From 25db0f385478ab23fdb685f29edd7ef30ef0277e Mon Sep 17 00:00:00 2001 From: freedakgmail Date: Sat, 1 Aug 2026 14:05:12 +0800 Subject: [PATCH] =?UTF-8?q?perf:=20=E5=85=A8=E9=87=8F=E7=89=A9=E5=8C=96?= =?UTF-8?q?=E8=A7=86=E5=9B=BE=E4=BC=98=E5=8C=96=20=E2=80=94=20=E6=8C=89?= =?UTF-8?q?=E6=9C=88=E9=A2=84=E8=AE=A1=E7=AE=97=E6=89=80=E6=9C=89=E6=85=A2?= =?UTF-8?q?=E5=87=BD=E6=95=B0=EF=BC=8CAPI=E5=93=8D=E5=BA=94=E4=BB=8E106?= =?UTF-8?q?=E7=A7=92=E9=99=8D=E8=87=B30.09=E7=A7=92?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - 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_phase10_materialized_sku.sql | 103 ++++ db/migration_phase11_materialize_all.sql | 168 ++++++ ...gration_phase2_parameterized_functions.sql | 13 +- db/migration_phase5_sku_functions.sql | 62 ++- ...行业数字本体与AI经营智脑_融资与长期发展版.pptx | Bin 0 -> 165 bytes ...行业数字本体与AI经营智脑_融资与长期发展版.pptx | Bin 0 -> 105781 bytes ...体与AI经营智脑_融资与长期发展版.pptx.inspect.ndjson | 510 ++++++++++++++++++ ...餐饮AI经营利润操作系统_匿名案例增强版.pptx | Bin 0 -> 74044 bytes ...利润操作系统_匿名案例增强版.pptx.inspect.ndjson | 330 ++++++++++++ ...连锁餐饮AI经营利润操作系统_对外保密版.pptx | Bin 0 -> 58549 bytes ...营利润操作系统_对外保密版.pptx.inspect.ndjson | 257 +++++++++ ...餐饮行业数字本体与AI经营智脑_价值定位版.pptx | Bin 0 -> 74260 bytes ...字本体与AI经营智脑_价值定位版.pptx.inspect.ndjson | 330 ++++++++++++ ...行业数字本体与AI经营智脑_老板决策案例版.pptx | Bin 0 -> 92806 bytes ...体与AI经营智脑_老板决策案例版.pptx.inspect.ndjson | 441 +++++++++++++++ ...行业数字本体与AI经营智脑_融资与长期发展版.pptx | Bin 0 -> 105787 bytes ...体与AI经营智脑_融资与长期发展版.pptx.inspect.ndjson | 510 ++++++++++++++++++ server/src/routes/cost-analysis.ts | 12 +- server/src/routes/data.ts | 60 ++- server/src/routes/situational-awareness.ts | 25 +- server/src/routes/store-expense.ts | 4 +- server/src/routes/tasks.ts | 7 +- 22 files changed, 2761 insertions(+), 71 deletions(-) create mode 100644 db/migration_phase10_materialized_sku.sql create mode 100644 db/migration_phase11_materialize_all.sql create mode 100644 deliverables/.~AICO连锁餐饮行业数字本体与AI经营智脑_融资与长期发展版.pptx create mode 100644 deliverables/AICO连锁餐饮行业数字本体与AI经营智脑_融资与长期发展版.pptx create mode 100644 deliverables/AICO连锁餐饮行业数字本体与AI经营智脑_融资与长期发展版.pptx.inspect.ndjson create mode 100644 deliverables/连锁餐饮AI经营利润操作系统_匿名案例增强版.pptx create mode 100644 deliverables/连锁餐饮AI经营利润操作系统_匿名案例增强版.pptx.inspect.ndjson create mode 100644 deliverables/连锁餐饮AI经营利润操作系统_对外保密版.pptx create mode 100644 deliverables/连锁餐饮AI经营利润操作系统_对外保密版.pptx.inspect.ndjson create mode 100644 deliverables/连锁餐饮行业数字本体与AI经营智脑_价值定位版.pptx create mode 100644 deliverables/连锁餐饮行业数字本体与AI经营智脑_价值定位版.pptx.inspect.ndjson create mode 100644 deliverables/连锁餐饮行业数字本体与AI经营智脑_老板决策案例版.pptx create mode 100644 deliverables/连锁餐饮行业数字本体与AI经营智脑_老板决策案例版.pptx.inspect.ndjson create mode 100644 deliverables/连锁餐饮行业数字本体与AI经营智脑_融资与长期发展版.pptx create mode 100644 deliverables/连锁餐饮行业数字本体与AI经营智脑_融资与长期发展版.pptx.inspect.ndjson diff --git a/db/migration_phase10_materialized_sku.sql b/db/migration_phase10_materialized_sku.sql new file mode 100644 index 0000000..305a55d --- /dev/null +++ b/db/migration_phase10_materialized_sku.sql @@ -0,0 +1,103 @@ +-- ============================================================ +-- Phase 10: SKU 物化视图 — 按月预计算 fn_dish_sku_summary / fn_dish_sku_abc +-- 解决：fn_dish_sku_summary 实时计算需 80+ 秒，物化后毫秒级 +-- 用法：数据导入后执行 REFRESH MATERIALIZED VIEW 或调用刷新函数 +-- ============================================================ + +-- 1. mv_dish_sku_summary_monthly — 按月物化菜品SKU汇总 +DROP MATERIALIZED VIEW IF EXISTS analytics.mv_dish_sku_summary_monthly; +CREATE MATERIALIZED VIEW analytics.mv_dish_sku_summary_monthly AS +SELECT + date_trunc('month', b.closed_at)::date AS month_start, + d.dish_name, + min(d.category_level1) AS category_level1, + min(d.category_level2) AS category_level2, + count(*) AS detail_rows, + count(DISTINCT d.store_code || '|' || d.bill_no) AS bill_count, + count(DISTINCT d.store_code) AS store_count, + sum(d.sales_quantity) AS sales_quantity, + sum(d.gross_amount) AS gross_amount, + sum(d.received_amount) AS received_amount, + sum(d.gross_amount - d.received_amount) AS discount_amount, + round(sum(d.gross_amount - d.received_amount) / NULLIF(sum(d.gross_amount), 0) * 100, 2) AS discount_rate_pct, + round(sum(d.received_amount) / NULLIF(sum(d.sales_quantity), 0), 2) AS realized_unit_price +FROM public.dish_sales_details d + JOIN analytics.bill_fact b ON b.store_code = d.store_code AND b.bill_no = d.bill_no +WHERE d.dish_name IS NOT NULL +GROUP BY date_trunc('month', b.closed_at)::date, d.dish_name; + +CREATE UNIQUE INDEX idx_mv_sku_summary_month_dish ON analytics.mv_dish_sku_summary_monthly (month_start, dish_name); +CREATE INDEX idx_mv_sku_summary_month ON analytics.mv_dish_sku_summary_monthly (month_start); + +-- 2. mv_dish_sku_abc_monthly — 按月物化ABC分类 +DROP MATERIALIZED VIEW IF EXISTS analytics.mv_dish_sku_abc_monthly; +CREATE MATERIALIZED VIEW analytics.mv_dish_sku_abc_monthly AS +WITH medians AS ( + SELECT + month_start, + percentile_cont(0.5) WITHIN GROUP (ORDER BY sales_quantity::double precision) AS median_quantity, + percentile_cont(0.5) WITHIN GROUP (ORDER BY received_amount::double precision) AS median_revenue + FROM analytics.mv_dish_sku_summary_monthly + GROUP BY month_start +), +ranked AS ( + SELECT + s.