def save(self, project_id, raw=False, assume_normalized=False):
# Normalize if needed
if not self._normalized:
if not assume_normalized:
self.normalize()
self._normalized = True
data = self._data
project = Project.objects.get_from_cache(id=project_id)
project._organization_cache = Organization.objects.get_from_cache(
id=project.organization_id)
# Ensure an event with the same ID does not exist before processing it.
# We use a first write wins approach since Clickhouse cannot merge
# events from different days. (The timestamp rounded to
# start of day is part of the primary key in Clickhouse).
event = self._get_event_from_storage(project_id, data["event_id"])
if event:
# Make sure we cache on the project before returning
event._project_cache = project
logger.info(
"duplicate.found",
exc_info=True,
extra={
"event_uuid": data["event_id"],
"project_id": project.id,
"model": Event.__name__,
},
)
return event
# Pull out the culprit
culprit = self.get_culprit()
# Pull the toplevel data we're interested in
level = data.get("level")
# TODO(mitsuhiko): this code path should be gone by July 2018.
# This is going to be fine because no code actually still depends
# on integers here. When we need an integer it will be converted
# into one later. Old workers used to send integers here.
if level is not None and isinstance(level, six.integer_types):
level = LOG_LEVELS[level]
transaction_name = data.get("transaction")
logger_name = data.get("logger")
release = data.get("release")
dist = data.get("dist")
environment = data.get("environment")
recorded_timestamp = data.get("timestamp")
# We need to swap out the data with the one internal to the newly
# created event object
event = self._get_event_instance(project_id=project_id)
self._data = data = event.data.data
event._project_cache = project
date = event.datetime
platform = event.platform
event_id = event.event_id
if transaction_name:
transaction_name = force_text(transaction_name)
# Right now the event type is the signal to skip the group. This
# is going to change a lot.
if event.get_event_type() == "transaction":
issueless_event = True
else:
issueless_event = False
# Some of the data that are toplevel attributes are duplicated
# into tags (logger, level, environment, transaction). These are
# different from legacy attributes which are normalized into tags
# ahead of time (site, server_name).
setdefault_path(data, "tags", value=[])
set_tag(data, "level", level)
if logger_name:
set_tag(data, "logger", logger_name)
if environment:
set_tag(data, "environment", environment)
if transaction_name:
set_tag(data, "transaction", transaction_name)
if release:
# dont allow a conflicting 'release' tag
pop_tag(data, "release")
release = Release.get_or_create(project=project,
version=release,
date_added=date)
set_tag(data, "sentry:release", release.version)
if dist and release:
dist = release.add_dist(dist, date)
# dont allow a conflicting 'dist' tag
pop_tag(data, "dist")
set_tag(data, "sentry:dist", dist.name)
else:
dist = None
event_user = self._get_event_user(project, data)
if event_user:
# dont allow a conflicting 'user' tag
pop_tag(data, "user")
set_tag(data, "sentry:user", event_user.tag_value)
# At this point we want to normalize the in_app values in case the
# clients did not set this appropriately so far.
grouping_config = load_grouping_config(
get_grouping_config_dict_for_event_data(data, project))
normalize_stacktraces_for_grouping(data, grouping_config)
for plugin in plugins.for_project(project, version=None):
added_tags = safe_execute(plugin.get_tags,
event,
_with_transaction=False)
if added_tags:
# plugins should not override user provided tags
for key, value in added_tags:
if get_tag(data, key) is None:
set_tag(data, key, value)
for path, iface in six.iteritems(event.interfaces):
for k, v in iface.iter_tags():
set_tag(data, k, v)
# Get rid of ephemeral interface data
if iface.ephemeral:
data.pop(iface.path, None)
