:%s|g|#tag1,tag2' % (j, i))
ma.submit_packets('histogram.%s:%s|h|#tag1,tag2' % (j, i))
ma.submit_packets('set.%s:%s|s|#tag1,tag2' % (j, i))
# sampled metrics
ma.submit_packets('counter.%s:%s|c|@0.5' % (j, i))
ma.submit_packets('gauge.%s:%s|g|@0.5' % (j, i))
ma.submit_packets('histogram.%s:%s|h|@0.5' % (j, i))
ma.submit_packets('set.%s:%s|s|@0.5' % (j, i))
ma.flush()
def test_gauge_buckets(self):
# Tests calling returing data from 2 time buckets
ag_interval = self.interval
stats = MetricsBucketAggregator('myhost', interval=ag_interval)
self.wait_for_bucket_boundary(ag_interval)
# Track some counters.
stats.submit_packets('my.first.gauge:1|g')
stats.submit_packets('my.first.gauge:5|g')
stats.submit_packets('my.second.gauge:1.5|g')
self.sleep_for_interval_length(ag_interval)
stats.submit_packets('my.second.gauge:9.5|g')
# Ensure that gauges roll up correctly.
self.sleep_for_interval_length(ag_interval)
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 3
first, second, second_b = metrics
assert first['metric'] == 'my.first.gauge'
assert first['points'][0][1] == 5
assert first['host'] == 'myhost'
assert second_b['metric'] == 'my.second.gauge'
assert second_b['points'][0][1] == 9.5
assert second['metric'] == 'my.second.gauge'
assert second['points'][0][1] == 1.5
# check that they come back empty
self.sleep_for_interval_length(ag_interval)
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 0
def test_sets_buckets(self):
stats = MetricsBucketAggregator('myhost', interval=self.interval)
stats.submit_packets('my.set:10|s')
stats.submit_packets('my.set:20|s')
stats.submit_packets('my.set:20|s')
stats.submit_packets('my.set:30|s')
stats.submit_packets('my.set:30|s')
stats.submit_packets('my.set:30|s')
self.sleep_for_interval_length()
stats.submit_packets('my.set:40|s')
# Assert that it's treated normally.
self.sleep_for_interval_length()
metrics = stats.flush()
assert len(metrics) == 2
m, m2 = metrics
assert m['metric'] == 'my.set'
assert m['points'][0][1] == 3
assert m2['metric'] == 'my.set'
assert m2['points'][0][1] == 1
# Assert there are no more sets
assert not stats.flush()
def test_gauge_flush_during_bucket(self):
# Tests returning data when flush is called in the middle of a time bucket that has data
ag_interval = self.interval
stats = MetricsBucketAggregator('myhost', interval=ag_interval)
self.wait_for_bucket_boundary(ag_interval)
# Track some counters.
stats.submit_packets('my.first.gauge:1|g')
stats.submit_packets('my.first.gauge:5|g')
stats.submit_packets('my.second.gauge:1.5|g')
self.sleep_for_interval_length(ag_interval)
stats.submit_packets('my.second.gauge:9.5|g')
# Ensure that gauges roll up correctly.
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 2
first, second = metrics
assert first['metric'] == 'my.first.gauge'
assert first['points'][0][1] == 5
assert first['host'] == 'myhost'
assert second['metric'] == 'my.second.gauge'
assert second['points'][0][1] == 1.5
self.sleep_for_interval_length(ag_interval)
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 1
assert second['metric'] == 'my.second.gauge'
assert second['points'][0][1] == 1.5
def test_dogstatsd_aggregation_perf(self):
ma = MetricsBucketAggregator('my.host')
for _ in xrange(self.FLUSH_COUNT):
for i in xrange(self.LOOPS_PER_FLUSH):
for j in xrange(self.METRIC_COUNT):
# metrics
ma.submit_packets('counter.%s:%s|c' % (j, i))
ma.submit_packets('gauge.%s:%s|g' % (j, i))
ma.submit_packets('histogram.%s:%s|h' % (j, i))
ma.submit_packets('set.%s:%s|s' % (j, 1.0))
# tagged metrics
ma.submit_packets('counter.%s:%s|c|#tag1,tag2' % (j, i))
ma.submit_packets('gauge.%s:%s|g|#tag1,tag2' % (j, i))
ma.submit_packets('histogram.%s:%s|h|#tag1,tag2' % (j, i))
ma.submit_packets('set.%s:%s|s|#tag1,tag2' % (j, i))
# sampled metrics
ma.submit_packets('counter.%s:%s|c|@0.5' % (j, i))
ma.submit_packets('gauge.%s:%s|g|@0.5' % (j, i))
ma.submit_packets('histogram.%s:%s|h|@0.5' % (j, i))
ma.submit_packets('set.%s:%s|s|@0.5' % (j, i))
ma.flush()
def test_histogram_flush_during_bucket(self):
ag_interval = 1
# The min is not enabled by default
stats = MetricsBucketAggregator(
'myhost',
interval=ag_interval,
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES + ['min'])