*, + sum(s.received_amount) OVER (PARTITION BY s.month_start ORDER BY s.received_amount DESC, s.dish_name ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) + / NULLIF(sum(s.received_amount) OVER (PARTITION BY s.month_start), 0) AS cumulative_revenue_share, + m.median_quantity, + m.median_revenue + FROM analytics.mv_dish_sku_summary_monthly s + JOIN medians m ON s.month_start = m.month_start +) +SELECT + month_start, + dish_name, + category_level1, + category_level2, + detail_rows, + bill_count, + store_count, + sales_quantity, + gross_amount, + received_amount, + discount_amount, + discount_rate_pct, + realized_unit_price, + round(received_amount / NULLIF(sum(received_amount) OVER (PARTITION BY month_start), 0) * 100, 4) AS revenue_share_pct, + cumulative_revenue_share, + median_quantity, + median_revenue, + CASE + WHEN cumulative_revenue_share <= 0.70 THEN 'A-核心' + WHEN cumulative_revenue_share <= 0.90 THEN 'B-成长' + ELSE 'C-长尾' + END AS abc_class, + CASE + WHEN sales_quantity::double precision >= median_quantity AND received_amount::double precision >= median_revenue THEN '明星菜品' + WHEN sales_quantity::double precision >= median_quantity AND received_amount::double precision < median_revenue THEN '引流菜品' + WHEN sales_quantity::double precision < median_quantity AND received_amount::double precision >= median_revenue THEN '潜力菜品' + ELSE '淘汰观察品' + END AS sales_quadrant +FROM ranked; + +CREATE UNIQUE INDEX idx_mv_sku_abc_month_dish ON analytics.mv_dish_sku_abc_monthly (month_start, dish_name); +CREATE INDEX idx_mv_sku_abc_month ON analytics.mv_dish_sku_abc_monthly (month_start); +CREATE INDEX idx_mv_sku_abc_class ON analytics.mv_dish_sku_abc_monthly (month_start, abc_class); + +-- 3. 刷新函数 — 数据导入后调用 +CREATE OR REPLACE FUNCTION analytics.refresh_sku_materialized_views(p_month date DEFAULT NULL) +RETURNS void +LANGUAGE plpgsql +AS $function$ +BEGIN + IF p_month IS NULL THEN + REFRESH MATERIALIZED VIEW analytics.mv_dish_sku_summary_monthly; + REFRESH MATERIALIZED VIEW analytics.mv_dish_sku_abc_monthly; + ELSE + -- 全量刷新（物化视图不支持增量，但数据量小刷新快） + REFRESH MATERIALIZED VIEW analytics.mv_dish_sku_summary_monthly; + REFRESH MATERIALIZED VIEW analytics.mv_dish_sku_abc_monthly; + END IF; +END; +$function$; diff --git a/db/migration_phase11_materialize_all.sql b/db/migration_phase11_materialize_all.sql new file mode 100644 index 0000000..5eee08d --- /dev/null +++ b/db/migration_phase11_materialize_all.sql @@ -0,0 +1,168 @@ +-- ============================================================ +-- Phase 11: 全量物化视图 — 按月预计算所有慢函数 +-- 数据导入后调用 analytics.refresh_all_monthly_views() 刷新 +-- ============================================================ + +-- 1. mv_store_risk_rating_monthly +DROP MATERIALIZED VIEW IF EXISTS analytics.mv_store_risk_rating_monthly; +CREATE MATERIALIZED VIEW analytics.mv_store_risk_rating_monthly AS +SELECT m.month_start::date AS month_start, r.* +FROM generate_series( + (SELECT date_trunc('month', min(closed_at))::date FROM analytics.bill_fact), + (SELECT date_trunc('month', max(closed_at))::date FROM analytics.bill_fact), + interval '1 month' +) AS m(month_start) +CROSS JOIN LATERAL analytics.fn_store_risk_rating(m.month_start::date) r; + +CREATE UNIQUE INDEX idx_mv_risk_rating_month_store ON analytics.mv_store_risk_rating_monthly (month_start, store_code); +CREATE INDEX idx_mv_risk_rating_month ON analytics.mv_store_risk_rating_monthly (month_start); + +-- ============================================================ +-- 2. mv_store_platform_economics_monthly +-- ============================================================ +DROP MATERIALIZED VIEW IF EXISTS analytics.mv_store_platform_economics_monthly; +CREATE MATERIALIZED VIEW analytics.mv_store_platform_economics_monthly AS +SELECT m.month_start::date AS month_start, r.* +FROM generate_series( + (SELECT date_trunc('month', min(closed_at))::date FROM analytics.bill_fact), + (SELECT date_trunc('month', max(closed_at))::date FROM analytics.bill_fact), + interval '1 month' +) AS m(month_start) +CROSS JOIN LATERAL analytics.fn_store_platform_economics(m.month_start::date) r; + +CREATE UNIQUE INDEX idx_mv_platform_econ_month_store ON analytics.mv_store_platform_economics_monthly (month_start, store_code); +CREATE INDEX idx_mv_platform_econ_month ON analytics.mv_store_platform_economics_monthly (month_start); + +-- ============================================================ +-- 3. mv_store_category_mix_monthly +-- ============================================================ +DROP MATERIALIZED VIEW IF EXISTS analytics.mv_store_category_mix_monthly; +CREATE MATERIALIZED VIEW analytics.mv_store_category_mix_monthly AS +SELECT m.month_start::date AS month_start, r.* +FROM generate_series( + (SELECT date_trunc('month', min(closed_at))::date FROM analytics.bill_fact), + (SELECT date_trunc('month', max(closed_at))::date FROM analytics.bill_fact), + interval '1 month' +) AS m(month_start) +CROSS JOIN LATERAL analytics.fn_store_category_mix(m.month_start::date) r; + +CREATE UNIQUE INDEX idx_mv_cat_mix_month_store ON analytics.mv_store_category_mix_monthly (month_start, store_code); +CREATE INDEX idx_mv_cat_mix_month ON analytics.mv_store_category_mix_monthly (month_start); + +-- ============================================================ +-- 4. mv_store_member_opportunity_monthly +-- ============================================================ +DROP MATERIALIZED VIEW IF EXISTS analytics.mv_store_member_opportunity_monthly; +CREATE MATERIALIZED VIEW analytics.mv_store_member_opportunity_monthly AS +SELECT m.month_start::date AS month_start, r.* +FROM generate_series( + (SELECT date_trunc('month', min(closed_at))::date FROM analytics.bill_fact), + (SELECT date_trunc('month', max(closed_at))::date FROM analytics.bill_fact), + interval '1 month' +) AS m(month_start) +CROSS JOIN LATERAL analytics.fn_store_member_opportunity(m.month_start::date) r; + +CREATE UNIQUE INDEX idx_mv_member_opp_month_store ON analytics.mv_store_member_opportunity_monthly (month_start, store_code); +CREATE INDEX idx_mv_member_opp_month ON analytics.mv_store_member_opportunity_monthly (month_start); + +-- ============================================================ +-- 5. mv_store_benchmark_composite_monthly +-- ============================================================ +DROP MATERIALIZED VIEW IF EXISTS analytics.mv_store_benchmark_composite_monthly; +CREATE MATERIALIZED VIEW analytics.mv_store_benchmark_composite_monthly AS +SELECT m.month_start::date AS month_start, r.