def test_monokey_batching_notags(self):
# The min is not enabled by default
stats = MetricsAggregator(
'host',
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES+['min']
)
stats.submit_packets('test_hist:0.3|ms:2.5|ms|@0.5:3|ms')
stats_ref = MetricsAggregator(
'host',
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES+['min']
)
packets = [
'test_hist:0.3|ms',
'test_hist:2.5|ms|@0.5',
'test_hist:3|ms'
]
stats_ref.submit_packets("\n".join(packets))
metrics = stats.flush()
metrics_ref = stats_ref.flush()
self.assertTrue(len(metrics) == len(metrics_ref) == 6, (metrics, metrics_ref))
for i in range(len(metrics)):
nt.assert_equal(metrics[i]['points'][0][1], metrics_ref[i]['points'][0][1])
def test_custom_single_percentile(self):
configstr = '0.40'
stats = MetricsAggregator(
'myhost',
histogram_percentiles=get_histogram_percentiles(configstr)
)
self.assertEquals(
stats.metric_config[Histogram]['percentiles'],
[0.40],
stats.metric_config[Histogram]
)
for i in xrange(20):
stats.submit_packets('myhistogram:{0}|h'.format(i))
metrics = stats.flush()
self.assertEquals(len(metrics), 5, metrics)
value_by_type = {}
for k in metrics:
value_by_type[k[0][len('myhistogram')+1:]] = k[2]
self.assertEquals(value_by_type['40percentile'], 7, value_by_type)
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_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())
nt.assert_equal(len(metrics), 5)
p95, pavg, pcount, pmax, pmed = self.sort_metrics(metrics)
nt.assert_equal(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(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_custom_aggregate(self):
configstr = 'median, max'
stats = MetricsAggregator(
'myhost',
histogram_aggregates=get_histogram_aggregates(configstr)
)
self.assertEquals(
sorted(stats.metric_config[Histogram]['aggregates']),
['max', 'median'],
stats.metric_config[Histogram]
)
for i in xrange(20):
stats.submit_packets('myhistogram:{0}|h'.format(i))
metrics = stats.flush()
self.assertEquals(len(metrics), 3, metrics)
value_by_type = {}
for k in metrics:
value_by_type[k['metric'][len('myhistogram')+1:]] = k['points'][0][1]
self.assertEquals(value_by_type['median'], 9, value_by_type)
self.assertEquals(value_by_type['max'], 19, value_by_type)
self.assertEquals(value_by_type['95percentile'], 18, value_by_type)
def test_custom_multiple_percentile(self):
configstr = '0.4, 0.65, 0.999'
stats = MetricsAggregator(
'myhost',
histogram_percentiles=get_histogram_percentiles(configstr)
)
self.assertEquals(
stats.metric_config[Histogram]['percentiles'],
[0.4, 0.65, 0.99],
stats.metric_config[Histogram]
)
for i in xrange(20):
stats.submit_packets('myhistogram:{0}|h'.format(i))
metrics = stats.flush()
self.assertEquals(len(metrics), 7, metrics)
value_by_type = {}
for k in metrics:
value_by_type[k['metric'][len('myhistogram')+1:]] = k['points'][0][1]
self.assertEquals(value_by_type['40percentile'], 7, value_by_type)
self.assertEquals(value_by_type['65percentile'], 12, value_by_type)
self.assertEquals(value_by_type['99percentile'], 19, value_by_type)
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_histogram(self):
# The min is not enabled by default
stats = MetricsAggregator(
'myhost',
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES+['min']
)
# 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())
nt.assert_equal(len(metrics), 6)
p95, pavg, pcount, pmax, pmed, pmin = self.sort_metrics(metrics)
nt.assert_equal(p95[0], 'my.p.95percentile')
self.assert_almost_equal(p95[2], 95, 10)
self.assert_almost_equal(pmax[2], 99, 1)
self.assert_almost_equal(pmed[2], 50, 2)
self.assert_almost_equal(pavg[2], 50, 2)
self.assert_almost_equal(pmin[2], 1, 1)
self.assert_almost_equal(pcount[2], 4000, 0) # 100 * 20 * 2
nt.assert_equals(p95[3]['hostname'], 'myhost')