# Sample all numbers between 1-100 many times. This
# means our percentiles should be relatively close to themselves.
self.wait_for_bucket_boundary(ag_interval)
percentiles = list(range(100))
random.shuffle(percentiles) # in place
for i in percentiles:
for j in range(20):
for type_ in ['h', 'ms']:
m = 'my.p:%s|%s' % (i, type_)
stats.submit_packets(m)
time.sleep(
self.BUCKET_BOUNDARY_TOLERANCE
) # Make sure that we'll wait for the _next_ bucket boundary
self.wait_for_bucket_boundary(ag_interval)
percentiles = list(range(50))
random.shuffle(percentiles) # in place
for i in percentiles:
for j in range(20):
for type_ in ['h', 'ms']:
m = 'my.p:%s|%s' % (i, type_)
stats.submit_packets(m)
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 6
p95, pavg, pcount, pmax, pmed, pmin = self.sort_metrics(metrics)
assert p95['metric'] == 'my.p.95percentile'
self.assert_almost_equal(p95['points'][0][1], 95, 10)
self.assert_almost_equal(pmax['points'][0][1], 99, 1)
self.assert_almost_equal(pmed['points'][0][1], 50, 2)
self.assert_almost_equal(pavg['points'][0][1], 50, 2)
self.assert_almost_equal(pmin['points'][0][1], 1, 1)
assert pcount['points'][0][1] == 4000 # 100 * 20 * 2
assert p95['host'] == 'myhost'
self.sleep_for_interval_length()
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 6
p95_b, pavg_b, pcount_b, pmax_b, pmed_b, pmin_b = self.sort_metrics(
metrics)
assert p95_b['metric'] == 'my.p.95percentile'
self.assert_almost_equal(p95_b['points'][0][1], 47, 10)
self.assert_almost_equal(pmax_b['points'][0][1], 49, 1)
self.assert_almost_equal(pmed_b['points'][0][1], 25, 2)
self.assert_almost_equal(pavg_b['points'][0][1], 25, 2)
self.assert_almost_equal(pmin_b['points'][0][1], 1, 1)
assert pcount_b['points'][0][1] == 2000 # 100 * 20 * 2
# Ensure that histograms are reset.
metrics = self.sort_metrics(stats.flush())
assert not metrics
def test_counter_buckets(self):
ag_interval = 5
stats = MetricsBucketAggregator('myhost', interval=ag_interval)
self.wait_for_bucket_boundary(ag_interval)
# Track some counters.
stats.submit_packets("my.first.counter:%s|c" % (1 * ag_interval))
stats.submit_packets("my.second.counter:%s|c" % (1 * ag_interval))
stats.submit_packets("my.third.counter:%s|c" % (3 * ag_interval))
time.sleep(ag_interval)
stats.submit_packets("my.first.counter:%s|c" % (5 * ag_interval))
# Want to get 2 different entries for my.first.counter in one set of metrics,
# so wait for the time bucket interval to pass
self.sleep_for_interval_length(ag_interval)
# Ensure they roll up nicely.
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 6
first, first_b, second, second_b, third, third_b = metrics
assert first['metric'] == 'my.first.counter'
assert first['points'][0][1] == 1
assert first['host'] == 'myhost'
assert first_b['metric'] == 'my.first.counter'
assert first_b['points'][0][1] == 5
assert (first_b['points'][0][0] - first['points'][0][0]) == ag_interval
assert first['points'][0][0] % ag_interval == 0
assert first_b['points'][0][0] % ag_interval == 0
assert second['metric'] == 'my.second.counter'
assert second['points'][0][1] == 1
assert second_b['metric'] == 'my.second.counter'
assert second_b['points'][0][1] == 0
assert third['metric'] == 'my.third.counter'
assert third['points'][0][1] == 3
assert third_b['metric'] == 'my.third.counter'
assert third_b['points'][0][1] == 0
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 0
self.sleep_for_interval_length(ag_interval)