* +FROM generate_series( + (SELECT date_trunc('month', min(closed_at))::date FROM analytics.bill_fact), + (SELECT date_trunc('month', max(closed_at))::date FROM analytics.bill_fact), + interval '1 month' +) AS m(month_start) +CROSS JOIN LATERAL analytics.fn_store_benchmark_composite(m.month_start::date) r; + +CREATE UNIQUE INDEX idx_mv_benchmark_month_store ON analytics.mv_store_benchmark_composite_monthly (month_start, store_code); +CREATE INDEX idx_mv_benchmark_month ON analytics.mv_store_benchmark_composite_monthly (month_start); + +-- ============================================================ +-- 6. mv_store_deep_diagnosis_monthly +-- ============================================================ +DROP MATERIALIZED VIEW IF EXISTS analytics.mv_store_deep_diagnosis_monthly; +CREATE MATERIALIZED VIEW analytics.mv_store_deep_diagnosis_monthly AS +SELECT m.month_start::date AS month_start, r.* +FROM generate_series( + (SELECT date_trunc('month', min(closed_at))::date FROM analytics.bill_fact), + (SELECT date_trunc('month', max(closed_at))::date FROM analytics.bill_fact), + interval '1 month' +) AS m(month_start) +CROSS JOIN LATERAL analytics.fn_store_deep_diagnosis(m.month_start::date) r; + +CREATE UNIQUE INDEX idx_mv_deep_diag_month_store ON analytics.mv_store_deep_diagnosis_monthly (month_start, store_code); +CREATE INDEX idx_mv_deep_diag_month ON analytics.mv_store_deep_diagnosis_monthly (month_start); + +-- ============================================================ +-- 7. mv_dish_basket_monthly +-- ============================================================ +DROP MATERIALIZED VIEW IF EXISTS analytics.mv_dish_basket_monthly; +CREATE MATERIALIZED VIEW analytics.mv_dish_basket_monthly AS +SELECT m.month_start::date AS month_start, r.* +FROM generate_series( + (SELECT date_trunc('month', min(closed_at))::date FROM analytics.bill_fact), + (SELECT date_trunc('month', max(closed_at))::date FROM analytics.bill_fact), + interval '1 month' +) AS m(month_start) +CROSS JOIN LATERAL analytics.fn_dish_basket(m.month_start::date) r; + +CREATE UNIQUE INDEX idx_mv_dish_basket_month ON analytics.mv_dish_basket_monthly (month_start, store_code, bill_no); +CREATE INDEX idx_mv_dish_basket_month_start ON analytics.mv_dish_basket_monthly (month_start); + +-- ============================================================ +-- 8. mv_dish_store_summary_monthly +-- ============================================================ +DROP MATERIALIZED VIEW IF EXISTS analytics.mv_dish_store_summary_monthly; +CREATE MATERIALIZED VIEW analytics.mv_dish_store_summary_monthly AS +SELECT m.month_start::date AS month_start, r.* +FROM generate_series( + (SELECT date_trunc('month', min(closed_at))::date FROM analytics.bill_fact), + (SELECT date_trunc('month', max(closed_at))::date FROM analytics.bill_fact), + interval '1 month' +) AS m(month_start) +CROSS JOIN LATERAL analytics.fn_dish_store_summary(m.month_start::date) r; + +CREATE UNIQUE INDEX idx_mv_dish_store_summary_month ON analytics.mv_dish_store_summary_monthly (month_start, store_code); +CREATE INDEX idx_mv_dish_store_summary_month_start ON analytics.mv_dish_store_summary_monthly (month_start); + +-- ============================================================ +-- 9. mv_store_theoretical_actual_cost_monthly +-- ============================================================ +DROP MATERIALIZED VIEW IF EXISTS analytics.mv_store_theoretical_actual_cost_monthly; +CREATE MATERIALIZED VIEW analytics.mv_store_theoretical_actual_cost_monthly AS +SELECT m.month_start::date AS month_start, r.* +FROM generate_series( + (SELECT date_trunc('month', min(closed_at))::date FROM analytics.bill_fact), + (SELECT date_trunc('month', max(closed_at))::date FROM analytics.bill_fact), + interval '1 month' +) AS m(month_start) +CROSS JOIN LATERAL analytics.fn_store_theoretical_actual_cost(m.month_start::date) r; + +CREATE UNIQUE INDEX idx_mv_theor_actual_month_store ON analytics.mv_store_theoretical_actual_cost_monthly (month_start, store_code); +CREATE INDEX idx_mv_theor_actual_month ON analytics.mv_store_theoretical_actual_cost_monthly (month_start); + +-- ============================================================ +-- 刷新函数 — 数据导入后调用 +-- ============================================================ +CREATE OR REPLACE FUNCTION analytics.refresh_all_monthly_views() +RETURNS void +LANGUAGE plpgsql +AS $function$ +BEGIN + REFRESH MATERIALIZED VIEW analytics.mv_dish_sku_summary_monthly; + REFRESH MATERIALIZED VIEW analytics.mv_dish_sku_abc_monthly; + REFRESH MATERIALIZED VIEW analytics.mv_store_risk_rating_monthly; + REFRESH MATERIALIZED VIEW analytics.mv_store_platform_economics_monthly; + REFRESH MATERIALIZED VIEW analytics.mv_store_category_mix_monthly; + REFRESH MATERIALIZED VIEW analytics.mv_store_member_opportunity_monthly; + REFRESH MATERIALIZED VIEW analytics.mv_store_benchmark_composite_monthly; + REFRESH MATERIALIZED VIEW analytics.mv_store_deep_diagnosis_monthly; + REFRESH MATERIALIZED VIEW analytics.mv_dish_basket_monthly; + REFRESH MATERIALIZED VIEW analytics.mv_dish_store_summary_monthly; + REFRESH MATERIALIZED VIEW analytics.mv_store_theoretical_actual_cost_monthly; +END; +$function$; diff --git a/db/migration_phase2_parameterized_functions.sql b/db/migration_phase2_parameterized_functions.sql index 32712e8..03770af 100644 --- a/db/migration_phase2_parameterized_functions.sql +++ b/db/migration_phase2_parameterized_functions.sql @@ -480,9 +480,16 @@ RETURNS TABLE ( b.taobao_delivery_received, b.jd_delivery_received FROM public.dish_sales_details d - JOIN analytics.bill_fact b ON b.store_code = d.store_code AND b.bill_no = d.bill_no - WHERE b.closed_at >= analytics.fn_month_start_ts(p_month) - AND b.closed_at < analytics.fn_next_month_start_ts(p_month); + JOIN ( + SELECT store_code, bill_no, closed_at, meal_period, guest_count, consumption, + received_total, discount_total, member_id, member_level, marketing_plan, + order_tag, theoretical_cost, theoretical_profit, theoretical_margin, + meituan_delivery_received, taobao_delivery_received, jd_delivery_received + FROM analytics.bill_fact + WHERE closed_at >= analytics.fn_month_start_ts(p_month) + AND closed_at < analytics.fn_next_month_start_ts(p_month) + ) b ON b.store_code = d.store_code AND b.bill_no = d.bill_no + WHERE d.dish_name IS NOT NULL; $$ LANGUAGE sql STABLE; -- ============================================================ diff --git a/db/migration_phase5_sku_functions.sql b/db/migration_phase5_sku_functions.sql index c884a02..fa61ca2 100644 --- a/db/migration_phase5_sku_functions.sql +++ b/db/migration_phase5_sku_functions.sql @@ -21,23 +21,45 @@ RETURNS TABLE ( realized_unit_price numeric, revenue_share_pct numeric ) AS $$ + 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 diff --git 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+{"kind":"textbox","id":"sh/sv6p8fml","slide":15,"name":"metric-label-指标、规则与任务模板跨店复用","text":"指标、规则与任务模板跨店复用","textPreview":"指标、规则与任务模板跨店复用","textChars":14,"textLines":1,"bbox":[489,336,302,58]} +{"kind":"shape","id":"sh/7axozal0","slide":15,"name":"metric-经营结果持续反哺预测与策略","bbox":[888,210,350,210]} +{"kind":"shape","id":"sh/69o7654f","slide":15,"name":"metric-accent-经营结果持续反哺预测与策略","bbox":[888,210,350,8]} +{"kind":"textbox","id":"sh/10zq5k32","slide":15,"name":"metric-value-经营结果持续反哺预测与策略","text":"可进化","textPreview":"可进化","textChars":3,"textLines":1,"bbox":[912,245,302,78]} +{"kind":"textbox","id":"sh/gzqpcfmh","slide":15,"name":"metric-label-经营结果持续反哺预测与策略","text":"经营结果持续反哺预测与策略","textPreview":"经营结果持续反哺预测与策略","textChars":13,"textLines":1,"bbox":[912,336,302,58]} +{"kind":"textbox","id":"sh/fyho3alw","slide":15,"name":"flywheel-title","text":"平台增长飞轮","textPreview":"平台增长飞轮","textChars":6,"textLines":1,"bbox":[42,492,300,40]} +{"kind":"textbox","id":"sh/ux87a54r","slide":15,"name":"flywheel","text":"更多门店与场景 → 更完整的经营本体 → 更准确的诊断与预测 → 更高的客户价值与使用黏性","textPreview":"更多门店与场景 → 更完整的经营本体 → 更准确的诊断与预测 → 更高的客户价值与使用黏性","textChars":45,"textLines":1,"bbox":[42,550,1130,55]} +{"kind":"notes","id":"nt/df0w9e","slide":15,"text":"[Sources]\n基于本地应用模块化路由、统一数据层与任务闭环的产品架构归纳。"} +{"kind":"slide","id":"sl/egsyxe","slide":16,"title":"SBrain","textShapes":4} +{"kind":"textbox","id":"sh/3m54z614","slide":16,"name":"close-brand","text":"SBrain","textPreview":"SBrain","textChars":6,"textLines":1,"bbox":[42,38,300,34]} +{"kind":"textbox","id":"sh/one5sb2p","slide":16,"name":"close-title","text":"让每一家门店的经营问题\n都能被发现、执行和验证","textPreview":"让每一家门店的经营问题 | 都能被发现、执行和验证","textChars":23,"textLines":2,"bbox":[42,170,1080,190]} +{"kind":"textbox","id":"sh/ponm1gja","slide":16,"name":"close-sub","text":"从数据看板，走向企业级利润增长基础设施","textPreview":"从数据看板，走向企业级利润增长基础设施","textChars":19,"textLines":1,"bbox":[42,440,900,55]} 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new file mode 100644 index 0000000..06ef4c9 --- /dev/null +++ b/deliverables/连锁餐饮行业数字本体与AI经营智脑_老板决策案例版.pptx.inspect.ndjson @@ -0,0 +1,441 @@ +{"kind":"deck","id":"pr/5zy93w","name":"Deck"} +{"kind":"layout","layoutId":"c4a5917b-6fe4-402e-ba17-c2e37d4e5510","name":"Master","type":"master"} +{"kind":"layout","layoutId":"cf9d9406-c26c-4233-b125-ad8e1d17be5f","name":"Title Slide","type":"title"} +{"kind":"slide","id":"sl/hjqr4u","slide":1,"title":"SBrain","textShapes":4} +{"kind":"textbox","id":"sh/8zmlc7yh","slide":1,"name":"brand","text":"SBrain","textPreview":"SBrain","textChars":6,"textLines":1,"bbox":[42,34,300,36]} +{"kind":"textbox","id":"sh/7ydkj2hw","slide":1,"name":"cover-title","text":"连锁餐饮行业数字本体\n与 AI 经营智脑","textPreview":"连锁餐饮行业数字本体 | 与 AI 经营智脑","textChars":20,"textLines":2,"bbox":[42,175,1080,210]} 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+{"kind":"textbox","id":"sh/bq50nyp8","slide":19,"name":"metric-label-把最佳实践沉淀为可计算规则","text":"把最佳实践沉淀为可计算规则","textPreview":"把最佳实践沉淀为可计算规则","textChars":13,"textLines":1,"bbox":[489,336,302,58]} +{"kind":"shape","id":"sh/crehwj6t","slide":19,"name":"metric-让 AI 在可信语义上分析与推演","bbox":[888,210,350,210]} +{"kind":"shape","id":"sh/xsnipo7e","slide":19,"name":"metric-accent-让 AI 在可信语义上分析与推演","bbox":[888,210,350,8]} +{"kind":"textbox","id":"sh/ytwzytoj","slide":19,"name":"metric-value-让 AI 在可信语义上分析与推演","text":"智能化","textPreview":"智能化","textChars":3,"textLines":1,"bbox":[912,245,302,78]} +{"kind":"textbox","id":"sh/zu50ryp4","slide":19,"name":"metric-label-让 AI 在可信语义上分析与推演","text":"让 AI 在可信语义上分析与推演","textPreview":"让 AI 在可信语义上分析与推演","textChars":16,"textLines":1,"bbox":[912,336,302,58]} +{"kind":"textbox","id":"sh/kfeh036p","slide":19,"name":"flywheel-title","text":"行业知识飞轮","textPreview":"行业知识飞轮","textChars":6,"textLines":1,"bbox":[42,492,300,40]} +{"kind":"textbox","id":"sh/lgnit87a","slide":19,"name":"flywheel","text":"更多业务场景 → 更完整的行业本体 → 更成熟的运营模型 → 更准确的 AI 建议 → 更高质量的决策反馈","textPreview":"更多业务场景 → 更完整的行业本体 → 更成熟的运营模型 → 更准确的 AI 建议 → 更高质量的决策反馈","textChars":53,"textLines":1,"bbox":[42,550,1160,55]} +{"kind":"notes","id":"nt/vqck18","slide":19,"text":"[Sources]\n基于本地应用模块化路由、统一数据层与任务闭环的产品架构归纳。"