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new last price schema

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This commit is contained in:
Paul Trowbridge 2025-08-06 11:23:40 -04:00
parent 18b8883dde
commit 8b6df1c917
1 changed files with 77 additions and 83 deletions
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148
new_targets/tables/lastpricedetail.ms.sql
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@ -1,12 +1,13 @@
-------------------------------------------------------------------------------- --------------------------------------------------------------------------------
-- Clear old data -- Reset target tables
-------------------------------------------------------------------------------- --------------------------------------------------------------------------------
DROP TABLE IF EXISTS pricing.lastpricedetail; --DROP TABLE IF EXISTS pricing.lastpricedetail;
DELETE FROM pricing.lastpricedetail; DELETE FROM pricing.lastpricedetail;
DROP TABLE IF EXISTS #flagged; DROP TABLE IF EXISTS #flagged;
-------------------------------------------------------------------------------- --------------------------------------------------------------------------------
-- Base cleaned input -- Stage 1: Load cleaned input rows
-- Filters out irrelevant quotes/orders and calculates unit prices
-------------------------------------------------------------------------------- --------------------------------------------------------------------------------
WITH base AS ( WITH base AS (
SELECT SELECT
@ -34,25 +35,33 @@ WITH base AS (
AND o."Order Status" <> 'CANCELLED' AND o."Order Status" <> 'CANCELLED'
AND o."Units" > 0 AND o."Units" > 0
AND o."Part Group" <> '' AND o."Part Group" <> ''
-- Optional filter for testing
-- AND o."Customer" = 'ESBENSHADES GREENHOUSE' -- AND o."Customer" = 'ESBENSHADES GREENHOUSE'
), ),
-------------------------------------------------------------------------------- --------------------------------------------------------------------------------
-- Rank rows for recency and volume -- Stage 2: Rank each row based on recency and volume rules
-- Flags include:
-- - rn_mrs: most recent sale
-- - rn_mrq: most recent quote
-- - rn_lvs: largest sale in last year
-- - rn_lvq: largest quote in last year
-- - rn_dss: most recent sale per dataseg
-- - rn_dsq: most recent quote per dataseg
-------------------------------------------------------------------------------- --------------------------------------------------------------------------------
ranked AS ( ranked AS (
SELECT SELECT
b.* b.*
-- most recent sale -- Most recent sale
,ROW_NUMBER() OVER ( ,ROW_NUMBER() OVER (
PARTITION BY b.customer, b.partgroup PARTITION BY b.customer, b.partgroup
ORDER BY CASE WHEN b.version = 'Actual' THEN b.odate ELSE NULL END DESC ORDER BY CASE WHEN b.version = 'Actual' THEN b.odate ELSE NULL END DESC
) AS rn_mrs ) AS rn_mrs
-- most recent quote -- Most recent quote
,ROW_NUMBER() OVER ( ,ROW_NUMBER() OVER (
PARTITION BY b.customer, b.partgroup PARTITION BY b.customer, b.partgroup
ORDER BY CASE WHEN b.version = 'Quotes' THEN b.odate ELSE NULL END DESC ORDER BY CASE WHEN b.version = 'Quotes' THEN b.odate ELSE NULL END DESC
) AS rn_mrq ) AS rn_mrq
-- largest volume sale -- Largest volume sale (last 12 months)
,ROW_NUMBER() OVER ( ,ROW_NUMBER() OVER (
PARTITION BY b.customer, b.partgroup PARTITION BY b.customer, b.partgroup
ORDER BY CASE ORDER BY CASE
@ -60,7 +69,7 @@ ranked AS (
THEN b.qty ELSE NULL THEN b.qty ELSE NULL
END DESC END DESC
) AS rn_lvs ) AS rn_lvs
-- largest volume quote -- Largest volume quote (last 12 months)
