HOTFIX výkon: delta-profile cache 44 s/site se přepočítávala každých 15 min

fn_fill_forecast_accuracy (tick :02/:17/:32/:47, 4 lokality) na konci volá
fn_refresh_site_pv_delta_profile_cache → fn_pv_forecast_delta_profile =
agregace 120 dní nad 4.1M řádky forecast_accuracy = ~44 s/site na prod
→ ~3 minuty plné DB zátěže KAŽDOU čtvrthodinu → timeouty /sites a
/health/detailed (30 s), celodenní 'pomalý server'.

Fix: (1) cache refresh throttle 6 h přes delta_profile_cached_at (+p_force;
profil má 14d poločas — 4×/den bohatě stačí); (2) 15min tick lookback
48→3 h (insert část); (3) denní 48h catch-up job 05:50.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

backend/app/lifespan.py

@@ -108,7 +108,7 @@ async def lifespan(app: FastAPI):
             for site in await _active_site_rows(conn):
                 try:
                     n = await conn.fetchval(
-                        "SELECT ems.fn_fill_forecast_accuracy($1, 48)",
+                        "SELECT ems.fn_fill_forecast_accuracy($1, 3)",
                         site["id"],
                     )
                     if n:
@@ -257,6 +257,19 @@ async def lifespan(app: FastAPI):
                         "scheduled_tuv_usage_stats site=%s failed", site["id"]
                     )
 
+    async def scheduled_forecast_accuracy_catchup() -> None:
+        """Denní 48h catch-up (pozdní telemetrie) — 15min tick jede jen 3 h okno."""
+        async with app.state.pg_pool.acquire() as conn:
+            for site in await _active_site_rows(conn):
+                try:
+                    await conn.fetchval(
+                        "SELECT ems.fn_fill_forecast_accuracy($1, 48)", site["id"]
+                    )
+                except Exception:
+                    logger.exception(
+                        "forecast_accuracy catchup site=%s failed", site["id"]
+                    )
+
     async def scheduled_ev_usage_stats() -> None:
         async with app.state.pg_pool.acquire() as conn:
             try:
@@ -431,6 +444,14 @@ async def lifespan(app: FastAPI):
         id="tuv_usage_stats",
         replace_existing=True,
     )
+    scheduler.add_job(
+        scheduled_forecast_accuracy_catchup,
+        "cron",
+        hour=5,
+        minute=50,
+        id="forecast_accuracy_catchup",
+        replace_existing=True,
+    )
     scheduler.add_job(
         scheduled_ev_usage_stats,
         "cron",

db/routines/R__018_fn_pv_delta_profile_cache.sql

@@ -1,13 +1,29 @@
 -- Cache delta profilu PV (těžká agregace forecast_accuracy) — refresh po fn_fill_forecast_accuracy.
 -- Prefix R__018: musí běžet před R__022 (volá fn_refresh_site_pv_delta_profile_cache).
 
-create or replace function ems.fn_refresh_site_pv_delta_profile_cache(p_site_id int)
+drop function if exists ems.fn_refresh_site_pv_delta_profile_cache(int);
+
+create or replace function ems.fn_refresh_site_pv_delta_profile_cache(
+  p_site_id int,
+  p_force boolean default false
+)
 returns void
 language plpgsql
 as $fn$
 declare
   v_profile jsonb;
 begin
+  -- VÝKON: agregace 120 dní nad forecast_accuracy trvá ~44 s/site na prod —
+  -- po 15 min ji přepočítávat dusilo celou DB (timeouty API). Profil má 14d
+  -- poločas, denní granularitu — čerstvost 6 h bohatě stačí.
+  if not p_force and exists (
+    select 1 from ems.site_pv_forecast_calibration c
+    where c.site_id = p_site_id
+      and c.delta_profile_cached_at > now() - interval '6 hours'
+  ) then
+    return;
+  end if;
+
   v_profile := ems.fn_pv_forecast_delta_profile(
     p_site_id,
     now() - interval '120 days',