def test_delete_old_measures(self):
self.storage.add_measures(self.metric, [
storage.Measure(datetime.datetime(2014, 1, 1, 12, 0, 1), 69),
storage.Measure(datetime.datetime(2014, 1, 1, 12, 7, 31), 42),
storage.Measure(datetime.datetime(2014, 1, 1, 12, 9, 31), 4),
storage.Measure(datetime.datetime(2014, 1, 1, 12, 12, 45), 44),
])
self.trigger_processing(self.storage, self.index)
self.assertEqual([
(utils.datetime_utc(2014, 1, 1), 86400.0, 39.75),
(utils.datetime_utc(2014, 1, 1, 12), 3600.0, 39.75),
(utils.datetime_utc(2014, 1, 1, 12), 300.0, 69.0),
(utils.datetime_utc(2014, 1, 1, 12, 5), 300.0, 23.0),
(utils.datetime_utc(2014, 1, 1, 12, 10), 300.0, 44.0),
], self.storage.get_measures(self.metric))
# One year later…
self.storage.add_measures(self.metric, [
storage.Measure(datetime.datetime(2015, 1, 1, 12, 0, 1), 69),
])
self.trigger_processing(self.storage, self.index)
self.assertEqual([
(utils.datetime_utc(2014, 1, 1), 86400.0, 39.75),
(utils.datetime_utc(2015, 1, 1), 86400.0, 69),
(utils.datetime_utc(2015, 1, 1, 12), 3600.0, 69),
(utils.datetime_utc(2015, 1, 1, 12), 300.0, 69),
], self.storage.get_measures(self.metric))
def treat_metric(self, metric_name, metric_type, value, sampling):
metric_name += "|" + metric_type
if metric_type == "ms":
if sampling is not None:
raise ValueError(
"Invalid sampling for ms: `%d`, should be none"
% sampling)
self.times[metric_name] = storage.Measure(
utils.dt_in_unix_ns(utils.utcnow()), value)
elif metric_type == "g":
if sampling is not None:
raise ValueError(
"Invalid sampling for g: `%d`, should be none"
% sampling)
self.gauges[metric_name] = storage.Measure(
utils.dt_in_unix_ns(utils.utcnow()), value)
elif metric_type == "c":
sampling = 1 if sampling is None else sampling
if metric_name in self.counters:
current_value = self.counters[metric_name].value
else:
current_value = 0
self.counters[metric_name] = storage.Measure(
utils.dt_in_unix_ns(utils.utcnow()),
current_value + (value * (1 / sampling)))
# TODO(jd) Support "set" type
# elif metric_type == "s":
# pass
else:
raise ValueError("Unknown metric type `%s'" % metric_type)
def test_get_measure_unknown_aggregation(self):
self.incoming.add_measures(self.metric, [
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 0, 1), 69),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 7, 31), 42),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 9, 31), 4),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 12, 45), 44),
])
self.assertRaises(storage.AggregationDoesNotExist,
self.storage.get_measures,
self.metric, aggregation='last')
def test_add_and_get_cross_metric_measures_with_holes(self):
metric2, __ = self._create_metric()
self.incoming.add_measures(self.metric, [
storage.Measure(datetime64(2014, 1, 1, 12, 0, 1), 69),
storage.Measure(datetime64(2014, 1, 1, 12, 7, 31), 42),
storage.Measure(datetime64(2014, 1, 1, 12, 5, 31), 8),
storage.Measure(datetime64(2014, 1, 1, 12, 9, 31), 4),
storage.Measure(datetime64(2014, 1, 1, 12, 12, 45), 42),
])
self.incoming.add_measures(metric2, [
storage.Measure(datetime64(2014, 1, 1, 12, 0, 5), 9),
storage.Measure(datetime64(2014, 1, 1, 12, 7, 31), 2),
storage.Measure(datetime64(2014, 1, 1, 12, 9, 31), 6),
storage.Measure(datetime64(2014, 1, 1, 12, 13, 10), 2),
])
self.trigger_processing([str(self.metric.id), str(metric2.id)])
values = cross_metric.get_cross_metric_measures(
self.storage, [self.metric, metric2])
self.assertEqual([(datetime64(2014, 1, 1, 0, 0,
0), numpy.timedelta64(1, 'D'), 18.875),
