def test_tags(self): stats = MetricsAggregator('myhost') 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') metrics = self.sort_metrics(stats.flush()) assert len(metrics) == 3 first, second, third = metrics nt.assert_equal(first['metric'], 'gauge') nt.assert_equal(first['dimensions'], None) nt.assert_equal(first['points'][0][1], 3) nt.assert_equal(first['host'], 'myhost') nt.assert_equal(second['metric'], 'gauge') nt.assert_equal(second['dimensions'], ('tag1', 'tag2')) nt.assert_equal(second['points'][0][1], 12) nt.assert_equal(second['host'], 'myhost') nt.assert_equal(third['metric'], 'gauge') nt.assert_equal(third['dimensions'], ('tag3', 'tag4')) nt.assert_equal(third['points'][0][1], 16) nt.assert_equal(third['host'], 'myhost')
def test_histogram(self): stats = MetricsAggregator('myhost') # 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) metrics = self.sort_metrics(stats.flush()) def assert_almost_equal(i, j, e=1): # Floating point math? assert abs(i - j) <= e, "%s %s %s" % (i, j, e) nt.assert_equal(len(metrics), 5) p95, pavg, pcount, pmax, pmed = self.sort_metrics(metrics) nt.assert_equal(p95['metric'], 'my.p.95percentile') assert_almost_equal(p95['points'][0][1], 95, 10) assert_almost_equal(pmax['points'][0][1], 99, 1) assert_almost_equal(pmed['points'][0][1], 50, 2) assert_almost_equal(pavg['points'][0][1], 50, 2) assert_almost_equal(pcount['points'][0][1], 4000, 0) # 100 * 20 * 2 nt.assert_equals(p95['host'], 'myhost') # Ensure that histograms are reset. metrics = self.sort_metrics(stats.flush()) assert not metrics
def test_gauge(self): stats = MetricsAggregator('myhost') # 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. metrics = self.sort_metrics(stats.flush()) assert len(metrics) == 2 first, second = metrics nt.assert_equals(first['metric'], 'my.first.gauge') nt.assert_equals(first['points'][0][1], 5) nt.assert_equals(first['host'], 'myhost') nt.assert_equals(second['metric'], 'my.second.gauge') nt.assert_equals(second['points'][0][1], 1.5) # Ensure that old gauges get dropped due to old timestamps stats.gauge('my.first.gauge', 5) stats.gauge('my.first.gauge', 1, timestamp=1000000000) stats.gauge('my.second.gauge', 20, timestamp=1000000000) metrics = self.sort_metrics(stats.flush()) assert len(metrics) == 1 first = metrics[0] nt.assert_equals(first['metric'], 'my.first.gauge') nt.assert_equals(first['points'][0][1], 5) nt.assert_equals(first['host'], 'myhost')
def test_scientific_notation(self): stats = MetricsAggregator('myhost', interval=10) stats.submit_packets('test.scinot:9.512901e-05|g') metrics = self.sort_metrics(stats.flush()) assert len(metrics) == 1 ts, val = metrics[0].get('points')[0] nt.assert_almost_equal(val, 9.512901e-05)
def test_sampled_counter(self): # Submit a sampled counter. stats = MetricsAggregator('myhost') stats.submit_packets('sampled.counter:1|c|@0.5') metrics = stats.flush() assert len(metrics) == 1 m = metrics[0] assert m['metric'] == 'sampled.counter' nt.assert_equal(m['points'][0][1], 2)
def test_batch_submission(self): # Submit a sampled histogram. stats = MetricsAggregator('myhost') metrics = ['counter:1|c', 'counter:1|c', 'gauge:1|g'] packet = "\n".join(metrics) stats.submit_packets(packet) metrics = self.sort_metrics(stats.flush()) nt.assert_equal(2, len(metrics)) counter, gauge = metrics assert counter['points'][0][1] == 2 assert gauge['points'][0][1] == 1
