def _do_symbolicate_event(cache_key, start_time, event_id, symbolicate_task, data=None):
from sentry.lang.native.processing import get_symbolication_function
if data is None:
data = default_cache.get(cache_key)
if data is None:
metrics.incr(
"events.failed", tags={"reason": "cache", "stage": "symbolicate"}, skip_internal=False
)
error_logger.error("symbolicate.failed.empty", extra={"cache_key": cache_key})
return
data = CanonicalKeyDict(data)
project_id = data["project"]
set_current_project(project_id)
event_id = data["event_id"]
symbolication_function = get_symbolication_function(data)
has_changed = False
from_reprocessing = symbolicate_task is symbolicate_event_from_reprocessing
try:
with sentry_sdk.start_span(op="tasks.store.symbolicate_event.symbolication") as span:
span.set_data("symbolicaton_function", symbolication_function.__name__)
with metrics.timer("tasks.store.symbolicate_event.symbolication"):
symbolicated_data = safe_execute(
symbolication_function, data, _passthrough_errors=(RetrySymbolication,)
)
span.set_data("symbolicated_data", bool(symbolicated_data))
if symbolicated_data:
data = symbolicated_data
has_changed = True
except RetrySymbolication as e:
if start_time and (time() - start_time) > settings.SYMBOLICATOR_PROCESS_EVENT_WARN_TIMEOUT:
error_logger.warning(
"symbolicate.slow", extra={"project_id": project_id, "event_id": event_id}
)
if start_time and (time() - start_time) > settings.SYMBOLICATOR_PROCESS_EVENT_HARD_TIMEOUT:
# Do not drop event but actually continue with rest of pipeline
# (persisting unsymbolicated event)
error_logger.exception(
"symbolicate.failed.infinite_retry",
extra={"project_id": project_id, "event_id": event_id},
)
else:
# Requeue the task in the "sleep" queue
retry_symbolicate_event.apply_async(
args=(),
kwargs={
"symbolicate_task_name": symbolicate_task.__name__,
"task_kwargs": {
"cache_key": cache_key,
"event_id": event_id,
"start_time": start_time,
},
},
countdown=e.retry_after,
)
return
# We cannot persist canonical types in the cache, so we need to
# downgrade this.
if isinstance(data, CANONICAL_TYPES):
data = dict(data.items())
if has_changed:
default_cache.set(cache_key, data, 3600)
process_task = process_event_from_reprocessing if from_reprocessing else process_event
_do_process_event(
cache_key=cache_key,
start_time=start_time,
event_id=event_id,
process_task=process_task,
data=data,
data_has_changed=has_changed,
from_symbolicate=True,
)
def _do_symbolicate_event(cache_key,
start_time,
event_id,
symbolicate_task,
data=None):
from sentry.lang.native.processing import get_symbolication_function
if data is None:
data = event_processing_store.get(cache_key)
if data is None:
metrics.incr("events.failed",
tags={
"reason": "cache",
"stage": "symbolicate"
},
skip_internal=False)
error_logger.error("symbolicate.failed.empty",
extra={"cache_key": cache_key})
return
data = CanonicalKeyDict(data)
project_id = data["project"]
set_current_event_project(project_id)
event_id = data["event_id"]
if killswitch_matches_context(
"store.load-shed-symbolicate-event-projects",
{
"project_id": project_id,
"event_id": event_id,
"platform": data.get("platform") or "null",
},
):
return
symbolication_function = get_symbolication_function(data)
has_changed = False
from_reprocessing = symbolicate_task is symbolicate_event_from_reprocessing
