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4 Commits

Author SHA1 Message Date
8b6df1c917 new last price schema 2025-08-06 11:23:40 -04:00
18b8883dde save work on old lastprice 2025-08-06 11:17:15 -04:00
414f830b19 new history template 2025-08-06 11:16:36 -04:00
0bdf7afca2 build new last price 2025-08-06 10:40:48 -04:00
4 changed files with 761 additions and 1 deletions

280
new_targets/history.json Normal file
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@ -0,0 +1,280 @@
{
"v1:B..CSE..": [
{
"version": "Actual",
"part": "XNS0T1G2G18C140",
"qty": 8960.00,
"price": 0.092910,
"odate": "2016-02-10",
"ordnum": 784718,
"quoten": 28971,
"flags": []
},
{
"version": "Quotes",
"part": "XNS0T1G2G18C140",
"qty": 9100.00,
"price": 0.092910,
"odate": "2016-02-10",
"ordnum": 0,
"quoten": 29543,
"flags": []
}
],
"v1:T..CSE..": [
{
"version": "Quotes",
"part": "XNS0T1G2X03C140",
"qty": 6020.00,
"price": 0.092910,
"odate": "2016-02-10",
"ordnum": 0,
"quoten": 29543,
"flags": []
},
{
"version": "Actual",
"part": "XNS0T1G2X03C140",
"qty": 6020.00,
"price": 0.092910,
"odate": "2016-02-09",
"ordnum": 784655,
"flags": []
}
],
"v1:B..PLT..": [
{
"version": "Actual",
"part": "XNS0T1G3G18B096",
"qty": 9600.00,
"price": 0.126130,
"odate": "2024-10-31",
"ordnum": 992442,
"quoten": 79774,
"flags": [
"most_recent_sale",
"largest_volume_sale"
]
},
{
"version": "Quotes",
"part": "XNS0T1G3G18B096",
"qty": 38400.00,
"price": 0.126130,
"odate": "2024-10-29",
"ordnum": 0,
"quoten": 79774,
"flags": [
"most_recent_quote",
"largest_volume_quote"
]
},
{
"version": "Actual",
"part": "XNS0T1G3G18B096",
"qty": 9600.00,
"price": 0.126130,
"odate": "2024-08-02",
"ordnum": 985899,
"flags": []
},
{
"version": "Actual",
"part": "XNS0T1G3G18B096",
"qty": 38400.00,
"price": 0.128250,
"odate": "2023-12-04",
"ordnum": 969894,
"quoten": 75273,
"flags": []
},
{
"version": "Quotes",
"part": "XNS0T1G3G18B096",
"qty": 38400.00,
"price": 0.128250,
"odate": "2023-12-04",
"ordnum": 0,
"quoten": 75273,
"flags": []
},
{
"version": "Quotes",
"part": "XNS0T1G3G18B096",
"qty": 19200.00,
"price": 0.135000,
"odate": "2023-02-13",
"ordnum": 0,
"quoten": 73602,
"flags": []
},
{
"version": "Quotes",
"part": "XNS0T1G3G18B096",
"qty": 38400.00,
"price": 0.145020,
"odate": "2022-01-26",
"ordnum": 0,
"quoten": 69130,
"flags": []
},
{
"version": "Actual",
"part": "XNS0T1G3G18B096",
"qty": 28800.00,
"price": 0.125480,
"odate": "2021-07-16",
"ordnum": 922664,
"quoten": 64686,
"flags": []
},
{
"version": "Quotes",
"part": "XNS0T1G3G18B096",
"qty": 38400.00,
"price": 0.125480,
"odate": "2021-07-08",
"ordnum": 0,
"quoten": 64686,
"flags": []
},
{
"version": "Actual",
"part": "XNS0T1G3G18B096",
"qty": 38400.00,
"price": 0.100390,
"odate": "2020-11-12",
"ordnum": 905400,
"flags": []
},
{
"version": "Quotes",
"part": "XNS0T1G3G18B096",
"qty": 38400.00,
"price": 0.100390,
"odate": "2020-08-13",
"ordnum": 0,
"quoten": 58215,
"flags": []
},
{
"version": "Quotes",
"part": "XNS0T1G3G18B096",
"qty": 28800.00,
"price": 0.100390,
"odate": "2020-06-11",
"ordnum": 0,
"quoten": 57254,
"flags": []
},
{
"version": "Actual",
"part": "XNS0T1G3G18B096",
"qty": 28800.00,
"price": 0.100390,
"odate": "2020-06-10",
"ordnum": 890715,
"quoten": 57254,
"flags": []
},
{
"version": "Actual",
"part": "XNS0T1G3G18B096",
"qty": 28800.00,
"price": 0.098910,