def test_sampled_histogram(self): # Submit a sampled histogram. stats = MetricsAggregator('myhost') stats.submit_packets('sampled.hist:5|h|@0.5') # Assert we scale up properly. metrics = self.sort_metrics(stats.flush()) p95, pavg, pcount, pmax, pmed = self.sort_metrics(metrics) nt.assert_equal(pcount['points'][0][1], 2) for p in [p95, pavg, pmed, pmax]: nt.assert_equal(p['points'][0][1], 5)
def test_histogram_normalization(self): stats = MetricsAggregator('myhost', interval=10) for i in range(5): stats.submit_packets('h1:1|h') for i in range(20): stats.submit_packets('h2:1|h') metrics = self.sort_metrics(stats.flush()) _, _, h1count, _, _, _, _, h2count, _, _ = metrics nt.assert_equal(h1count['points'][0][1], 0.5) nt.assert_equal(h2count['points'][0][1], 2)
def test_gauge_sample_rate(self): stats = MetricsAggregator('myhost') # Submit a sampled gauge metric. stats.submit_packets('sampled.gauge:10|g|@0.1') # Assert that it's treated normally. metrics = stats.flush() nt.assert_equal(len(metrics), 1) m = metrics[0] nt.assert_equal(m['metric'], 'sampled.gauge') nt.assert_equal(m['points'][0][1], 10)
def test_tags(self): stats = MetricsAggregator('myhost') 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') metrics = self.sort_metrics(stats.flush()) assert len(metrics) == 3 first, second, third = metrics nt.assert_equal(first['metric'], 'gauge') nt.assert_equal(first['dimensions'], None) nt.assert_equal(first['points'][0][1], 3) nt.assert_equal(first['host'], 'myhost') nt.assert_equal(second['metric'], 'gauge') nt.assert_equal(second['dimensions'], ('tag1', 'tag2')) nt.assert_equal(second['points'][0][1], 12) nt.assert_equal(second['host'], 'myhost') nt.assert_equal(third['metric'], 'gauge') nt.assert_equal(third['dimensions'], ('tag3', 'tag4')) nt.assert_equal(third['points'][0][1], 16) nt.assert_equal(third['host'], 'myhost')
def test_event_tags(self): stats = MetricsAggregator('myhost') stats.submit_packets('_e{6,4}:title1|text') stats.submit_packets('_e{6,4}:title2|text|#t1') stats.submit_packets('_e{6,4}:title3|text|#t1,t2:v2,t3,t4') stats.submit_packets('_e{6,4}:title4|text|k:key|p:normal|#t1,t2') events = self.sort_events(stats.flush_events()) assert len(events) == 4 first, second, third, fourth = events try: first['dimensions'] except Exception: assert True else: assert False, "event['tags'] shouldn't be defined when no tags aren't explicited in the packet" nt.assert_equal(first['title'], 'title1') nt.assert_equal(first['text'], 'text') nt.assert_equal(second['title'], 'title2') nt.assert_equal(second['text'], 'text') nt.assert_equal(second['dimensions'], sorted(['t1'])) nt.assert_equal(third['title'], 'title3') nt.assert_equal(third['text'], 'text') nt.assert_equal(third['dimensions'], sorted(['t1', 't2:v2', 't3', 't4'])) nt.assert_equal(fourth['title'], 'title4') nt.assert_equal(fourth['text'], 'text') nt.assert_equal(fourth['aggregation_key'], 'key') nt.assert_equal(fourth['priority'], 'normal') nt.assert_equal(fourth['dimensions'], sorted(['t1', 't2']))
def test_rate(self): stats = MetricsAggregator('myhost') stats.submit_packets('my.rate:10|_dd-r') # Sleep 1 second so the time interval > 0 time.sleep(1) stats.submit_packets('my.rate:40|_dd-r') # Check that the rate is calculated correctly metrics = stats.flush() nt.assert_equal(len(metrics), 1) m = metrics[0] nt.assert_equals(m['metric'], 'my.rate') nt.assert_equals(m['points'][0][1], 30) # Assert that no more rates are given assert not stats.flush()