(datetime64(2014, 1, 1, 12, 0,
0), numpy.timedelta64(1, 'h'), 18.875),
(datetime64(2014, 1, 1, 12, 0,
0), numpy.timedelta64(5, 'm'), 39.0),
(datetime64(2014, 1, 1, 12, 5,
0), numpy.timedelta64(5, 'm'), 11.0),
(datetime64(2014, 1, 1, 12, 10,
0), numpy.timedelta64(5, 'm'), 22.0)],
values)
def test_add_and_get_cross_metric_measures_with_holes(self):
metric2, __ = self._create_metric()
self.incoming.add_measures(self.metric, [
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 0, 1), 69),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 7, 31), 42),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 5, 31), 8),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 9, 31), 4),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 12, 45), 42),
])
self.incoming.add_measures(metric2, [
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 0, 5), 9),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 7, 31), 2),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 9, 31), 6),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 13, 10), 2),
])
self.trigger_processing([str(self.metric.id), str(metric2.id)])
values = self.storage.get_cross_metric_measures([self.metric, metric2])
self.assertEqual([
(utils.datetime_utc(2014, 1, 1, 0, 0, 0), 86400.0, 18.875),
(utils.datetime_utc(2014, 1, 1, 12, 0, 0), 3600.0, 18.875),
(utils.datetime_utc(2014, 1, 1, 12, 0, 0), 300.0, 39.0),
(utils.datetime_utc(2014, 1, 1, 12, 5, 0), 300.0, 11.0),
(utils.datetime_utc(2014, 1, 1, 12, 10, 0), 300.0, 22.0)
], values)
def test_get_measure_unknown_aggregation(self):
self.storage.add_measures(self.metric, [
storage.Measure(datetime.datetime(2014, 1, 1, 12, 0, 1), 69),
storage.Measure(datetime.datetime(2014, 1, 1, 12, 7, 31), 42),
storage.Measure(datetime.datetime(2014, 1, 1, 12, 9, 31), 4),
storage.Measure(datetime.datetime(2014, 1, 1, 12, 12, 45), 44),
])
self.assertRaises(storage.AggregationDoesNotExist,
self.storage.get_measures,
self.metric,
aggregation='last')
def test_delete_old_measures(self):
self.incoming.add_measures(self.metric, [
storage.Measure(datetime64(2014, 1, 1, 12, 0, 1), 69),
storage.Measure(datetime64(2014, 1, 1, 12, 7, 31), 42),
storage.Measure(datetime64(2014, 1, 1, 12, 9, 31), 4),
storage.Measure(datetime64(2014, 1, 1, 12, 12, 45), 44),
])
self.trigger_processing()
self.assertEqual([
(datetime64(2014, 1, 1), numpy.timedelta64(1, 'D'), 39.75),
(datetime64(2014, 1, 1, 12), numpy.timedelta64(1, 'h'), 39.75),
(datetime64(2014, 1, 1, 12), numpy.timedelta64(5, 'm'), 69.0),
(datetime64(2014, 1, 1, 12, 5), numpy.timedelta64(5, 'm'), 23.0),
(datetime64(2014, 1, 1, 12, 10), numpy.timedelta64(5, 'm'), 44.0),
], self.storage.get_measures(self.metric))
# One year later…
self.incoming.add_measures(self.metric, [
storage.Measure(datetime64(2015, 1, 1, 12, 0, 1), 69),
])
self.trigger_processing()
self.assertEqual([
(datetime64(2014, 1, 1), numpy.timedelta64(1, 'D'), 39.75),
(datetime64(2015, 1, 1), numpy.timedelta64(1, 'D'), 69),
(datetime64(2015, 1, 1, 12), numpy.timedelta64(1, 'h'), 69),
(datetime64(2015, 1, 1, 12), numpy.timedelta64(5, 'm'), 69),
], self.storage.get_measures(self.metric))
self.assertEqual(
{
carbonara.SplitKey(numpy.datetime64(1244160000, 's'),
numpy.timedelta64(1, 'D')),
},
self.storage._list_split_keys_for_metric(self.metric, "mean",
numpy.timedelta64(1,
'D')))
self.assertEqual(
{
carbonara.SplitKey(numpy.datetime64(1412640000, 's'),
numpy.timedelta64(1, 'h')),
},
self.storage._list_split_keys_for_metric(self.metric, "mean",