# Ensure that counters reset to zero.
metrics = self.sort_metrics(stats.flush())
first, second, third = metrics
assert first['metric'] == 'my.first.counter'
assert first['points'][0][1] == 0
assert second['metric'] == 'my.second.counter'
assert second['points'][0][1] == 0
assert third['metric'] == 'my.third.counter'
assert third['points'][0][1] == 0
def test_tags(self):
stats = MetricsBucketAggregator('myhost', interval=self.interval)
stats.submit_packets('gauge:1|c')
stats.submit_packets('gauge:2|c|@1')
stats.submit_packets('gauge:4|c|#tag1,tag2')
stats.submit_packets(
'gauge:8|c|#tag2,tag1') # Should be the same as above
stats.submit_packets('gauge:16|c|#tag3,tag4')
self.sleep_for_interval_length()
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 3
first, second, third = metrics
assert first['metric'] == 'gauge'
assert first['tags'] is None
assert first['points'][0][1] == 3
assert first['host'] == 'myhost'
assert second['metric'] == 'gauge'
assert second['tags'] == ('tag1', 'tag2')
assert second['points'][0][1] == 12
assert second['host'] == 'myhost'
assert third['metric'] == 'gauge'
assert third['tags'] == ('tag3', 'tag4')
assert third['points'][0][1] == 16
assert third['host'] == 'myhost'
def test_sampled_counter(self):
# Submit a sampled counter.
stats = MetricsBucketAggregator('myhost', interval=self.interval)
stats.submit_packets('sampled.counter:1|c|@0.5')
self.sleep_for_interval_length()
metrics = stats.flush()
assert len(metrics) == 1
m = metrics[0]
assert m['metric'] == 'sampled.counter'
assert m['points'][0][1] == 2
def test_scientific_notation(self):
ag_interval = 10
stats = MetricsBucketAggregator('myhost', interval=ag_interval)
stats.submit_packets('test.scinot:9.512901e-05|g')
self.sleep_for_interval_length(ag_interval)
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 1
ts, val = metrics[0].get('points')[0]
self.assert_almost_equal(val, 9.512901e-05)
def test_sdstatsd_ascii_events(self):
ma = MetricsBucketAggregator('my.host')
for _ in xrange(self.FLUSH_COUNT):
for i in xrange(self.LOOPS_PER_FLUSH):
for j in xrange(self.METRIC_COUNT):
ma.submit_packets(self.create_event_packet(
'asldkfj fdsaljfas dflksjafs fasdfkjaldsfkjasldf',
"""alkdjfa slfalskdfjas lkfdjaoisudhfalsdkjbfaksdhfbasjdk fa;sf ljda fsafksadfh alsdjfhaskjdfgahls d;fjasdlkfh9823udjs dlfhaspdf98as ufdaksjhfaisdhufalskdjfhas df"""
))
ma.submit_packets(self.create_event_packet(
'kdjfsofuousodifu982309rijdfsljsd dfsdf sdf',
"""dflskjdfs8d9fsdfjs sldfjka ;dlfjapfoia jsdflakjsdfp 0adsfuolwejf wflsdjf lsdkjf0saoiufja dlfjasd of;lasdjf ;askdjf asodfhas lkmfbashudf asd,fasdfna s,dfjas lcjx vjaskdlfjals dfkjasdflk jasldfkj asldkfjas ldfkasjdf a"""
))
ma.submit_packets(self.create_event_packet(
'asdf askdjf asldfkjsad lfkajsdlfksajd fasdfsdfdf',
"""skdfjsld flskdjf alksdjfpasdofuapo sdfjalksdjf ;as.kjdf ;ljLKJL :KJL:KJ l;kdsjf ;lkj :Lkj FLDKFJ LSKFDJ ;LDFJ SLKDJF KSDLjf: Lfjldkj fLKDSJf lSKDjf ls;kdjf s;lkfjs L:KAJ :LFKJDL:DKjf L:SKjf;lKDJfl;SKJDf :LKSDj;lsdfj fsdljfsd ofisunafoialjsflmsdifjas;dlkfaj sdfkasjd flaksjdfnpmsao;difjkas dfnlaksdfa;sodljfas lfdjasdflmajsdlfknaf98wouanepr9qo3ud fadspuf oaisdufpoasid fj askdjn LKJH LKJHFL KJDHSF DSFLHSL JKDFHLSK DJFHLS KJDFHS"""
))
ma.flush()
def test_batch_submission(self):
