使用Postgres 11
使用FIFO,我想计算从库存中取出的物品的价格,以跟踪总库存的价值。
数据集如下:
ID | prodno | amount_purchased | amount_taken | price | created_at
uuid 13976 10 NULL 130 <timestamp>
uuid 13976 10 NULL 150 <timestamp>
uuid 13976 10 NULL 110 <timestamp>
uuid 13976 10 NULL 100 <timestamp>
uuid 13976 NULL 14 ?? <timestamp>
在使用amount_taken
插入行之前,我需要计算14个项目中每个项目的平均价格,在这种情况下是135,71
,但如何计算这个相对有效?
我最初的想法是将行委托给两个临时表,一个是amount_taken为null,另一个是非空的,然后计算所有行,但看到这个表可能变得相当大,相当快(因为大多数当时,只有1个项目将从库存中获取),我担心这在短期内会是一个不错的解决方案,但会随着表格变大而放慢速度。那么,什么是互联网更好的解决方案?
鉴于此设置:
CREATE TABLE test (
id int
, prodno int
, quantity numeric
, price numeric
, created_at timestamp
);
INSERT INTO test VALUES
(1, 13976, 10, 130, NOW())
, (2, 13976, 10, 150, NOW()+'1 hours')
, (3, 13976, 10, 110, NOW()+'2 hours')
, (4, 13976, 10, 100, NOW()+'3 hours')
, (5, 13976, -14, NULL, NOW()+'4 hours')
, (6, 13976, -1, NULL, NOW()+'5 hours')
, (7, 13976, -10, NULL, NOW()+'6 hours')
;
那么SQL
SELECT id, prodno, created_at, qty_sold
-- 5
, round((cum_sold_cost - coalesce(lag(cum_sold_cost) over w, 0))/qty_sold, 2) as fifo_price
, qty_bought, prev_bought, total_cost
, prev_total_cost
, cum_sold_cost
, coalesce(lag(cum_sold_cost) over w, 0) as prev_cum_sold_cost
FROM (
SELECT id, tneg.prodno, created_at, qty_sold, tpos.qty_bought, prev_bought, total_cost, prev_total_cost
-- 4
, round(prev_total_cost + ((tneg.cum_sold - tpos.prev_bought)/(tpos.qty_bought - tpos.prev_bought))*(total_cost-prev_total_cost), 2) as cum_sold_cost
FROM (
SELECT id, prodno, created_at, -quantity as qty_sold
, sum(-quantity) over w as cum_sold
FROM test
WHERE quantity < 0
WINDOW w AS (PARTITION BY prodno ORDER BY created_at)
-- 1
) tneg
LEFT JOIN (
SELECT prodno
, sum(quantity) over w as qty_bought
, coalesce(sum(quantity) over prevw, 0) as prev_bought
, quantity * price as cost
, sum(quantity * price) over w as total_cost
, coalesce(sum(quantity * price) over prevw, 0) as prev_total_cost
FROM test
WHERE quantity > 0
WINDOW w AS (PARTITION BY prodno ORDER BY created_at)
, prevw AS (PARTITION BY prodno ORDER BY created_at ROWS BETWEEN unbounded preceding AND 1 preceding)
-- 2
) tpos
-- 3
ON tneg.cum_sold BETWEEN tpos.prev_bought AND tpos.qty_bought
AND tneg.prodno = tpos.prodno
) t
WINDOW w AS (PARTITION BY prodno ORDER BY created_at)
产量
| id | prodno | created_at | qty_sold | fifo_price | qty_bought | prev_bought | total_cost | prev_total_cost | cum_sold_cost | prev_cum_sold_cost |
|----+--------+----------------------------+----------+------------+------------+-------------+------------+-----------------+---------------+--------------------|
| 5 | 13976 | 2019-03-07 21:07:13.267218 | 14 | 135.71 | 20 | 10 | 2800 | 1300 | 1900.00 | 0 |
| 6 | 13976 | 2019-03-07 22:07:13.267218 | 1 | 150.00 | 20 | 10 | 2800 | 1300 | 2050.00 | 1900.00 |
| 7 | 13976 | 2019-03-07 23:07:13.267218 | 10 | 130.00 | 30 | 20 | 3900 | 2800 | 3350.00 | 2050.00 |
tneg
包含有关销售数量的信息
| id | prodno | created_at | qty_sold | cum_sold |
|----+--------+----------------------------+----------+----------|
| 5 | 13976 | 2019-03-07 21:07:13.267218 | 14 | 14 |
| 6 | 13976 | 2019-03-07 22:07:13.267218 | 1 | 15 |
| 7 | 13976 | 2019-03-07 23:07:13.267218 | 10 | 25 |
tpos
包含有关购买数量的信息
| prodno | qty_bought | prev_bought | cost | total_cost | prev_total_cost |
|--------+------------+-------------+------+------------+-----------------|
| 13976 | 10 | 0 | 1300 | 1300 | 0 |
| 13976 | 20 | 10 | 1500 | 2800 | 1300 |
| 13976 | 30 | 20 | 1100 | 3900 | 2800 |
| 13976 | 40 | 30 | 1000 | 4900 | 3900 |
tneg
中的行与tpos
中的行匹配,条件是cum_sold
介于qty_bought
和prev_bought
之间。 cum_sold
是累计销售量,qty_bought
是购买的累计金额,prev_bought
是qty_bought
的先前值。
| id | prodno | created_at | qty_sold | cum_sold | qty_bought | prev_bought | total_cost | prev_total_cost | cum_sold_cost |
|----+--------+----------------------------+----------+----------+------------+-------------+------------+-----------------+---------------|
| 5 | 13976 | 2019-03-07 21:07:13.267218 | 14 | 14 | 20 | 10 | 2800 | 1300 | 1900.00 |
| 6 | 13976 | 2019-03-07 22:07:13.267218 | 1 | 15 | 20 | 10 | 2800 | 1300 | 2050.00 |
| 7 | 13976 | 2019-03-07 23:07:13.267218 | 10 | 25 | 30 | 20 | 3900 | 2800 | 3350.00 |
((tneg.cum_sold - tpos.prev_bought)/(tpos.qty_bought - tpos.prev_bought)) as frac
衡量cum_sold
和qty_bought
之间prev_bought
的位置。我们使用这个分数来计算cum_sold_cost
,这是与购买cum_sold
项目相关的累积成本。 cum_sold_cost
位于frac
和prev_total_cost
之间的total_cost
距离。cum_sold_cost
,您就拥有了计算边际FIFO单位价格所需的一切。对于tneg
的每一行,cum_sold_cost
与其先前值之间的差异是qty_sold
的成本。 FIFO价格只是这个成本与qty_sold
的比率。