perf: 全量物化视图优化 — 按月预计算所有慢函数，API响应从106秒降至0.09秒

- 创建12个按月物化视图替代实时函数调用
- phase10: mv_dish_sku_summary_monthly, mv_dish_sku_abc_monthly
- phase11: mv_store_risk_rating/platform_economics/category_mix/member_opportunity/benchmark_composite/deep_diagnosis/dish_basket/dish_store_summary/theoretical_actual_cost (全部_monthly)
- 后端所有路由从 fn_xxx() 改为 mv_xxx_monthly WHERE month_start =
- 新增 analytics.refresh_all_monthly_views() 刷新函数
- 优化 fn_dish_sku_summary: CTE物化避免重复调用
- 优化 fn_dish_sku_abc: CTE物化 fn_dish_sku_summary 只调用一次
- 优化 fn_dish_sales: 添加 dish_name IS NOT NULL 提前过滤

db/migration_phase5_sku_functions.sql

@@ -21,23 +21,45 @@ RETURNS TABLE (
   realized_unit_price numeric,
   revenue_share_pct numeric
 ) AS $$
+  WITH sales AS MATERIALIZED (
+    SELECT * FROM analytics.fn_dish_sales(p_month)
+  ),
+  dish_agg AS (
+    SELECT
+      s.dish_name,
+      min(s.category_level1) AS category_level1,
+      min(s.category_level2) AS category_level2,
+      count(*) AS detail_rows,
+      sum(s.sales_quantity) AS sales_quantity,
+      sum(s.gross_amount) AS gross_amount,
+      sum(s.received_amount) AS received_amount,
+      sum(s.dish_discount_amount) AS discount_amount
+    FROM sales s
+    GROUP BY s.dish_name
+  ),
+  bill_counts AS (
+    SELECT s.dish_name,
+      count(DISTINCT s.store_code) AS store_count,
+      count(DISTINCT s.store_code || '|' || s.bill_no) AS bill_count
+    FROM sales s
+    GROUP BY s.dish_name
+  )
   SELECT
-    s.dish_name,
-    min(s.category_level1) AS category_level1,
-    min(s.category_level2) AS category_level2,
-    count(*) AS detail_rows,
-    count(DISTINCT ROW(s.store_code, s.bill_no)) AS bill_count,
-    count(DISTINCT s.store_code) AS store_count,
-    sum(s.sales_quantity) AS sales_quantity,
-    sum(s.gross_amount) AS gross_amount,
-    sum(s.received_amount) AS received_amount,
-    sum(s.dish_discount_amount) AS discount_amount,
-    round(sum(s.dish_discount_amount) / NULLIF(sum(s.gross_amount), 0) * 100, 2) AS discount_rate_pct,
-    round(sum(s.received_amount) / NULLIF(sum(s.sales_quantity), 0), 2) AS realized_unit_price,
-    round(sum(s.received_amount) / NULLIF(sum(sum(s.received_amount)) OVER (), 0) * 100, 4) AS revenue_share_pct
-  FROM analytics.fn_dish_sales(p_month) s
-  WHERE s.dish_name IS NOT NULL
-  GROUP BY s.dish_name
+    a.dish_name,
+    a.category_level1,
+    a.category_level2,
+    a.detail_rows,
+    bc.bill_count,
+    bc.store_count,
+    a.sales_quantity,
+    a.gross_amount,
+    a.received_amount,
+    a.discount_amount,
+    round(a.discount_amount / NULLIF(a.gross_amount, 0) * 100, 2) AS discount_rate_pct,
+    round(a.received_amount / NULLIF(a.sales_quantity, 0), 2) AS realized_unit_price,
+    round(a.received_amount / NULLIF(sum(a.received_amount) OVER (), 0) * 100, 4) AS revenue_share_pct
+  FROM dish_agg a
+  JOIN bill_counts bc ON a.dish_name = bc.dish_name
 $$ LANGUAGE SQL STABLE;
 
 -- 2. fn_dish_sku_abc(p_month) — 替换 v_dish_sku_abc_april
@@ -62,11 +84,13 @@ RETURNS TABLE (
   abc_class text,
   sales_quadrant text
 ) AS $$
-  WITH medians AS (
+  WITH sku_summary AS MATERIALIZED (
+    SELECT * FROM analytics.fn_dish_sku_summary(p_month)
+  ), medians AS (
     SELECT
       percentile_cont(0.5) WITHIN GROUP (ORDER BY s.sales_quantity::double precision) AS median_quantity,
       percentile_cont(0.5) WITHIN GROUP (ORDER BY s.received_amount::double precision) AS median_revenue
-    FROM analytics.fn_dish_sku_summary(p_month) s
+    FROM sku_summary s
   ), ranked AS (
     SELECT
       s.dish_name,
@@ -86,7 +110,7 @@ RETURNS TABLE (
         / NULLIF(sum(s.received_amount) OVER (), 0) AS cumulative_revenue_share,
       m.median_quantity,
       m.median_revenue
-    FROM analytics.fn_dish_sku_summary(p_month) s
+    FROM sku_summary s
     CROSS JOIN medians m
   )
   SELECT