# The active grouping config was put into the event in the
# normalize step before. We now also make sure that the
# fingerprint was set to `'{{ default }}' just in case someone
# removed it from the payload. The call to get_hashes will then
# look at `grouping_config` to pick the right paramters.
data["fingerprint"] = data.get("fingerprint") or ["{{ default }}"]
apply_server_fingerprinting(
data, get_fingerprinting_config_for_project(project))
# Here we try to use the grouping config that was requested in the
# event. If that config has since been deleted (because it was an
# experimental grouping config) we fall back to the default.
try:
hashes = event.get_hashes()
except GroupingConfigNotFound:
data["grouping_config"] = get_grouping_config_dict_for_project(
project)
hashes = event.get_hashes()
data["hashes"] = hashes
# we want to freeze not just the metadata and type in but also the
# derived attributes. The reason for this is that we push this
# data into kafka for snuba processing and our postprocessing
# picks up the data right from the snuba topic. For most usage
# however the data is dynamically overriden by Event.title and
# Event.location (See Event.as_dict)
materialized_metadata = self.materialize_metadata()
event_metadata = materialized_metadata["metadata"]
data.update(materialized_metadata)
data["culprit"] = culprit
# index components into ``Event.message``
# See GH-3248
event.message = self.get_search_message(event_metadata, culprit)
received_timestamp = event.data.get("received") or float(
event.datetime.strftime("%s"))
if not issueless_event:
# The group gets the same metadata as the event when it's flushed but
# additionally the `last_received` key is set. This key is used by
# _save_aggregate.
group_metadata = dict(materialized_metadata)
group_metadata["last_received"] = received_timestamp
kwargs = {
"platform": platform,
"message": event.message,
"culprit": culprit,
"logger": logger_name,
"level": LOG_LEVELS_MAP.get(level),
"last_seen": date,
"first_seen": date,
"active_at": date,
"data": group_metadata,
}
if release:
kwargs["first_release"] = release
try:
group, is_new, is_regression, is_sample = self._save_aggregate(
event=event, hashes=hashes, release=release, **kwargs)
except HashDiscarded:
event_discarded.send_robust(project=project,
sender=EventManager)
metrics.incr(
"events.discarded",
skip_internal=True,
tags={
"organization_id": project.organization_id,
"platform": platform
},
)
raise
else:
event_saved.send_robust(project=project,
event_size=event.size,
sender=EventManager)
event.group = group
else:
group = None
is_new = False
is_regression = False
is_sample = False
event_saved.send_robust(project=project,
event_size=event.size,
sender=EventManager)
# store a reference to the group id to guarantee validation of isolation
event.data.bind_ref(event)
environment = Environment.get_or_create(project=project,
name=environment)
if group:
group_environment, is_new_group_environment = GroupEnvironment.get_or_create(
group_id=group.id,
environment_id=environment.id,
defaults={"first_release": release if release else None},
)
else:
is_new_group_environment = False
if release:
ReleaseEnvironment.get_or_create(project=project,
release=release,
environment=environment,
datetime=date)
ReleaseProjectEnvironment.get_or_create(project=project,
release=release,
environment=environment,
datetime=date)
if group:
grouprelease = GroupRelease.get_or_create(
group=group,
release=release,
environment=environment,
datetime=date)
counters = [(tsdb.models.project, project.id)]
if group:
counters.append((tsdb.models.group, group.id))
if release:
counters.append((tsdb.models.release, release.id))
tsdb.incr_multi(counters,
timestamp=event.datetime,
environment_id=environment.id)
frequencies = [