numpy.timedelta64(1,
'h')))
self.assertEqual(
{
carbonara.SplitKey(numpy.datetime64(1419120000, 's'),
numpy.timedelta64(5, 'm')),
},
self.storage._list_split_keys_for_metric(self.metric, "mean",
numpy.timedelta64(5,
'm')))
def test_resize_policy(self):
name = str(uuid.uuid4())
ap = archive_policy.ArchivePolicy(name, 0, [(3, 5)])
self.index.create_archive_policy(ap)
m = storage.Metric(uuid.uuid4(), ap)
self.index.create_metric(m.id, str(uuid.uuid4()), str(uuid.uuid4()),
name)
self.storage.add_measures(m, [
storage.Measure(datetime.datetime(2014, 1, 1, 12, 0, 0), 1),
storage.Measure(datetime.datetime(2014, 1, 1, 12, 0, 5), 1),
storage.Measure(datetime.datetime(2014, 1, 1, 12, 0, 10), 1),
])
self.storage.process_background_tasks(self.index, sync=True)
self.assertEqual([
(utils.datetime_utc(2014, 1, 1, 12, 0, 0), 5.0, 1.0),
(utils.datetime_utc(2014, 1, 1, 12, 0, 5), 5.0, 1.0),
(utils.datetime_utc(2014, 1, 1, 12, 0, 10), 5.0, 1.0),
], self.storage.get_measures(m))
# expand to more points
self.index.update_archive_policy(
name, [archive_policy.ArchivePolicyItem(granularity=5, points=6)])
self.storage.add_measures(m, [
storage.Measure(datetime.datetime(2014, 1, 1, 12, 0, 15), 1),
])
self.storage.process_background_tasks(self.index, sync=True)
self.assertEqual([
(utils.datetime_utc(2014, 1, 1, 12, 0, 0), 5.0, 1.0),
(utils.datetime_utc(2014, 1, 1, 12, 0, 5), 5.0, 1.0),
(utils.datetime_utc(2014, 1, 1, 12, 0, 10), 5.0, 1.0),
(utils.datetime_utc(2014, 1, 1, 12, 0, 15), 5.0, 1.0),
], self.storage.get_measures(m))
# shrink timespan
self.index.update_archive_policy(
name, [archive_policy.ArchivePolicyItem(granularity=5, points=2)])
# unchanged after update if no samples
self.storage.process_background_tasks(self.index, sync=True)
self.assertEqual([
(utils.datetime_utc(2014, 1, 1, 12, 0, 0), 5.0, 1.0),
(utils.datetime_utc(2014, 1, 1, 12, 0, 5), 5.0, 1.0),
(utils.datetime_utc(2014, 1, 1, 12, 0, 10), 5.0, 1.0),
(utils.datetime_utc(2014, 1, 1, 12, 0, 15), 5.0, 1.0),
], self.storage.get_measures(m))
# drop points
self.storage.add_measures(m, [
storage.Measure(datetime.datetime(2014, 1, 1, 12, 0, 20), 1),
])
self.storage.process_background_tasks(self.index, sync=True)
self.assertEqual([
(utils.datetime_utc(2014, 1, 1, 12, 0, 15), 5.0, 1.0),
(utils.datetime_utc(2014, 1, 1, 12, 0, 20), 5.0, 1.0),
], self.storage.get_measures(m))
def test_iter_on_sacks_to_process(self):
if (self.incoming.iter_on_sacks_to_process ==
incoming.IncomingDriver.iter_on_sacks_to_process):
self.skipTest("Incoming driver does not implement "
"iter_on_sacks_to_process")
found = threading.Event()
sack_to_find = self.incoming.sack_for_metric(self.metric.id)
def _iter_on_sacks_to_process():
for sack in self.incoming.iter_on_sacks_to_process():
self.assertIsInstance(sack, int)
if sack == sack_to_find:
found.set()
break
finder = threading.Thread(target=_iter_on_sacks_to_process)
finder.daemon = True
finder.start()
# Try for 30s to get a notification about this sack
for _ in range(30):
if found.wait(timeout=1):
break
# NOTE(jd) Retry to send measures. It cannot be done only once as
# there might be a race condition between the threads
self.incoming.add_measures(self.metric, [
storage.Measure(numpy.datetime64("2014-01-01 12:00:01"), 69),
])
else:
self.fail("Notification for metric not received")
def test_delete_nonempty_metric(self):
self.storage.add_measures(self.metric, [
storage.Measure(datetime.datetime(2014, 1, 1, 12, 0, 1), 69),
])
