feat(statistical-detectors): Temporarily forward regressions from fun… (

#57157)

…ction trends

We're still ironing out the detection pipeline but in order to produce
an occurrence for the regression issue, start creating them from the
results of the function trends endpoint.

src/sentry/api/endpoints/organization_profiling_functions.py

@@ -2,8 +2,9 @@
 
 from datetime import timedelta
 from enum import Enum
-from typing import Any
+from typing import Any, List
 
+import sentry_sdk
 from rest_framework import serializers
 from rest_framework.request import Request
 from rest_framework.response import Response
@@ -14,9 +15,11 @@
 from sentry.api.bases import NoProjects, OrganizationEventsV2EndpointBase
 from sentry.api.paginator import GenericOffsetPaginator
 from sentry.exceptions import InvalidSearchQuery
+from sentry.models.organization import Organization
+from sentry.profiles.utils import get_from_profiling_service
 from sentry.search.events.builder import ProfileTopFunctionsTimeseriesQueryBuilder
 from sentry.search.events.types import QueryBuilderConfig
-from sentry.seer.utils import detect_breakpoints
+from sentry.seer.utils import BreakpointData, detect_breakpoints
 from sentry.snuba import functions
 from sentry.snuba.dataset import Dataset
 from sentry.snuba.referrer import Referrer
@@ -68,12 +71,12 @@ class OrganizationProfilingFunctionTrendsEndpoint(OrganizationEventsV2EndpointBa
         "GET": ApiPublishStatus.UNKNOWN,
     }
 
-    def has_feature(self, organization, request):
+    def has_feature(self, organization: Organization, request: Request):
         return features.has(
             "organizations:profiling-global-suspect-functions", organization, actor=request.user
         )
 
-    def get(self, request: Request, organization) -> Response:
+    def get(self, request: Request, organization: Organization) -> Response:
         if not self.has_feature(organization, request):
             return Response(status=404)
 
@@ -154,7 +157,7 @@ def get_event_stats(_columns, query, params, _rollup, zerofill_results, _compari
 
             return results
 
-        def get_trends_data(stats_data):
+        def get_trends_data(stats_data) -> List[BreakpointData]:
             if not stats_data:
                 return []
 
@@ -220,6 +223,17 @@ def get_trends_data(stats_data):
             reverse=data["trend"] is TrendType.REGRESSION,
         )
 
+        if data["trend"] is TrendType.REGRESSION:
+            try:
+                if features.has(
+                    "organizations:profile-function-regression-exp-ingest",
+                    organization,
+                    actor=request.user,
+                ):
+                    forward_regression_occurrences(organization, trending_functions, stats_data)
+            except Exception as e:
+                sentry_sdk.capture_exception(e)
+
         def paginate_trending_events(offset, limit):
             return {"data": trending_functions[offset : limit + offset]}
 
@@ -308,3 +322,48 @@ def get_interval_from_range(date_range: timedelta) -> str:
         return "2h"
 
     return "1h"
+
+
+def forward_regression_occurrences(
+    organization: Organization,
+    regressions: List[BreakpointData],
+    stats_data: Any,
+):
+    payloads = []
+
+    for entry in regressions:
+        project_id = int(entry["project"])
+        fingerprint = int(entry["transaction"])
+
+        profile_id = None
+        examples = (
+            stats_data.get(f"{project_id},{fingerprint}", {}).get("worst()", {}).get("data", [])
+        )
+        for row in reversed(examples):
+            example = row[1][0]["count"]
+            if isinstance(example, str):
+                profile_id = example
+                break
+
+        if profile_id is None:
+            continue
+
+        payloads.append(
+            {
+                "organization_id": organization.id,
+                "project_id": project_id,
+                "profile_id": profile_id,
+                "fingerprint": fingerprint,
+                "absolute_percentage_change": entry["absolute_percentage_change"],
+                "aggregate_range_1": entry["aggregate_range_1"],
+                "aggregate_range_2": entry["aggregate_range_2"],
+                "breakpoint": int(entry["breakpoint"]),
+                "trend_difference": entry["trend_difference"],
+                "trend_percentage": entry["trend_percentage"],
+                "unweighted_p_value": entry["unweighted_p_value"],
+                "unweighted_t_value": entry["unweighted_t_value"],
+            }
+        )
+
+    get_from_profiling_service(method="POST", path="/regressed", json_data=payloads)
+    assert 0