new last price schema
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18b8883dde
commit
8b6df1c917
@ -1,12 +1,13 @@
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--------------------------------------------------------------------------------
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-- Clear old data
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-- Reset target tables
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--------------------------------------------------------------------------------
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DROP TABLE IF EXISTS pricing.lastpricedetail;
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--DROP TABLE IF EXISTS pricing.lastpricedetail;
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DELETE FROM pricing.lastpricedetail;
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DROP TABLE IF EXISTS #flagged;
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--------------------------------------------------------------------------------
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-- Base cleaned input
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-- Stage 1: Load cleaned input rows
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-- Filters out irrelevant quotes/orders and calculates unit prices
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--------------------------------------------------------------------------------
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WITH base AS (
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SELECT
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@ -34,25 +35,33 @@ WITH base AS (
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AND o."Order Status" <> 'CANCELLED'
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AND o."Units" > 0
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AND o."Part Group" <> ''
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-- Optional filter for testing
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-- AND o."Customer" = 'ESBENSHADES GREENHOUSE'
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),
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--------------------------------------------------------------------------------
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-- Rank rows for recency and volume
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-- Stage 2: Rank each row based on recency and volume rules
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-- Flags include:
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-- - rn_mrs: most recent sale
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-- - rn_mrq: most recent quote
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-- - rn_lvs: largest sale in last year
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-- - rn_lvq: largest quote in last year
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-- - rn_dss: most recent sale per dataseg
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-- - rn_dsq: most recent quote per dataseg
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--------------------------------------------------------------------------------
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ranked AS (
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SELECT
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b.*
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-- most recent sale
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-- Most recent sale
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,ROW_NUMBER() OVER (
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PARTITION BY b.customer, b.partgroup
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ORDER BY CASE WHEN b.version = 'Actual' THEN b.odate ELSE NULL END DESC
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) AS rn_mrs
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-- most recent quote
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-- Most recent quote
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,ROW_NUMBER() OVER (
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PARTITION BY b.customer, b.partgroup
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ORDER BY CASE WHEN b.version = 'Quotes' THEN b.odate ELSE NULL END DESC
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) AS rn_mrq
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-- largest volume sale
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-- Largest volume sale (last 12 months)
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,ROW_NUMBER() OVER (
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PARTITION BY b.customer, b.partgroup
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ORDER BY CASE
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@ -60,7 +69,7 @@ ranked AS (
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THEN b.qty ELSE NULL
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END DESC
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) AS rn_lvs
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-- largest volume quote
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-- Largest volume quote (last 12 months)
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,ROW_NUMBER() OVER (
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PARTITION BY b.customer, b.partgroup
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ORDER BY CASE
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@ -68,66 +77,63 @@ ranked AS (
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THEN b.qty ELSE NULL
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END DESC
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) AS rn_lvq
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-- most recent sale for data segment
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-- Most recent sale per data segment
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,ROW_NUMBER() OVER (
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PARTITION BY b.customer, b.partgroup, b.dataseg, b.version
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ORDER BY CASE WHEN b.version = 'Actual' THEN b.odate ELSE NULL END DESC
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) AS rn_dss
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-- most recent quote for data segment
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-- Most recent quote per data segment
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,ROW_NUMBER() OVER (
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PARTITION BY b.customer, b.partgroup, b.dataseg, b.version
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ORDER BY CASE WHEN b.version = 'Quotes' THEN b.odate ELSE NULL END DESC
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) AS rn_dsq
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FROM base b
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)
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SELECT * INTO #flagged FROM ranked
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--------------------------------------------------------------------------------
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-- Stage 2.5: Save only rows that meet any of the above criteria
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-- and annotate each with global-level flag (mrs, mrq, lvs, lvq)
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--------------------------------------------------------------------------------
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SELECT
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*,
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CASE WHEN rn_mrs = 1 THEN 'mrs' END AS f1,
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CASE WHEN rn_mrq = 1 THEN 'mrq' END AS f2,
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CASE WHEN rn_lvs = 1 THEN 'lvs' END AS f3,
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CASE WHEN rn_lvq = 1 THEN 'lvq' END AS f4,
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CASE WHEN rn_dss = 1 THEN 'dss' END AS f5,
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CASE WHEN rn_dsq = 1 THEN 'dsq' END AS f6
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INTO #flagged
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FROM ranked
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WHERE
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1=1
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-- AND partgroup = 'XNS0T1G3'
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AND (
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rn_mrs = 1
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OR rn_mrq = 1
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OR rn_lvs = 1
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OR rn_lvq = 1
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OR rn_dss = 1
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OR rn_dsq = 1
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)
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rn_mrs = 1
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OR rn_mrq = 1
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OR rn_lvs = 1
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OR rn_lvq = 1
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OR rn_dss = 1
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OR rn_dsq = 1;
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CREATE NONCLUSTERED INDEX ix_flagged_lookup
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ON #flagged(customer, partgroup, dataseg, version, part, qty, price, odate, ordnum, quoten);
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--SELECT * FROM #flagged WHERE customer LIKE 'ESBENSHADE%' AND partgroup = 'XNS0T1G3'
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--------------------------------------------------------------------------------
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-- Assumes you already have #flagged built from ranked rows
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-- with columns: customer, partgroup, dataseg, version, part, qty, price, odate, ordnum, quoten,
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-- and rank columns: rn_mrs, rn_mrq, rn_lvs, rn_lvq, rn_dss, rn_dsq
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-- Stage 3: Build JSON from flagged rows
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--------------------------------------------------------------------------------
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-- Step 1: Flatten flag-based records