symbolication_start_time = time()
with sentry_sdk.start_span(
op="tasks.store.symbolicate_event.symbolication") as span:
span.set_data("symbolicaton_function", symbolication_function.__name__)
with metrics.timer(
"tasks.store.symbolicate_event.symbolication",
tags={
"symbolication_function": symbolication_function.__name__
},
):
while True:
try:
with sentry_sdk.start_span(
op="tasks.store.symbolicate_event.%s" %
symbolication_function.__name__) as span:
symbolicated_data = symbolication_function(data)
span.set_data("symbolicated_data",
bool(symbolicated_data))
if symbolicated_data:
data = symbolicated_data
has_changed = True
break
except RetrySymbolication as e:
if (time() - symbolication_start_time
) > settings.SYMBOLICATOR_PROCESS_EVENT_WARN_TIMEOUT:
error_logger.warning(
"symbolicate.slow",
extra={
"project_id": project_id,
"event_id": event_id
},
)
if (time() - symbolication_start_time
) > settings.SYMBOLICATOR_PROCESS_EVENT_HARD_TIMEOUT:
# Do not drop event but actually continue with rest of pipeline
# (persisting unsymbolicated event)
metrics.incr(
"tasks.store.symbolicate_event.fatal",
tags={
"reason":
"timeout",
"symbolication_function":
symbolication_function.__name__,
},
)
error_logger.exception(
"symbolicate.failed.infinite_retry",
extra={
"project_id": project_id,
"event_id": event_id
},
)
data.setdefault("_metrics",
{})["flag.processing.error"] = True
data.setdefault("_metrics",
{})["flag.processing.fatal"] = True
has_changed = True
break
else:
# sleep for `retry_after` but max 5 seconds and try again
metrics.incr(
"tasks.store.symbolicate_event.retry",
tags={
"symbolication_function":
symbolication_function.__name__
},
)
sleep(min(e.retry_after, SYMBOLICATOR_MAX_RETRY_AFTER))
continue
except Exception:
metrics.incr(
"tasks.store.symbolicate_event.fatal",
tags={
"reason":
"error",
"symbolication_function":
symbolication_function.__name__,
},
)
error_logger.exception(
"tasks.store.symbolicate_event.symbolication")
data.setdefault("_metrics",
{})["flag.processing.error"] = True
data.setdefault("_metrics",
{})["flag.processing.fatal"] = True
has_changed = True
break
# We cannot persist canonical types in the cache, so we need to
# downgrade this.
if isinstance(data, CANONICAL_TYPES):
data = dict(data.items())
if has_changed:
cache_key = event_processing_store.store(data)
process_task = process_event_from_reprocessing if from_reprocessing else process_event
_do_process_event(
cache_key=cache_key,
start_time=start_time,
event_id=event_id,
process_task=process_task,
data=data,
data_has_changed=has_changed,
from_symbolicate=True,
)
def _do_symbolicate_event(
cache_key, start_time, event_id, symbolicate_task, data=None, queue_switches=0
):
from sentry.lang.native.processing import get_symbolication_function
if data is None:
data = event_processing_store.get(cache_key)
if data is None:
metrics.incr(
"events.failed", tags={"reason": "cache", "stage": "symbolicate"}, skip_internal=False
)
error_logger.error("symbolicate.failed.empty", extra={"cache_key": cache_key})
return
data = CanonicalKeyDict(data)
project_id = data["project"]
set_current_event_project(project_id)
event_id = data["event_id"]
from_reprocessing = (
symbolicate_task is symbolicate_event_from_reprocessing
or symbolicate_task is symbolicate_event_from_reprocessing_low_priority
)