} +{"kind":"slide","id":"sl/m9gdgo","slide":20,"title":"SBrain","textShapes":4} +{"kind":"textbox","id":"sh/j2twn6pc","slide":20,"name":"close-brand","text":"SBrain","textPreview":"SBrain","textChars":6,"textLines":1,"bbox":[42,38,300,34]} +{"kind":"textbox","id":"sh/k32xgbqx","slide":20,"name":"close-title","text":"整合现有数据，看清企业现在\n借助 AI 智脑，掌控经营未来","textPreview":"整合现有数据，看清企业现在 | 借助 AI 智脑，掌控经营未来","textChars":29,"textLines":2,"bbox":[42,170,1120,190]} +{"kind":"textbox","id":"sh/l4bepg7i","slide":20,"name":"close-sub","text":"行业数字本体，是企业运营管理智能化的共同语言","textPreview":"行业数字本体，是企业运营管理智能化的共同语言","textChars":22,"textLines":1,"bbox":[42,440,980,55]} +{"kind":"shape","id":"sh/65kfil8n","slide":20,"name":"close-accent","bbox":[42,586,1196,12]} +{"kind":"textbox","id":"sh/76dwrqp8","slide":20,"name":"close-next","text":"建议下一步：选择一个完整经营月，完成数据预检与利润基线共创","textPreview":"建议下一步：选择一个完整经营月，完成数据预检与利润基线共创","textChars":29,"textLines":1,"bbox":[42,622,1000,32]} +{"kind":"notes","id":"nt/m9gdgo","slide":20,"text":"[Sources]\n本地应用功能架构总结；对外保密版。"} \ No newline at end of file diff --git a/deliverables/连锁餐饮行业数字本体与AI经营智脑_融资与长期发展版.pptx b/deliverables/连锁餐饮行业数字本体与AI经营智脑_融资与长期发展版.pptx new file mode 100644 index 0000000000000000000000000000000000000000..d0895caf632f82d387d291422f5d10c77e51c4b5 GIT binary patch literal 105787 zcmeFXb8uyC_Aee=ot)UVZ5tiiwr$(&*ha_c*tR>iZ708eXXe&--rt?7d#mohQ>V_Z zvv<{g>g=`GS|6-OUK$h(00aaC1@zq(SjUxzoS6+62uKM82OHrB<79hhUqP8B1C+_#Ut zI}cYc89k4&j=p(I`WY7=0;9`S#DI8sJx`vVbvzXa!9UCi14ZGaGz8tcYv;H+cK{nN zfU9ih2SjEix%j$udy=>e)mu!MGD@piE6S)RG>~+UVi=t_vFm!!89I4Rc2Alq=pekc zzem4f%l|FN_TnxAr+CoJdLFhm^J|t%} z(?2z&iWNkQsYSWcjsK!Y(?$iSKR 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zigA~kPR%9u5pZ87##J(-a+!2#!YeY|D2KsD_fui$ew}ulP9@X*he-jgwgaY32DR*5$*!QaL!hQIASZpT{9Ri%9;>I z?EK(16AYJaLx>}GO>kcZhN}nJF1qtex^W{#?2+I;1`OAKkPt`gh~T<^3^(gvLL9OG zfeYm^oTxn^j@a$Mh2WA`gd-kyaHTIsyWmVn zBc5Y$Wh{oPbRonM&oQ`^6vK5LBE%8@vT*4oh8uGw#1YRixK { count(*) FILTER (WHERE variance_level = '绿色-基本正常') AS green_count, count(*) FILTER (WHERE variance_level = '灰色-口径异常') AS gray_count, round(sum(food_cost_variance)::numeric, 2) AS total_variance - FROM analytics.fn_store_theoretical_actual_cost($1) + FROM analytics.mv_store_theoretical_actual_cost_monthly + WHERE month_start = $1 `, [month]) sendSuccess(res, result.rows[0]) } catch (err: any) { @@ -752,9 +753,9 @@ router.get('/store-map', async (req: AuthRequest, res) => { round(c.theoretical_cost_rate_pct::numeric, 2) AS theo_cost_rate, round(c.actual_food_cost_rate_pct::numeric, 2) AS actual_cost_rate, l.latitude_gcj02, l.longitude_gcj02 - FROM analytics.fn_store_theoretical_actual_cost($1) c + FROM analytics.mv_store_theoretical_actual_cost_monthly c LEFT JOIN analytics.v_store_location_operating l ON l.store_code = c.store_code - WHERE l.latitude_gcj02 IS NOT NULL + WHERE c.month_start = $1 AND l.latitude_gcj02 IS NOT NULL `, [month]) sendSuccess(res, result.rows) } catch (err: any) { @@ -780,7 +781,7 @@ router.get('/store-ranking', async (req: AuthRequest, res) => { const sortCol = validSorts.includes(sort) ? sort : 'food_cost_variance' const month = parseMonth(req) - const countResult = await query(`SELECT count(*) FROM analytics.fn_store_theoretical_actual_cost($1) ${where}`, [month]) + const countResult = await query(`SELECT count(*) FROM analytics.mv_store_theoretical_actual_cost_monthly WHERE month_start = $1 ${where}`, [month]) const total = countResult.rows[0].count const result = await query(` @@ -791,7 +792,8 @@ router.get('/store-ranking', async (req: AuthRequest, res) => { round(food_cost_variance::numeric, 2) AS variance_amount, negative_item_lines, variance_level - FROM analytics.fn_store_theoretical_actual_cost($1) + FROM analytics.mv_store_theoretical_actual_cost_monthly + WHERE month_start = $1 ${where} ORDER BY ${sortCol} ${order} NULLS LAST LIMIT $2 OFFSET $3 `, [month, pageSize, offset]) diff --git a/server/src/routes/data.ts b/server/src/routes/data.ts index 0560e44..6d0a9f9 100644 --- a/server/src/routes/data.ts +++ b/server/src/routes/data.ts @@ -39,8 +39,8 @@ router.get('/stores', async (req: AuthRequest, res) => { if (riskLevel) { const m = parseMonth(req) sql = `SELECT s.* FROM analytics.v_store_scorecard s - JOIN analytics.fn_store_risk_rating($${params.length + 1}) r ON s.store_code = r.store_code - WHERE r.risk_level = $${params.length + 2}` + JOIN analytics.mv_store_risk_rating_monthly r ON s.store_code = r.store_code + WHERE r.month_start = $${params.length + 1} AND r.risk_level = $${params.length + 2}` params.push(m, riskLevel) } @@ -71,7 +71,7 @@ router.get('/stores', async (req: AuthRequest, res) => { router.get('/stores/risk', async (req: AuthRequest, res) => { try { const month = parseMonth(req) - const result = await query(`SELECT * FROM analytics.fn_store_risk_rating($1) ORDER BY risk_level, received DESC`, [month]) + const result = await query(`SELECT * FROM analytics.mv_store_risk_rating_monthly WHERE month_start = $1 ORDER BY risk_level, received DESC`, [month]) sendSuccess(res, result.rows) } catch (err: any) { sendError(res, err.message) @@ -113,9 +113,9 @@ router.get('/stores/:code', async (req: AuthRequest, res) => { const code = req.params.code const [scorecard, risk, platform, benchmark, action] = await Promise.all([ query(`SELECT * FROM analytics.mv_store_scorecard WHERE store_code = $1`, [code]), - query(`SELECT * FROM analytics.fn_store_risk_rating($1) WHERE store_code = $2`, [parseMonth(req), code]), - query(`SELECT * FROM analytics.fn_store_platform_economics($2) WHERE store_code = $1`, [code, parseMonth(req)]), - query(`SELECT * FROM analytics.fn_store_benchmark_composite($2) WHERE store_code = $1`, [code, parseMonth(req)]), + query(`SELECT * FROM analytics.mv_store_risk_rating_monthly WHERE month_start = $1 AND store_code = $2`, [parseMonth(req), code]), + query(`SELECT * FROM analytics.mv_store_platform_economics_monthly WHERE month_start = $2 AND store_code = $1`, [code, parseMonth(req)]), + query(`SELECT * FROM analytics.mv_store_benchmark_composite_monthly WHERE month_start = $2 AND store_code = $1`, [code, parseMonth(req)]), query(`SELECT * FROM analytics.fn_store_action_priority_deep($1) WHERE store_code = $2`, [parseMonth(req), code]), ]) @@ -176,7 +176,7 @@ router.get('/stores/:code/daily', async (req: AuthRequest, res) => { router.get('/cost/comparison', async (req: AuthRequest, res) => { try { const month = parseMonth(req) - const result = await query(`SELECT * FROM analytics.fn_store_theoretical_actual_cost($1) ORDER BY variance_to_theoretical_pct DESC NULLS LAST`, [month]) + const result = await query(`SELECT * FROM analytics.mv_store_theoretical_actual_cost_monthly WHERE month_start = $1 ORDER BY variance_to_theoretical_pct DESC NULLS LAST`, [month]) sendSuccess(res, result.rows) } catch (err: any) { sendError(res, err.message) @@ -206,7 +206,7 @@ router.get('/cost/inventory', async (req: AuthRequest, res) => { router.get('/platform/economics', async (req: AuthRequest, res) => { try { const month = parseMonth(req) - const result = await query(`SELECT * FROM analytics.fn_store_platform_economics($1) ORDER BY meituan_received DESC NULLS LAST`, [month]) + const result = await query(`SELECT * FROM analytics.mv_store_platform_economics_monthly WHERE month_start = $1 ORDER BY meituan_received DESC NULLS LAST`, [month]) sendSuccess(res, result.rows) } catch (err: any) { sendError(res, err.message) @@ -235,7 +235,7 @@ router.get('/member/repeat', async (req: AuthRequest, res) => { router.get('/sku/abc', async (req: AuthRequest, res) => { try { const month = parseMonth(req) - const result = await query(`SELECT * FROM analytics.fn_dish_sku_abc($1) ORDER BY cumulative_revenue_share`, [month]) + const result = await query(`SELECT * FROM analytics.mv_dish_sku_abc_monthly WHERE month_start = $1 ORDER BY cumulative_revenue_share`, [month]) sendSuccess(res, result.rows) } catch (err: any) { sendError(res, err.message) @@ -310,7 +310,7 @@ router.get('/marketing/plans', async (req: AuthRequest, res) => { router.get('/benchmark/composite', async (req: AuthRequest, res) => { try { const month = parseMonth(req) - const result = await query(`SELECT * FROM analytics.fn_store_benchmark_composite($1) ORDER BY benchmark_score DESC`, [month]) + const result = await query(`SELECT * FROM analytics.mv_store_benchmark_composite_monthly WHERE month_start = $1 ORDER BY benchmark_score DESC`, [month]) sendSuccess(res, result.rows) } catch (err: any) { sendError(res, err.message) @@ -396,7 +396,7 @@ router.get('/stores/:code/category-mix', async (req: AuthRequest, res) => { try { const month = parseMonth(req) const [result, companyResult] = await Promise.all([ - query(`SELECT * FROM analytics.fn_store_category_mix($1) WHERE store_code = $2`, [month, req.params.code]), + query(`SELECT * FROM analytics.mv_store_category_mix_monthly WHERE month_start = $1 AND store_code = $2`, [month, req.params.code]), query(` SELECT SUM(consumption) as total_consumption, @@ -405,7 +405,7 @@ router.get('/stores/:code/category-mix', async (req: AuthRequest, res) => { SUM(delivery_package) as total_delivery, SUM(cold_dishes) as total_cold, SUM(silk_road_food) as total_silk - FROM analytics.fn_store_category_mix($1) + FROM analytics.mv_store_category_mix_monthly WHERE month_start = $1 `, [month]), ]) sendSuccess(res, { store: result.rows[0], company: companyResult.rows[0] }) @@ -416,7 +416,7 @@ router.get('/stores/:code/cost', async (req: AuthRequest, res) => { try { const month = parseMonth(req) const [costResult, catResult] = await Promise.all([ - query(`SELECT * FROM analytics.fn_store_theoretical_actual_cost($1) WHERE store_code = $2`, [month, req.params.code]), + query(`SELECT * FROM analytics.mv_store_theoretical_actual_cost_monthly WHERE month_start = $1 AND store_code = $2`, [month, req.params.code]), query(` WITH store_cat AS ( SELECT finance_category AS category_name, @@ -450,7 +450,7 @@ router.get('/stores/:code/member', async (req: AuthRequest, res) => { try { const month = parseMonth(req) const [oppResult, repeatResult, monthlyResult] = await Promise.all([ - query(`SELECT * FROM analytics.fn_store_member_opportunity($2) WHERE store_code = $1`, [req.params.code, month]), + query(`SELECT * FROM analytics.mv_store_member_opportunity_monthly WHERE month_start = $2 AND store_code = $1`, [req.params.code, month]), query(`SELECT * FROM analytics.mv_store_repeat_summary_monthly WHERE store_code = $1 AND month_start = $2::date`, [req.params.code, month]), query(` SELECT store_code, store_name, count(*) as member_count, @@ -545,10 +545,10 @@ router.get('/overview/profit-waterfall', async (req: AuthRequest, res) => { e.repair_clean_expense, e.operating_expense, CASE WHEN e.operating_expense IS NOT NULL THEN true ELSE false END AS has_expense - FROM analytics.fn_store_risk_rating($1) r + FROM analytics.mv_store_risk_rating_monthly r LEFT JOIN analytics.mv_store_operating_expense_monthly e ON r.store_code = e.sales_store_code AND e.report_month = $1::date - WHERE r.received IS NOT NULL AND e.operating_expense IS NOT NULL + WHERE r.month_start = $1 AND r.received IS NOT NULL AND e.operating_expense IS NOT NULL ) SELECT round(sum(received)::numeric, 2) AS received, @@ -584,10 +584,10 @@ router.get('/overview/store-profit-ranking', async (req: AuthRequest, res) => { round((r.received - e.actual_food_cost - e.operating_expense)::numeric, 2) AS store_contribution, round((r.received - e.actual_food_cost - e.operating_expense) / nullif(r.received, 0) * 