self.trigger_processing(self.storage, self.index)
self.storage.delete_metric(self.metric)
self.trigger_processing(self.storage, self.index)
def test_delete_nonempty_metric(self):
self.storage.add_measures(self.metric, [
storage.Measure(datetime.datetime(2014, 1, 1, 12, 0, 1), 69),
])
self.storage.process_background_tasks(self.index, sync=True)
self.storage.delete_metric(self.metric)
self.storage.process_background_tasks(self.index, sync=True)
def test_add_measures_big(self):
m, __ = self._create_metric('high')
self.incoming.add_measures(m, [
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, i, j), 100)
for i in six.moves.range(0, 60) for j in six.moves.range(0, 60)])
self.trigger_processing([str(m.id)])
self.assertEqual(3661, len(self.storage.get_measures(m)))
def todo(metric):
for _ in six.moves.range(conf.batch_of_measures):
measures = [
storage.Measure(utils.to_timestamp(datetime.datetime.now()),
random.random())
for __ in six.moves.range(conf.measures_per_batch)
]
s.add_measures(metric, measures)
def test_delete_expunge_metric(self):
self.incoming.add_measures(self.metric, [
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 0, 1), 69),
])
self.trigger_processing()
self.index.delete_metric(self.metric.id)
self.storage.expunge_metrics(self.incoming, self.index, sync=True)
self.assertRaises(indexer.NoSuchMetric, self.index.delete_metric,
self.metric.id)
def test_add_measures_big(self):
m, __ = self._create_metric('high')
self.storage.add_measures(m, [
storage.Measure(datetime.datetime(2014, 1, 1, 12, i, j), 100)
for i in six.moves.range(0, 60) for j in six.moves.range(0, 60)
])
self.storage.process_background_tasks(self.index, sync=True)
self.assertEqual(3661, len(self.storage.get_measures(m)))
def test_add_measures_big(self):
m, __ = self._create_metric('high')
self.storage.add_measures(m, [
storage.Measure(datetime.datetime(2014, 1, 1, 12, i, j), 100)
for i in six.moves.range(0, 60) for j in six.moves.range(0, 60)
])
self.trigger_processing(self.storage, self.index)
self.assertEqual(3661, len(self.storage.get_measures(m)))
def test_delete_expunge_metric(self):
self.storage.add_measures(self.metric, [
storage.Measure(datetime.datetime(2014, 1, 1, 12, 0, 1), 69),
])
self.trigger_processing(self.storage, self.index)
self.index.delete_metric(self.metric.id)
self.storage.expunge_metrics(self.index, sync=True)
self.assertRaises(indexer.NoSuchMetric, self.index.delete_metric,
self.metric.id)
def test_updated_measures(self):
self.incoming.add_measures(self.metric, [
storage.Measure(datetime64(2014, 1, 1, 12, 0, 1), 69),
storage.Measure(datetime64(2014, 1, 1, 12, 7, 31), 42),
])
self.trigger_processing()
self.assertEqual([
(datetime64(2014, 1, 1), numpy.timedelta64(1, 'D'), 55.5),
(datetime64(2014, 1, 1, 12), numpy.timedelta64(1, 'h'), 55.5),
(datetime64(2014, 1, 1, 12), numpy.timedelta64(5, 'm'), 69),
(datetime64(2014, 1, 1, 12, 5), numpy.timedelta64(5, 'm'), 42.0),
], self.storage.get_measures(self.metric))
self.incoming.add_measures(self.metric, [
storage.Measure(datetime64(2014, 1, 1, 12, 9, 31), 4),
storage.Measure(datetime64(2014, 1, 1, 12, 12, 45), 44),
])
self.trigger_processing()
self.assertEqual([
(datetime64(2014, 1, 1), numpy.timedelta64(1, 'D'), 39.75),
(datetime64(2014, 1, 1, 12), numpy.timedelta64(1, 'h'), 39.75),
(datetime64(2014, 1, 1, 12), numpy.timedelta64(5, 'm'), 69.0),
(datetime64(2014, 1, 1, 12, 5), numpy.timedelta64(5, 'm'), 23.0),
(datetime64(2014, 1, 1, 12, 10), numpy.timedelta64(5, 'm'), 44.0),