# Ensure that histograms are reset.
metrics = self.sort_metrics(stats.flush())
assert not metrics
def test_monokey_batching_withtags_with_sampling(self):
# The min is not enabled by default
stats = MetricsAggregator(
'host',
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES+['min']
)
stats.submit_packets('test_metric:1.5|c|#tag1:one,tag2:two:2.3|g|#tag3:three:3|g:42|h|#tag1:12,tag42:42|@0.22')
stats_ref = MetricsAggregator(
'host',
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES+['min']
)
packets = [
'test_metric:1.5|c|#tag1:one,tag2:two',
'test_metric:2.3|g|#tag3:three',
'test_metric:3|g',
'test_metric:42|h|#tag1:12,tag42:42|@0.22'
]
stats_ref.submit_packets("\n".join(packets))
metrics = self.sort_metrics(stats.flush())
metrics_ref = self.sort_metrics(stats_ref.flush())
self.assertTrue(len(metrics) == len(metrics_ref) == 9, (metrics, metrics_ref))
for i in range(len(metrics)):
nt.assert_equal(metrics[i]['points'][0][1], metrics_ref[i]['points'][0][1])
nt.assert_equal(metrics[i]['tags'], metrics_ref[i]['tags'])
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_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_diagnostic_stats(self):
stats = MetricsAggregator("myhost")
for i in xrange(10):
stats.submit_packets("metric:10|c")
stats.send_packet_count("datadog.dogstatsd.packet.count")
metrics = self.sort_metrics(stats.flush())
nt.assert_equals(2, len(metrics))
first, second = metrics
nt.assert_equal(first["metric"], "datadog.dogstatsd.packet.count")
nt.assert_equal(first["points"][0][1], 10)
def test_diagnostic_stats(self):
stats = MetricsAggregator('myhost')
for i in xrange(10):
stats.submit_packets('metric:10|c')
stats.send_packet_count('datadog.dogstatsd.packet.count')
metrics = self.sort_metrics(stats.flush())
nt.assert_equals(2, len(metrics))
first, second = metrics
nt.assert_equal(first['metric'], 'datadog.dogstatsd.packet.count')
nt.assert_equal(first['points'][0][1], 10)
def test_ignore_distribution(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('my.dist:5.0|d')
stats.submit_packets('my.gauge:1|g')
# Assert that it's treated normally, and that the distribution is ignored
metrics = stats.flush()
nt.assert_equal(len(metrics), 1)
m = metrics[0]
nt.assert_equal(m['metric'], 'my.gauge')
nt.assert_equal(m['points'][0][1], 1)
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_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_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["tags"], 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["tags"], ("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["tags"], ("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["tags"]
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["msg_title"], "title1")
nt.assert_equal(first["msg_text"], "text")
nt.assert_equal(second["msg_title"], "title2")
nt.assert_equal(second["msg_text"], "text")
nt.assert_equal(second["tags"], sorted(["t1"]))
nt.assert_equal(third["msg_title"], "title3")
nt.assert_equal(third["msg_text"], "text")
nt.assert_equal(third["tags"], sorted(["t1", "t2:v2", "t3", "t4"]))
nt.assert_equal(fourth["msg_title"], "title4")
nt.assert_equal(fourth["msg_text"], "text")
nt.assert_equal(fourth["aggregation_key"], "key")
nt.assert_equal(fourth["priority"], "normal")
nt.assert_equal(fourth["tags"], sorted(["t1", "t2"]))
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['tags']
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['msg_title'], 'title1')
nt.assert_equal(first['msg_text'], 'text')
nt.assert_equal(second['msg_title'], 'title2')
nt.assert_equal(second['msg_text'], 'text')
nt.assert_equal(second['tags'], sorted(['t1']))