,ROW_NUMBER() OVER ( ,ROW_NUMBER() OVER (
PARTITION BY b.customer, b.partgroup PARTITION BY b.customer, b.partgroup
ORDER BY CASE ORDER BY CASE
@ -68,66 +77,63 @@ ranked AS (
THEN b.qty ELSE NULL THEN b.qty ELSE NULL
END DESC END DESC
) AS rn_lvq ) AS rn_lvq
-- most recent sale for data segment -- Most recent sale per data segment
,ROW_NUMBER() OVER ( ,ROW_NUMBER() OVER (
PARTITION BY b.customer, b.partgroup, b.dataseg, b.version PARTITION BY b.customer, b.partgroup, b.dataseg, b.version
ORDER BY CASE WHEN b.version = 'Actual' THEN b.odate ELSE NULL END DESC ORDER BY CASE WHEN b.version = 'Actual' THEN b.odate ELSE NULL END DESC
) AS rn_dss ) AS rn_dss
-- most recent quote for data segment -- Most recent quote per data segment
,ROW_NUMBER() OVER ( ,ROW_NUMBER() OVER (
PARTITION BY b.customer, b.partgroup, b.dataseg, b.version PARTITION BY b.customer, b.partgroup, b.dataseg, b.version
ORDER BY CASE WHEN b.version = 'Quotes' THEN b.odate ELSE NULL END DESC ORDER BY CASE WHEN b.version = 'Quotes' THEN b.odate ELSE NULL END DESC
) AS rn_dsq ) AS rn_dsq
FROM base b FROM base b
) )
SELECT * INTO #flagged FROM ranked --------------------------------------------------------------------------------
-- Stage 2.5: Save only rows that meet any of the above criteria
-- and annotate each with global-level flag (mrs, mrq, lvs, lvq)
--------------------------------------------------------------------------------
SELECT
*,
CASE WHEN rn_mrs = 1 THEN 'mrs' END AS f1,
CASE WHEN rn_mrq = 1 THEN 'mrq' END AS f2,
CASE WHEN rn_lvs = 1 THEN 'lvs' END AS f3,
CASE WHEN rn_lvq = 1 THEN 'lvq' END AS f4,
CASE WHEN rn_dss = 1 THEN 'dss' END AS f5,
CASE WHEN rn_dsq = 1 THEN 'dsq' END AS f6
INTO #flagged
FROM ranked
WHERE WHERE
1=1
-- AND partgroup = 'XNS0T1G3'
AND (
rn_mrs = 1 rn_mrs = 1
OR rn_mrq = 1 OR rn_mrq = 1
OR rn_lvs = 1 OR rn_lvs = 1
OR rn_lvq = 1 OR rn_lvq = 1
OR rn_dss = 1 OR rn_dss = 1
OR rn_dsq = 1 OR rn_dsq = 1;
)
CREATE NONCLUSTERED INDEX ix_flagged_lookup CREATE NONCLUSTERED INDEX ix_flagged_lookup
ON #flagged(customer, partgroup, dataseg, version, part, qty, price, odate, ordnum, quoten); ON #flagged(customer, partgroup, dataseg, version, part, qty, price, odate, ordnum, quoten);
--SELECT * FROM #flagged WHERE customer LIKE 'ESBENSHADE%' AND partgroup = 'XNS0T1G3'
-------------------------------------------------------------------------------- --------------------------------------------------------------------------------
-- Assumes you already have #flagged built from ranked rows -- Stage 3: Build JSON from flagged rows
-- with columns: customer, partgroup, dataseg, version, part, qty, price, odate, ordnum, quoten,
-- and rank columns: rn_mrs, rn_mrq, rn_lvs, rn_lvq, rn_dss, rn_dsq
-------------------------------------------------------------------------------- --------------------------------------------------------------------------------
-- Step 1: Flatten flag-based records -- Step 3.1: Explode all flags from the #flagged table
WITH exploded AS ( WITH exploded_flags AS (
SELECT *,
CASE WHEN rn_mrs = 1 THEN 'mrs' END AS f1,
CASE WHEN rn_mrq = 1 THEN 'mrq' END AS f2,
CASE WHEN rn_lvs = 1 THEN 'lvs' END AS f3,
CASE WHEN rn_lvq = 1 THEN 'lvq' END AS f4
FROM #flagged
-- WHERE customer LIKE 'ESBENSHADE%' AND partgroup = 'XNS0T1G3'
)
,flags AS (
SELECT SELECT
customer, partgroup, dataseg, version, part, qty, price, odate, ordnum, quoten, customer, partgroup, dataseg, version, part, qty, price, odate, ordnum, quoten,
flag flag
FROM exploded FROM #flagged
CROSS APPLY (VALUES (f1), (f2), (f3), (f4)) AS f(flag) CROSS APPLY (VALUES (f1), (f2), (f3), (f4), (f5), (f6)) AS f(flag)