"odate": "2019-07-23",
"ordnum": 870300,
"quoten": 51460,
"flags": []
},
{
"version": "Quotes",
"part": "XNS0T1G3G18B096",
"qty": 28800.00,
"price": 0.098910,
"odate": "2019-07-18",
"ordnum": 0,
"quoten": 51460,
"flags": []
},
{
"version": "Actual",
"part": "XNS0T1G3G18B096",
"qty": 19200.00,
"price": 0.095290,
"odate": "2018-10-09",
"ordnum": 853112,
"quoten": 44775,
"flags": []
},
{
"version": "Actual",
"part": "XNS0T1G3G18B096",
"qty": 9600.00,
"price": 0.095290,
"odate": "2018-10-09",
"ordnum": 853112,
"quoten": 44775,
"flags": []
},
{
"version": "Quotes",
"part": "XNS0T1G3G18B096",
"qty": 9600.00,
"price": 0.095290,
"odate": "2018-08-21",
"ordnum": 0,
"quoten": 44775,
"flags": []
},
{
"version": "Quotes",
"part": "XNS0T1G3G18B096",
"qty": 38400.00,
"price": 0.094160,
"odate": "2017-10-13",
"ordnum": 0,
"quoten": 38844,
"flags": []
},
{
"version": "Actual",
"part": "XNS0T1G2G18B079",
"qty": 47790.00,
"price": 0.092910,
"odate": "2016-06-10",
"ordnum": 794232,
"flags": []
},
{
"version": "Quotes",
"part": "XNS0T1G2G18B079",
"qty": 47790.00,
"price": 0.092910,
"odate": "2016-02-10",
"ordnum": 0,
"quoten": 29543,
"flags": []
},
{
"version": "Quotes",
"part": "XNS0T1G2G18B079",
"qty": 47790.00,
"price": 0.091200,
"odate": "2015-12-17",
"ordnum": 0,
"quoten": 28971,
"flags": []
},
{
"version": "Quotes",
"part": "XNS0T1G2G18B079",
"qty": 47790.00,
"price": 0.091200,
"odate": "2015-09-21",
"ordnum": 0,
"quoten": 27873,
"flags": []
}
]
}

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@ -0,0 +1,63 @@
{
"mrs": {
"version": "Actual",
"datasegment": "v1:T..CSE..",
"part": "XNS0T1G3X18C140",
"qty": 4200.00,
"price": 0.146300,
"odate": "2025-08-01",
"ordnum": 1011917,
"flag": "mrs"
},
"mrq": {
"version": "Quotes",
"datasegment": "v1:B..CSE..",
"part": "XNS0T1G3G18C140",
"qty": 7560.00,
"price": 0.115800,
"odate": "2024-12-10",
"ordnum": 0,
"quoten": 81983,
"flag": "mrq"
},
"lvs": {
"version": "Actual",
"datasegment": "v1:B..PLT..",
"part": "XNS0T1G3G18B096",
"qty": 28800.00,
"price": 0.098360,
"odate": "2025-05-23",
"ordnum": 1006860,
"flag": "lvs"
},
"lvq": {
"version": "Quotes",
"datasegment": "v1:B..CSE..",
"part": "XNS0T1G3G18C140",
"qty": 7560.00,
"price": 0.115800,
"odate": "2024-12-10",
"ordnum": 0,
"quoten": 81983,
"flag": "lvq"
},
"v1:B..CSE..": {
"dss": {
"version": "Actual",
"datasegment": "v1:B..CSE..",
"part": "XNS0T1G3G18C140",
"qty": 2520.00,
"price": 0.106540,
"odate": "2025-07-17",
"ordnum": 1010952
},
"dsq": {
"version": "Quotes",
"datasegment": "v1:B..CSE..",
"part": "XNS0T1G3G18C140",
"qty": 2520.00,
"price": 0.106540,
"odate": "2025-07-17",
"quoten": 81983
}}
}

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@ -29,7 +29,7 @@ srt AS (
i.item = o.[Part Code] i.item = o.[Part Code]
WHERE WHERE
--quotes can't be integrated until we have datasegment or correct part code --quotes can't be integrated until we have datasegment or correct part code
o.[Data Source] IN ('Actual'/*,'Quotes'*/) AND o.[Data Source] IN ('Actual','Quotes') AND
customer IS NOT NULL AND customer IS NOT NULL AND
[Financial Statement Line] = '41010' AND [Financial Statement Line] = '41010' AND
o.[Order Status] <> 'CANCELLED' AND o.[Order Status] <> 'CANCELLED' AND
@ -66,3 +66,199 @@ INSERT INTO pricing.lastprice SELECT * FROM onerow;
--SELECT * FROM pricing.lastprice l --SELECT * FROM pricing.lastprice l
