def get_attrs(self, item_list, user):
attrs = super(GroupReleaseWithStatsSerializer,
self).get_attrs(item_list, user)
items = {}
for item in item_list:
items.setdefault(item.group_id, []).append(item.id)
attrs[item]["stats"] = {}
for key, (segments, interval) in six.iteritems(self.STATS_PERIODS):
until = self.until or timezone.now()
since = self.since or until - (segments * interval)
try:
stats = tsdb.get_frequency_series(
model=tsdb.models.frequent_releases_by_group,
items=items,
start=since,
end=until,
rollup=int(interval.total_seconds()),
)
except NotImplementedError:
# TODO(dcramer): probably should log this, but not worth
# erring out
stats = {}
for item in item_list:
attrs[item]["stats"][key] = [
(k, v[item.id]) for k, v in stats.get(item.group_id, {})
]
return attrs
def get_attrs(self, item_list, user):
attrs = {
item: {'stats': {}}
for item in item_list
}
items = {self.group.id: []}
for item in item_list:
items[self.group.id].append(item.id)
for key, (segments, interval) in six.iteritems(self.STATS_PERIODS):
until = self.until or timezone.now()
since = self.since or until - (segments * interval)
try:
stats = tsdb.get_frequency_series(
model=tsdb.models.frequent_environments_by_group,
items=items,
start=since,
end=until,
rollup=int(interval.total_seconds()),
)
except NotImplementedError:
# TODO(dcramer): probably should log this, but not worth
# erring out
stats = {}
for item in item_list:
attrs[item]['stats'][key] = [
(k, v[item.id])
for k, v in stats.get(self.group.id, {})
]
return attrs
def get_attrs(self, item_list, user):
attrs = {item: {"stats": {}} for item in item_list}
items = {self.group.id: []}
for item in item_list:
items[self.group.id].append(item.id)
for key, (segments, interval) in six.iteritems(self.STATS_PERIODS):
until = self.until or timezone.now()
since = self.since or until - (segments * interval)
try:
stats = tsdb.get_frequency_series(
model=tsdb.models.frequent_environments_by_group,
items=items,
start=since,
end=until,
rollup=int(interval.total_seconds()),
)
except NotImplementedError:
# TODO(dcramer): probably should log this, but not worth
# erring out
stats = {}
for item in item_list:
attrs[item]["stats"][key] = [
(k, v[item.id]) for k, v in stats.get(self.group.id, {})
]
return attrs
def get_attrs(self, item_list, user):
attrs = super(GroupReleaseWithStatsSerializer, self).get_attrs(item_list, user)
items = {}
for item in item_list:
items.setdefault(item.group_id, []).append(item.id)
attrs[item]['stats'] = {}
for key, (segments, interval) in six.iteritems(self.STATS_PERIODS):
until = self.until or timezone.now()
since = self.since or until - (segments * interval)
try:
stats = tsdb.get_frequency_series(
model=tsdb.models.frequent_releases_by_group,
items=items,
start=since,
end=until,
rollup=int(interval.total_seconds()),
)
except NotImplementedError:
# TODO(dcramer): probably should log this, but not worth
# erring out
stats = {}
for item in item_list:
attrs[item]['stats'][key] = [
(k, v[item.id]) for k, v in stats.get(item.group_id, {})
]
return attrs
def test_unmerge(self):
now = before_now(minutes=5).replace(microsecond=0, tzinfo=pytz.utc)
def time_from_now(offset=0):
return now + timedelta(seconds=offset)
project = self.create_project()
sequence = itertools.count(0)
tag_values = itertools.cycle(["red", "green", "blue"])
user_values = itertools.cycle([{"id": 1}, {"id": 2}])
def create_message_event(template, parameters, environment, release, fingerprint="group1"):
i = next(sequence)
event_id = uuid.UUID(fields=(i, 0x0, 0x1000, 0x80, 0x80, 0x808080808080)).hex
tags = [["color", next(tag_values)]]
if release:
tags.append(["sentry:release", release])
event = self.store_event(
data={
"event_id": event_id,
"message": template % parameters,
"type": "default",
"user": next(user_values),
"tags": tags,
"fingerprint": [fingerprint],
"timestamp": iso_format(now + timedelta(seconds=i)),
"environment": environment,
"release": release,
},
project_id=project.id,
)
UserReport.objects.create(
project_id=project.id,
group_id=event.group.id,
event_id=event_id,
name="Log Hat",
email="*****@*****.**",
comments="Quack",
)
features.record([event])
return event
events = OrderedDict()
for event in (
create_message_event(
"This is message #%s.", i, environment="production", release="version"
)
for i in xrange(10)
):
events.setdefault(get_fingerprint(event), []).append(event)
for event in (
create_message_event(
"This is message #%s!",
i,
environment="production",
release="version2",
fingerprint="group2",
)
for i in xrange(10, 16)
):
events.setdefault(get_fingerprint(event), []).append(event)
event = create_message_event(