nt.assert_equal(third['msg_title'], 'title3')
nt.assert_equal(third['msg_text'], 'text')
nt.assert_equal(third['tags'], sorted(['t1', 't2:v2', 't3', 't4']))
nt.assert_equal(fourth['msg_title'], 'title4')
nt.assert_equal(fourth['msg_text'], 'text')
nt.assert_equal(fourth['aggregation_key'], 'key')
nt.assert_equal(fourth['priority'], 'normal')
nt.assert_equal(fourth['tags'], sorted(['t1', 't2']))
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['tags'], 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['tags'], ('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['tags'], ('tag3', 'tag4'))
nt.assert_equal(third['points'][0][1], 16)
nt.assert_equal(third['host'], 'myhost')
def test_magic_tags(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('my.gauge.a:1|c|#host:test-a')
stats.submit_packets('my.gauge.b:4|c|#tag1,tag2,host:test-b')
stats.submit_packets('my.gauge.b:8|c|#host:test-b,tag2,tag1')
stats.submit_packets('my.gauge.c:10|c|#tag3')
stats.submit_packets('my.gauge.c:16|c|#device:floppy,tag3')
metrics = self.sort_metrics(stats.flush())
nt.assert_equal(len(metrics), 4)
first, second, third, fourth = metrics
nt.assert_equal(first['metric'], 'my.gauge.a')
nt.assert_equal(first['tags'], None)
nt.assert_equal(first['points'][0][1], 1)
nt.assert_equal(first['host'], 'test-a')
nt.assert_equal(second['metric'], 'my.gauge.b')
nt.assert_equal(second['tags'], ('tag1', 'tag2'))
nt.assert_equal(second['points'][0][1], 12)
nt.assert_equal(second['host'], 'test-b')
nt.assert_equal(third['metric'], 'my.gauge.c')
nt.assert_equal(third['tags'], ('tag3', ))
nt.assert_equal(third['points'][0][1], 10)
nt.assert_equal(third['device_name'], None)
nt.assert_equal(fourth['metric'], 'my.gauge.c')
nt.assert_equal(fourth['tags'], ('tag3', ))
nt.assert_equal(fourth['points'][0][1], 16)
nt.assert_equal(fourth['device_name'], 'floppy')
def test_service_check_tags(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('_sc|check.1|0')
stats.submit_packets('_sc|check.2|0|#t1')
stats.submit_packets('_sc|check.3|0|h:i-abcd1234|#t1,t2|m:fakeout#t5')
stats.submit_packets('_sc|check.4|0|#t1,t2:v2,t3,t4')
service_checks = self.sort_service_checks(stats.flush_service_checks())
assert len(service_checks) == 4
first, second, third, fourth = service_checks
nt.assert_equal(first['check'], 'check.1')
assert first.get('tags') is None, "service_check['tags'] shouldn't be" + \
"defined when no tags aren't explicited in the packet"
nt.assert_equal(second['check'], 'check.2')
nt.assert_equal(second['tags'], sorted(['t1']))
nt.assert_equal(third['check'], 'check.3')
nt.assert_equal(third['host_name'], 'i-abcd1234')
nt.assert_equal(third['message'], 'fakeout#t5')
nt.assert_equal(third['tags'], sorted(['t1', 't2']))
nt.assert_equal(fourth['check'], 'check.4')
nt.assert_equal(fourth['tags'], sorted(['t1', 't2:v2', 't3', 't4']))
def test_event_text_utf8(self):
stats = MetricsAggregator('myhost', utf8_decoding=True)
# Should raise because content is not encoded
self.assertRaises(Exception, stats.submit_packets, u'_e{2,19}:t4|♬ †øU †øU ¥ºu T0µ ♪')
stats.submit_packets(u'_e{2,19}:t4|♬ †øU †øU ¥ºu T0µ ♪'.encode('utf-8')) # utf-8 compliant
# Normal packet
stats.submit_packets('_e{2,23}:t3|First line\\nSecond line') # \n is a newline
events = self.sort_events(stats.flush_events())
assert len(events) == 2
nt.assert_equal(events[0]['msg_text'], 'First line\nSecond line')
nt.assert_equal(events[1]['msg_text'], u'♬ †øU †øU ¥ºu T0µ ♪')
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[2] == 2
assert gauge[2] == 1
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_sampled_histogram(self):
