在FIFO SQL中计算出价格

Question

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>

在插入带有amount_taken的行之前，我需要计算14个项目中每个项目的平均价格是135,71 ，在这种情况下为135,71 ，但是如何计算这种相对有效的呢？

我最初的想法是将行委托到两个临时表中，一个临时表中的amount_taken为空，另一个临时表中的非空，然后向下计算所有行，但是看到此表可能会变得相当大，相当快（因为大多数在这种情况下，从库存中只会拿出一件商品），我担心这在短期内将是一个不错的解决方案，但是随着表格的变大，它会放慢速度。 那么，什么是更好的互联网解决方案？

Answer 1

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')
    ;

然后是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 |

---

1. tneg包含有关已售数量的信息

    | 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 | 

2. 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 | 

3. 我们将tneg中的行与tneg中的行进行tpos ，条件是cum_sold在qty_bought和prev_bought之间。 cum_sold是累计卖出金额， qty_bought是累计金额买的， prev_bought是以前的值qty_bought 。

    | 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 | 

4. 分数

    ((tneg.cum_sold - tpos.prev_bought)/(tpos.qty_bought - tpos.prev_bought)) as frac 

   度量cum_sold在qty_bought和prev_bought之间的prev_bought 。 我们使用此分数来计算cum_sold_cost ，这是与购买cum_sold项目相关的累计成本。 cum_sold_cost在于frac之间的距离prev_total_cost和total_cost 。

5. 一旦获得cum_sold_cost ，您便拥有了计算边际FIFO单价所需的一切。 对于每一行tneg ，之间的差cum_sold_cost和其之前的值是成本qty_sold 。 FIFO价格只是该成本与qty_sold之比。