# Submit a sampled histogram.
stats = MetricsBucketAggregator('myhost', interval=self.interval)
metrics = ['counter:1|c', 'counter:1|c', 'gauge:1|g']
packet = "\n".join(metrics)
stats.submit_packets(packet)
self.sleep_for_interval_length()
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 2
counter, gauge = metrics
assert counter['points'][0][1] == 2
assert gauge['points'][0][1] == 1
def test_diagnostic_stats(self):
stats = MetricsBucketAggregator('myhost', interval=self.interval)
for i in range(10):
stats.submit_packets('metric:10|c')
stats.send_packet_count('datadog.dogstatsd.packet.count')
self.sleep_for_interval_length()
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 2
first, second = metrics
assert first['metric'] == 'datadog.dogstatsd.packet.count'
assert first['points'][0][1] == 10
def test_sdstatsd_utf8_events(self):
ma = MetricsBucketAggregator('my.host')
for _ in xrange(self.FLUSH_COUNT):
for i in xrange(self.LOOPS_PER_FLUSH):
for j in xrange(self.METRIC_COUNT):
ma.submit_packets(self.create_event_packet(
'Τη γλώσσα μου έδωσαν ελληνική',
"""τὸ σπίτι φτωχικὸ στὶς ἀμμουδιὲς τοῦ Ὁμήρου. Μονάχη ἔγνοια ἡ γλῶσσα μου στὶς ἀμμουδιὲς τοῦ Ὁμήρου. ἀπὸ τὸ Ἄξιον ἐστί τοῦ Ὀδυσσέα Ἐλύτη"""
))
ma.submit_packets(self.create_event_packet(
'ვეპხის ტყაოსანი შოთა რუსთაველი',
"""ღმერთსი შემვედრე, ნუთუ კვლა დამხსნას სოფლისა შრომასა, ცეცხლს, წყალსა და მიწასა, ჰაერთა თანა მრომასა; მომცნეს ფრთენი და აღვფრინდე, მივჰხვდე მას ჩემსა ნდომასა, დღისით და ღამით ვჰხედვიდე მზისა ელვათა კრთომაასა.
"""
))
ma.submit_packets(self.create_event_packet(
'Traité sur la tolérance',
"""Ose supposer qu'un Ministre éclairé & magnanime, un Prélat humain & sage, un Prince qui sait que son intérêt consiste dans le grand nombre de ses Sujets, & sa gloire dans leur bonheur, daigne jetter les yeux sur cet Ecrit informe & défectueux; il y supplée par ses propres lumieres; il se dit à lui-même: Que risquerai-je à voir la terre cultivée & ornée par plus de mains laborieuses, les tributs augmentés, l'Etat plus florissant?"""
))
ma.flush()
def test_string_sets(self):
stats = MetricsBucketAggregator('myhost', interval=self.interval)
stats.submit_packets('my.set:string|s')
stats.submit_packets('my.set:sets|s')
stats.submit_packets('my.set:sets|s')
stats.submit_packets('my.set:test|s')
stats.submit_packets('my.set:test|s')
stats.submit_packets('my.set:test|s')
# Assert that it's treated normally.
self.sleep_for_interval_length()
metrics = stats.flush()
assert len(metrics) == 1
m = metrics[0]
assert m['metric'] == 'my.set'
assert m['points'][0][1] == 3
# Assert there are no more sets
assert not stats.flush()
self.sleep_for_interval_length()
assert not stats.flush()
def test_empty_counter(self):
ag_interval = self.interval
stats = MetricsBucketAggregator('myhost', interval=ag_interval)
self.sleep_for_interval_length(ag_interval)
metrics = self.sort_metrics(stats.flush())
# Should be an empty list
assert len(metrics) == 0
# Track some counters.
stats.submit_packets('my.first.counter:%s|c' % (1 * ag_interval))
# Call flush before the bucket_length has been exceeded
metrics = self.sort_metrics(stats.flush())
# Should be an empty list
assert len(metrics) == 0
self.sleep_for_interval_length(ag_interval)
metrics = self.sort_metrics(stats.flush())
# Should now have the data
assert len(metrics) == 1
assert metrics[0]['metric'] == 'my.first.counter'
assert metrics[0]['points'][0][1] == 1
def test_gauge(self):
ag_interval = 2
stats = MetricsBucketAggregator('myhost', interval=ag_interval)
self.wait_for_bucket_boundary(ag_interval)
# Track some counters.
stats.submit_packets('my.first.gauge:1|g')
stats.submit_packets('my.first.gauge:5|g')
stats.submit_packets('my.second.gauge:1.5|g')
# Ensure that gauges roll up correctly.
self.sleep_for_interval_length(ag_interval)
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 2
first, second = metrics
assert first['metric'] == 'my.first.gauge'
assert first['points'][0][1] == 5
assert first['host'] == 'myhost'
assert second['metric'] == 'my.second.gauge'
assert second['points'][0][1] == 1.5
# Ensure that old gauges get dropped due to old timestamps
stats.submit_metric('my.first.gauge', 5, 'g')
stats.submit_metric('my.first.gauge', 1, 'g', timestamp=1000000000)
stats.submit_metric('my.second.gauge', 20, 'g', timestamp=1000000000)
self.sleep_for_interval_length(ag_interval)
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 1
first = metrics[0]
assert first['metric'] == 'my.first.gauge'
assert first['points'][0][1] == 5
assert first['host'] == 'myhost'
def test_gauge_sample_rate(self):
ag_interval = self.interval
stats = MetricsBucketAggregator('myhost', interval=ag_interval)