# (tsdb.models.frequent_projects_by_organization, {
# project.organization_id: {
# project.id: 1,
# },
# }),
# (tsdb.models.frequent_issues_by_project, {
# project.id: {
# group.id: 1,
# },
# })
]
if group:
frequencies.append((tsdb.models.frequent_environments_by_group, {
group.id: {
environment.id: 1
}
}))
if release:
frequencies.append((tsdb.models.frequent_releases_by_group, {
group.id: {
grouprelease.id: 1
}
}))
if frequencies:
tsdb.record_frequency_multi(frequencies, timestamp=event.datetime)
if group:
UserReport.objects.filter(project=project,
event_id=event_id).update(
group=group, environment=environment)
# save the event unless its been sampled
if not is_sample:
try:
with transaction.atomic(using=router.db_for_write(Event)):
event.save()
except IntegrityError:
logger.info(
"duplicate.found",
exc_info=True,
extra={
"event_uuid": event_id,
"project_id": project.id,
"group_id": group.id if group else None,
"model": Event.__name__,
},
)
return event
tagstore.delay_index_event_tags(
organization_id=project.organization_id,
project_id=project.id,
group_id=group.id if group else None,
environment_id=environment.id,
event_id=event.id,
tags=event.tags,
date_added=event.datetime,
)
if event_user:
counters = [(tsdb.models.users_affected_by_project, project.id,
(event_user.tag_value, ))]
if group:
counters.append((tsdb.models.users_affected_by_group, group.id,
(event_user.tag_value, )))
tsdb.record_multi(counters,
timestamp=event.datetime,
environment_id=environment.id)
if release:
if is_new:
buffer.incr(
ReleaseProject,
{"new_groups": 1},
{
"release_id": release.id,
"project_id": project.id
},
)
if is_new_group_environment:
buffer.incr(
ReleaseProjectEnvironment,
{"new_issues_count": 1},
{
"project_id": project.id,
"release_id": release.id,
"environment_id": environment.id,
},
)
if group:
safe_execute(
Group.objects.add_tags,
group,
environment,
event.get_tags(),
_with_transaction=False,
)
if not raw:
if not project.first_event:
project.update(first_event=date)
first_event_received.send_robust(project=project,
event=event,
sender=Project)
eventstream.insert(
group=group,
event=event,
is_new=is_new,
is_sample=is_sample,
is_regression=is_regression,
is_new_group_environment=is_new_group_environment,
primary_hash=hashes[0],
# We are choosing to skip consuming the event back
# in the eventstream if it's flagged as raw.
# This means that we want to publish the event
# through the event stream, but we don't care
# about post processing and handling the commit.
skip_consume=raw,
)
metrics.timing(
"events.latency",
received_timestamp - recorded_timestamp,
tags={"project_id": project.id},
)
metrics.timing("events.size.data.post_save",
event.size,
tags={"project_id": project.id})
return event
def save(self, project_id, raw=False, assume_normalized=False):
# Normalize if needed
if not self._normalized:
if not assume_normalized:
self.normalize()
self._normalized = True
data = self._data
project = Project.objects.get_from_cache(id=project_id)
project._organization_cache = Organization.objects.get_from_cache(
id=project.organization_id)
# Check to make sure we're not about to do a bunch of work that's
# already been done if we've processed an event with this ID. (This
# isn't a perfect solution -- this doesn't handle ``EventMapping`` and
# there's a race condition between here and when the event is actually
# saved, but it's an improvement. See GH-7677.)
try:
event = Event.objects.get(
project_id=project.id,
event_id=data['event_id'],
)
except Event.DoesNotExist:
pass
else:
# Make sure we cache on the project before returning
event._project_cache = project
logger.info(
'duplicate.found',
exc_info=True,
extra={
'event_uuid': data['event_id'],
'project_id': project.id,
'model': Event.__name__,
}
)
return event
# Pull out the culprit
culprit = self.get_culprit()
# Pull the toplevel data we're interested in
level = data.get('level')
