Fixes for metrics calculations
This commit is contained in:
@@ -27,7 +27,7 @@ BEGIN
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p.visible as is_visible, p.replenishable,
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COALESCE(p.price, 0.00) as current_price, COALESCE(p.regular_price, 0.00) as current_regular_price,
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COALESCE(p.cost_price, 0.00) as current_cost_price,
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COALESCE(p.landing_cost_price, p.cost_price, 0.00) as current_effective_cost, -- Use landing if available, else cost
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COALESCE(p.cost_price, 0.00) as current_effective_cost,
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p.stock_quantity as current_stock, -- Use actual current stock for forecast base
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p.created_at, p.first_received, p.date_last_sold,
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p.moq,
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@@ -10,7 +10,7 @@ DECLARE
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_date DATE;
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_count INT;
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_total_records INT := 0;
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_begin_date DATE := (SELECT MIN(date)::date FROM orders WHERE date >= '2024-01-01'); -- Starting point for data rebuild
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_begin_date DATE := (SELECT MIN(date)::date FROM orders WHERE date >= '2020-01-01'); -- Starting point: captures all historical order data
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_end_date DATE := CURRENT_DATE;
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BEGIN
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RAISE NOTICE 'Beginning daily snapshots rebuild from % to %. Starting at %', _begin_date, _end_date, _start_time;
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@@ -36,7 +36,7 @@ BEGIN
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COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN o.quantity ELSE 0 END), 0) AS units_sold,
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COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN o.price * o.quantity ELSE 0 END), 0.00) AS gross_revenue_unadjusted,
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COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN o.discount ELSE 0 END), 0.00) AS discounts,
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COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN COALESCE(o.costeach, p.landing_cost_price, p.cost_price) * o.quantity ELSE 0 END), 0.00) AS cogs,
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COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN COALESCE(o.costeach, p.cost_price) * o.quantity ELSE 0 END), 0.00) AS cogs,
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COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN p.regular_price * o.quantity ELSE 0 END), 0.00) AS gross_regular_revenue,
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-- Aggregate Returns (Quantity < 0 or Status = Returned)
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@@ -68,7 +68,7 @@ BEGIN
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SELECT
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p.pid,
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p.stock_quantity,
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COALESCE(p.landing_cost_price, p.cost_price, 0.00) as effective_cost_price,
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COALESCE(p.cost_price, 0.00) as effective_cost_price,
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COALESCE(p.price, 0.00) as current_price,
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COALESCE(p.regular_price, 0.00) as current_regular_price
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FROM public.products p
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@@ -111,7 +111,7 @@ BEGIN
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COALESCE(sd.gross_revenue_unadjusted, 0.00),
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COALESCE(sd.discounts, 0.00),
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COALESCE(sd.returns_revenue, 0.00),
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COALESCE(sd.gross_revenue_unadjusted, 0.00) - COALESCE(sd.discounts, 0.00) AS net_revenue,
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COALESCE(sd.gross_revenue_unadjusted, 0.00) - COALESCE(sd.discounts, 0.00) - COALESCE(sd.returns_revenue, 0.00) AS net_revenue,
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COALESCE(sd.cogs, 0.00),
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COALESCE(sd.gross_regular_revenue, 0.00),
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(COALESCE(sd.gross_revenue_unadjusted, 0.00) - COALESCE(sd.discounts, 0.00)) - COALESCE(sd.cogs, 0.00) AS profit,
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@@ -28,8 +28,8 @@ BEGIN