CREATE UNIQUE INDEX lastprice_cust_partgroup ON pricing.lastprice(customer, partgroup); CREATE UNIQUE INDEX lastprice_cust_partgroup ON pricing.lastprice(customer, partgroup);
--------------------------------------------------------------------------------
-- Step 1: Rebuild last price history with flags for recency & feature-match
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
-- Step 1: Rebuild last price history with global recency + part-level feature match
--------------------------------------------------------------------------------
DELETE FROM pricing.lastprice;
WITH base AS (
SELECT
o."Customer" AS customer,
o."Part Group" AS partgroup,
RTRIM(i.V1DS) AS dataseg,
o."Data Source" AS version, -- 'Actual' or 'Quotes'
o."Part Code" AS part,
o."Units" AS qty,
ROUND(o.[Value USD] / o.[Units], 5) AS price,
o.[Order Date] AS odate,
o.[Order Number] AS ordnum,
o.[Quote Number] AS quoten
FROM
rlarp.osm_stack_pretty o
INNER JOIN CMSInterfaceIn.[CMS.CUSLG].ITEMM i
ON i.item = o.[Part Code]
WHERE
o.[Data Source] IN ('Actual', 'Quotes') AND
o."Customer" IS NOT NULL AND
o."Financial Statement Line" = '41010' AND
o."Order Status" <> 'CANCELLED' AND
o."Units" <> 0 AND
o."Part Group" <> ''
),
ranked AS (
SELECT
b.*,
ROW_NUMBER() OVER (
PARTITION BY b.customer, b.partgroup
ORDER BY CASE WHEN b.version = 'Actual' THEN b.odate ELSE NULL END DESC
) AS rn_recent_sale,
ROW_NUMBER() OVER (
PARTITION BY b.customer, b.partgroup
ORDER BY CASE WHEN b.version = 'Quotes' THEN b.odate ELSE NULL END DESC
) AS rn_recent_quote
FROM base b
),
last_feature_sale AS (
SELECT *
FROM (
SELECT *,
ROW_NUMBER() OVER (
PARTITION BY customer, partgroup, part
ORDER BY odate DESC
) AS rn
FROM base
WHERE version = 'Actual'
) x
WHERE rn = 1
),
last_feature_quote AS (
SELECT *
FROM (
SELECT *,
ROW_NUMBER() OVER (
PARTITION BY customer, partgroup, part
ORDER BY odate DESC
) AS rn
FROM base
WHERE version = 'Quotes'
) x
WHERE rn = 1
),
flagged AS (
SELECT
r.*,
CASE WHEN rn_recent_sale = 1 THEN 'most_recent_sale' END AS flag1,
CASE WHEN rn_recent_quote = 1 THEN 'most_recent_quote' END AS flag2,
CASE
WHEN r.version = 'Actual'
AND r.customer = s.customer
AND r.partgroup = s.partgroup
AND r.part = s.part
AND r.odate = s.odate
AND r.ordnum = s.ordnum
THEN 'last_feature_match_sale'
END AS flag3,
CASE
WHEN r.version = 'Quotes'
AND r.customer = q.customer
AND r.partgroup = q.partgroup
AND r.part = q.part
AND r.odate = q.odate
AND r.quoten = q.quoten
THEN 'last_feature_match_quote'
END AS flag4
FROM ranked r
LEFT JOIN last_feature_sale s
ON r.version = 'Actual'
AND r.customer = s.customer
AND r.partgroup = s.partgroup
AND r.part = s.part
LEFT JOIN last_feature_quote q
ON r.version = 'Quotes'
AND r.customer = q.customer
AND r.partgroup = q.partgroup
AND r.part = q.part
)
SELECT * FROM flagged WHERE customer LIKE 'ESBENSHADE%' AND partgroup = 'XNS0T1G3' AND flag3 = 'last_feature_match_sale'
flags_aggregated AS (
SELECT
customer,
partgroup,
dataseg,
version,
part,
qty,
price,
odate,
ordnum,
quoten,
JSON_QUERY(
'[' + STRING_AGG(QUOTENAME(flag, '"'), ',') + ']'
) AS flags
FROM (
SELECT
customer, partgroup, dataseg, version, part, qty, price, odate, ordnum, quoten,
flag
FROM flagged
CROSS APPLY (VALUES (flag1), (flag2), (flag3), (flag4)) AS f(flag)
WHERE flag IS NOT NULL
) AS flags_expanded