# Submit a sampled gauge metric.
stats.submit_packets('sampled.gauge:10|g|@0.1')
# Assert that it's treated normally.
self.sleep_for_interval_length(ag_interval)
metrics = stats.flush()
assert len(metrics) == 1
m = metrics[0]
assert m['metric'] == 'sampled.gauge'
assert m['points'][0][1] == 10
def test_dogstatsd_utf8_events(self):
ma = MetricsBucketAggregator('my.host')
for _ in xrange(self.FLUSH_COUNT):
for i in xrange(self.LOOPS_PER_FLUSH):
for j in xrange(self.METRIC_COUNT):
ma.submit_packets(
self.create_event_packet(
'Τη γλώσσα μου έδωσαν ελληνική',
"""τὸ σπίτι φτωχικὸ στὶς ἀμμουδιὲς τοῦ Ὁμήρου. Μονάχη ἔγνοια ἡ γλῶσσα μου στὶς ἀμμουδιὲς τοῦ Ὁμήρου. ἀπὸ τὸ Ἄξιον ἐστί τοῦ Ὀδυσσέα Ἐλύτη"""
))
ma.submit_packets(
self.create_event_packet(
'ვეპხის ტყაოსანი შოთა რუსთაველი',
"""ღმერთსი შემვედრე, ნუთუ კვლა დამხსნას სოფლისა შრომასა, ცეცხლს, წყალსა და მიწასა, ჰაერთა თანა მრომასა; მომცნეს ფრთენი და აღვფრინდე, მივჰხვდე მას ჩემსა ნდომასა, დღისით და ღამით ვჰხედვიდე მზისა ელვათა კრთომაასა.
"""))
ma.submit_packets(
self.create_event_packet(
'Traité sur la tolérance',
"""Ose supposer qu'un Ministre éclairé & magnanime, un Prélat humain & sage, un Prince qui sait que son intérêt consiste dans le grand nombre de ses Sujets, & sa gloire dans leur bonheur, daigne jetter les yeux sur cet Ecrit informe & défectueux; il y supplée par ses propres lumieres; il se dit à lui-même: Que risquerai-je à voir la terre cultivée & ornée par plus de mains laborieuses, les tributs augmentés, l'Etat plus florissant?"""
))
ma.flush()
def test_dogstatsd_ascii_events(self):
ma = MetricsBucketAggregator('my.host')
for _ in xrange(self.FLUSH_COUNT):
for i in xrange(self.LOOPS_PER_FLUSH):
for j in xrange(self.METRIC_COUNT):
ma.submit_packets(
self.create_event_packet(
'asldkfj fdsaljfas dflksjafs fasdfkjaldsfkjasldf',
"""alkdjfa slfalskdfjas lkfdjaoisudhfalsdkjbfaksdhfbasjdk fa;sf ljda fsafksadfh alsdjfhaskjdfgahls d;fjasdlkfh9823udjs dlfhaspdf98as ufdaksjhfaisdhufalskdjfhas df"""
))
ma.submit_packets(
self.create_event_packet(
'kdjfsofuousodifu982309rijdfsljsd dfsdf sdf',
"""dflskjdfs8d9fsdfjs sldfjka ;dlfjapfoia jsdflakjsdfp 0adsfuolwejf wflsdjf lsdkjf0saoiufja dlfjasd of;lasdjf ;askdjf asodfhas lkmfbashudf asd,fasdfna s,dfjas lcjx vjaskdlfjals dfkjasdflk jasldfkj asldkfjas ldfkasjdf a"""
))
ma.submit_packets(
self.create_event_packet(
'asdf askdjf asldfkjsad lfkajsdlfksajd fasdfsdfdf',
"""skdfjsld flskdjf alksdjfpasdofuapo sdfjalksdjf ;as.kjdf ;ljLKJL :KJL:KJ l;kdsjf ;lkj :Lkj FLDKFJ LSKFDJ ;LDFJ SLKDJF KSDLjf: Lfjldkj fLKDSJf lSKDjf ls;kdjf s;lkfjs L:KAJ :LFKJDL:DKjf L:SKjf;lKDJfl;SKJDf :LKSDj;lsdfj fsdljfsd ofisunafoialjsflmsdifjas;dlkfaj sdfkasjd flaksjdfnpmsao;difjkas dfnlaksdfa;sodljfas lfdjasdflmajsdlfknaf98wouanepr9qo3ud fadspuf oaisdufpoasid fj askdjn LKJH LKJHFL KJDHSF DSFLHSL JKDFHLSK DJFHLS KJDFHS"""
))
ma.flush()
def test_histogram(self):
ag_interval = self.interval
# The min is not enabled by default
stats = MetricsBucketAggregator(
'myhost',
interval=ag_interval,
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES + ['min'])
self.wait_for_bucket_boundary(ag_interval)