WHERE flag IS NOT NULL WHERE flag IS NOT NULL
) )
--SELECT * FROM flags --SELECT * FROM exploded_flags
-- Step 2: JSON object for each flag (mrs/mrq/lvs/lvq) -- Step 3.2: Serialize each row into its JSON snippet
,serialized_flags AS ( ,serialized_flags AS (
SELECT SELECT
customer, customer,
partgroup, partgroup,
dataseg,
flag, flag,
CONCAT( CONCAT(
'"', flag, '":', '"', flag, '":',
@ -145,65 +151,58 @@ WITH exploded AS (
FOR JSON PATH, WITHOUT_ARRAY_WRAPPER FOR JSON PATH, WITHOUT_ARRAY_WRAPPER
)) ))
) AS json_piece ) AS json_piece
FROM flags FROM exploded_flags
) )
--SELECT * FROM serialized_flags
-- Step 3.3: Collect all global-level flags (mrs, mrq, lvs, lvq)
,flag_json AS ( ,flag_json AS (
SELECT SELECT
customer, customer,
partgroup, partgroup,
STRING_AGG(json_piece, ',') AS json_block STRING_AGG(json_piece, ',') AS json_block
FROM serialized_flags FROM serialized_flags
WHERE flag IN ('mrs', 'mrq', 'lvs', 'lvq')
GROUP BY customer, partgroup GROUP BY customer, partgroup
) )
--SELECT * FROM flag_json --SELECT * FROM flag_json
-- Step 3: One row per (customer, partgroup, dataseg) — most recent -- Step 3.4: Nest dss/dsq under each dataseg
,seg_rows AS ( ,seg_pieces AS (
SELECT *
FROM (
SELECT *,
ROW_NUMBER() OVER (
PARTITION BY customer, partgroup, dataseg
ORDER BY odate DESC
) AS rk
FROM #flagged
-- WHERE customer LIKE 'ESBENSHADE%' AND partgroup = 'XNS0T1G3'
) x
WHERE rk = 1
)
--SELECT * FROM seg_rows
-- Step 4: JSON object for each dataseg
, serialized_segs AS (
SELECT SELECT
customer, customer,
partgroup, partgroup,
dataseg, dataseg,
CONCAT( STRING_AGG(json_piece, ',') AS inner_json
'"', dataseg, '":', FROM serialized_flags
JSON_QUERY(( WHERE flag IN ('dss', 'dsq')
GROUP BY customer, partgroup, dataseg
)
--SELECT * FROM seg_pieces
-- Step 3.5: Wrap the inner_json under dataseg key
,wrapped_segs AS (
SELECT SELECT
version, customer,
dataseg AS datasegment, partgroup,
part, CONCAT(
qty, '"', dataseg, '": {', inner_json, '}'
price,
odate,
ordnum,
quoten
FOR JSON PATH, WITHOUT_ARRAY_WRAPPER
))
) AS json_piece ) AS json_piece
FROM seg_rows FROM seg_pieces
), )
seg_json AS ( -- Step 3.6: Aggregate all dataseg entries into one JSON block per customer/partgroup
,seg_json AS (
SELECT SELECT
customer, customer,
partgroup, partgroup,
STRING_AGG(json_piece, ',') AS json_block STRING_AGG(json_piece, ',') AS json_block
FROM serialized_segs FROM wrapped_segs
GROUP BY customer, partgroup GROUP BY customer, partgroup
) )
--SELECT * FROM seg_json --SELECT * FROM seg_json
-- Step 5: Merge into final JSON per (customer, partgroup) --------------------------------------------------------------------------------
-- Stage 4: Merge flags and segment blocks into a single JSON object
-- Write final pricing history to pricing.lastpricedetail
--------------------------------------------------------------------------------
INSERT INTO
pricing.lastpricedetail
SELECT SELECT
COALESCE(f.customer, s.customer) AS customer, COALESCE(f.customer, s.customer) AS customer,
COALESCE(f.partgroup, s.partgroup) AS partgroup, COALESCE(f.partgroup, s.partgroup) AS partgroup,
@ -217,11 +216,6 @@ SELECT
COALESCE(s.json_block, ''), COALESCE(s.json_block, ''),
'}' '}'
) AS part_stats ) AS part_stats
INTO #final_json
FROM flag_json f FROM flag_json f
FULL OUTER JOIN seg_json s FULL OUTER JOIN seg_json s
ON f.customer = s.customer AND f.partgroup = s.partgroup; ON f.customer = s.customer AND f.partgroup = s.partgroup;
-- Final output
SELECT * FROM #FINAL_JSON WHERE customer = 'GRIFFIN' AND partgroup = 'XNS0T1G3'