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COUNT(DISTINCT CASE WHEN pm.sales_30d > 0 THEN pm.pid END) AS products_with_sales_30d,
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SUM(CASE WHEN pm.sales_30d > 0 THEN pm.sales_30d ELSE 0 END) AS sales_30d,
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SUM(CASE WHEN pm.revenue_30d > 0 THEN pm.revenue_30d ELSE 0 END) AS revenue_30d,
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SUM(CASE WHEN pm.cogs_30d > 0 THEN pm.cogs_30d ELSE 0 END) AS cogs_30d,
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SUM(CASE WHEN pm.profit_30d != 0 THEN pm.profit_30d ELSE 0 END) AS profit_30d,
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SUM(COALESCE(pm.cogs_30d, 0)) AS cogs_30d,
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SUM(COALESCE(pm.profit_30d, 0)) AS profit_30d,
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COUNT(DISTINCT CASE WHEN pm.sales_365d > 0 THEN pm.pid END) AS products_with_sales_365d,
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SUM(CASE WHEN pm.sales_365d > 0 THEN pm.sales_365d ELSE 0 END) AS sales_365d,
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@@ -28,8 +28,8 @@ BEGIN
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SUM(CASE WHEN pm.revenue_7d > 0 THEN pm.revenue_7d ELSE 0 END) AS revenue_7d,
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SUM(CASE WHEN pm.sales_30d > 0 THEN pm.sales_30d ELSE 0 END) AS sales_30d,
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SUM(CASE WHEN pm.revenue_30d > 0 THEN pm.revenue_30d ELSE 0 END) AS revenue_30d,
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SUM(CASE WHEN pm.cogs_30d > 0 THEN pm.cogs_30d ELSE 0 END) AS cogs_30d,
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SUM(CASE WHEN pm.profit_30d != 0 THEN pm.profit_30d ELSE 0 END) AS profit_30d,
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SUM(COALESCE(pm.cogs_30d, 0)) AS cogs_30d,
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SUM(COALESCE(pm.profit_30d, 0)) AS profit_30d,
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SUM(CASE WHEN pm.sales_365d > 0 THEN pm.sales_365d ELSE 0 END) AS sales_365d,
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SUM(CASE WHEN pm.revenue_365d > 0 THEN pm.revenue_365d ELSE 0 END) AS revenue_365d,
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SUM(CASE WHEN pm.lifetime_sales > 0 THEN pm.lifetime_sales ELSE 0 END) AS lifetime_sales,
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@@ -38,58 +38,56 @@ BEGIN
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JOIN public.product_metrics pm ON pc.pid = pm.pid
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GROUP BY pc.cat_id
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),
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-- Calculate rolled-up metrics (including all descendant categories)
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-- Map each category to ALL distinct products in it or any descendant.
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-- Uses the path array from category_hierarchy: for product P in category C,
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-- P contributes to C and every ancestor in C's path.
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-- DISTINCT ensures each (ancestor, pid) pair appears only once, preventing
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-- double-counting when a product belongs to multiple categories under the same parent.
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CategoryProducts AS (
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SELECT DISTINCT
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ancestor_cat_id,
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pc.pid
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FROM public.product_categories pc
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JOIN category_hierarchy ch ON pc.cat_id = ch.cat_id
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CROSS JOIN LATERAL unnest(ch.path) AS ancestor_cat_id
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),
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-- Calculate rolled-up metrics using deduplicated product sets
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RolledUpMetrics AS (
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SELECT
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ch.cat_id,
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-- Sum metrics from this category and all its descendants
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SUM(dcm.product_count) AS product_count,
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SUM(dcm.active_product_count) AS active_product_count,
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SUM(dcm.replenishable_product_count) AS replenishable_product_count,
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SUM(dcm.current_stock_units) AS current_stock_units,
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SUM(dcm.current_stock_cost) AS current_stock_cost,
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SUM(dcm.current_stock_retail) AS current_stock_retail,