], self.storage.get_measures(self.metric))
self.assertEqual([
(datetime64(2014, 1, 1), numpy.timedelta64(1, 'D'), 69),
(datetime64(2014, 1, 1, 12), numpy.timedelta64(1, 'h'), 69.0),
(datetime64(2014, 1, 1, 12), numpy.timedelta64(5, 'm'), 69.0),
(datetime64(2014, 1, 1, 12, 5), numpy.timedelta64(5, 'm'), 42.0),
(datetime64(2014, 1, 1, 12, 10), numpy.timedelta64(5, 'm'), 44.0),
], self.storage.get_measures(self.metric, aggregation='max'))
self.assertEqual([
(datetime64(2014, 1, 1), numpy.timedelta64(1, 'D'), 4),
(datetime64(2014, 1, 1, 12), numpy.timedelta64(1, 'h'), 4),
(datetime64(2014, 1, 1, 12), numpy.timedelta64(5, 'm'), 69.0),
(datetime64(2014, 1, 1, 12, 5), numpy.timedelta64(5, 'm'), 4.0),
(datetime64(2014, 1, 1, 12, 10), numpy.timedelta64(5, 'm'), 44.0),
], self.storage.get_measures(self.metric, aggregation='min'))
def test_add_measures_update_subset(self):
m, m_sql = self._create_metric('medium')
measures = [
storage.Measure(utils.dt_to_unix_ns(2014, 1, 6, i, j, 0), 100)
for i in six.moves.range(2) for j in six.moves.range(0, 60, 2)]
self.incoming.add_measures(m, measures)
self.trigger_processing([str(m.id)])
# add measure to end, in same aggregate time as last point.
new_point = utils.dt_to_unix_ns(2014, 1, 6, 1, 58, 1)
self.incoming.add_measures(
m, [storage.Measure(new_point, 100)])
with mock.patch.object(self.incoming, 'add_measures') as c:
self.trigger_processing([str(m.id)])
for __, args, __ in c.mock_calls:
self.assertEqual(
list(args[3])[0][0], carbonara.round_timestamp(
new_point, args[1].granularity * 10e8))
def test_measures_reporting(self):
m2, __ = self._create_metric('medium')
for i in six.moves.range(60):
self.incoming.add_measures(self.metric, [
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 0, i), 69),
])
self.incoming.add_measures(m2, [
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 0, i), 69),
])
report = self.incoming.measures_report(True)
self.assertIsInstance(report, dict)
self.assertEqual(2, report['summary']['metrics'])
self.assertEqual(120, report['summary']['measures'])
self.assertIn('details', report)
self.assertIsInstance(report['details'], dict)
report = self.incoming.measures_report(False)
self.assertIsInstance(report, dict)
self.assertEqual(2, report['summary']['metrics'])
self.assertEqual(120, report['summary']['measures'])
def test_updated_measures(self):
self.incoming.add_measures(self.metric, [
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 0, 1), 69),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 7, 31), 42),
])
self.trigger_processing()
self.assertEqual([
(utils.datetime_utc(2014, 1, 1), 86400.0, 55.5),
(utils.datetime_utc(2014, 1, 1, 12), 3600.0, 55.5),
(utils.datetime_utc(2014, 1, 1, 12), 300.0, 69),
(utils.datetime_utc(2014, 1, 1, 12, 5), 300.0, 42.0),
], self.storage.get_measures(self.metric))
self.incoming.add_measures(self.metric, [
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 9, 31), 4),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 12, 45), 44),
])
self.trigger_processing()
self.assertEqual([
(utils.datetime_utc(2014, 1, 1), 86400.0, 39.75),
(utils.datetime_utc(2014, 1, 1, 12), 3600.0, 39.75),
(utils.datetime_utc(2014, 1, 1, 12), 300.0, 69.0),
(utils.datetime_utc(2014, 1, 1, 12, 5), 300.0, 23.0),
(utils.datetime_utc(2014, 1, 1, 12, 10), 300.0, 44.0),
], self.storage.get_measures(self.metric))
self.assertEqual([
(utils.datetime_utc(2014, 1, 1), 86400.0, 69),
(utils.datetime_utc(2014, 1, 1, 12), 3600.0, 69.0),
(utils.datetime_utc(2014, 1, 1, 12), 300.0, 69.0),