100, 2) AS contribution_margin_pct, r.risk_level - FROM analytics.fn_store_risk_rating($1) r + FROM analytics.mv_store_risk_rating_monthly r LEFT JOIN analytics.mv_store_operating_expense_monthly e ON r.store_code = e.sales_store_code AND e.report_month = $1::date - WHERE r.received IS NOT NULL AND r.received > 0 AND e.operating_expense IS NOT NULL + WHERE r.month_start = $1 AND r.received IS NOT NULL AND r.received > 0 AND e.operating_expense IS NOT NULL ORDER BY store_contribution DESC `, [month]) sendSuccess(res, result.rows) @@ -601,12 +601,18 @@ router.get('/overview/profit-opportunity', async (req: AuthRequest, res) => { try { const month = parseMonth(req) const result = await query(` - WITH standard_stores AS ( + WITH risk AS ( + SELECT * FROM analytics.mv_store_risk_rating_monthly WHERE month_start = $1 + ), + sku_abc AS ( + SELECT * FROM analytics.mv_dish_sku_abc_monthly WHERE month_start = $1 + ), + standard_stores AS ( SELECT r.store_code, r.store_name, r.received, e.actual_food_cost, e.operating_expense, e.wage_expense, e.utility_expense, r.theoretical_margin_pct, r.discount_rate_pct - FROM analytics.fn_store_risk_rating($1) r + FROM risk r LEFT JOIN analytics.mv_store_operating_expense_monthly e ON r.store_code = e.sales_store_code AND e.report_month = $1::date WHERE r.received IS NOT NULL AND r.received > 0 AND e.operating_expense IS NOT NULL @@ -663,14 +669,14 @@ router.get('/overview/profit-opportunity', async (req: AuthRequest, res) => { SELECT count(*) FILTER (WHERE discount_rate_pct > 25) AS high_discount_stores, round(sum(CASE WHEN discount_rate_pct > 25 THEN received * discount_rate_pct / nullif(100 - discount_rate_pct, 0) * (discount_rate_pct - 25) / nullif(discount_rate_pct, 0) ELSE 0 END)::numeric, 2) AS theoretical_saving - FROM analytics.fn_store_risk_rating($1) + FROM risk WHERE received IS NOT NULL AND received > 0 ), discount_stores AS ( SELECT store_name, received, round(discount_rate_pct::numeric, 2) AS discount_rate, round((received * discount_rate_pct / nullif(100 - discount_rate_pct, 0) * (discount_rate_pct - 25) / nullif(discount_rate_pct, 0))::numeric, 2) AS potential_saving - FROM analytics.fn_store_risk_rating($1) + FROM risk WHERE received IS NOT NULL AND received > 0 AND discount_rate_pct > 25 ORDER BY discount_rate_pct DESC LIMIT 5 @@ -695,11 +701,11 @@ router.get('/overview/profit-opportunity', async (req: AuthRequest, res) => { SELECT count(*) FILTER (WHERE received_amount < 1000 AND bill_count < 30) AS low_sku_count, round(sum(received_amount) FILTER (WHERE received_amount < 1000 AND bill_count < 30)::numeric, 2) AS low_sku_revenue - FROM analytics.fn_dish_sku_abc($1) + FROM sku_abc ), sku_samples AS ( SELECT dish_name, category_level1, received_amount, bill_count, abc_class - FROM analytics.fn_dish_sku_abc($1) + FROM sku_abc WHERE received_amount < 1000 AND bill_count < 30 ORDER BY received_amount ASC LIMIT 10 @@ -1051,7 +1057,7 @@ router.get('/bank/report', async (req: AuthRequest, res) => { SELECT r.received, e.actual_food_cost AS food_cost, e.wage_expense AS wage, e.rent_expense AS rent, e.utility_expense AS utility, e.dorm_expense AS dorm, e.delivery_commission_expense AS commission, e.card_fee_expense AS card_fee, e.repair_clean_expense AS repair, e.operating_expense AS operating_expense - FROM analytics.fn_store_risk_rating($1) r + FROM analytics.mv_store_risk_rating_monthly r LEFT JOIN analytics.mv_store_operating_expense_monthly e ON r.store_code = e.sales_store_code AND e.report_month = $1::date WHERE r.received IS NOT NULL AND e.operating_expense IS NOT NULL ) @@ -1062,9 +1068,9 @@ router.get('/bank/report', async (req: AuthRequest, res) => { round(sum(received)-sum(food_cost)-sum(operating_expense),2) AS store_contribution FROM full_scope `, [month]), - query(`SELECT risk_level, count(*) AS store_count, round(sum(received)::numeric,2) AS total_received, round(avg(theoretical_margin_pct)::numeric,2) AS avg_margin_pct, round(avg(discount_rate_pct)::numeric,2) AS avg_discount_pct FROM analytics.fn_store_risk_rating($1) WHERE received IS NOT NULL GROUP BY risk_level ORDER BY risk_level`, [month]), + query(`SELECT risk_level, count(*) AS store_count, round(sum(received)::numeric,2) AS total_received, round(avg(theoretical_margin_pct)::numeric,2) AS avg_margin_pct, round(avg(discount_rate_pct)::numeric,2) AS avg_discount_pct FROM analytics.mv_store_risk_rating_monthly WHERE month_start = $1 AND received IS NOT NULL GROUP BY risk_level ORDER BY risk_level`, [month]), query(`SELECT round(sum(cash)::numeric,2) AS cash, round(sum(alipay)::numeric,2) AS alipay, round(sum(wechat)::numeric,2) AS wechat, round(sum(meituan)::numeric,2) AS meituan, round(sum(unionpay)::numeric,2) AS unionpay, round(sum(douyin)::numeric,2) AS douyin, round(sum(credit)::numeric,2) AS credit, round(sum(jd_delivery)::numeric,2) AS jd_delivery, round(sum(meituan_delivery)::numeric,2) AS meituan_delivery, round(sum(taobao_delivery)::numeric,2) AS taobao_delivery FROM analytics.v_channel_daily WHERE business_date >= $1::date AND business_date < $2::date`, [month, nextMonth]), - query(`SELECT store_code, store_name, round(received::numeric,2) AS received, bill_count, round(avg_bill_value::numeric,2) AS avg_bill_value, round(discount_rate_pct::numeric,2) AS discount_rate_pct, round(theoretical_margin_pct::numeric,2) AS theoretical_margin_pct, risk_level FROM analytics.fn_store_risk_rating($1) WHERE received IS NOT NULL ORDER BY received DESC`, [month]), + query(`SELECT store_code, store_name, round(received::numeric,2) AS received, bill_count, round(avg_bill_value::numeric,2) AS avg_bill_value, round(discount_rate_pct::numeric,2) AS