SQLite中具有多个条件和列的AVG函数

Question

我想出了如何使用 condition/s 执行 avg 函数，但我无法让它满足我的特定需求。 假设我正在使用名为 sales_performance 的表

  product_ID  sales_period  sales_qty  sales_index  product_sub goal_met
         C12          0001         15           20          D71        Y
         D71          0001         07           09          C12        N
         F20          0001         25           30          C05        Y
         C05          0001         10           15          F20        N
         C12          0002         15           30          C05        Y
         C05          0002         12           06          C12        N
         D71          0002         30           20          F20        Y
         F20          0002         20           15          D71        N
         C12          0003         05           04          F20        N
         F20          0003         40           35          C12        Y
         D71          0003         20           20          C05        Y
         C05          0003         12           10          D71        N

我想为产品 C12 计算一个名为 sales_index_goal 的新值。那么，这个值的公式是：

产品'C12' 和Goal_Met = 'Y' 的sales_index 和sub_product 的sales_index 和Goal_Met = 'N' 在之前的销售期间的平均值。

例如，如果我想为 sales_period 0003 计算产品 'C12' 的 sales_index_goal，它将计算为：

(30,20,15) 的平均值，其中30 和20 是产品'C12' 在销售期间'C12' 的sales_indexes 1 和@9876543440@ 和@9876 @是产品'F20'在销售期间2的sales_index。

我在计算确切销售期间的这个值时没有任何问题。但是，我很难想出一个查询来计算所有销售期间产品'C12' 的此值。目前，我编写了这个不起作用的查询：

SELECT 
    s.*, 
    AVG(CASE 
        WHEN s2.goal_met = "Y" AND s2.product_id = "C2" 
            THEN s2.sales_index 
        WHEN s2.product_id = (
            SELECT s2.product_sub WHERE s2.product_id = "C12"
        ) AND s2.goals_met = "N" 
            THEN s2.sales_index
        ELSE NULL 
    END)
    OVER (
        ORDER BY s.sales_period 
        ROWS BETWEEN UNBOUNDED PRECEDING AND 1 PRECEDING
    ) AS sales_index_goal
FROM 
    sales_performance s, 
    sales_performance s2
WHERE s.product_id = "C12" 

我非常感谢您对此的任何帮助。奖励：为所有销售期间的所有产品计算此值。

编辑：以下答案适用于计算产品 C12 的 sales_index_goal 但是，它不适用于产品 F20（有关它不起作用的更详细原因在我在答案下方的评论中） 可以看到查询产品F20here的结果

Answer 1

使用窗口函数是一个很好的起点。一个问题在于，您希望对来自不同列的值进行平均，这可能具有不同的出现次数。

我认为您需要分解计算以计算平均值：将值相加，然后将其除以出现次数的总和。

考虑：

SELECT *
FROM (
    SELECT 
        s.*,
        (
            0.0 + 
            COALESCE(SUM(CASE WHEN goal_met = 'Y' THEN sales_index END) OVER(
                PARTITION BY product_id 
                ORDER BY sales_period 
                ROWS BETWEEN UNBOUNDED PRECEDING AND 1 PRECEDING
            ), 0)
            + COALESCE(SUM(CASE WHEN goal_met = 'N' THEN sales_index END) OVER(
                PARTITION BY product_sub 
                ORDER BY sales_period 
                ROWS BETWEEN UNBOUNDED PRECEDING AND 1 PRECEDING
            ), 0)
        ) / (
            COALESCE(SUM(goal_met = 'Y') OVER(
                PARTITION BY product_id 
                ORDER BY sales_period 
                ROWS BETWEEN UNBOUNDED PRECEDING AND 1 PRECEDING
            ), 0)
            + COALESCE(SUM(goal_met = 'N') OVER(
                PARTITION BY product_sub 
                ORDER BY sales_period 
                ROWS BETWEEN UNBOUNDED PRECEDING AND 1 PRECEDING
            ), 0)
        ) AS sales_index_goal
    FROM sales_performance s
) x WHERE product_ID = 'C12'

在 this DB fiddle 中，使用您的示例数据返回：

| product_ID | sales_period | sales_qty | sales_index | product_sub | goal_met | sales_index_goal   |
| ---------- | ------------ | --------- | ----------- | ----------- | -------- | ------------------ |
| C12        | 1            | 15        | 20          | D71         | Y        |                    |
| C12        | 2            | 15        | 30          | C05         | Y        | 20                 |
| C12        | 3            | 5         | 4           | F20         | N        | 21.666666666666668 |

Answer 2

不确定这是否真的需要窗口函数。

下面的示例只是按 C12 产品自链接表和组。

CREATE TABLE sales_performance
(
 product_ID varchar(3) not null,
 sales_period varchar(4) not null,
 sales_qty char(2) not null,
 sales_index char(2) not null,
 product_sub char(3) not null,
 goal_met char(1)  not null,
 PRIMARY KEY (product_ID, sales_period)
)

INSERT INTO sales_performance
(product_ID,sales_period,sales_qty,sales_index,product_sub,goal_met) 
VALUES
 ('C12','0001','15','20','D71','Y')
,('D71','0001','07','09','C12','N')
,('F20','0001','25','30','C05','Y')
,('C05','0001','10','15','F20','N')
,('C12','0002','15','30','C05','Y')
,('C05','0002','12','06','C12','N')
,('D71','0002','30','20','F20','Y')
,('F20','0002','20','15','D71','N')
,('C12','0003','05','04','F20','N')
,('F20','0003','40','35','C12','Y')
,('D71','0003','20','20','C05','Y')
,('C05','0003','12','10','D71','N')
;

SELECT c12.*, sub.sales_index
FROM sales_performance c12
LEFT JOIN sales_performance sub 
  ON sub.sales_period < c12.sales_period 
 AND 
 (
    (sub.product_ID = c12.product_sub AND sub.goal_met = 'N') OR
    (sub.product_ID = c12.product_ID AND sub.goal_met = 'Y')
 )
WHERE c12.product_id = 'C12'
ORDER BY c12.product_ID, c12.sales_period, sub.product_ID

产品ID |销售期 |销售数量 |销售指数 |产品_sub |目标满足 |销售指数 :--------- | :----------- | :-------- | :------------ | :------------ | :------- | :---------- C12 | 0001 | 15 | 20 | D71 |是 | 空 C12 | 0002 | 15 | 30 | C05 |是 | 15 C12 | 0002 | 15 | 30 | C05 |是 | 20 C12 | 0003 | 05 | 04 | F20 | N | 20 C12 | 0003 | 05 | 04 | F20 | N | 30 C12 | 0003 | 05 | 04 | F20 | N | 15

SELECT 
 c12.*
 , ROUND(AVG(sub.sales_index),1) AS sales_index_goal
FROM sales_performance c12
LEFT JOIN sales_performance sub 
  ON sub.sales_period < c12.sales_period 
 AND 
 (
    (sub.product_ID = c12.product_sub AND sub.goal_met = 'N') OR
    (sub.product_ID = c12.product_ID AND sub.goal_met = 'Y')
 )
WHERE c12.product_id = 'C12' 
GROUP BY c12.product_ID, c12.sales_period
ORDER BY c12.product_ID, c12.sales_period;

产品ID |销售期 |销售数量 |销售指数 |产品_sub |目标满足 | sales_index_goal :--------- | :----------- | :-------- | :------------ | :------------ | :------- | :--------------- C12 | 0001 | 15 | 20 | D71 |是 | 空 C12 | 0002 | 15 | 30 | C05 |是 | 17.5 C12 | 0003 | 05 | 04 | F20 | N | 21.7

db小提琴here