# Submit a sampled histogram.
# The min is not enabled by default
stats = MetricsAggregator(
'myhost',
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES+['min']
)
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, pmin = self.sort_metrics(metrics)
nt.assert_equal(pcount['points'][0][1], 2)
for p in [p95, pavg, pmed, pmax, pmin]:
nt.assert_equal(p['points'][0][1], 5)
def test_monokey_batching_withtags(self):
stats = MetricsAggregator('host')
stats.submit_packets(
'test_gauge:1.5|g|#tag1:one,tag2:two:2.3|g|#tag3:three:3|g')
stats_ref = MetricsAggregator('host')
packets = [
'test_gauge:1.5|g|#tag1:one,tag2:two',
'test_gauge:2.3|g|#tag3:three', 'test_gauge:3|g'
]
stats_ref.submit_packets("\n".join(packets))
metrics = self.sort_metrics(stats.flush())
metrics_ref = self.sort_metrics(stats_ref.flush())
self.assertTrue(
len(metrics) == len(metrics_ref) == 3, (metrics, metrics_ref))
for i in range(len(metrics)):
nt.assert_equal(metrics[i]['points'][0][1],
metrics_ref[i]['points'][0][1])
nt.assert_equal(metrics[i]['tags'], metrics_ref[i]['tags'])
def test_monokey_batching_notags(self):
# The min is not enabled by default
stats = MetricsAggregator(
'host',
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES + ['min'])
stats.submit_packets('test_hist:0.3|ms:2.5|ms|@0.5:3|ms')
stats_ref = MetricsAggregator(
'host',
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES + ['min'])
packets = [
'test_hist:0.3|ms', 'test_hist:2.5|ms|@0.5', 'test_hist:3|ms'
]
stats_ref.submit_packets('\n'.join(packets))
metrics = stats.flush()[:-1]
metrics_ref = stats_ref.flush()[:-1]
assert len(metrics) == len(metrics_ref) == 6
for i in range(len(metrics)):
assert metrics[i]['points'][0][1] == metrics_ref[i]['points'][0][1]
def test_monokey_batching_notags(self):
# The min is not enabled by default
stats = MetricsAggregator(
'host',
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES + ['min'])
stats.submit_packets('test_hist:0.3|ms:2.5|ms|@0.5:3|ms')
stats_ref = MetricsAggregator(
'host',
histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES + ['min'])
packets = [
'test_hist:0.3|ms', 'test_hist:2.5|ms|@0.5', 'test_hist:3|ms'
]
stats_ref.submit_packets("\n".join(packets))
metrics = stats.flush()
metrics_ref = stats_ref.flush()
self.assertTrue(
len(metrics) == len(metrics_ref) == 6, (metrics, metrics_ref))
for i in range(len(metrics)):
nt.assert_equal(metrics[i][2], metrics_ref[i][2])
def test_custom_aggregate(self):
configstr = 'median, max'
stats = MetricsAggregator(
'myhost', histogram_aggregates=get_histogram_aggregates(configstr))
self.assertEquals(sorted(stats.metric_config[Histogram]['aggregates']),
['max', 'median'], stats.metric_config[Histogram])
for i in xrange(20):
stats.submit_packets('myhistogram:{0}|h'.format(i))
metrics = stats.flush()
self.assertEquals(len(metrics), 3, metrics)
value_by_type = {}
for k in metrics:
value_by_type[k['metric'][len('myhistogram') +
1:]] = k['points'][0][1]
self.assertEquals(value_by_type['median'], 9, value_by_type)
self.assertEquals(value_by_type['max'], 19, value_by_type)
self.assertEquals(value_by_type['95percentile'], 18, value_by_type)
def test_default(self):
stats = MetricsAggregator('myhost')
for i in xrange(20):
stats.submit_packets('myhistogram:{0}|h'.format(i))
metrics = stats.flush()
self.assertEquals(len(metrics), 5, metrics)
value_by_type = {}
for k in metrics:
value_by_type[k[0][len('myhistogram') + 1:]] = k[2]
self.assertEquals(sorted(value_by_type.keys()),
['95percentile', 'avg', 'count', 'max', 'median'],
value_by_type)
self.assertEquals(value_by_type['max'], 19, value_by_type)
self.assertEquals(value_by_type['median'], 9, value_by_type)
self.assertEquals(value_by_type['avg'], 9.5, value_by_type)
self.assertEquals(value_by_type['count'], 20.0, value_by_type)
self.assertEquals(value_by_type['95percentile'], 18, value_by_type)
def test_default(self):
stats = MetricsAggregator('myhost')
