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Optimize orders import

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Matt
2026-02-09 09:03:21 -05:00
parent 7c41a7f799
commit 6aefc1b40d
197 changed files with 397 additions and 69413 deletions
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227
inventory-server/scripts/metrics-new/update_daily_snapshots.sql
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-- Description: Calculates and updates daily aggregated product data.
-- Self-healing: automatically detects and fills gaps in snapshot history.
-- Always reprocesses recent days to pick up new orders and data corrections.
-- Dependencies: Core import tables (products, orders, purchase_orders), calculate_status table.
-- Frequency: Hourly (Run ~5-10 minutes after hourly data import completes).
DO $$
DECLARE
_module_name TEXT := 'daily_snapshots';
_start_time TIMESTAMPTZ := clock_timestamp();
_target_date DATE;
_total_records INT := 0;
_days_processed INT := 0;
_max_backfill_days INT := 90; -- Safety cap: max days to backfill per run
_recent_recheck_days INT := 2; -- Always reprocess this many recent days (today + yesterday)
_latest_snapshot DATE;
_backfill_start DATE;
BEGIN
RAISE NOTICE 'Running % script. Start Time: %', _module_name, _start_time;
-- 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
WHERE snapshot_date = _target_date;
-- Proceed with calculating daily metrics only for products with actual activity
WITH SalesData AS (
SELECT
p.pid,
p.sku,
-- Track number of orders to ensure we have real data
COUNT(o.id) as order_count,
-- Aggregate Sales (Quantity > 0, Status not Canceled/Returned)
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,
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, -- Before discount
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,
COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN
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.cost_price -- Final fallback to current cost
) * o.quantity
ELSE 0 END), 0.00) AS cogs,
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, -- Use current regular price for simplicity here
-- Aggregate Returns (Quantity < 0 or Status = Returned)
COALESCE(SUM(CASE WHEN o.quantity < 0 OR COALESCE(o.status, 'pending') = 'returned' THEN ABS(o.quantity) ELSE 0 END), 0) AS units_returned,
COALESCE(SUM(CASE WHEN o.quantity < 0 OR COALESCE(o.status, 'pending') = 'returned' THEN o.price * ABS(o.quantity) ELSE 0 END), 0.00) AS returns_revenue
FROM public.products p -- Start from products to include those with no orders today
JOIN public.orders o -- Changed to INNER JOIN to only process products with orders
ON p.pid = o.pid
AND o.date::date = _target_date -- Cast to date to ensure compatibility regardless of original type
GROUP BY p.pid, p.sku
-- No HAVING clause here - we always want to include all orders
),
ReceivingData AS (
SELECT
r.pid,
-- Track number of receiving docs to ensure we have real data
COUNT(DISTINCT r.receiving_id) as receiving_doc_count,
-- Sum the quantities received on this date
SUM(r.qty_each) AS units_received,
-- Calculate the cost received (qty * cost)
SUM(r.qty_each * r.cost_each) AS cost_received
FROM public.receivings r
WHERE r.received_date::date = _target_date
-- Optional: Filter out canceled receivings if needed
-- AND r.status <> 'canceled'
GROUP BY r.pid
-- Only include products with actual receiving activity
HAVING COUNT(DISTINCT r.receiving_id) > 0 OR SUM(r.qty_each) > 0
),
CurrentStock AS (
-- Use historical stock from stock_snapshots when available,
-- falling back to current stock from products table
SELECT
p.pid,
COALESCE(ss.stock_quantity, p.stock_quantity) AS stock_quantity,
COALESCE(ss.stock_value, p.stock_quantity * COALESCE(p.cost_price, 0.00)) AS stock_value,
COALESCE(p.price, 0.00) AS current_price,
COALESCE(p.regular_price, 0.00) AS current_regular_price
FROM public.products p
LEFT JOIN stock_snapshots ss ON p.pid = ss.pid AND ss.snapshot_date = _target_date
),
ProductsWithActivity AS (
-- Quick pre-filter to only process products with activity
SELECT DISTINCT pid
FROM (
SELECT pid FROM SalesData
UNION
SELECT pid FROM ReceivingData
) a
)
-- Now insert records, but ONLY for products with actual activity
INSERT INTO public.daily_product_snapshots (
snapshot_date,
pid,
sku,
eod_stock_quantity,
eod_stock_cost,
eod_stock_retail,
eod_stock_gross,
stockout_flag,
units_sold,
units_returned,
gross_revenue,
discounts,
returns_revenue,
net_revenue,
cogs,
gross_regular_revenue,
profit,
units_received,
cost_received,
calculation_timestamp
)
SELECT
_target_date AS snapshot_date,
COALESCE(sd.pid, rd.pid) AS pid, -- Use sales or receiving PID
COALESCE(sd.sku, p.sku) AS sku, -- Get SKU from sales data or products table
-- Inventory Metrics (Using CurrentStock)
cs.stock_quantity AS eod_stock_quantity,
cs.stock_value AS eod_stock_cost,
cs.stock_quantity * cs.current_price AS eod_stock_retail,
cs.stock_quantity * cs.current_regular_price AS eod_stock_gross,
(cs.stock_quantity <= 0) AS stockout_flag,
-- Sales Metrics (From SalesData)
COALESCE(sd.units_sold, 0),
COALESCE(sd.units_returned, 0),
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) - 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.returns_revenue, 0.00)) - COALESCE(sd.cogs, 0.00) AS profit,
-- Receiving Metrics (From ReceivingData)
COALESCE(rd.units_received, 0),
COALESCE(rd.cost_received, 0.00),
_start_time -- Timestamp of this calculation run
FROM SalesData sd
FULL OUTER JOIN ReceivingData rd ON sd.pid = rd.pid
JOIN ProductsWithActivity pwa ON COALESCE(sd.pid, rd.pid) = pwa.pid
LEFT JOIN public.products p ON COALESCE(sd.pid, rd.pid) = p.pid
LEFT JOIN CurrentStock cs ON COALESCE(sd.pid, rd.pid) = cs.pid
WHERE p.pid IS NOT NULL; -- Ensure we only insert for existing products
-- Get the total number of records inserted for this date
GET DIAGNOSTICS _total_records = ROW_COUNT;
RAISE NOTICE 'Created % daily snapshot records for % with sales/receiving activity', _total_records, _target_date;
END LOOP;
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;
-- 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 $$;
-- Return the total records processed for tracking
SELECT
COUNT(*) as rows_processed,
COUNT(DISTINCT snapshot_date) as days_processed,
MIN(snapshot_date) as earliest_date,
MAX(snapshot_date) as latest_date,
SUM(units_sold) as total_units_sold,
SUM(units_received) as total_units_received
FROM public.daily_product_snapshots
WHERE calculation_timestamp >= (NOW() - INTERVAL '5 minutes'); -- Recent updates only