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SUM(dcm.sales_7d) AS sales_7d,
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SUM(dcm.revenue_7d) AS revenue_7d,
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SUM(dcm.sales_30d) AS sales_30d,
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SUM(dcm.revenue_30d) AS revenue_30d,
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SUM(dcm.cogs_30d) AS cogs_30d,
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SUM(dcm.profit_30d) AS profit_30d,
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SUM(dcm.sales_365d) AS sales_365d,
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SUM(dcm.revenue_365d) AS revenue_365d,
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SUM(dcm.lifetime_sales) AS lifetime_sales,
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SUM(dcm.lifetime_revenue) AS lifetime_revenue
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FROM category_hierarchy ch
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LEFT JOIN DirectCategoryMetrics dcm ON
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dcm.cat_id = ch.cat_id OR
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dcm.cat_id = ANY(SELECT cat_id FROM category_hierarchy WHERE ch.cat_id = ANY(ancestor_ids))
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GROUP BY ch.cat_id
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),
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PreviousPeriodCategoryMetrics AS (
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-- Get previous period metrics for growth calculation
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SELECT
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pc.cat_id,
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SUM(CASE WHEN dps.snapshot_date >= CURRENT_DATE - INTERVAL '59 days'
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AND dps.snapshot_date < CURRENT_DATE - INTERVAL '29 days'
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THEN dps.units_sold ELSE 0 END) AS sales_prev_30d,
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SUM(CASE WHEN dps.snapshot_date >= CURRENT_DATE - INTERVAL '59 days'
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AND dps.snapshot_date < CURRENT_DATE - INTERVAL '29 days'
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THEN dps.net_revenue ELSE 0 END) AS revenue_prev_30d
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FROM public.daily_product_snapshots dps
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JOIN public.product_categories pc ON dps.pid = pc.pid
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GROUP BY pc.cat_id
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cp.ancestor_cat_id AS cat_id,
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COUNT(DISTINCT cp.pid) AS product_count,
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COUNT(DISTINCT CASE WHEN pm.is_visible THEN cp.pid END) AS active_product_count,
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COUNT(DISTINCT CASE WHEN pm.is_replenishable THEN cp.pid END) AS replenishable_product_count,
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SUM(pm.current_stock) AS current_stock_units,
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SUM(pm.current_stock_cost) AS current_stock_cost,
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SUM(pm.current_stock_retail) AS current_stock_retail,
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SUM(CASE WHEN pm.sales_7d > 0 THEN pm.sales_7d ELSE 0 END) AS sales_7d,
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SUM(CASE WHEN pm.revenue_7d > 0 THEN pm.revenue_7d ELSE 0 END) AS revenue_7d,
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SUM(CASE WHEN pm.sales_30d > 0 THEN pm.sales_30d ELSE 0 END) AS sales_30d,
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SUM(CASE WHEN pm.revenue_30d > 0 THEN pm.revenue_30d ELSE 0 END) AS revenue_30d,
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SUM(COALESCE(pm.cogs_30d, 0)) AS cogs_30d,
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SUM(COALESCE(pm.profit_30d, 0)) AS profit_30d,
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SUM(CASE WHEN pm.sales_365d > 0 THEN pm.sales_365d ELSE 0 END) AS sales_365d,
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SUM(CASE WHEN pm.revenue_365d > 0 THEN pm.revenue_365d ELSE 0 END) AS revenue_365d,
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SUM(CASE WHEN pm.lifetime_sales > 0 THEN pm.lifetime_sales ELSE 0 END) AS lifetime_sales,
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SUM(CASE WHEN pm.lifetime_revenue > 0 THEN pm.lifetime_revenue ELSE 0 END) AS lifetime_revenue
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FROM CategoryProducts cp
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JOIN public.product_metrics pm ON cp.pid = pm.pid
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GROUP BY cp.ancestor_cat_id
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),