for i in xrange(20):
stats.submit_packets('myhistogram:{0}|h'.format(i))
metrics = stats.flush()
assert len(metrics) == 5
value_by_type = {}
for k in metrics:
value_by_type[k['metric'][len('myhistogram') +
1:]] = k['points'][0][1]
assert sorted(value_by_type.keys()) == \
['95percentile', 'avg', 'count', 'max', 'median']
assert value_by_type['max'] == 19
assert value_by_type['median'] == 9
assert value_by_type['avg'] == 9.5
assert value_by_type['count'] == 20.0
assert value_by_type['95percentile'] == 18
def test_custom_multiple_percentile(self):
configstr = '0.4, 0.65, 0.999'
stats = MetricsAggregator(
'myhost',
histogram_percentiles=get_histogram_percentiles(configstr))
self.assertEquals(stats.metric_config[Histogram]['percentiles'],
[0.4, 0.65, 0.99], stats.metric_config[Histogram])
for i in xrange(20):
stats.submit_packets('myhistogram:{0}|h'.format(i))
metrics = stats.flush()
self.assertEquals(len(metrics), 7, metrics)
value_by_type = {}
for k in metrics:
value_by_type[k[0][len('myhistogram') + 1:]] = k[2]
self.assertEquals(value_by_type['40percentile'], 7, value_by_type)
self.assertEquals(value_by_type['65percentile'], 12, value_by_type)
self.assertEquals(value_by_type['99percentile'], 19, value_by_type)
def test_rate_errors(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('my.rate:10|_dd-r')
# Sleep 1 second so the time interval > 0 (timestamp is converted to an int)
time.sleep(1)
stats.submit_packets('my.rate:9|_dd-r')
# Since the difference < 0 we shouldn't get a value
metrics = stats.flush()
nt.assert_equal(len(metrics), 0)
stats.submit_packets('my.rate:10|_dd-r')
# Trying to have the times be the same
stats.submit_packets('my.rate:40|_dd-r')
metrics = stats.flush()
nt.assert_equal(len(metrics), 0)
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_event_title(self):
stats = MetricsAggregator('myhost', utf8_decoding=True)
stats.submit_packets('_e{0,4}:|text')
stats.submit_packets(u'_e{9,4}:2intitulé|text'.encode('utf-8')) # comes from socket
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
nt.assert_equal(events[0]['msg_title'], '')
nt.assert_equal(events[1]['msg_title'], u'2intitulé')
nt.assert_equal(events[2]['msg_title'], '3title content')
nt.assert_equal(events[3]['msg_title'], '4title|content')
nt.assert_equal(events[4]['msg_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['msg_text'], '')
nt.assert_equal(second['msg_text'], 'text|content')
nt.assert_equal(third['msg_text'], 'First line\nSecond line')
nt.assert_equal(fourth['msg_text'], u'♬ †øU †øU ¥ºu T0µ ♪')
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_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_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()
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()
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['msg_title'], '')
nt.assert_equal(second['msg_title'], u'2intitulé')
nt.assert_equal(third['msg_title'], '3title content')
nt.assert_equal(fourth['msg_title'], '4title|content')
nt.assert_equal(fifth['msg_title'], '5title\\ntitle')
def test_ignore_distribution(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('my.dist:5.0|d')
stats.submit_packets('my.other.dist:5.0|dk')
stats.submit_packets('my.gauge:1|g')
# Assert that it's treated normally, and that the distribution is ignored
metrics = stats.flush()
assert len(metrics) == 2
m = metrics[0]
assert m['metric'] == 'my.gauge'
assert m['points'][0][1] == 1
def test_ignore_distribution(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('my.dist:5.0|d')
stats.submit_packets('my.other.dist:5.0|dk')
stats.submit_packets('my.gauge:1|g')
# Assert that it's treated normally, and that the distribution is ignored
metrics = stats.flush()
nt.assert_equal(len(metrics), 1)
m = metrics[0]
nt.assert_equal(m['metric'], 'my.gauge')
nt.assert_equal(m['points'][0][1], 1)
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
events = self.sort_events(stats.flush_events())