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WITH exploded AS (
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SELECT *,
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CASE WHEN rn_mrs = 1 THEN 'mrs' END AS f1,
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CASE WHEN rn_mrq = 1 THEN 'mrq' END AS f2,
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CASE WHEN rn_lvs = 1 THEN 'lvs' END AS f3,
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CASE WHEN rn_lvq = 1 THEN 'lvq' END AS f4
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FROM #flagged
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-- WHERE customer LIKE 'ESBENSHADE%' AND partgroup = 'XNS0T1G3'
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)
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,flags AS (
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-- Step 3.1: Explode all flags from the #flagged table
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WITH exploded_flags AS (
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SELECT
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customer, partgroup, dataseg, version, part, qty, price, odate, ordnum, quoten,
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flag
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FROM exploded
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CROSS APPLY (VALUES (f1), (f2), (f3), (f4)) AS f(flag)
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FROM #flagged
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CROSS APPLY (VALUES (f1), (f2), (f3), (f4), (f5), (f6)) AS f(flag)
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WHERE flag IS NOT NULL
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)
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--SELECT * FROM flags
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-- Step 2: JSON object for each flag (mrs/mrq/lvs/lvq)
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--SELECT * FROM exploded_flags
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-- Step 3.2: Serialize each row into its JSON snippet
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,serialized_flags AS (
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SELECT
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customer,
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partgroup,
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dataseg,
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flag,
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CONCAT(
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'"', flag, '":',
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@ -145,65 +151,58 @@ WITH exploded AS (
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FOR JSON PATH, WITHOUT_ARRAY_WRAPPER
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))
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) AS json_piece
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FROM flags
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FROM exploded_flags
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)
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--SELECT * FROM serialized_flags
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-- Step 3.3: Collect all global-level flags (mrs, mrq, lvs, lvq)
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,flag_json AS (
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SELECT
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customer,
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partgroup,
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STRING_AGG(json_piece, ',') AS json_block
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FROM serialized_flags
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WHERE flag IN ('mrs', 'mrq', 'lvs', 'lvq')
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GROUP BY customer, partgroup
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)
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--SELECT * FROM flag_json
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-- Step 3: One row per (customer, partgroup, dataseg) — most recent
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,seg_rows AS (
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SELECT *
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FROM (
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SELECT *,
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ROW_NUMBER() OVER (
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PARTITION BY customer, partgroup, dataseg
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ORDER BY odate DESC
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) AS rk
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FROM #flagged
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-- WHERE customer LIKE 'ESBENSHADE%' AND partgroup = 'XNS0T1G3'
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) x
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WHERE rk = 1
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)
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--SELECT * FROM seg_rows
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-- Step 4: JSON object for each dataseg
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, serialized_segs AS (
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-- Step 3.4: Nest dss/dsq under each dataseg
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,seg_pieces AS (
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SELECT
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customer,
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partgroup,
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dataseg,
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STRING_AGG(json_piece, ',') AS inner_json
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FROM serialized_flags
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WHERE flag IN ('dss', 'dsq')
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GROUP BY customer, partgroup, dataseg
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)
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--SELECT * FROM seg_pieces
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-- Step 3.5: Wrap the inner_json under dataseg key
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,wrapped_segs AS (
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SELECT
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customer,
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partgroup,
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CONCAT(
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'"', dataseg, '":',
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JSON_QUERY((
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SELECT
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version,
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dataseg AS datasegment,
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part,
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qty,
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price,
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odate,
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ordnum,
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quoten
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FOR JSON PATH, WITHOUT_ARRAY_WRAPPER
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))
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'"', dataseg, '": {', inner_json, '}'
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) AS json_piece
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FROM seg_rows
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),
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seg_json AS (
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FROM seg_pieces
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)
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-- Step 3.6: Aggregate all dataseg entries into one JSON block per customer/partgroup
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,seg_json AS (
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SELECT
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customer,
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partgroup,
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STRING_AGG(json_piece, ',') AS json_block
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FROM serialized_segs
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FROM wrapped_segs
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GROUP BY customer, partgroup
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)
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--SELECT * FROM seg_json
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-- Step 5: Merge into final JSON per (customer, partgroup)
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--------------------------------------------------------------------------------
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-- Stage 4: Merge flags and segment blocks into a single JSON object
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-- Write final pricing history to pricing.lastpricedetail
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--------------------------------------------------------------------------------
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INSERT INTO
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pricing.lastpricedetail
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SELECT
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COALESCE(f.customer, s.customer) AS customer,
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COALESCE(f.partgroup, s.partgroup) AS partgroup,
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@ -217,11 +216,6 @@ SELECT
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COALESCE(s.json_block, ''),
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'}'
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) AS part_stats
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INTO #final_json
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FROM flag_json f
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FULL OUTER JOIN seg_json s
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ON f.customer = s.customer AND f.partgroup = s.partgroup;
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-- Final output
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SELECT * FROM #FINAL_JSON WHERE customer = 'GRIFFIN' AND partgroup = 'XNS0T1G3'
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