"This is message #%s!",
17,
environment="staging",
release="version3",
fingerprint="group3",
)
events.setdefault(get_fingerprint(event), []).append(event)
merge_source, source, destination = list(Group.objects.all())
assert len(events) == 3
assert sum(map(len, events.values())) == 17
production_environment = Environment.objects.get(
organization_id=project.organization_id, name="production"
)
with self.tasks():
eventstream_state = eventstream.start_merge(project.id, [merge_source.id], source.id)
merge_groups.delay([merge_source.id], source.id)
eventstream.end_merge(eventstream_state)
assert set(
[
(gtv.value, gtv.times_seen)
for gtv in tagstore.get_group_tag_values(
project.id, source.id, production_environment.id, "color"
)
]
) == set([("red", 6), ("green", 5), ("blue", 5)])
similar_items = features.compare(source)
assert len(similar_items) == 2
assert similar_items[0][0] == source.id
assert similar_items[0][1]["message:message:character-shingles"] == 1.0
assert similar_items[1][0] == destination.id
assert similar_items[1][1]["message:message:character-shingles"] < 1.0
with self.tasks():
eventstream_state = eventstream.start_unmerge(
project.id, [list(events.keys())[0]], source.id, destination.id
)
unmerge.delay(
project.id, source.id, destination.id, [list(events.keys())[0]], None, batch_size=5
)
eventstream.end_unmerge(eventstream_state)
assert (
list(
Group.objects.filter(id=merge_source.id).values_list(
"times_seen", "first_seen", "last_seen"
)
)
== []
)
assert list(
Group.objects.filter(id=source.id).values_list("times_seen", "first_seen", "last_seen")
) == [(6, time_from_now(10), time_from_now(15))]
assert list(
Group.objects.filter(id=destination.id).values_list(
"times_seen", "first_seen", "last_seen"
)
) == [(11, time_from_now(0), time_from_now(16))]
assert source.id != destination.id
assert source.project == destination.project
destination_event_ids = map(lambda event: event.event_id, list(events.values())[1])
assert set(
UserReport.objects.filter(group_id=source.id).values_list("event_id", flat=True)
) == set(destination_event_ids)
assert set(
GroupHash.objects.filter(group_id=source.id).values_list("hash", flat=True)
) == set(itertools.islice(events.keys(), 2))
assert set(
GroupRelease.objects.filter(group_id=source.id).values_list(
"environment", "first_seen", "last_seen"
)
) == set([(u"production", time_from_now(10), time_from_now(15))])
assert set(
[
(gtv.value, gtv.times_seen)
for gtv in tagstore.get_group_tag_values(
project.id, destination.id, production_environment.id, "color"
)
]
) == set([(u"red", 4), (u"green", 3), (u"blue", 3)])
destination_event_ids = map(
lambda event: event.event_id, list(events.values())[0] + list(events.values())[2]
)
assert set(
UserReport.objects.filter(group_id=destination.id).values_list("event_id", flat=True)
) == set(destination_event_ids)
assert set(
GroupHash.objects.filter(group_id=destination.id).values_list("hash", flat=True)
) == set(itertools.islice(events.keys(), 2, 3))
assert set(
GroupRelease.objects.filter(group_id=destination.id).values_list(
"environment", "first_seen", "last_seen"
)
) == set(
[
("production", time_from_now(0), time_from_now(9)),
("staging", time_from_now(16), time_from_now(16)),
]
)
assert set(
[
(gtk.value, gtk.times_seen)
for gtk in tagstore.get_group_tag_values(
project.id, destination.id, production_environment.id, "color"
)
]
) == set([("red", 4), ("blue", 3), ("green", 3)])
rollup_duration = 3600
time_series = tsdb.get_range(
tsdb.models.group,
[source.id, destination.id],
now - timedelta(seconds=rollup_duration),
time_from_now(17),
rollup_duration,
)
environment_time_series = tsdb.get_range(
tsdb.models.group,
[source.id, destination.id],
now - timedelta(seconds=rollup_duration),
time_from_now(17),
rollup_duration,
environment_ids=[production_environment.id],
)
def get_expected_series_values(rollup, events, function=None):
if function is None:
def function(aggregate, event):
return (aggregate if aggregate is not None else 0) + 1
expected = {}
for event in events:
k = float((to_timestamp(event.datetime) // rollup_duration) * rollup_duration)
expected[k] = function(expected.get(k), event)
return expected
def assert_series_contains(expected, actual, default=0):
actual = dict(actual)
for key, value in expected.items():
assert actual.get(key, 0) == value
for key in set(actual.keys()) - set(expected.keys()):
assert actual.get(key, 0) == default
assert_series_contains(
get_expected_series_values(rollup_duration, list(events.values())[1]),
time_series[source.id],
0,
)
assert_series_contains(
get_expected_series_values(