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-- Previous period rolled up using same deduplicated product sets
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RolledUpPreviousPeriod AS (
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-- Calculate rolled-up previous period metrics
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SELECT
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ch.cat_id,
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SUM(ppcm.sales_prev_30d) AS sales_prev_30d,
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SUM(ppcm.revenue_prev_30d) AS revenue_prev_30d
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FROM category_hierarchy ch
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LEFT JOIN PreviousPeriodCategoryMetrics ppcm ON
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ppcm.cat_id = ch.cat_id OR
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ppcm.cat_id = ANY(SELECT cat_id FROM category_hierarchy WHERE ch.cat_id = ANY(ancestor_ids))
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GROUP BY ch.cat_id
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cp.ancestor_cat_id AS cat_id,
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SUM(CASE WHEN dps.snapshot_date >= CURRENT_DATE - INTERVAL '59 days'
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AND dps.snapshot_date < CURRENT_DATE - INTERVAL '29 days'
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THEN dps.units_sold ELSE 0 END) AS sales_prev_30d,
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SUM(CASE WHEN dps.snapshot_date >= CURRENT_DATE - INTERVAL '59 days'
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AND dps.snapshot_date < CURRENT_DATE - INTERVAL '29 days'
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THEN dps.net_revenue ELSE 0 END) AS revenue_prev_30d
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FROM CategoryProducts cp
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JOIN public.daily_product_snapshots dps ON cp.pid = dps.pid
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GROUP BY cp.ancestor_cat_id
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),
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AllCategories AS (
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-- Ensure all categories are included
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@@ -29,8 +29,8 @@ BEGIN
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COUNT(DISTINCT CASE WHEN pm.sales_30d > 0 THEN pm.pid END) AS products_with_sales_30d,
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SUM(CASE WHEN pm.sales_30d > 0 THEN pm.sales_30d ELSE 0 END) AS sales_30d,
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SUM(CASE WHEN pm.revenue_30d > 0 THEN pm.revenue_30d ELSE 0 END) AS revenue_30d,
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SUM(CASE WHEN pm.cogs_30d > 0 THEN pm.cogs_30d ELSE 0 END) AS cogs_30d,
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SUM(CASE WHEN pm.profit_30d != 0 THEN pm.profit_30d ELSE 0 END) AS profit_30d,
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SUM(COALESCE(pm.cogs_30d, 0)) AS cogs_30d,
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SUM(COALESCE(pm.profit_30d, 0)) AS profit_30d,
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COUNT(DISTINCT CASE WHEN pm.sales_365d > 0 THEN pm.pid END) AS products_with_sales_365d,
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SUM(CASE WHEN pm.sales_365d > 0 THEN pm.sales_365d ELSE 0 END) AS sales_365d,
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@@ -72,7 +72,7 @@ BEGIN
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END))::int AS avg_lead_time_days_hist -- Avg lead time from HISTORICAL received POs
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FROM public.purchase_orders po
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-- Join to receivings table to find when items were received
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LEFT JOIN public.receivings r ON r.pid = po.pid
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LEFT JOIN public.receivings r ON r.pid = po.pid AND r.supplier_id = po.supplier_id
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WHERE po.vendor IS NOT NULL AND po.vendor <> ''
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AND po.date >= CURRENT_DATE - INTERVAL '1 year' -- Look at POs created in the last year
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AND po.status = 'done' -- Only calculate lead time on completed POs
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@@ -0,0 +1,38 @@
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-- Migration: Map existing numeric order statuses to text values
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-- Run this ONCE on the production PostgreSQL database after deploying the updated orders import.
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-- This updates ~2.88M rows. On a busy system, consider running during low-traffic hours.
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-- The WHERE clause ensures idempotency - only rows with numeric statuses are updated.