assert len(events) == 3
nt.assert_equal(events[0]['msg_text'], '')
nt.assert_equal(events[1]['msg_text'], 'text|content')
nt.assert_equal(events[2]['msg_text'], 'First line\nSecond line')
def test_service_check_message(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('_sc|check.1|0|m:testing')
stats.submit_packets('_sc|check.2|0|m:First line\\nSecond line')
stats.submit_packets(u'_sc|check.3|0|m:♬ †øU †øU ¥ºu T0µ ♪')
stats.submit_packets('_sc|check.4|0|m:|t:|m\:|d:')
service_checks = self.sort_service_checks(stats.flush_service_checks())
assert len(service_checks) == 4
first, second, third, fourth = service_checks
nt.assert_equal(first['check'], 'check.1')
nt.assert_equal(first['message'], 'testing')
nt.assert_equal(second['check'], 'check.2')
nt.assert_equal(second['message'], 'First line\nSecond line')
nt.assert_equal(third['check'], 'check.3')
nt.assert_equal(third['message'], u'♬ †øU †øU ¥ºu T0µ ♪')
nt.assert_equal(fourth['check'], 'check.4')
nt.assert_equal(fourth['message'], '|t:|m:|d:')
def test_service_check_message(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('_sc|check.1|0|m:testing')
stats.submit_packets('_sc|check.2|0|m:First line\\nSecond line')
stats.submit_packets('_sc|check.3|0|m:♬ †øU †øU ¥ºu T0µ ♪')
stats.submit_packets(r'_sc|check.4|0|m:|t:|m\:|d:')
service_checks = self.sort_service_checks(stats.flush_service_checks())
assert len(service_checks) == 4
first, second, third, fourth = service_checks
assert first['check'] == 'check.1'
assert first['message'] == 'testing'
assert second['check'] == 'check.2'
assert second['message'] == 'First line\nSecond line'
assert third['check'] == 'check.3'
assert third['message'] == '♬ †øU †øU ¥ºu T0µ ♪'
assert fourth['check'] == 'check.4'
assert fourth['message'] == '|t:|m:|d:'
def test_event_text_utf8(self):
stats = MetricsAggregator('myhost', utf8_decoding=True)
# Should raise because content is not encoded
with pytest.raises(Exception):
stats.submit_packets(u'_e{2,19}:t4|♬ †øU †øU ¥ºu T0µ ♪')
stats.submit_packets(u'_e{2,19}:t4|♬ †øU †øU ¥ºu T0µ ♪'.encode('utf-8')) # utf-8 compliant
# Normal packet
stats.submit_packets('_e{2,23}:t3|First line\\nSecond line') # \n is a newline
events = self.sort_events(stats.flush_events())
assert len(events) == 2
assert events[0]['msg_text'] == 'First line\nSecond line'
assert events[1]['msg_text'] == u'♬ †øU †øU ¥ºu T0µ ♪'
def test_sets(self):
stats = MetricsAggregator('myhost')
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')
# Assert that it's treated normally.
metrics = stats.flush()
nt.assert_equal(len(metrics), 1)
m = metrics[0]
nt.assert_equal(m[0], 'my.set')
nt.assert_equal(m[2], 3)
# Assert there are no more sets
assert not stats.flush()
def test_packet_string_endings(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('line_ending.generic:500|c')
stats.submit_packets('line_ending.unix:400|c\n')
stats.submit_packets('line_ending.windows:300|c\r\n')
metrics = self.sort_metrics(stats.flush()[:-1])
assert len(metrics) == 3
first, second, third = metrics
assert first['metric'] == 'line_ending.generic'
assert first['points'][0][1] == 500
assert second['metric'] == 'line_ending.unix'
assert second['points'][0][1] == 400
assert third['metric'] == 'line_ending.windows'
assert third['points'][0][1] == 300
def test_service_check_tag_key_ends_with_m(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('_sc|check.1|0|#keym:value')
stats.submit_packets('_sc|check.2|0|#key2m:value|m:fakeout')
stats.submit_packets('_sc|check.3|0|#key:valuem:value2,key2:value2|m:fakeoutm\:|h:#5')
service_checks = self.sort_service_checks(stats.flush_service_checks())
assert len(service_checks) == 3
first, second, third = service_checks
assert first['check'] == 'check.1'
assert first['tags'] == ['keym:value']
assert 'message' not in first
assert second['check'] == 'check.2'
assert second['tags'] == ['key2m:value']
assert second['message'] == 'fakeout'