rollup_duration, list(events.values())[0] + list(events.values())[2]
),
time_series[destination.id],
0,
)
assert_series_contains(
get_expected_series_values(rollup_duration, list(events.values())[1]),
environment_time_series[source.id],
0,
)
assert_series_contains(
get_expected_series_values(
rollup_duration, list(events.values())[0][:-1] + list(events.values())[2]
),
environment_time_series[destination.id],
0,
)
time_series = tsdb.get_distinct_counts_series(
tsdb.models.users_affected_by_group,
[source.id, destination.id],
now - timedelta(seconds=rollup_duration),
time_from_now(17),
rollup_duration,
)
environment_time_series = tsdb.get_distinct_counts_series(
tsdb.models.users_affected_by_group,
[source.id, destination.id],
now - timedelta(seconds=rollup_duration),
time_from_now(17),
rollup_duration,
environment_id=production_environment.id,
)
def collect_by_user_tag(aggregate, event):
aggregate = aggregate if aggregate is not None else set()
aggregate.add(get_event_user_from_interface(event.data["user"]).tag_value)
return aggregate
for series in [time_series, environment_time_series]:
assert_series_contains(
{
timestamp: len(values)
for timestamp, values in get_expected_series_values(
rollup_duration, list(events.values())[1], collect_by_user_tag
).items()
},
series[source.id],
)
assert_series_contains(
{
timestamp: len(values)
for timestamp, values in get_expected_series_values(
rollup_duration,
list(events.values())[0] + list(events.values())[2],
collect_by_user_tag,
).items()
},
time_series[destination.id],
)
def strip_zeroes(data):
for group_id, series in data.items():
for _, values in series:
for key, val in list(values.items()):
if val == 0:
values.pop(key)
return data
def collect_by_release(group, aggregate, event):
aggregate = aggregate if aggregate is not None else {}
release = event.get_tag("sentry:release")
if not release:
return aggregate
release = GroupRelease.objects.get(
group_id=group.id,
environment=event.data["environment"],
release_id=Release.objects.get(
organization_id=project.organization_id, version=release
).id,
).id
aggregate[release] = aggregate.get(release, 0) + 1
return aggregate
items = {}
for i in [source.id, destination.id]:
items[i] = list(GroupRelease.objects.filter(group_id=i).values_list("id", flat=True))
time_series = strip_zeroes(
tsdb.get_frequency_series(
tsdb.models.frequent_releases_by_group,
items,
now - timedelta(seconds=rollup_duration),
time_from_now(17),
rollup_duration,
)
)
assert_series_contains(
get_expected_series_values(
rollup_duration,
list(events.values())[1],
functools.partial(collect_by_release, source),
),
time_series[source.id],
{},
)
assert_series_contains(
get_expected_series_values(
rollup_duration,
list(events.values())[0] + list(events.values())[2],
functools.partial(collect_by_release, destination),
),
time_series[destination.id],
{},
)
items = {}
for i in [source.id, destination.id]:
items[i] = list(Environment.objects.all().values_list("id", flat=True))
time_series = strip_zeroes(
tsdb.get_frequency_series(
tsdb.models.frequent_environments_by_group,
items,
now - timedelta(seconds=rollup_duration),
time_from_now(17),
rollup_duration,
)
)
def collect_by_environment(aggregate, event):
aggregate = aggregate if aggregate is not None else {}
environment = Environment.objects.get(
organization_id=project.organization_id, name=event.data["environment"]
).id
aggregate[environment] = aggregate.get(environment, 0) + 1
return aggregate
assert_series_contains(
get_expected_series_values(
rollup_duration, list(events.values())[1], collect_by_environment
),
time_series[source.id],
{},
)
assert_series_contains(
get_expected_series_values(
rollup_duration,
list(events.values())[0] + list(events.values())[2],
collect_by_environment,
),
time_series[destination.id],
{},
)
source_similar_items = features.compare(source)
assert source_similar_items[0] == (
source.id,
{
"exception:message:character-shingles": None,
"exception:stacktrace:application-chunks": None,
"exception:stacktrace:pairs": None,
"message:message:character-shingles": 1.0,
},
)
assert source_similar_items[1][0] == destination.id
assert source_similar_items[1][1]["message:message:character-shingles"] < 1.0
destination_similar_items = features.compare(destination)
assert destination_similar_items[0] == (
destination.id,
{
"exception:message:character-shingles": None,
"exception:stacktrace:application-chunks": None,
"exception:stacktrace:pairs": None,
"message:message:character-shingles": 1.0,
},
)
assert destination_similar_items[1][0] == source.id
assert destination_similar_items[1][1]["message:message:character-shingles"] < 1.0