def test_batch_submission(self): # Submit a sampled histogram. stats = MetricsAggregator('myhost') metrics = [ 'counter:1|c', 'counter:1|c', 'gauge:1|g' ] packet = "\n".join(metrics) stats.submit_packets(packet) metrics = self.sort_metrics(stats.flush()) nt.assert_equal(2, len(metrics)) counter, gauge = metrics assert counter['points'][0][1] == 2 assert gauge['points'][0][1] == 1
def test_metrics_expiry(self): # Ensure metrics eventually expire and stop submitting. stats = MetricsAggregator('myhost', expiry_seconds=1) stats.submit_packets('test.counter:123|c') # Ensure points keep submitting assert stats.flush() assert stats.flush() time.sleep(0.5) assert stats.flush() # Now sleep for longer than the expiry window and ensure # no points are submitted 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') assert stats.flush()
def test_counter(self): stats = MetricsAggregator('myhost') # 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. metrics = self.sort_metrics(stats.flush()) assert len(metrics) == 3 first, second, third = metrics nt.assert_equals(first['metric'], 'my.first.counter') nt.assert_equals(first['points'][0][1], 6) nt.assert_equals(first['host'], 'myhost') nt.assert_equals(second['metric'], 'my.second.counter') nt.assert_equals(second['points'][0][1], 1) nt.assert_equals(third['metric'], 'my.third.counter') nt.assert_equals(third['points'][0][1], 3) # Ensure that counters reset to zero. metrics = self.sort_metrics(stats.flush()) first, second, third = metrics nt.assert_equals(first['metric'], 'my.first.counter') nt.assert_equals(first['points'][0][1], 0) nt.assert_equals(second['metric'], 'my.second.counter') nt.assert_equals(second['points'][0][1], 0) nt.assert_equals(third['metric'], 'my.third.counter') nt.assert_equals(third['points'][0][1], 0)
def test_event_text(self): stats = MetricsAggregator('myhost') stats.submit_packets('_e{2,0}:t1|') stats.submit_packets('_e{2,12}:t2|text|content') stats.submit_packets('_e{2,23}:t3|First line\\nSecond line') # \n is a newline stats.submit_packets(u'_e{2,19}:t4|♬ †øU †øU ¥ºu T0µ ♪') # utf-8 compliant events = self.sort_events(stats.flush_events()) assert len(events) == 4 first, second, third, fourth = events nt.assert_equal(first['text'], '') nt.assert_equal(second['text'], 'text|content') nt.assert_equal(third['text'], 'First line\nSecond line') nt.assert_equal(fourth['text'], u'♬ †øU †øU ¥ºu T0µ ♪')
def test_bad_packets_throw_errors(self): packets = [ 'missing.value.and.type', 'missing.type:2', 'missing.value|c', '2|c', 'unknown.type:2|z', 'string.value:abc|c', 'string.sample.rate:0|c|@abc', # Bad event-like packets '_ev{1,2}:bad_header' '_e{1,}:invalid|headers', '_e:missing|size|headers', '_e:{1,1}:t|t|t:bad_meta|h', ] stats = MetricsAggregator('myhost') for packet in packets: try: stats.submit_packets(packet) except Exception: assert True else: assert False, 'invalid : %s' % packet
def test_string_sets(self): stats = MetricsAggregator('myhost') 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. metrics = stats.flush() nt.assert_equal(len(metrics), 1) m = metrics[0] nt.assert_equal(m['metric'], 'my.set') nt.assert_equal(m['points'][0][1], 3) # Assert there are no more sets assert not stats.flush()
