Calculating Cost of Sales in SQL using FIFO method - sql

Question

From a stock transaction table I've created following sorted view table to be ready for FIFO:
rowN
date_
stockCode
sign_
amount
unitPrice
1
'2022-01-20'
ABC
in
5
29.20
2
'2022-01-22'
ABC
in
3
32.50
3
'2022-01-23'
ABC
out
7
40.00
4
'2022-01-23'
ABC
out
1
42.00
5
'2022-01-01'
XYZ
in
3
20.50
6
'2022-01-03'
XYZ
out
3
25.00
and I want to create a select query which looks like the previous table with only "out" rows and added cost_of_sales columns which is FIFO cost of that sale. But my knowledge of SQL is limited by just joins and sum over partitions.
The resulting table in my mind should look like this:
rowN
date_
stockCode
sign_
amount
unitPrice
cost_of_sales_uP
cost_of_sales
3
'2022-01-23'
ABC
out
7
40.00
30.1428
211.00
4
'2022-01-23'
ABC
out
1
42.00
32.50
32.50
6
'2022-01-03'
XYZ
out
3
25.00
20.50
61.50
I have no idea how to achieve this. Any help and guidance is appreciated. Result table doesn't have to be exactly like that but the main idea is there.
Thanks!

Answer 1

The following method might not be the fastest.
But it gets the job done.
First the incoming are unfolded into a temp table.
Then, by looping over the outgoing, each incoming unit is assigned to an outgoing on a First-In-First-Out basis.
The final query then uses the results of the temp table to calculate the total & average of the incoming.
IF OBJECT_ID('tempdb..#tmpStock') IS NOT NULL DROP TABLE #tmpStock;
CREATE TABLE #tmpStock (
id int identity primary key,
code varchar(30),
date_in date,
rowN int,
unitPrice decimal(10,2),
rowN_out int
);
--
-- Using a recursive CTE to unfold the incoming for the temp table
--
with RCTE as (
select stockCode, date_, rowN, amount, unitPrice
, 1 as lvl
from stock_transactions
where sign_ = 'in'
union all
select stockCode, date_, rowN, amount, unitPrice
, lvl + 1
from RCTE
where lvl < amount
)
insert into #tmpStock (code, date_in, rowN, unitPrice)
select stockCode, date_, rowN, unitPrice
from RCTE
order by stockCode, date_, rowN
option (maxrecursion 0);
DECLARE #IdOut INT = 1;
DECLARE #RowsOut INT = 0;
DECLARE #code VARCHAR(30);
DECLARE #amount SMALLINT;
DECLARE #date DATE;
DECLARE #rowN INT;
DECLARE #StockOut TABLE (
id int identity primary key,
code varchar(30),
date_out date,
rowN int,
amount smallint
);
insert into #StockOut (code, date_out, rowN, amount)
select stockCode, date_, rowN, amount
from stock_transactions
where sign_ = 'out'
order by stockCode, date_, rowN;
SELECT #RowsOut = COUNT(*) FROM #StockOut;
WHILE #IdOut <= #RowsOut
BEGIN
SELECT
#code = code
, #amount = amount
, #date = date_out
, #rowN = rowN
FROM #StockOut
WHERE id = #IdOut;
;WITH cte_in as (
select *
, rn = row_number() over (order by date_in, rowN)
from #tmpStock
where code = #code
and date_in <= #date
and rowN_out is null
)
UPDATE cte_in
SET rowN_out = #rowN
WHERE rn <= #amount;
SET #IdOut = #IdOut + 1;
END;
select * from #tmpStock
id | code | date_in | rowN | unitPrice | rowN_out
-: | :--- | :--------- | ---: | --------: | -------:
1 | ABC | 2022-01-20 | 1 | 29.20 | 3
2 | ABC | 2022-01-20 | 1 | 29.20 | 3
3 | ABC | 2022-01-20 | 1 | 29.20 | 3
4 | ABC | 2022-01-20 | 1 | 29.20 | 3
5 | ABC | 2022-01-20 | 1 | 29.20 | 3
6 | ABC | 2022-01-22 | 2 | 32.50 | 3
7 | ABC | 2022-01-22 | 2 | 32.50 | 3
8 | ABC | 2022-01-22 | 2 | 32.50 | 4
9 | XYZ | 2022-01-01 | 5 | 20.50 | 6
10 | XYZ | 2022-01-01 | 5 | 20.50 | 6
11 | XYZ | 2022-01-01 | 5 | 20.50 | 6
SELECT o.*
, CAST(i.AveragePriceIn AS DECIMAL(10,2)) AS cost_of_sales_uP
, i.TotalPriceIn AS cost_of_sales
FROM stock_transactions o
LEFT JOIN (
SELECT rowN_out
, AVG(unitPrice) as AveragePriceIn
, SUM(unitPrice) as TotalPriceIn
FROM #tmpStock
GROUP BY rowN_out
) i on i.rowN_out = o.rowN
WHERE o.sign_ = 'out'
ORDER BY o.rowN;
rowN | date_ | stockCode | sign_ | amount | unitPrice | cost_of_sales_uP | cost_of_sales
---: | :--------- | :-------- | :---- | -----: | --------: | ---------------: | ------------:
3 | 2022-01-23 | ABC | out | 7 | 40.00 | 30.14 | 211.00
4 | 2022-01-23 | ABC | out | 1 | 42.00 | 32.50 | 32.50
6 | 2022-01-03 | XYZ | out | 3 | 25.00 | 20.50 | 61.50
Demo on db<>fiddle here