(utils.datetime_utc(2014, 1, 1, 12, 5), 300.0, 42.0),
(utils.datetime_utc(2014, 1, 1, 12, 10), 300.0, 44.0),
], self.storage.get_measures(self.metric, aggregation='max'))
self.assertEqual([
(utils.datetime_utc(2014, 1, 1), 86400.0, 4),
(utils.datetime_utc(2014, 1, 1, 12), 3600.0, 4),
(utils.datetime_utc(2014, 1, 1, 12), 300.0, 69.0),
(utils.datetime_utc(2014, 1, 1, 12, 5), 300.0, 4.0),
(utils.datetime_utc(2014, 1, 1, 12, 10), 300.0, 44.0),
], self.storage.get_measures(self.metric, aggregation='min'))
def test_search_value(self):
metric2, __ = self._create_metric()
self.incoming.add_measures(self.metric, [
storage.Measure(datetime64(
2014,
1,
1,
12,
0,
1,
), 69),
storage.Measure(datetime64(2014, 1, 1, 12, 7, 31), 42),
storage.Measure(datetime64(2014, 1, 1, 12, 5, 31), 8),
storage.Measure(datetime64(2014, 1, 1, 12, 9, 31), 4),
storage.Measure(datetime64(2014, 1, 1, 12, 12, 45), 42),
])
self.incoming.add_measures(metric2, [
storage.Measure(datetime64(2014, 1, 1, 12, 0, 5), 9),
storage.Measure(datetime64(2014, 1, 1, 12, 7, 31), 2),
storage.Measure(datetime64(2014, 1, 1, 12, 9, 31), 6),
storage.Measure(datetime64(2014, 1, 1, 12, 13, 10), 2),
])
self.trigger_processing([str(self.metric.id), str(metric2.id)])
self.assertEqual(
{
metric2: [],
self.metric:
[(datetime64(2014, 1, 1), numpy.timedelta64(1, 'D'), 33),
(datetime64(2014, 1, 1, 12), numpy.timedelta64(1, 'h'), 33),
(datetime64(2014, 1, 1, 12), numpy.timedelta64(5, 'm'), 69),
(datetime64(2014, 1, 1, 12, 10), numpy.timedelta64(5,
'm'), 42)]
}, self.storage.search_value([metric2, self.metric], {u"≥": 30}))
self.assertEqual(
{
metric2: [],
self.metric: []
},
self.storage.search_value([metric2, self.metric],
{u"∧": [{
u"eq": 100
}, {
u"≠": 50
}]}))
def test_delete_nonempty_metric_unprocessed(self):
self.incoming.add_measures(self.metric, [
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 0, 1), 69),
])
self.index.delete_metric(self.metric.id)
self.trigger_processing()
__, __, details = self.incoming._build_report(True)
self.assertIn(str(self.metric.id), details)
self.storage.expunge_metrics(self.incoming, self.index, sync=True)
__, __, details = self.incoming._build_report(True)
self.assertNotIn(str(self.metric.id), details)
def test_delete_nonempty_metric(self):
self.incoming.add_measures(self.metric, [
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 0, 1), 69),
])
self.trigger_processing()
self.storage.delete_metric(self.incoming, self.metric, sync=True)
self.trigger_processing()
self.assertEqual([], self.storage.get_measures(self.metric))
self.assertRaises(storage.MetricDoesNotExist,
self.storage._get_unaggregated_timeserie,
self.metric)
def test_list_metric_with_measures_to_process(self):
metrics = tests_utils.list_all_incoming_metrics(self.incoming)
self.assertEqual(set(), metrics)
self.incoming.add_measures(self.metric, [
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 0, 1), 69),
])
metrics = tests_utils.list_all_incoming_metrics(self.incoming)
self.assertEqual(set([str(self.metric.id)]), metrics)
self.trigger_processing()
metrics = tests_utils.list_all_incoming_metrics(self.incoming)
self.assertEqual(set([]), metrics)
def test_add_measures_update_subset(self):
m, m_sql = self._create_metric('medium')
measures = [
storage.Measure(datetime.datetime(2014, 1, 6, i, j, 0), 100)
for i in six.moves.range(2) for j in six.moves.range(0, 60, 2)
]
self.storage.add_measures(m, measures)
self.trigger_processing(self.storage, self.index)