# TODO(mitsuhiko): this code path should be gone by July 2018.
# This is going to be fine because no code actually still depends
# on integers here. When we need an integer it will be converted
# into one later. Old workers used to send integers here.
if level is not None and isinstance(level, six.integer_types):
level = LOG_LEVELS[level]
transaction_name = data.get('transaction')
logger_name = data.get('logger')
release = data.get('release')
dist = data.get('dist')
environment = data.get('environment')
recorded_timestamp = data.get('timestamp')
# We need to swap out the data with the one internal to the newly
# created event object
event = self._get_event_instance(project_id=project_id)
self._data = data = event.data.data
event._project_cache = project
date = event.datetime
platform = event.platform
event_id = event.event_id
if transaction_name:
transaction_name = force_text(transaction_name)
# Some of the data that are toplevel attributes are duplicated
# into tags (logger, level, environment, transaction). These are
# different from legacy attributes which are normalized into tags
# ahead of time (site, server_name).
setdefault_path(data, 'tags', value=[])
set_tag(data, 'level', level)
if logger_name:
set_tag(data, 'logger', logger_name)
if environment:
set_tag(data, 'environment', environment)
if transaction_name:
set_tag(data, 'transaction', transaction_name)
if release:
# dont allow a conflicting 'release' tag
pop_tag(data, 'release')
release = Release.get_or_create(
project=project,
version=release,
date_added=date,
)
set_tag(data, 'sentry:release', release.version)
if dist and release:
dist = release.add_dist(dist, date)
# dont allow a conflicting 'dist' tag
pop_tag(data, 'dist')
set_tag(data, 'sentry:dist', dist.name)
else:
dist = None
event_user = self._get_event_user(project, data)
if event_user:
# dont allow a conflicting 'user' tag
pop_tag(data, 'user')
set_tag(data, 'sentry:user', event_user.tag_value)
# At this point we want to normalize the in_app values in case the
# clients did not set this appropriately so far.
grouping_config = load_grouping_config(
get_grouping_config_dict_for_event_data(data, project))
normalize_stacktraces_for_grouping(data, grouping_config)
for plugin in plugins.for_project(project, version=None):
added_tags = safe_execute(plugin.get_tags, event, _with_transaction=False)
if added_tags:
# plugins should not override user provided tags
for key, value in added_tags:
if get_tag(data, key) is None:
set_tag(data, key, value)
for path, iface in six.iteritems(event.interfaces):
for k, v in iface.iter_tags():
set_tag(data, k, v)
# Get rid of ephemeral interface data
if iface.ephemeral:
data.pop(iface.path, None)
# The active grouping config was put into the event in the
# normalize step before. We now also make sure that the
# fingerprint was set to `'{{ default }}' just in case someone
# removed it from the payload. The call to get_hashes will then
# look at `grouping_config` to pick the right paramters.
data['fingerprint'] = data.get('fingerprint') or ['{{ default }}']
apply_server_fingerprinting(data, get_fingerprinting_config_for_project(project))
# Here we try to use the grouping config that was requested in the
# event. If that config has since been deleted (because it was an
# experimental grouping config) we fall back to the default.
try:
hashes = event.get_hashes()
except GroupingConfigNotFound:
data['grouping_config'] = get_grouping_config_dict_for_project(project)
hashes = event.get_hashes()
data['hashes'] = hashes
# we want to freeze not just the metadata and type in but also the
# derived attributes. The reason for this is that we push this
# data into kafka for snuba processing and our postprocessing
# picks up the data right from the snuba topic. For most usage
# however the data is dynamically overriden by Event.title and
# Event.location (See Event.as_dict)
materialized_metadata = self.materialize_metadata()
event_metadata = materialized_metadata['metadata']
data.update(materialized_metadata)
data['culprit'] = culprit
# index components into ``Event.message``
# See GH-3248
event.message = self.get_search_message(event_metadata, culprit)
received_timestamp = event.data.get('received') or float(event.datetime.strftime('%s'))
