def get_event_stats(
query_columns: Sequence[str],
query: str,
params: Dict[str, str],
rollup: int,
zerofill_results: bool,
comparison_delta: Optional[datetime],
) -> SnubaTSResult:
if top_events > 0:
return discover.top_events_timeseries(
timeseries_columns=query_columns,
selected_columns=self.get_field_list(
organization, request),
equations=self.get_equation_list(organization, request),
user_query=query,
params=params,
orderby=self.get_orderby(request),
rollup=rollup,
limit=top_events,
organization=organization,
referrer=referrer + ".find-topn",
allow_empty=False,
zerofill_results=zerofill_results,
include_other=self.has_top_events(organization, request),
)
return discover.timeseries_query(
selected_columns=query_columns,
query=query,
params=params,
rollup=rollup,
referrer=referrer,
zerofill_results=zerofill_results,
comparison_delta=comparison_delta,
)
def get_event_stats(query_columns, query, params, rollup,
zerofill_results):
if top_events > 0:
return discover.top_events_timeseries(
timeseries_columns=query_columns,
selected_columns=self.get_field_list(
organization, request),
equations=self.get_equation_list(organization, request),
user_query=query,
params=params,
orderby=self.get_orderby(request),
rollup=rollup,
limit=top_events,
organization=organization,
referrer="api.organization-event-stats.find-topn",
allow_empty=False,
zerofill_results=zerofill_results,
include_other=self.has_top_events(organization, request),
)
return discover.timeseries_query(
selected_columns=query_columns,
query=query,
params=params,
rollup=rollup,
referrer="api.organization-event-stats",
zerofill_results=zerofill_results,
)
def get_event_stats(query_columns, query, params, rollup):
return discover.top_events_timeseries(
query_columns,
selected_columns,
query,
params,
orderby,
rollup,
min(5, len(events_results["data"])),
organization,
top_events=events_results,
referrer="api.trends.get-event-stats",
)
def get_event_stats(
query_columns, query, params, rollup, zerofill_results, comparison_delta=None
):
return discover.top_events_timeseries(
query_columns,
selected_columns,
query,
params,
orderby,
rollup,
min(5, len(events_results["data"])),
organization,
top_events=events_results,
referrer="api.trends.get-event-stats",
zerofill_results=zerofill_results,
use_snql=use_snql,
)
def get_event_stats(query_columns, query, params, rollup):
if top_events:
return discover.top_events_timeseries(
timeseries_columns=query_columns,
selected_columns=request.GET.getlist("field")[:],
user_query=query,
params=params,
orderby=self.get_orderby(request),
rollup=rollup,
limit=limit,
organization=organization,
referrer="api.organization-event-stats.find-topn",
)
return discover.timeseries_query(
selected_columns=query_columns,
query=query,
params=params,
rollup=rollup,
referrer="api.organization-event-stats",
)
def get_stats(self, project_ids, query):
# we need to compute stats at 1d (1h resolution), and 14d
segments, interval = STATS_PERIOD_CHOICES[self.stats_period]
now = timezone.now()
params = {
"project_id": project_ids,
"start": now - ((segments - 1) * interval),
"end": now,
}
if self.environment_id:
query = f"{query} environment:{self.environment_id}"
# Generate a query result to skip the top_events.find query
top_events = {"data": [{"project_id": p} for p in project_ids]}
stats = discover.top_events_timeseries(
timeseries_columns=["count()"],
selected_columns=["project_id"],
user_query=query,
params=params,
orderby="project_id",
rollup=int(interval.total_seconds()),
limit=10000,
organization=None,
referrer="api.serializer.projects.get_stats",
top_events=top_events,
)
results = {}
for project_id in project_ids:
serialized = []
str_id = str(project_id)
if str_id in stats:
for item in stats[str_id].data["data"]:
serialized.append((item["time"], item.get("count", 0)))
results[project_id] = serialized
return results