assert third['check'] == 'check.3'
assert third['tags'] == sorted(['key:valuem:value2', 'key2:value2'])
assert third['message'] == 'fakeoutm:|h:#5'
def test_packet_string_endings(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('line_ending.generic:500|c')
stats.submit_packets('line_ending.unix:400|c\n')
stats.submit_packets('line_ending.windows:300|c\r\n')
metrics = self.sort_metrics(stats.flush())
assert len(metrics) == 3
first, second, third = metrics
nt.assert_equals(first['metric'], 'line_ending.generic')
nt.assert_equals(first['points'][0][1], 500)
nt.assert_equals(second['metric'], 'line_ending.unix')
nt.assert_equals(second['points'][0][1], 400)
nt.assert_equals(third['metric'], 'line_ending.windows')
nt.assert_equals(third['points'][0][1], 300)
def test_service_check_tag_key_ends_with_m(self):
stats = MetricsAggregator('myhost')
stats.submit_packets('_sc|check.1|0|#keym:value')
stats.submit_packets('_sc|check.2|0|#key2m:value|m:fakeout')
stats.submit_packets('_sc|check.3|0|#key:valuem:value2,key2:value2|m:fakeoutm\:|h:#5')
service_checks = self.sort_service_checks(stats.flush_service_checks())
assert len(service_checks) == 3
first, second, third = service_checks
nt.assert_equal(first['check'], 'check.1')
nt.assert_equal(first['tags'], ['keym:value'])
#nt.assert_not_in('message', first)
nt.assert_equal(second['check'], 'check.2')
nt.assert_equal(second['tags'], ['key2m:value'])
nt.assert_equal(second['message'], 'fakeout')
nt.assert_equal(third['check'], 'check.3')
nt.assert_equal(third['tags'], sorted(['key:valuem:value2', 'key2:value2']))
nt.assert_equal(third['message'], 'fakeoutm:|h:#5')
def test_sets(self):
stats = MetricsAggregator('myhost')
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')
# Assert that it's treated normally.
metrics = stats.flush()
assert len(metrics) == 2
m = metrics[0]
assert m['metric'] == 'my.set'
assert m['points'][0][1] == 3
# Assert there are no more sets
metrics = stats.flush()
assert len(metrics) == 1
assert metrics[0]['metric'] == 'datadog.agent.running'
def test_formatter(self):
stats = MetricsAggregator('myhost', interval=10,
formatter = get_formatter({"statsd_metric_namespace": "datadog"}))
stats.submit_packets('gauge:16|c|#tag3,tag4')
metrics = self.sort_metrics(stats.flush())
self.assertTrue(len(metrics) == 1)
self.assertTrue(metrics[0]['metric'] == "datadog.gauge")
stats = MetricsAggregator('myhost', interval=10,
formatter = get_formatter({"statsd_metric_namespace": "datadoge."}))
stats.submit_packets('gauge:16|c|#tag3,tag4')
metrics = self.sort_metrics(stats.flush())
self.assertTrue(len(metrics) == 1)
self.assertTrue(metrics[0]['metric'] == "datadoge.gauge")
stats = MetricsAggregator('myhost', interval=10,
formatter = get_formatter({"statsd_metric_namespace": None}))
stats.submit_packets('gauge:16|c|#tag3,tag4')
metrics = self.sort_metrics(stats.flush())
self.assertTrue(len(metrics) == 1)
self.assertTrue(metrics[0]['metric'] == "gauge")
def test_formatter(self):
stats = MetricsAggregator('myhost', interval=10,
formatter=get_formatter({'dogstatsd': {'metric_namespace': 'datadog'}}))
stats.submit_packets('gauge:16|c|#tag3,tag4')
metrics = self.sort_metrics(stats.flush()[:-1])
assert (len(metrics) == 1)
assert (metrics[0]['metric'] == 'datadog.gauge')
stats = MetricsAggregator('myhost', interval=10,
formatter=get_formatter({'dogstatsd': {'metric_namespace': 'datadoge'}}))
stats.submit_packets('gauge:16|c|#tag3,tag4')
metrics = self.sort_metrics(stats.flush()[:-1])
assert (len(metrics) == 1)
assert (metrics[0]['metric'] == 'datadoge.gauge')
stats = MetricsAggregator('myhost', interval=10,
formatter=get_formatter({'dogstatsd': {'metric_namespace': None}}))
stats.submit_packets('gauge:16|c|#tag3,tag4')
metrics = self.sort_metrics(stats.flush()[:-1])
assert (len(metrics) == 1)
assert (metrics[0]['metric'] == 'gauge')
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')