GROUP BY customer, partgroup, dataseg, version, part, qty, price, odate, ordnum, quoten
),
all_rows_with_flags AS (
SELECT
b.customer,
b.partgroup,
b.dataseg,
b.version,
b.part,
b.qty,
b.price,
b.odate,
b.ordnum,
b.quoten,
ISNULL(f.flags, JSON_QUERY('[]')) AS flags
FROM base b
LEFT JOIN flags_aggregated f
ON b.customer = f.customer
AND b.partgroup = f.partgroup
AND b.dataseg = f.dataseg
AND b.version = f.version
AND b.part = f.part
AND b.qty = f.qty
AND b.price = f.price
AND b.odate = f.odate
AND b.ordnum = f.ordnum
AND ISNULL(b.quoten, -1) = ISNULL(f.quoten, -1)
),
json_rows AS (
SELECT
customer,
partgroup,
dataseg,
CONCAT(
'"', dataseg, '":',
(
SELECT
version, part, qty, price, odate, ordnum, quoten, flags
FROM all_rows_with_flags sub
WHERE sub.customer = main.customer
AND sub.partgroup = main.partgroup
AND sub.dataseg = main.dataseg
FOR JSON PATH
)
) AS part_json
FROM all_rows_with_flags main
GROUP BY customer, partgroup, dataseg
),
onerow AS (
SELECT
customer,
partgroup,
CONCAT('{', STRING_AGG(part_json, ','), '}') AS part_stats
FROM json_rows
GROUP BY customer, partgroup
)
INSERT INTO pricing.lastprice
SELECT * FROM onerow;
CREATE UNIQUE INDEX lastprice_cust_partgroup ON pricing.lastprice(customer, partgroup);

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@ -0,0 +1,221 @@
--------------------------------------------------------------------------------
-- Reset target tables
--------------------------------------------------------------------------------
--DROP TABLE IF EXISTS pricing.lastpricedetail;
DELETE FROM pricing.lastpricedetail;
DROP TABLE IF EXISTS #flagged;
--------------------------------------------------------------------------------
-- Stage 1: Load cleaned input rows
-- Filters out irrelevant quotes/orders and calculates unit prices
--------------------------------------------------------------------------------
WITH base AS (
SELECT
o."Customer" AS customer,
o."Part Group" AS partgroup,
RTRIM(i.V1DS) AS dataseg,
o."Data Source" AS version,
o."Part Code" AS part,
o."Units" AS qty,
CASE
WHEN o."Units" = 0 THEN NULL
ELSE ROUND(o.[Value USD] / NULLIF(o."Units", 0), 5)
END AS price,
o.[Order Date] AS odate,
o.[Order Number] AS ordnum,
o.[Quote Number] AS quoten
FROM
rlarp.osm_stack_pretty o
INNER JOIN CMSInterfaceIn.[CMS.CUSLG].ITEMM i
ON i.item = o.[Part Code]
WHERE
o.[Data Source] IN ('Actual', 'Quotes')
AND o."Customer" IS NOT NULL
AND o."Financial Statement Line" = '41010'
AND o."Order Status" <> 'CANCELLED'
AND o."Units" > 0
AND o."Part Group" <> ''
-- Optional filter for testing
-- AND o."Customer" = 'ESBENSHADES GREENHOUSE'
),
--------------------------------------------------------------------------------
-- 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 (
SELECT
b.*
-- Most recent sale
,ROW_NUMBER() OVER (
PARTITION BY b.customer, b.partgroup
ORDER BY CASE WHEN b.version = 'Actual' THEN b.odate ELSE NULL END DESC
) AS rn_mrs
-- Most recent quote
,ROW_NUMBER() OVER (
PARTITION BY b.customer, b.partgroup
ORDER BY CASE WHEN b.version = 'Quotes' THEN b.odate ELSE NULL END DESC
) AS rn_mrq
-- Largest volume sale (last 12 months)
,ROW_NUMBER() OVER (
PARTITION BY b.customer, b.partgroup
ORDER BY CASE
WHEN b.version = 'Actual' AND b.odate >= DATEADD(YEAR, -1, GETDATE())
THEN b.qty ELSE NULL
END DESC
) AS rn_lvs
-- Largest volume quote (last 12 months)
,ROW_NUMBER() OVER (