# The group gets the same metadata as the event when it's flushed but
# additionally the `last_received` key is set. This key is used by
# _save_aggregate.
group_metadata = dict(materialized_metadata)
group_metadata['last_received'] = received_timestamp
kwargs = {
'platform': platform,
'message': event.message,
'culprit': culprit,
'logger': logger_name,
'level': LOG_LEVELS_MAP.get(level),
'last_seen': date,
'first_seen': date,
'active_at': date,
'data': group_metadata,
}
if release:
kwargs['first_release'] = release
try:
group, is_new, is_regression, is_sample = self._save_aggregate(
event=event, hashes=hashes, release=release, **kwargs
)
except HashDiscarded:
event_discarded.send_robust(
project=project,
sender=EventManager,
)
metrics.incr(
'events.discarded',
skip_internal=True,
tags={
'organization_id': project.organization_id,
'platform': platform,
},
)
raise
else:
event_saved.send_robust(
project=project,
event_size=event.size,
sender=EventManager,
)
event.group = group
# store a reference to the group id to guarantee validation of isolation
event.data.bind_ref(event)
# When an event was sampled, the canonical source of truth
# is the EventMapping table since we aren't going to be writing out an actual
# Event row. Otherwise, if the Event isn't being sampled, we can safely
# rely on the Event table itself as the source of truth and ignore
# EventMapping since it's redundant information.
if is_sample:
try:
with transaction.atomic(using=router.db_for_write(EventMapping)):
EventMapping.objects.create(project=project, group=group, event_id=event_id)
except IntegrityError:
logger.info(
'duplicate.found',
exc_info=True,
extra={
'event_uuid': event_id,
'project_id': project.id,
'group_id': group.id,
'model': EventMapping.__name__,
}
)
return event
environment = Environment.get_or_create(
project=project,
name=environment,
)
group_environment, is_new_group_environment = GroupEnvironment.get_or_create(
group_id=group.id,
environment_id=environment.id,
defaults={
'first_release': release if release else None,
},
)
if release:
ReleaseEnvironment.get_or_create(
project=project,
release=release,
environment=environment,
datetime=date,
)
ReleaseProjectEnvironment.get_or_create(
project=project,
release=release,
environment=environment,
datetime=date,
)
grouprelease = GroupRelease.get_or_create(
group=group,
release=release,
environment=environment,
datetime=date,
)
counters = [
(tsdb.models.group, group.id),
(tsdb.models.project, project.id),
]
if release:
counters.append((tsdb.models.release, release.id))
tsdb.incr_multi(counters, timestamp=event.datetime, environment_id=environment.id)
frequencies = [
# (tsdb.models.frequent_projects_by_organization, {
# project.organization_id: {
# project.id: 1,
# },
# }),
# (tsdb.models.frequent_issues_by_project, {
# project.id: {
# group.id: 1,
# },
# })
(tsdb.models.frequent_environments_by_group, {
group.id: {
environment.id: 1,
},
})
]
if release:
frequencies.append(
(tsdb.models.frequent_releases_by_group, {
group.id: {
grouprelease.id: 1,
},
})
)
tsdb.record_frequency_multi(frequencies, timestamp=event.datetime)
UserReport.objects.filter(
project=project,
event_id=event_id,
).update(
group=group,
environment=environment,
)