def test_event_title(self): stats = MetricsAggregator('myhost') stats.submit_packets('_e{0,4}:|text') stats.submit_packets(u'_e{9,4}:2intitulé|text') stats.submit_packets('_e{14,4}:3title content|text') stats.submit_packets('_e{14,4}:4title|content|text') stats.submit_packets('_e{13,4}:5title\\ntitle|text') # \n stays escaped events = self.sort_events(stats.flush_events()) assert len(events) == 5 first, second, third, fourth, fifth = events nt.assert_equal(first['title'], '') nt.assert_equal(second['title'], u'2intitulé') nt.assert_equal(third['title'], '3title content') nt.assert_equal(fourth['title'], '4title|content') nt.assert_equal(fifth['title'], '5title\\ntitle')
def test_event_text(self): stats = MetricsAggregator('myhost') stats.submit_packets('_e{2,0}:t1|') stats.submit_packets('_e{2,12}:t2|text|content') stats.submit_packets( '_e{2,23}:t3|First line\\nSecond line') # \n is a newline stats.submit_packets( u'_e{2,19}:t4|♬ †øU †øU ¥ºu T0µ ♪') # utf-8 compliant events = self.sort_events(stats.flush_events()) assert len(events) == 4 first, second, third, fourth = events nt.assert_equal(first['text'], '') nt.assert_equal(second['text'], 'text|content') nt.assert_equal(third['text'], 'First line\nSecond line') nt.assert_equal(fourth['text'], u'♬ †øU †øU ¥ºu T0µ ♪')
def test_event_title(self): stats = MetricsAggregator('myhost') stats.submit_packets('_e{0,4}:|text') stats.submit_packets(u'_e{9,4}:2intitulé|text') stats.submit_packets('_e{14,4}:3title content|text') stats.submit_packets('_e{14,4}:4title|content|text') stats.submit_packets( '_e{13,4}:5title\\ntitle|text') # \n stays escaped events = self.sort_events(stats.flush_events()) assert len(events) == 5 first, second, third, fourth, fifth = events nt.assert_equal(first['title'], '') nt.assert_equal(second['title'], u'2intitulé') nt.assert_equal(third['title'], '3title content') nt.assert_equal(fourth['title'], '4title|content') nt.assert_equal(fifth['title'], '5title\\ntitle')
def test_histogram_counter(self): # Test whether histogram.count == increment # same deal with a sample rate cnt = 100000 for run in [1, 2]: stats = MetricsAggregator('myhost') for i in xrange(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') metrics = self.sort_metrics(stats.flush()) assert len(metrics) > 0 nt.assert_equal([m['points'][0][1] for m in metrics if m['metric'] == 'test.counter'], [cnt * run]) nt.assert_equal([m['points'][0][1] for m in metrics if m['metric'] == 'test.hist.count'], [cnt * run])
def test_histogram_counter(self): # Test whether histogram.count == increment # same deal with a sample rate cnt = 100000 for run in [1, 2]: stats = MetricsAggregator('myhost') for i in xrange(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') metrics = self.sort_metrics(stats.flush()) assert len(metrics) > 0 nt.assert_equal([ m['points'][0][1] for m in metrics if m['metric'] == 'test.counter' ], [cnt * run]) nt.assert_equal([ m['points'][0][1] for m in metrics if m['metric'] == 'test.hist.count' ], [cnt * run])
def test_counter_normalization(self): stats = MetricsAggregator('myhost', interval=10) # 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') metrics = self.sort_metrics(stats.flush()) assert len(metrics) == 2 floatc, intc = metrics nt.assert_equal(floatc['metric'], 'float') nt.assert_equal(floatc['points'][0][1], 0.5) nt.assert_equal(floatc['host'], 'myhost') nt.assert_equal(intc['metric'], 'int') nt.assert_equal(intc['points'][0][1], 2) nt.assert_equal(intc['host'], 'myhost')
def test_dogstatsd_aggregation_perf(self): ma = MetricsAggregator('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()