freedakgmail
85 lines
3.8 KiB
PL/PgSQL
85 lines
3.8 KiB
PL/PgSQL
-- ============================================================
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-- Phase 8: mv_store_risk_rating 参数化函数
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-- 替换普通表 mv_store_risk_rating（4月快照）为参数化函数
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-- 依赖: bill_fact, v_anomaly_bills
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-- ============================================================
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CREATE OR REPLACE FUNCTION analytics.fn_store_risk_rating(p_month date)
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RETURNS TABLE (
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store_code text,
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store_name text,
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bill_count bigint,
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active_days bigint,
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received numeric,
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avg_daily_received numeric,
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avg_bill_value numeric,
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avg_guest_value numeric,
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discount_rate_pct numeric,
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theoretical_margin_pct numeric,
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member_bill_share_pct numeric,
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anomaly_rate_pct numeric,
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risk_level text,
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primary_issue text
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) AS $$
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WITH base AS (
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SELECT
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b.store_code,
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b.store_name,
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count(*) AS bill_count,
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count(DISTINCT b.closed_at::date) AS active_days,
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sum(b.received_total) AS received,
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round(sum(b.received_total) / NULLIF(count(DISTINCT b.closed_at::date), 0), 2) AS avg_daily_received,
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round(sum(b.received_total) / count(*), 2) AS avg_bill_value,
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round(sum(b.received_total) / NULLIF(sum(b.guest_count), 0), 2) AS avg_guest_value,
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round(sum(b.discount_total) / NULLIF(sum(b.consumption), 0) * 100, 2) AS discount_rate_pct,
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round(sum(b.theoretical_profit) / NULLIF(sum(b.received_total), 0) * 100, 2) AS theoretical_margin_pct,
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round(count(*) FILTER (WHERE b.member_id IS NOT NULL)::numeric / count(*) * 100, 2) AS member_bill_share_pct
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FROM analytics.bill_fact b
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WHERE b.closed_at >= analytics.fn_month_start_ts(p_month)
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AND b.closed_at < analytics.fn_next_month_start_ts(p_month)
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GROUP BY b.store_code, b.store_name
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),
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anomaly AS (
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SELECT
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a.store_code,
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round(count(*)::numeric / NULLIF(bc.bill_count, 0) * 100, 2) AS anomaly_rate_pct
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FROM analytics.v_anomaly_bills a
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JOIN (SELECT store_code, count(*) AS bill_count FROM analytics.bill_fact
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WHERE closed_at >= analytics.fn_month_start_ts(p_month)
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AND closed_at < analytics.fn_next_month_start_ts(p_month)
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GROUP BY store_code) bc ON a.store_code = bc.store_code
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WHERE a.closed_at >= analytics.fn_month_start_ts(p_month)
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AND a.closed_at < analytics.fn_next_month_start_ts(p_month)
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GROUP BY a.store_code, bc.bill_count
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),
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combined AS (
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SELECT
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b.*,
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COALESCE(an.anomaly_rate_pct, 0) AS anomaly_rate_pct,
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CASE
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WHEN b.received IS NULL OR b.received = 0 THEN '绿色'
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WHEN b.theoretical_margin_pct < 68 OR b.discount_rate_pct > 25 OR COALESCE(an.anomaly_rate_pct, 0) > 3 THEN '红色'
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WHEN b.theoretical_margin_pct >= 70 AND b.discount_rate_pct <= 22 AND COALESCE(an.anomaly_rate_pct, 0) <= 1.5 THEN '绿色'
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ELSE '黄色'
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END AS risk_level,
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CASE
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WHEN b.theoretical_margin_pct < 68 AND b.discount_rate_pct > 25 AND COALESCE(an.anomaly_rate_pct, 0) > 3 THEN '毛利率低；优惠率高；异常率高'
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WHEN b.theoretical_margin_pct < 68 AND b.discount_rate_pct > 25 THEN '毛利率低；优惠率高'
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WHEN b.theoretical_margin_pct < 68 AND COALESCE(an.anomaly_rate_pct, 0) > 3 THEN '毛利率低；异常率高'
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WHEN b.discount_rate_pct > 25 AND COALESCE(an.anomaly_rate_pct, 0) > 3 THEN '优惠率高；异常率高'
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WHEN b.theoretical_margin_pct < 68 THEN '毛利率低'
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WHEN b.discount_rate_pct > 25 THEN '优惠率高'
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WHEN COALESCE(an.anomaly_rate_pct, 0) > 3 THEN '异常率高'
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ELSE ''
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END AS primary_issue
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FROM base b
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LEFT JOIN anomaly an ON b.store_code = an.store_code
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)
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SELECT
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store_code, store_name, bill_count, active_days, received,
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avg_daily_received, avg_bill_value, avg_guest_value,
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discount_rate_pct, theoretical_margin_pct, member_bill_share_pct,
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anomaly_rate_pct, risk_level, primary_issue
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FROM combined
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$$ LANGUAGE SQL STABLE;
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