# Update any event attachment that arrived before the event group was defined.
EventAttachment.objects.filter(
project_id=project.id,
event_id=event_id,
).update(
group_id=group.id,
)
# save the event unless its been sampled
if not is_sample:
try:
with transaction.atomic(using=router.db_for_write(Event)):
event.save()
except IntegrityError:
logger.info(
'duplicate.found',
exc_info=True,
extra={
'event_uuid': event_id,
'project_id': project.id,
'group_id': group.id,
'model': Event.__name__,
}
)
return event
tagstore.delay_index_event_tags(
organization_id=project.organization_id,
project_id=project.id,
group_id=group.id,
environment_id=environment.id,
event_id=event.id,
tags=event.tags,
date_added=event.datetime,
)
if event_user:
tsdb.record_multi(
(
(tsdb.models.users_affected_by_group, group.id, (event_user.tag_value, )),
(tsdb.models.users_affected_by_project, project.id, (event_user.tag_value, )),
),
timestamp=event.datetime,
environment_id=environment.id,
)
if release:
if is_new:
buffer.incr(
ReleaseProject, {'new_groups': 1}, {
'release_id': release.id,
'project_id': project.id,
}
)
if is_new_group_environment:
buffer.incr(
ReleaseProjectEnvironment, {'new_issues_count': 1}, {
'project_id': project.id,
'release_id': release.id,
'environment_id': environment.id,
}
)
safe_execute(
Group.objects.add_tags,
group,
environment,
event.get_tags(),
_with_transaction=False)
if not raw:
if not project.first_event:
project.update(first_event=date)
first_event_received.send_robust(project=project, group=group, sender=Project)
eventstream.insert(
group=group,
event=event,
is_new=is_new,
is_sample=is_sample,
is_regression=is_regression,
is_new_group_environment=is_new_group_environment,
primary_hash=hashes[0],
# We are choosing to skip consuming the event back
# in the eventstream if it's flagged as raw.
# This means that we want to publish the event
# through the event stream, but we don't care
# about post processing and handling the commit.
skip_consume=raw,
)
metrics.timing(
'events.latency',
received_timestamp - recorded_timestamp,
tags={
'project_id': project.id,
},
)
metrics.timing(
'events.size.data.post_save',
event.size,
tags={'project_id': project.id}
)
return event
def save(self, project_id, raw=False, assume_normalized=False):
# Normalize if needed
if not self._normalized:
if not assume_normalized:
self.normalize()
self._normalized = True
data = self._data
project = Project.objects.get_from_cache(id=project_id)
project._organization_cache = Organization.objects.get_from_cache(
id=project.organization_id)
# Check to make sure we're not about to do a bunch of work that's
# already been done if we've processed an event with this ID. (This
# isn't a perfect solution -- this doesn't handle ``EventMapping`` and
# there's a race condition between here and when the event is actually
# saved, but it's an improvement. See GH-7677.)
try:
event = Event.objects.get(
project_id=project.id,
event_id=data['event_id'],
)
except Event.DoesNotExist:
pass
else:
# Make sure we cache on the project before returning
event._project_cache = project
logger.info(
'duplicate.found',
exc_info=True,
extra={
'event_uuid': data['event_id'],
'project_id': project.id,
'model': Event.__name__,
}
)
return event
# Pull out the culprit
culprit = self.get_culprit()
# Pull the toplevel data we're interested in
level = data.get('level')
# TODO(mitsuhiko): this code path should be gone by July 2018.
# This is going to be fine because no code actually still depends
# on integers here. When we need an integer it will be converted
# into one later. Old workers used to send integers here.
if level is not None and isinstance(level, six.integer_types):
level = LOG_LEVELS[level]
transaction_name = data.get('transaction')
logger_name = data.get('logger')
release = data.get('release')
dist = data.get('dist')
environment = data.get('environment')
recorded_timestamp = data.get('timestamp')
# We need to swap out the data with the one internal to the newly
# created event object
event = self._get_event_instance(project_id=project_id)
self._data = data = event.data.data
event._project_cache = project
date = event.datetime
platform = event.platform
event_id = event.event_id
if transaction_name:
transaction_name = force_text(transaction_name)