# Sample all numbers between 1-100 many times. This
# means our percentiles should be relatively close to themselves.
percentiles = range(100)
random.shuffle(percentiles) # in place
for i in percentiles:
for j in xrange(20):
for type_ in ['h', 'ms']:
m = 'my.p:%s|%s' % (i, type_)
stats.submit_packets(m)
self.sleep_for_interval_length(ag_interval)
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 6
p95, pavg, pcount, pmax, pmed, pmin = self.sort_metrics(metrics)
assert p95['metric'] == 'my.p.95percentile'
self.assert_almost_equal(p95['points'][0][1], 95, 10)
self.assert_almost_equal(pmax['points'][0][1], 99, 1)
self.assert_almost_equal(pmed['points'][0][1], 50, 2)
self.assert_almost_equal(pavg['points'][0][1], 50, 2)
self.assert_almost_equal(pmin['points'][0][1], 1, 1)
assert pcount['points'][0][1] == 4000 # 100 * 20 * 2
assert p95['host'] == 'myhost'
# Ensure that histograms are reset.
metrics = self.sort_metrics(stats.flush())
assert not metrics
def test_counter(self):
ag_interval = 1.0
stats = MetricsBucketAggregator('myhost', interval=ag_interval)
# Track some counters.
stats.submit_packets('my.first.counter:1|c')
stats.submit_packets('my.first.counter:5|c')
stats.submit_packets('my.second.counter:1|c')
stats.submit_packets('my.third.counter:3|c')
# Ensure they roll up nicely.
self.sleep_for_interval_length(ag_interval)
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 3
first, second, third = metrics
assert first['metric'] == 'my.first.counter'
assert first['points'][0][1] == 6
assert first['host'] == 'myhost'
assert second['metric'] == 'my.second.counter'
assert second['points'][0][1] == 1
assert third['metric'] == 'my.third.counter'
assert third['points'][0][1] == 3
self.sleep_for_interval_length(ag_interval)
# Ensure that counters reset to zero.
metrics = self.sort_metrics(stats.flush())
first, second, third = metrics
assert first['metric'] == 'my.first.counter'
assert first['points'][0][1] == 0
assert second['metric'] == 'my.second.counter'
assert second['points'][0][1] == 0
assert third['metric'] == 'my.third.counter'
assert third['points'][0][1] == 0
def test_sampled_histogram(self):
# Submit a sampled histogram.
# The min is not enabled by default
stats = MetricsBucketAggregator(
'myhost',
interval=self.interval,
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES + ['min'])
stats.submit_packets('sampled.hist:5|h|@0.5')
# Assert we scale up properly.
self.sleep_for_interval_length()
metrics = self.sort_metrics(stats.flush())
p95, pavg, pcount, pmax, pmed, pmin = self.sort_metrics(metrics)
assert pcount['points'][0][1] == 2
for p in [p95, pavg, pmed, pmax, pmin]:
assert p['points'][0][1] == 5
def test_histogram_normalization(self):
ag_interval = 10
# The min is not enabled by default
stats = MetricsBucketAggregator(
'myhost',
interval=ag_interval,
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES + ['min'])
for i in range(5):
stats.submit_packets('h1:1|h')
for i in range(20):
stats.submit_packets('h2:1|h')
self.sleep_for_interval_length(ag_interval)
metrics = self.sort_metrics(stats.flush())
_, _, h1count, _, _, _, _, _, h2count, _, _, _ = metrics
assert h1count['points'][0][1] == 0.5
assert h2count['points'][0][1] == 2
def test_histogram_counter(self):
# Test whether histogram.count == increment
# same deal with a sample rate
ag_interval = self.interval
cnt = 100000
for run in [1, 2]:
stats = MetricsBucketAggregator('myhost', interval=ag_interval)
for i in range(cnt):
if run == 2:
stats.submit_packets('test.counter:1|c|@0.5')
stats.submit_packets('test.hist:1|ms|@0.5')
else:
stats.submit_packets('test.counter:1|c')
stats.submit_packets('test.hist:1|ms')
self.sleep_for_interval_length(ag_interval)
metrics = self.sort_metrics(stats.flush())
assert len(metrics) > 0
# depending on timing, some runs may return the metric more that
# one bucket, meaning there may be more than one 'metric' for each
# of the counters
counter_count = 0
hist_count = 0
for num in [
m['points'][0][1] for m in metrics
if m['metric'] == 'test.counter'
]:
counter_count += num
for num in [
m['points'][0][1] for m in metrics
if m['metric'] == 'test.hist.count'
]:
hist_count += num
assert counter_count == (cnt * run)
assert hist_count == (cnt * run)
def test_counter_normalization(self):
ag_interval = 10
stats = MetricsBucketAggregator('myhost', interval=ag_interval)