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UPDATE orders SET status = CASE status
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WHEN '0' THEN 'created'
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WHEN '10' THEN 'unfinished'
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WHEN '15' THEN 'canceled'
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WHEN '16' THEN 'combined'
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WHEN '20' THEN 'placed'
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WHEN '22' THEN 'placed_incomplete'
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WHEN '30' THEN 'canceled'
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WHEN '40' THEN 'awaiting_payment'
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WHEN '50' THEN 'awaiting_products'
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WHEN '55' THEN 'shipping_later'
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WHEN '56' THEN 'shipping_together'
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WHEN '60' THEN 'ready'
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WHEN '61' THEN 'flagged'
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WHEN '62' THEN 'fix_before_pick'
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WHEN '65' THEN 'manual_picking'
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WHEN '70' THEN 'in_pt'
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WHEN '80' THEN 'picked'
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WHEN '90' THEN 'awaiting_shipment'
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WHEN '91' THEN 'remote_wait'
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WHEN '92' THEN 'awaiting_pickup'
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WHEN '93' THEN 'fix_before_ship'
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WHEN '95' THEN 'shipped_confirmed'
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WHEN '100' THEN 'shipped'
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ELSE status
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END
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WHERE status ~ '^\d+$'; -- Only update rows that still have numeric statuses
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-- Verify the migration
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SELECT status, COUNT(*) as count
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FROM orders
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GROUP BY status
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ORDER BY count DESC;
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@@ -0,0 +1,51 @@
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-- Migration 002: Fix discount double-counting in orders
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--
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-- PROBLEM: The orders import was calculating discount as:
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-- discount = (prod_price_reg - prod_price) * quantity <-- "sale savings" (WRONG)
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-- + prorated points discount
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-- + item-level promo discounts
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--
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-- Since `price` in the orders table already IS the sale price (prod_price, not prod_price_reg),
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-- the "sale savings" component double-counted the markdown. This resulted in inflated discounts
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-- and near-zero net_revenue for products sold on sale.
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--
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-- Example: Product with regular_price=$30, sale_price=$15, qty=2
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-- BEFORE (buggy): discount = ($30-$15)*2 + 0 + 0 = $30.00
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-- net_revenue = $15*2 - $30 = $0.00 (WRONG!)
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-- AFTER (fixed): discount = 0 + 0 + 0 = $0.00
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-- net_revenue = $15*2 - $0 = $30.00 (CORRECT!)
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--
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-- FIX: This cannot be fixed with a pure SQL migration because PostgreSQL doesn't store
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-- prod_price_reg. The discount column has the inflated value baked in, and we can't
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-- decompose which portion was the base_discount vs actual promo discounts.
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--
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-- REQUIRED ACTION: Run a FULL (non-incremental) orders re-import after deploying the
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-- fixed orders.js. This will recalculate all discounts using the corrected formula.
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--
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-- Steps:
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-- 1. Deploy updated orders.js (base_discount removed from discount calculation)
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-- 2. Run: node scripts/import/orders.js --full
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-- (or trigger a full sync through whatever mechanism is used)
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-- 3. After re-import, run the daily snapshots rebuild to propagate corrected revenue:
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-- psql -f scripts/metrics-new/backfill/rebuild_daily_snapshots.sql
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-- 4. Re-run metrics calculation:
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-- node scripts/metrics-new/calculate-metrics-new.js
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--
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-- VERIFICATION: After re-import, check the previously-affected products:
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SELECT
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o.pid,
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p.title,
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o.order_number,
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o.price,
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o.quantity,
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o.discount,
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(o.price * o.quantity) as gross_revenue,
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(o.price * o.quantity - o.discount) as net_revenue
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FROM orders o
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JOIN products p ON o.pid = p.pid
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WHERE o.pid IN (624756, 614513)
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ORDER BY o.date DESC
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LIMIT 10;
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-- Expected: discount should be 0 (or small promo amount) for regular sales,
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-- and net_revenue should be close to gross_revenue.
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@@ -1,75 +1,73 @@
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-- Description: Calculates and updates daily aggregated product data for recent days.
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-- Uses UPSERT (INSERT ON CONFLICT UPDATE) for idempotency.
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-- Description: Calculates and updates daily aggregated product data.
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-- Self-healing: automatically detects and fills gaps in snapshot history.
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-- Always reprocesses recent days to pick up new orders and data corrections.
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-- Dependencies: Core import tables (products, orders, purchase_orders), calculate_status table.
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-- Frequency: Hourly (Run ~5-10 minutes after hourly data import completes).