# check whether the event is in the wrong queue and if so, move it to the other one.
# we do this at most SYMBOLICATOR_MAX_QUEUE_SWITCHES times.
if queue_switches >= SYMBOLICATOR_MAX_QUEUE_SWITCHES:
metrics.gauge("tasks.store.symbolicate_event.low_priority.max_queue_switches", 1)
else:
is_low_priority = symbolicate_task in [
symbolicate_event_low_priority,
symbolicate_event_from_reprocessing_low_priority,
]
should_be_low_priority = should_demote_symbolication(project_id)
if is_low_priority != should_be_low_priority:
metrics.gauge("tasks.store.symbolicate_event.low_priority.wrong_queue", 1)
submit_symbolicate(
should_be_low_priority,
from_reprocessing,
cache_key,
event_id,
start_time,
data,
queue_switches + 1,
)
return
def _continue_to_process_event():
process_task = process_event_from_reprocessing if from_reprocessing else process_event
_do_process_event(
cache_key=cache_key,
start_time=start_time,
event_id=event_id,
process_task=process_task,
data=data,
data_has_changed=has_changed,
from_symbolicate=True,
)
symbolication_function = get_symbolication_function(data)
symbolication_function_name = getattr(symbolication_function, "__name__", "none")
if killswitch_matches_context(
"store.load-shed-symbolicate-event-projects",
{
"project_id": project_id,
"event_id": event_id,
"platform": data.get("platform") or "null",
"symbolication_function": symbolication_function_name,
},
):
return _continue_to_process_event()
has_changed = False
symbolication_start_time = time()
submission_ratio = options.get("symbolicate-event.low-priority.metrics.submission-rate")
submit_realtime_metrics = not from_reprocessing and random.random() < submission_ratio
if submit_realtime_metrics:
with sentry_sdk.start_span(op="tasks.store.symbolicate_event.low_priority.metrics.counter"):
timestamp = int(symbolication_start_time)
try:
realtime_metrics.increment_project_event_counter(project_id, timestamp)
except Exception as e:
sentry_sdk.capture_exception(e)
with sentry_sdk.start_span(op="tasks.store.symbolicate_event.symbolication") as span:
span.set_data("symbolication_function", symbolication_function_name)
with metrics.timer(
"tasks.store.symbolicate_event.symbolication",
tags={"symbolication_function": symbolication_function_name},
):
while True:
try:
with sentry_sdk.start_span(
op="tasks.store.symbolicate_event.%s" % symbolication_function_name
) as span:
symbolicated_data = symbolication_function(data)
span.set_data("symbolicated_data", bool(symbolicated_data))
if symbolicated_data:
data = symbolicated_data
has_changed = True
break
except RetrySymbolication as e:
if (
time() - symbolication_start_time
) > settings.SYMBOLICATOR_PROCESS_EVENT_WARN_TIMEOUT:
error_logger.warning(
"symbolicate.slow",
extra={"project_id": project_id, "event_id": event_id},
)
if (
time() - symbolication_start_time
) > settings.SYMBOLICATOR_PROCESS_EVENT_HARD_TIMEOUT:
# Do not drop event but actually continue with rest of pipeline
# (persisting unsymbolicated event)
metrics.incr(
"tasks.store.symbolicate_event.fatal",
tags={
"reason": "timeout",
"symbolication_function": symbolication_function_name,
},
)
error_logger.exception(
"symbolicate.failed.infinite_retry",
extra={"project_id": project_id, "event_id": event_id},
)
data.setdefault("_metrics", {})["flag.processing.error"] = True
data.setdefault("_metrics", {})["flag.processing.fatal"] = True
has_changed = True
break
else:
# sleep for `retry_after` but max 5 seconds and try again
metrics.incr(
"tasks.store.symbolicate_event.retry",
tags={"symbolication_function": symbolication_function_name},
)
sleep(min(e.retry_after, SYMBOLICATOR_MAX_RETRY_AFTER))
continue
except Exception:
metrics.incr(
"tasks.store.symbolicate_event.fatal",
tags={
"reason": "error",
"symbolication_function": symbolication_function_name,
},
)
error_logger.exception("tasks.store.symbolicate_event.symbolication")
data.setdefault("_metrics", {})["flag.processing.error"] = True
data.setdefault("_metrics", {})["flag.processing.fatal"] = True
has_changed = True
break
if submit_realtime_metrics:
with sentry_sdk.start_span(
op="tasks.store.symbolicate_event.low_priority.metrics.histogram"
):
symbolication_duration = int(time() - symbolication_start_time)
try:
realtime_metrics.increment_project_duration_counter(
project_id, timestamp, symbolication_duration
)
except Exception as e:
sentry_sdk.capture_exception(e)
# We cannot persist canonical types in the cache, so we need to
# downgrade this.
if isinstance(data, CANONICAL_TYPES):
data = dict(data.items())
if has_changed:
cache_key = event_processing_store.store(data)
return _continue_to_process_event()