# Assert counters are normalized.
stats.submit_packets('int:1|c')
stats.submit_packets('int:4|c')
stats.submit_packets('int:15|c')
stats.submit_packets('float:5|c')
self.sleep_for_interval_length(ag_interval)
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 2
floatc, intc = metrics
assert floatc['metric'] == 'float'
assert floatc['points'][0][1] == 0.5
assert floatc['host'] == 'myhost'
assert intc['metric'] == 'int'
assert intc['points'][0][1] == 2
assert intc['host'] == 'myhost'
def test_recent_point_threshold(self):
ag_interval = 1
threshold = 100
# The min is not enabled by default
stats = MetricsBucketAggregator(
'myhost',
recent_point_threshold=threshold,
interval=ag_interval,
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES + ['min'])
timestamp_beyond_threshold = time.time() - threshold * 2
# Ensure that old gauges get dropped due to old timestamps
stats.submit_metric('my.first.gauge', 5, 'g')
stats.submit_metric('my.first.gauge',
1,
'g',
timestamp=timestamp_beyond_threshold)
stats.submit_metric('my.second.gauge',
20,
'g',
timestamp=timestamp_beyond_threshold)
self.sleep_for_interval_length(ag_interval)
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 1
first = metrics[0]
assert first['metric'] == 'my.first.gauge'
assert first['points'][0][1] == 5
assert first['host'] == 'myhost'
timestamp_within_threshold = time.time() - threshold / 2
bucket_for_timestamp_within_threshold = timestamp_within_threshold - (
timestamp_within_threshold % ag_interval)
stats.submit_metric('my.1.gauge', 5, 'g')
stats.submit_metric('my.1.gauge',
1,
'g',
timestamp=timestamp_within_threshold)
stats.submit_metric('my.2.counter',
20,
'c',
timestamp=timestamp_within_threshold)
stats.submit_metric('my.3.set',
20,
's',
timestamp=timestamp_within_threshold)
stats.submit_metric('my.4.histogram',
20,
'h',
timestamp=timestamp_within_threshold)
self.sleep_for_interval_length(ag_interval)
flush_timestamp = time.time()
# The bucket timestamp is the beginning of the bucket that ended before we flushed
bucket_timestamp = flush_timestamp - (flush_timestamp %
ag_interval) - ag_interval
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 11
first, first_b, second, second_b, third, h1, h2, h3, h4, h5, h6 = metrics
assert first['metric'] == 'my.1.gauge'
assert first['points'][0][1] == 1
assert first['host'] == 'myhost'
self.assert_almost_equal(first['points'][0][0],
bucket_for_timestamp_within_threshold, 0.1)
assert first_b['metric'] == 'my.1.gauge'
assert first_b['points'][0][1] == 5
self.assert_almost_equal(first_b['points'][0][0], bucket_timestamp,
0.1)
assert second['metric'] == 'my.2.counter'
assert second['points'][0][1] == 20
self.assert_almost_equal(second['points'][0][0],
bucket_for_timestamp_within_threshold, 0.1)
assert second_b['metric'] == 'my.2.counter'
assert second_b['points'][0][1] == 0
self.assert_almost_equal(second_b['points'][0][0], bucket_timestamp,
0.1)
assert third['metric'] == 'my.3.set'
assert third['points'][0][1] == 1
self.assert_almost_equal(third['points'][0][0],
bucket_for_timestamp_within_threshold, 0.1)
assert h1['metric'] == 'my.4.histogram.95percentile'
assert h1['points'][0][1] == 20
self.assert_almost_equal(h1['points'][0][0],
bucket_for_timestamp_within_threshold, 0.1)
assert h1['points'][0][0] == h2['points'][0][0]
assert h1['points'][0][0] == h3['points'][0][0]
assert h1['points'][0][0] == h4['points'][0][0]
assert h1['points'][0][0] == h5['points'][0][0]
def test_counter_flush_during_bucket(self):
ag_interval = 5
stats = MetricsBucketAggregator('myhost', interval=ag_interval)
self.wait_for_bucket_boundary(ag_interval)
time.sleep(0.5)