# Some of the data that are toplevel attributes are duplicated
# into tags (logger, level, environment, transaction). These are
# different from legacy attributes which are normalized into tags
# ahead of time (site, server_name).
setdefault_path(data, 'tags', value=[])
set_tag(data, 'level', level)
if logger_name:
set_tag(data, 'logger', logger_name)
if environment:
set_tag(data, 'environment', environment)
if transaction_name:
set_tag(data, 'transaction', transaction_name)
if release:
# dont allow a conflicting 'release' tag
pop_tag(data, 'release')
release = Release.get_or_create(
project=project,
version=release,
date_added=date,
)
set_tag(data, 'sentry:release', release.version)
if dist and release:
dist = release.add_dist(dist, date)
# dont allow a conflicting 'dist' tag
pop_tag(data, 'dist')
set_tag(data, 'sentry:dist', dist.name)
else:
dist = None
event_user = self._get_event_user(project, data)
if event_user:
# dont allow a conflicting 'user' tag
pop_tag(data, 'user')
set_tag(data, 'sentry:user', event_user.tag_value)
# At this point we want to normalize the in_app values in case the
# clients did not set this appropriately so far.
grouping_config = load_grouping_config(
get_grouping_config_dict_for_event_data(data, project))
normalize_stacktraces_for_grouping(data, grouping_config)
for plugin in plugins.for_project(project, version=None):
added_tags = safe_execute(plugin.get_tags, event, _with_transaction=False)
if added_tags:
# plugins should not override user provided tags
for key, value in added_tags:
if get_tag(data, key) is None:
set_tag(data, key, value)
for path, iface in six.iteritems(event.interfaces):
for k, v in iface.iter_tags():
set_tag(data, k, v)
# Get rid of ephemeral interface data
if iface.ephemeral:
data.pop(iface.path, None)
# The active grouping config was put into the event in the
# normalize step before. We now also make sure that the
# fingerprint was set to `'{{ default }}' just in case someone
# removed it from the payload. The call to get_hashes will then
# look at `grouping_config` to pick the right paramters.
data['fingerprint'] = data.get('fingerprint') or ['{{ default }}']
apply_server_fingerprinting(data, get_fingerprinting_config_for_project(project))
hashes = event.get_hashes()
data['hashes'] = hashes
# we want to freeze not just the metadata and type in but also the
# derived attributes. The reason for this is that we push this
# data into kafka for snuba processing and our postprocessing
# picks up the data right from the snuba topic. For most usage
# however the data is dynamically overriden by Event.title and
# Event.location (See Event.as_dict)
materialized_metadata = self.materialize_metadata()
event_metadata = materialized_metadata['metadata']
data.update(materialized_metadata)
data['culprit'] = culprit
# index components into ``Event.message``
# See GH-3248
event.message = self.get_search_message(event_metadata, culprit)
received_timestamp = event.data.get('received') or float(event.datetime.strftime('%s'))
# The group gets the same metadata as the event when it's flushed but
# additionally the `last_received` key is set. This key is used by
# _save_aggregate.
group_metadata = dict(materialized_metadata)
group_metadata['last_received'] = received_timestamp
kwargs = {
'platform': platform,
'message': event.message,
'culprit': culprit,
'logger': logger_name,
'level': LOG_LEVELS_MAP.get(level),
'last_seen': date,
'first_seen': date,
'active_at': date,
'data': group_metadata,
}
if release:
kwargs['first_release'] = release
try:
group, is_new, is_regression, is_sample = self._save_aggregate(
event=event, hashes=hashes, release=release, **kwargs
)
except HashDiscarded:
event_discarded.send_robust(
project=project,
sender=EventManager,
)
metrics.incr(
'events.discarded',
skip_internal=True,
tags={
'organization_id': project.organization_id,
'platform': platform,
},
)
raise
else:
event_saved.send_robust(
project=project,
event_size=event.size,
sender=EventManager,
)
event.group = group
# store a reference to the group id to guarantee validation of isolation
event.data.bind_ref(event)