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DO $$
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DECLARE
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_module_name TEXT := 'daily_snapshots';
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_start_time TIMESTAMPTZ := clock_timestamp(); -- Time execution started
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_last_calc_time TIMESTAMPTZ;
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_target_date DATE; -- Will be set in the loop
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_start_time TIMESTAMPTZ := clock_timestamp();
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_target_date DATE;
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_total_records INT := 0;
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_has_orders BOOLEAN := FALSE;
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_process_days INT := 5; -- Number of days to check/process (today plus previous 4 days)
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_day_counter INT;
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_missing_days INT[] := ARRAY[]::INT[]; -- Array to store days with missing or incomplete data
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_days_processed INT := 0;
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_max_backfill_days INT := 90; -- Safety cap: max days to backfill per run
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_recent_recheck_days INT := 2; -- Always reprocess this many recent days (today + yesterday)
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_latest_snapshot DATE;
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_backfill_start DATE;
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BEGIN
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-- Get the timestamp before the last successful run of this module
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SELECT last_calculation_timestamp INTO _last_calc_time
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FROM public.calculate_status
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WHERE module_name = _module_name;
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RAISE NOTICE 'Running % script. Start Time: %', _module_name, _start_time;
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-- First, check which days need processing by comparing orders data with snapshot data
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FOR _day_counter IN 0..(_process_days-1) LOOP
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_target_date := CURRENT_DATE - (_day_counter * INTERVAL '1 day');
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-- Check if this date needs updating by comparing orders to snapshot data
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-- If the date has orders but not enough snapshots, or if snapshots show zero sales but orders exist, it's incomplete
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SELECT
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CASE WHEN (
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-- We have orders for this date but not enough snapshots, or snapshots with wrong total
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(EXISTS (SELECT 1 FROM public.orders WHERE date::date = _target_date) AND
|
||||
(
|
||||
-- No snapshots exist for this date
|
||||
NOT EXISTS (SELECT 1 FROM public.daily_product_snapshots WHERE snapshot_date = _target_date) OR
|
||||
-- Or snapshots show zero sales but orders exist
|
||||
(SELECT COALESCE(SUM(units_sold), 0) FROM public.daily_product_snapshots WHERE snapshot_date = _target_date) = 0 OR
|
||||
-- Or the count of snapshot records is significantly less than distinct products in orders