# Track some counters.
stats.submit_packets("my.first.counter:%s|c" % (1 * ag_interval))
stats.submit_packets("my.second.counter:%s|c" % (1 * ag_interval))
stats.submit_packets("my.third.counter:%s|c" % (3 * ag_interval))
time.sleep(ag_interval)
stats.submit_packets("my.first.counter:%s|c" % (5 * ag_interval))
# Want to get the date from the 2 buckets in 2 differnt calls, so don't wait for
# the bucket interval to pass
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 3
first, second, third = metrics
assert first['metric'] == 'my.first.counter'
assert first['points'][0][1] == 1
assert first['host'] == 'myhost'
assert second['metric'] == 'my.second.counter'
assert second['points'][0][1] == 1
assert third['metric'] == 'my.third.counter'
assert third['points'][0][1] == 3
# Now wait for the bucket interval to pass, and get the other points
self.sleep_for_interval_length(ag_interval)
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 3
first, second, third = metrics
assert first['metric'] == 'my.first.counter'
assert first['points'][0][1] == 5
assert first['host'] == 'myhost'
assert second['metric'] == 'my.second.counter'
assert second['points'][0][1] == 0
assert third['metric'] == 'my.third.counter'
assert third['points'][0][1] == 0
self.sleep_for_interval_length(ag_interval)
# Ensure that counters reset to zero.
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 3
first, second, third = metrics
assert first['metric'] == 'my.first.counter'
assert first['points'][0][1] == 0
assert second['metric'] == 'my.second.counter'
assert second['points'][0][1] == 0
assert third['metric'] == 'my.third.counter'
assert third['points'][0][1] == 0
self.sleep_for_interval_length(ag_interval)
# Ensure that counters reset to zero.
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 3
first, second, third = metrics
assert first['metric'] == 'my.first.counter'
assert first['points'][0][1] == 0
assert second['metric'] == 'my.second.counter'
assert second['points'][0][1] == 0
assert third['metric'] == 'my.third.counter'
assert third['points'][0][1] == 0
def test_metrics_expiry(self):
# Ensure metrics eventually expire and stop submitting.
ag_interval = self.interval
expiry = ag_interval * 5 + 2
# The min is not enabled by default
stats = MetricsBucketAggregator(
'myhost',
interval=ag_interval,
expiry_seconds=expiry,
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES + ['min'])
stats.submit_packets('test.counter:123|c')
stats.submit_packets('test.gauge:55|g')
stats.submit_packets('test.set:44|s')
stats.submit_packets('test.histogram:11|h')
submit_time = time.time()
submit_bucket_timestamp = submit_time - (submit_time % ag_interval)
# Ensure points keep submitting
self.sleep_for_interval_length()
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 9
assert metrics[0]['metric'] == 'test.counter'
assert metrics[0]['points'][0][1] == 123
assert metrics[0]['points'][0][0] == submit_bucket_timestamp
# flush without waiting - should get nothing
metrics = self.sort_metrics(stats.flush())
assert not metrics, str(metrics)
# Don't sumbit anything
submit_time = time.time()
bucket_timestamp = submit_time - (submit_time % ag_interval)
self.sleep_for_interval_length()
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 1
assert metrics[0]['metric'] == 'test.counter'
assert metrics[0]['points'][0][1] == 0
assert metrics[0]['points'][0][0] == bucket_timestamp
stats.submit_packets('test.gauge:5|g')
self.sleep_for_interval_length()
time.sleep(0.3)
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 2
assert metrics[0]['metric'] == 'test.counter'
assert metrics[0]['points'][0][1] == 0
assert metrics[1]['metric'] == 'test.gauge'
assert metrics[1]['points'][0][1] == 5
# flush without waiting - should get nothing
metrics = self.sort_metrics(stats.flush())
assert not metrics, str(metrics)
self.sleep_for_interval_length()
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 1
assert metrics[0]['metric'] == 'test.counter'
assert metrics[0]['points'][0][1] == 0
# Now sleep for longer than the expiry window and ensure
# no points are submitted
self.sleep_for_interval_length()
time.sleep(2)
m = stats.flush()
assert not m, str(m)
# If we submit again, we're all good.
stats.submit_packets('test.counter:123|c')
stats.submit_packets('test.gauge:55|g')
stats.submit_packets('test.set:44|s')
stats.submit_packets('test.histogram:11|h')
self.sleep_for_interval_length()
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 9
assert metrics[0]['metric'] == 'test.counter'
assert metrics[0]['points'][0][1] == 123