# When an event was sampled, the canonical source of truth
# is the EventMapping table since we aren't going to be writing out an actual
# Event row. Otherwise, if the Event isn't being sampled, we can safely
# rely on the Event table itself as the source of truth and ignore
# EventMapping since it's redundant information.
if is_sample:
try:
with transaction.atomic(using=router.db_for_write(EventMapping)):
EventMapping.objects.create(project=project, group=group, event_id=event_id)
except IntegrityError:
logger.info(
'duplicate.found',
exc_info=True,
extra={
'event_uuid': event_id,
'project_id': project.id,
'group_id': group.id,
'model': EventMapping.__name__,
}
)
return event
environment = Environment.get_or_create(
project=project,
name=environment,
)
group_environment, is_new_group_environment = GroupEnvironment.get_or_create(
group_id=group.id,
environment_id=environment.id,
defaults={
'first_release': release if release else None,
},
)
if release:
ReleaseEnvironment.get_or_create(
project=project,
release=release,
environment=environment,
datetime=date,
)
ReleaseProjectEnvironment.get_or_create(
project=project,
release=release,
environment=environment,
datetime=date,
)
grouprelease = GroupRelease.get_or_create(
group=group,
release=release,
environment=environment,
datetime=date,
)
counters = [
(tsdb.models.group, group.id),
(tsdb.models.project, project.id),
]
if release:
counters.append((tsdb.models.release, release.id))
tsdb.incr_multi(counters, timestamp=event.datetime, environment_id=environment.id)
frequencies = [
# (tsdb.models.frequent_projects_by_organization, {
# project.organization_id: {
# project.id: 1,
# },
# }),
# (tsdb.models.frequent_issues_by_project, {
# project.id: {
# group.id: 1,
# },
# })
(tsdb.models.frequent_environments_by_group, {
group.id: {
environment.id: 1,
},
})
]
if release:
frequencies.append(
(tsdb.models.frequent_releases_by_group, {
group.id: {
grouprelease.id: 1,
},
})
)
tsdb.record_frequency_multi(frequencies, timestamp=event.datetime)
UserReport.objects.filter(
project=project,
event_id=event_id,
).update(
group=group,
environment=environment,
)
# save the event unless its been sampled
if not is_sample:
try:
with transaction.atomic(using=router.db_for_write(Event)):
event.save()
except IntegrityError:
logger.info(
'duplicate.found',
exc_info=True,
extra={
'event_uuid': event_id,
'project_id': project.id,
'group_id': group.id,
'model': Event.__name__,
}
)
return event
tagstore.delay_index_event_tags(
organization_id=project.organization_id,
project_id=project.id,
group_id=group.id,
environment_id=environment.id,
event_id=event.id,
tags=event.tags,
date_added=event.datetime,
)
if event_user:
tsdb.record_multi(
(
(tsdb.models.users_affected_by_group, group.id, (event_user.tag_value, )),
(tsdb.models.users_affected_by_project, project.id, (event_user.tag_value, )),
),
timestamp=event.datetime,
environment_id=environment.id,
)
if release:
if is_new:
buffer.incr(
ReleaseProject, {'new_groups': 1}, {
'release_id': release.id,
'project_id': project.id,
}
)
if is_new_group_environment:
buffer.incr(
ReleaseProjectEnvironment, {'new_issues_count': 1}, {
'project_id': project.id,
'release_id': release.id,
'environment_id': environment.id,
}
)
safe_execute(
Group.objects.add_tags,
group,
environment,
event.get_tags(),
_with_transaction=False)
if not raw:
if not project.first_event:
project.update(first_event=date)
first_event_received.send_robust(project=project, group=group, sender=Project)
eventstream.insert(
group=group,
event=event,
is_new=is_new,
is_sample=is_sample,
is_regression=is_regression,
is_new_group_environment=is_new_group_environment,
primary_hash=hashes[0],
# We are choosing to skip consuming the event back
# in the eventstream if it's flagged as raw.
# This means that we want to publish the event
# through the event stream, but we don't care
# about post processing and handling the commit.
skip_consume=raw,
)
metrics.timing(
'events.latency',
received_timestamp - recorded_timestamp,
tags={
'project_id': project.id,
},
)
metrics.timing(
'events.size.data.post_save',
event.size,
tags={'project_id': project.id}
)
return event