|
||||
(SELECT COUNT(*) FROM public.daily_product_snapshots WHERE snapshot_date = _target_date) <
|
||||
(SELECT COUNT(DISTINCT pid) FROM public.orders WHERE date::date = _target_date) * 0.8
|
||||
)
|
||||
)
|
||||
) THEN TRUE ELSE FALSE END
|
||||
INTO _has_orders;
|
||||
|
||||
IF _has_orders THEN
|
||||
-- This day needs processing - add to our array
|
||||
_missing_days := _missing_days || _day_counter;
|
||||
RAISE NOTICE 'Day % needs updating (incomplete or missing data)', _target_date;
|
||||
END IF;
|
||||
END LOOP;
|
||||
|
||||
-- If no days need updating, exit early
|
||||
IF array_length(_missing_days, 1) IS NULL THEN
|
||||
RAISE NOTICE 'No days need updating - all snapshot data appears complete';
|
||||
|
||||
-- Still update the calculate_status to record this run
|
||||
UPDATE public.calculate_status
|
||||
SET last_calculation_timestamp = _start_time
|
||||
WHERE module_name = _module_name;
|
||||
|
||||
RETURN;
|
||||
END IF;
|
||||
|
||||
RAISE NOTICE 'Need to update % days with missing or incomplete data', array_length(_missing_days, 1);
|
||||
|
||||
-- Process only the days that need updating
|
||||
FOREACH _day_counter IN ARRAY _missing_days LOOP
|
||||
_target_date := CURRENT_DATE - (_day_counter * INTERVAL '1 day');
|
||||
RAISE NOTICE 'Processing date: %', _target_date;
|
||||
-- Find the latest existing snapshot date to determine where gaps begin
|
||||
SELECT MAX(snapshot_date) INTO _latest_snapshot
|
||||
FROM public.daily_product_snapshots;
|
||||
|
||||
-- Determine how far back to look for gaps, capped at _max_backfill_days
|
||||
_backfill_start := GREATEST(
|
||||
COALESCE(_latest_snapshot + 1, CURRENT_DATE - _max_backfill_days),
|
||||
CURRENT_DATE - _max_backfill_days
|
||||
);
|
||||
|
||||
IF _latest_snapshot IS NULL THEN
|
||||
RAISE NOTICE 'No existing snapshots found. Backfilling up to % days.', _max_backfill_days;
|
||||
ELSIF _backfill_start > _latest_snapshot + 1 THEN
|
||||
RAISE NOTICE 'Latest snapshot: %. Gap exceeds % day cap — backfilling from %. Use rebuild script for full history.',
|
||||
_latest_snapshot, _max_backfill_days, _backfill_start;
|
||||
ELSE
|
||||
RAISE NOTICE 'Latest snapshot: %. Checking for gaps from %.', _latest_snapshot, _backfill_start;
|
||||
END IF;
|
||||
|
||||
-- Process all dates that need snapshots:
|
||||
-- 1. Gap fill: dates with orders/receivings but no snapshots (older than recent window)
|
||||
-- 2. Recent recheck: last N days always reprocessed (picks up new orders, corrections)
|
||||
FOR _target_date IN
|
||||
SELECT d FROM (
|
||||
-- Gap fill: find dates with activity but missing snapshots
|
||||
SELECT activity_dates.d
|
||||
FROM (
|
||||
SELECT DISTINCT date::date AS d FROM public.orders
|
||||
WHERE date::date >= _backfill_start AND date::date < CURRENT_DATE - _recent_recheck_days
|
||||
UNION
|
||||
SELECT DISTINCT received_date::date AS d FROM public.receivings
|
||||
WHERE received_date::date >= _backfill_start AND received_date::date < CURRENT_DATE - _recent_recheck_days
|
||||
) activity_dates
|
||||
WHERE NOT EXISTS (
|
||||
SELECT 1 FROM public.daily_product_snapshots dps WHERE dps.snapshot_date = activity_dates.d
|
||||
)
|
||||
UNION
|
||||
-- Recent days: always reprocess
|
||||
SELECT d::date
|
||||
FROM generate_series(
|
||||
(CURRENT_DATE - _recent_recheck_days)::timestamp,
|
||||
CURRENT_DATE::timestamp,
|
||||
'1 day'::interval
|
||||
) d
|
||||
) dates_to_process
|
||||
ORDER BY d
|
||||
LOOP
|
||||
_days_processed := _days_processed + 1;
|
||||
RAISE NOTICE 'Processing date: % [%/%]', _target_date, _days_processed,
|
||||
_days_processed; -- count not known ahead of time, but shows progress
|
||||
|
||||