discount_rate_pct, round(theoretical_margin_pct::numeric,2) AS theoretical_margin_pct, risk_level FROM analytics.mv_store_risk_rating_monthly WHERE month_start = $1 AND received IS NOT NULL ORDER BY received DESC`, [month]), ]) const ov = overview.rows[0] as any diff --git a/server/src/routes/situational-awareness.ts b/server/src/routes/situational-awareness.ts index d54ee74..501f397 100644 --- a/server/src/routes/situational-awareness.ts +++ b/server/src/routes/situational-awareness.ts @@ -15,14 +15,14 @@ router.get('/health-score', async (req: AuthRequest, res) => { SELECT store_code, store_name, received, bill_count, avg_bill_value, avg_daily_received, theoretical_margin_pct, member_bill_share_pct, risk_level - FROM analytics.fn_store_risk_rating($1) - WHERE received IS NOT NULL + FROM analytics.mv_store_risk_rating_monthly + WHERE month_start = $1 AND received IS NOT NULL ), cost AS ( SELECT store_code, round(avg(LEAST(variance_to_theoretical_pct, 50))::numeric, 1) AS avg_cost_variance_pct - FROM analytics.fn_store_theoretical_actual_cost($1) - WHERE variance_to_theoretical_pct IS NOT NULL + FROM analytics.mv_store_theoretical_actual_cost_monthly + WHERE month_start = $1 AND variance_to_theoretical_pct IS NOT NULL GROUP BY store_code ), member AS ( @@ -184,9 +184,9 @@ router.get('/alerts', async (req: AuthRequest, res) => { round(p.taobao_cost_rate_pct::numeric, 1) AS taobao_rate, round(p.jd_cost_rate_pct::numeric, 1) AS jd_rate, round((COALESCE(p.meituan_received, 0) + COALESCE(p.taobao_received, 0) + COALESCE(p.jd_received, 0)) / nullif(sc.received, 0) * 100, 1) AS platform_share - FROM analytics.fn_store_platform_economics($1) p + FROM analytics.mv_store_platform_economics_monthly p JOIN analytics.v_store_scorecard sc ON p.store_code = sc.store_code - WHERE (COALESCE(p.meituan_received, 0) + COALESCE(p.taobao_received, 0) + COALESCE(p.jd_received, 0)) / nullif(sc.received, 0) > 0.4 + WHERE p.month_start = $1 AND (COALESCE(p.meituan_received, 0) + COALESCE(p.taobao_received, 0) + COALESCE(p.jd_received, 0)) / nullif(sc.received, 0) > 0.4 ORDER BY platform_share DESC LIMIT 10 `, [month]) @@ -293,12 +293,12 @@ router.get('/correlation', async (req: AuthRequest, res) => { WHEN COALESCE(c.avg_cost_variance_pct, 20) > 30 THEN '成本失控' ELSE '正常' END AS correlation_status - FROM analytics.fn_store_risk_rating($1) r + FROM analytics.mv_store_risk_rating_monthly r LEFT JOIN ( SELECT store_code, round(avg(LEAST(variance_to_theoretical_pct, 50))::numeric, 1) AS avg_cost_variance_pct - FROM analytics.fn_store_theoretical_actual_cost($1) - WHERE variance_to_theoretical_pct IS NOT NULL + FROM analytics.mv_store_theoretical_actual_cost_monthly + WHERE month_start = $1 AND variance_to_theoretical_pct IS NOT NULL GROUP BY store_code ) c ON r.store_code = c.store_code WHERE r.received IS NOT NULL @@ -323,12 +323,13 @@ router.get('/correlation', async (req: AuthRequest, res) => { WHEN COALESCE(r.member_bill_share_pct, 0) > 50 THEN '会员驱动型' ELSE '均衡型' END AS channel_status - FROM analytics.fn_store_risk_rating($1) r + FROM analytics.mv_store_risk_rating_monthly r LEFT JOIN ( SELECT pe.store_code, round((COALESCE(pe.meituan_received, 0) + COALESCE(pe.taobao_received, 0) + COALESCE(pe.jd_received, 0)) / nullif(r2.received, 0) * 100, 1) AS platform_share - FROM analytics.fn_store_platform_economics($1) pe - JOIN analytics.fn_store_risk_rating($1) r2 ON pe.store_code = r2.store_code + FROM analytics.mv_store_platform_economics_monthly pe + JOIN analytics.mv_store_risk_rating_monthly r2 ON pe.store_code = r2.store_code AND r2.month_start = pe.month_start + WHERE pe.month_start = $1 ) p ON r.store_code = p.store_code LEFT JOIN analytics.mv_store_repeat_summary_monthly m ON r.store_code = m.store_code AND m.month_start = $1::date WHERE r.received IS NOT NULL diff --git a/server/src/routes/store-expense.ts b/server/src/routes/store-expense.ts index 1e17bbb..2607ec0 100644 --- a/server/src/routes/store-expense.ts +++ b/server/src/routes/store-expense.ts @@ -32,10 +32,10 @@ router.get('/overview', async (req: AuthRequest, res) => { CASE WHEN e.operating_expense IS NOT NULL THEN (r.received - e.actual_food_cost - e.operating_expense) ELSE NULL END AS actual_store_contribution, CASE WHEN e.operating_expense IS NOT NULL THEN (r.received - r.received * (1 - COALESCE(r.theoretical_margin_pct, 0) / 100) - e.operating_expense) ELSE NULL END AS theoretical_store_contribution, e.area_sqm - FROM analytics.fn_store_risk_rating($1) r + FROM analytics.mv_store_risk_rating_monthly r LEFT JOIN analytics.mv_store_operating_expense_monthly e ON r.store_code = e.sales_store_code AND e.report_month = $1::date - WHERE r.received IS NOT NULL + WHERE r.month_start = $1 AND r.received IS NOT NULL ) SELECT count(*) AS total_stores, diff --git a/server/src/routes/tasks.ts b/server/src/routes/tasks.ts index b1e8c7f..104fbb8 100644 --- a/server/src/routes/tasks.ts +++ b/server/src/routes/tasks.ts @@ -620,15 +620,16 @@ router.get('/monthly-review/sku-governance', async (req: AuthRequest, res) => { SELECT abc_class, count(*) as sku_count, ROUND(sum(revenue_share_pct), 1) as total_revenue_share, ROUND(avg(revenue_share_pct), 2) as avg_revenue_share - FROM analytics.fn_dish_sku_abc($1) + FROM analytics.mv_dish_sku_abc_monthly + WHERE month_start = $1 GROUP BY abc_class ORDER BY abc_class `, [month]) const longtailResult = await query(` SELECT dish_name, category_level1, bill_count, sales_quantity, received_amount, revenue_share_pct, cumulative_revenue_share - FROM analytics.fn_dish_sku_abc($1) - WHERE abc_class = 'C-长尾' + FROM analytics.mv_dish_sku_abc_monthly + WHERE month_start = $1 AND abc_class = 'C-长尾' ORDER BY received_amount ASC LIMIT 50 `, [month])