# add measure to end, in same aggregate time as last point.
new_point = datetime.datetime(2014, 1, 6, 1, 58, 1)
self.storage.add_measures(m, [storage.Measure(new_point, 100)])
with mock.patch.object(self.storage, '_add_measures') as c:
self.trigger_processing(self.storage, self.index)
for __, args, __ in c.mock_calls:
self.assertEqual(
args[3].first,
carbonara.TimeSerie.round_timestamp(
new_point, args[1].granularity * 10e8))
def test_search_value(self):
metric2, __ = self._create_metric()
self.incoming.add_measures(self.metric, [
storage.Measure(utils.dt_to_unix_ns(
2014,
1,
1,
12,
0,
1,
), 69),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 7, 31), 42),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 5, 31), 8),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 9, 31), 4),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 12, 45), 42),
])
self.incoming.add_measures(metric2, [
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 0, 5), 9),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 7, 31), 2),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 9, 31), 6),
storage.Measure(utils.dt_to_unix_ns(2014, 1, 1, 12, 13, 10), 2),
])
self.trigger_processing([str(self.metric.id), str(metric2.id)])
self.assertEqual(
{
metric2: [],
self.metric: [(utils.datetime_utc(2014, 1, 1), 86400, 33),
(utils.datetime_utc(2014, 1, 1, 12), 3600, 33),
(utils.datetime_utc(2014, 1, 1, 12), 300, 69),
(utils.datetime_utc(2014, 1, 1, 12, 10), 300, 42)
]
}, self.storage.search_value([metric2, self.metric], {u"≥": 30}))
self.assertEqual(
{
metric2: [],
self.metric: []
},
self.storage.search_value([metric2, self.metric],
{u"∧": [{
u"eq": 100
}, {
u"≠": 50
}]}))
def test_search_value(self):
metric2, __ = self._create_metric()
self.storage.add_measures(self.metric, [
storage.Measure(datetime.datetime(
2014,
1,
1,
12,
0,
1,
), 69),
storage.Measure(datetime.datetime(2014, 1, 1, 12, 7, 31), 42),
storage.Measure(datetime.datetime(2014, 1, 1, 12, 5, 31), 8),
storage.Measure(datetime.datetime(2014, 1, 1, 12, 9, 31), 4),
storage.Measure(datetime.datetime(2014, 1, 1, 12, 12, 45), 42),
])
self.storage.add_measures(metric2, [
storage.Measure(datetime.datetime(2014, 1, 1, 12, 0, 5), 9),
storage.Measure(datetime.datetime(2014, 1, 1, 12, 7, 31), 2),
storage.Measure(datetime.datetime(2014, 1, 1, 12, 9, 31), 6),
storage.Measure(datetime.datetime(2014, 1, 1, 12, 13, 10), 2),
])
self.storage.process_background_tasks(self.index, sync=True)
self.assertEqual(
{
metric2: [],
self.metric: [(utils.datetime_utc(2014, 1, 1), 86400, 33),
(utils.datetime_utc(2014, 1, 1, 12), 3600, 33),
(utils.datetime_utc(2014, 1, 1, 12), 300, 69),
(utils.datetime_utc(2014, 1, 1, 12, 10), 300, 42)
]
}, self.storage.search_value([metric2, self.metric], {u"≥": 30}))
self.assertEqual(
{
metric2: [],
self.metric: []
},
self.storage.search_value([metric2, self.metric],
{u"∧": [{
u"eq": 100
}, {
u"≠": 50
}]}))
def test_add_measures_big_update_subset(self):
m, m_sql = self._create_metric('medium')
measures = [