PARTITION BY b.customer, b.partgroup
ORDER BY CASE
WHEN b.version = 'Quotes' AND b.odate >= DATEADD(YEAR, -1, GETDATE())
THEN b.qty ELSE NULL
END DESC
) AS rn_lvq
-- Most recent sale per data segment
,ROW_NUMBER() OVER (
PARTITION BY b.customer, b.partgroup, b.dataseg, b.version
ORDER BY CASE WHEN b.version = 'Actual' THEN b.odate ELSE NULL END DESC
) AS rn_dss
-- Most recent quote per data segment
,ROW_NUMBER() OVER (
PARTITION BY b.customer, b.partgroup, b.dataseg, b.version
ORDER BY CASE WHEN b.version = 'Quotes' THEN b.odate ELSE NULL END DESC
) AS rn_dsq
FROM base b
)
--------------------------------------------------------------------------------
-- 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
rn_mrs = 1
OR rn_mrq = 1
OR rn_lvs = 1
OR rn_lvq = 1
OR rn_dss = 1
OR rn_dsq = 1;
CREATE NONCLUSTERED INDEX ix_flagged_lookup
ON #flagged(customer, partgroup, dataseg, version, part, qty, price, odate, ordnum, quoten);
--------------------------------------------------------------------------------
-- Stage 3: Build JSON from flagged rows
--------------------------------------------------------------------------------
-- Step 3.1: Explode all flags from the #flagged table
WITH exploded_flags AS (
SELECT
customer, partgroup, dataseg, version, part, qty, price, odate, ordnum, quoten,
flag
FROM #flagged
CROSS APPLY (VALUES (f1), (f2), (f3), (f4), (f5), (f6)) AS f(flag)
WHERE flag IS NOT NULL
)
--SELECT * FROM exploded_flags
-- Step 3.2: Serialize each row into its JSON snippet
,serialized_flags AS (
SELECT
customer,
partgroup,
dataseg,
flag,
CONCAT(
'"', flag, '":',
JSON_QUERY((
SELECT
version,
dataseg AS datasegment,
part,
qty,
price,
odate,
ordnum,
quoten,
flag
FOR JSON PATH, WITHOUT_ARRAY_WRAPPER
))
) AS json_piece
FROM exploded_flags
)
--SELECT * FROM serialized_flags
-- Step 3.3: Collect all global-level flags (mrs, mrq, lvs, lvq)
,flag_json AS (
SELECT
customer,
partgroup,
STRING_AGG(json_piece, ',') AS json_block
FROM serialized_flags
WHERE flag IN ('mrs', 'mrq', 'lvs', 'lvq')
GROUP BY customer, partgroup
)
--SELECT * FROM flag_json
-- Step 3.4: Nest dss/dsq under each dataseg
,seg_pieces AS (
SELECT
customer,
partgroup,
dataseg,
STRING_AGG(json_piece, ',') AS inner_json
FROM serialized_flags
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
customer,
partgroup,
CONCAT(
'"', dataseg, '": {', inner_json, '}'
) AS json_piece
FROM seg_pieces
)
-- Step 3.6: Aggregate all dataseg entries into one JSON block per customer/partgroup
,seg_json AS (
SELECT
customer,
partgroup,
STRING_AGG(json_piece, ',') AS json_block
FROM wrapped_segs
GROUP BY customer, partgroup
)
--SELECT * FROM seg_json
--------------------------------------------------------------------------------
-- Stage 4: Merge flags and segment blocks into a single JSON object
-- Write final pricing history to pricing.lastpricedetail
--------------------------------------------------------------------------------
INSERT INTO
pricing.lastpricedetail
SELECT
COALESCE(f.customer, s.customer) AS customer,
COALESCE(f.partgroup, s.partgroup) AS partgroup,
CONCAT(
'{',
COALESCE(f.json_block, ''),
CASE
WHEN f.json_block IS NOT NULL AND s.json_block IS NOT NULL THEN ','
ELSE ''
END,
COALESCE(s.json_block, ''),
'}'
) AS part_stats
FROM flag_json f
FULL OUTER JOIN seg_json s
ON f.customer = s.customer AND f.partgroup = s.partgroup;