-- IMPORTANT: First delete any existing data for this date to prevent duplication
|
||||
DELETE FROM public.daily_product_snapshots
|
||||
@@ -90,7 +88,6 @@ BEGIN
|
||||
COALESCE(
|
||||
o.costeach, -- First use order-specific cost if available
|
||||
get_weighted_avg_cost(p.pid, o.date::date), -- Then use weighted average cost
|
||||
p.landing_cost_price, -- Fallback to landing cost
|
||||
p.cost_price -- Final fallback to current cost
|
||||
) * o.quantity
|
||||
ELSE 0 END), 0.00) AS cogs,
|
||||
@@ -128,7 +125,7 @@ BEGIN
|
||||
SELECT
|
||||
pid,
|
||||
stock_quantity,
|
||||
COALESCE(landing_cost_price, cost_price, 0.00) as effective_cost_price,
|
||||
COALESCE(cost_price, 0.00) as effective_cost_price,
|
||||
COALESCE(price, 0.00) as current_price,
|
||||
COALESCE(regular_price, 0.00) as current_regular_price
|
||||
FROM public.products
|
||||
@@ -181,7 +178,7 @@ BEGIN
|
||||
COALESCE(sd.gross_revenue_unadjusted, 0.00),
|
||||
COALESCE(sd.discounts, 0.00),
|
||||
COALESCE(sd.returns_revenue, 0.00),
|
||||
COALESCE(sd.gross_revenue_unadjusted, 0.00) - COALESCE(sd.discounts, 0.00) AS net_revenue,
|
||||
COALESCE(sd.gross_revenue_unadjusted, 0.00) - COALESCE(sd.discounts, 0.00) - COALESCE(sd.returns_revenue, 0.00) AS net_revenue,
|
||||
COALESCE(sd.cogs, 0.00),
|
||||
COALESCE(sd.gross_regular_revenue, 0.00),
|
||||
(COALESCE(sd.gross_revenue_unadjusted, 0.00) - COALESCE(sd.discounts, 0.00)) - COALESCE(sd.cogs, 0.00) AS profit, -- Basic profit: Net Revenue - COGS
|
||||
@@ -201,12 +198,18 @@ BEGIN
|
||||
RAISE NOTICE 'Created % daily snapshot records for % with sales/receiving activity', _total_records, _target_date;
|
||||
END LOOP;
|
||||
|
||||
-- Update the status table with the timestamp from the START of this run
|
||||
UPDATE public.calculate_status
|
||||
SET last_calculation_timestamp = _start_time
|
||||
WHERE module_name = _module_name;
|
||||
IF _days_processed = 0 THEN
|
||||
RAISE NOTICE 'No days need updating — all snapshot data is current.';
|
||||
ELSE
|
||||
RAISE NOTICE 'Processed % days total.', _days_processed;
|
||||
END IF;
|
||||
|
||||
RAISE NOTICE 'Finished % processing for multiple dates. Duration: %', _module_name, clock_timestamp() - _start_time;
|
||||
-- Update the status table with the timestamp from the START of this run
|
||||
INSERT INTO public.calculate_status (module_name, last_calculation_timestamp)
|
||||
VALUES (_module_name, _start_time)
|
||||
ON CONFLICT (module_name) DO UPDATE SET last_calculation_timestamp = _start_time;
|
||||
|
||||
RAISE NOTICE 'Finished % script. Duration: %', _module_name, clock_timestamp() - _start_time;
|
||||
|
||||
END $$;
|
||||
|
||||
|
||||
@@ -52,7 +52,7 @@ BEGIN
|
||||
COALESCE(p.price, 0.00) as current_price,
|
||||
COALESCE(p.regular_price, 0.00) as current_regular_price,
|
||||
COALESCE(p.cost_price, 0.00) as current_cost_price,
|
||||
COALESCE(p.landing_cost_price, p.cost_price, 0.00) as current_effective_cost, -- Use landing if available, else cost
|
||||
COALESCE(p.cost_price, 0.00) as current_effective_cost,
|
||||
p.stock_quantity as current_stock,
|
||||
p.created_at,
|
||||
p.first_received,
|
||||
@@ -321,10 +321,10 @@ BEGIN
|
||||
(GREATEST(0, ci.historical_total_sold - COALESCE(lr.lifetime_units_from_orders, 0)) *
|
||||
COALESCE(
|
||||
-- Use oldest known price from snapshots as proxy
|
||||
(SELECT revenue_7d / NULLIF(sales_7d, 0)
|
||||
FROM daily_product_snapshots
|
||||
WHERE pid = ci.pid AND sales_7d > 0
|
||||
ORDER BY snapshot_date ASC
|
||||
(SELECT net_revenue / NULLIF(units_sold, 0)
|
||||
FROM daily_product_snapshots
|
||||
WHERE pid = ci.pid AND units_sold > 0
|
||||
ORDER BY snapshot_date ASC
|
||||
LIMIT 1),
|
||||
ci.current_price
|
||||
))
|
||||
|
||||
Reference in New Issue
Block a user