storage.Measure(datetime.datetime(2014, 1, i, j, 0, 0), 100)
for i in six.moves.range(1, 6) for j in six.moves.range(0, 24)
]
measures.append(
storage.Measure(datetime.datetime(2014, 1, 6, 0, 0, 0), 100))
self.storage.add_measures(m, measures)
self.storage.process_background_tasks(self.index, sync=True)
self.storage.add_measures(
m, [storage.Measure(datetime.datetime(2014, 1, 6, 1, 0, 0), 100)])
with mock.patch.object(self.storage, '_store_metric_measures') as c:
self.storage.process_background_tasks(self.index, sync=True)
count = 0
for call in c.mock_calls:
if mock.call(m_sql, mock.ANY, 'mean', 3600.0, mock.ANY) == call:
count += 1
self.assertEqual(1, count)
def test_rewrite_measures_corruption_bad_data(self):
# Create an archive policy that spans on several splits. Each split
# being 3600 points, let's go for 36k points so we have 10 splits.
apname = str(uuid.uuid4())
ap = archive_policy.ArchivePolicy(apname, 0, [(36000, 60)])
self.index.create_archive_policy(ap)
self.metric = storage.Metric(uuid.uuid4(), ap)
self.index.create_metric(self.metric.id, str(uuid.uuid4()), apname)
# First store some points scattered across different splits
self.incoming.add_measures(self.metric, [
storage.Measure(utils.dt_to_unix_ns(2016, 1, 1, 12, 0, 1), 69),
storage.Measure(utils.dt_to_unix_ns(2016, 1, 2, 13, 7, 31), 42),
storage.Measure(utils.dt_to_unix_ns(2016, 1, 4, 14, 9, 31), 4),
storage.Measure(utils.dt_to_unix_ns(2016, 1, 6, 15, 12, 45), 44),
])
self.trigger_processing()
splits = {'1451520000.0', '1451736000.0', '1451952000.0'}
self.assertEqual(
splits,
self.storage._list_split_keys_for_metric(self.metric, "mean",
60.0))
if self.storage.WRITE_FULL:
assertCompressedIfWriteFull = self.assertTrue
else:
assertCompressedIfWriteFull = self.assertFalse
data = self.storage._get_measures(self.metric, '1451520000.0', "mean",
60.0)
self.assertTrue(carbonara.AggregatedTimeSerie.is_compressed(data))
data = self.storage._get_measures(self.metric, '1451736000.0', "mean",
60.0)
self.assertTrue(carbonara.AggregatedTimeSerie.is_compressed(data))
data = self.storage._get_measures(self.metric, '1451952000.0', "mean",
60.0)
assertCompressedIfWriteFull(
carbonara.AggregatedTimeSerie.is_compressed(data))
self.assertEqual([
(utils.datetime_utc(2016, 1, 1, 12), 60.0, 69),
(utils.datetime_utc(2016, 1, 2, 13, 7), 60.0, 42),
(utils.datetime_utc(2016, 1, 4, 14, 9), 60.0, 4),
(utils.datetime_utc(2016, 1, 6, 15, 12), 60.0, 44),
], self.storage.get_measures(self.metric, granularity=60.0))
# Test what happens if we write garbage
self.storage._store_metric_measures(self.metric, '1451952000.0',
"mean", 60.0, b"oh really?")
# Now store brand new points that should force a rewrite of one of the
# split (keep in mind the back window size in one hour here). We move
# the BoundTimeSerie processing timeserie far away from its current
# range.
self.incoming.add_measures(self.metric, [
storage.Measure(utils.dt_to_unix_ns(2016, 1, 10, 16, 18, 45), 45),
storage.Measure(utils.dt_to_unix_ns(2016, 1, 10, 17, 12, 45), 46),
])
self.trigger_processing()
