Question

我试图回答一个问题here，我需要根据前3个月的实际情况或预测来计算销售预测。

Month   Actuals Forecast  
1       10    
2       15    
3       17    
4                14.00 
5                15.33  
6                15.44 
7                14.93

Month 4 = (10+15+17)/3 
Month 5 = (15+17+14)/3 
Month 6 = (17+14+15.33)/3
Month 7 = (14+15.33+15.44)/3

我一直试图使用递归CTE来做到这一点：

;WITH cte([month],forecast) AS (
    SELECT 1,CAST(10 AS DECIMAL(28,2))
    UNION ALL
    SELECT 2,CAST(15 AS DECIMAL(28,2))
    UNION ALL 
    SELECT 3,CAST(17 AS DECIMAL(28,2))
    UNION ALL
    SELECT
        [month]=[month]+1,
        forecast=CAST(AVG(forecast) OVER (ORDER BY [month] ROWS BETWEEN 3 PRECEDING AND 1 PRECEDING) AS DECIMAL(28,2))
    FROM
        cte
    WHERE
        [month]<=12
)
SELECT * FROM cte WHERE month<=12;

小提琴：http://sqlfiddle.com/#!6/9ac4a/3

但它没有按预期工作，因为它返回以下结果：

| month | forecast |
|-------|----------|
|     1 |       10 |
|     2 |       15 |
|     3 |       17 |
|     4 |   (null) |
|     5 |   (null) |
|     6 |   (null) |
|     7 |   (null) |
|     8 |   (null) |
|     9 |   (null) |
|    10 |   (null) |
|    11 |   (null) |
|    12 |   (null) |
|     3 |   (null) |
|     4 |   (null) |
|     5 |   (null) |
|     6 |   (null) |
|     7 |   (null) |
|     8 |   (null) |
|     9 |   (null) |
|    10 |   (null) |
|    11 |   (null) |
|    12 |   (null) |
|     2 |   (null) |
|     3 |   (null) |
|     4 |   (null) |
|     5 |   (null) |
|     6 |   (null) |
|     7 |   (null) |
|     8 |   (null) |
|     9 |   (null) |
|    10 |   (null) |
|    11 |   (null) |
|    12 |   (null) |

预期产出：

| month | forecast |
|-------|----------|
|     1 |       10 |
|     2 |       15 |
|     3 |       17 |
|     4 |    14.00 |
|     5 |    15.33 |
|     6 |    15.44 |
|     7 |    14.93 |
|     8 |    15.23 |
|     9 |    15.20 |
|    10 |    15.12 |
|    11 |    15.18 |
|    12 |    15.17 |

有人可以告诉我这个查询有什么问题吗？

Answer 1

我建议这样的事情：

WITH T AS
(
    SELECT 1 AS [month], CAST(10 AS DECIMAL(28,2)) AS [forecast], CAST(-5 AS DECIMAL(28,2)) AS three_months_ago_forecast, CAST(9 AS decimal(28,2)) AS two_months_ago_forecast, CAST(26 AS decimal(28,2)) as one_month_ago_forecast
    UNION ALL
    SELECT 2,CAST(15 AS DECIMAL(28,2)), CAST(9 AS decimal(28,2)), CAST(26 AS decimal(28,2)), CAST(10 AS DECIMAL(28,2))
    UNION ALL 
    SELECT 3,CAST(17 AS DECIMAL(28,2)), CAST(26 AS decimal(28,2)), CAST(10 AS DECIMAL(28,2)), CAST(15 AS DECIMAL(28,2))
),
LT AS -- LastForecast
(
    SELECT *
    FROM T
    WHERE [month] = 3
),
FF AS -- Future Forecast
(
    SELECT *
    FROM LT

    UNION ALL

    SELECT 
        FF.[month] + 1 AS [month], 
        CAST( (FF.forecast * 4 - FF.three_months_ago_forecast) / 3 AS decimal(28,2)) AS forecast,
        FF.two_months_ago_forecast as three_months_ago_forecast,
        FF.one_month_ago_forecast as two_months_ago_forecast,
        FF.forecast as one_month_ago_forecast
    FROM FF
    WHERE
        FF.[month] < 12

)
SELECT * FROM T
WHERE [month] < 3
UNION ALL
SELECT * FROM FF

输出：

+-------+----------+---------------------------+-------------------------+------------------------+
| month | forecast | three_months_ago_forecast | two_months_ago_forecast | one_month_ago_forecast |
+-------+----------+---------------------------+-------------------------+------------------------+
|     1 | 10.00    | -5.00                     | 9.00                    | 26.00                  |
|     2 | 15.00    | 9.00                      | 26.00                   | 10.00                  |
|     3 | 17.00    | 26.00                     | 10.00                   | 15.00                  |
|     4 | 14.00    | 10.00                     | 15.00                   | 17.00                  |
|     5 | 15.33    | 15.00                     | 17.00                   | 14.00                  |
|     6 | 15.44    | 17.00                     | 14.00                   | 15.33                  |
|     7 | 14.92    | 14.00                     | 15.33                   | 15.44                  |
|     8 | 15.23    | 15.33                     | 15.44                   | 14.92                  |
|     9 | 15.20    | 15.44                     | 14.92                   | 15.23                  |
|    10 | 15.12    | 14.92                     | 15.23                   | 15.20                  |
|    11 | 15.19    | 15.23                     | 15.20                   | 15.12                  |
|    12 | 15.18    | 15.20                     | 15.12                   | 15.19                  |
+-------+----------+---------------------------+-------------------------+------------------------+

Answer 2

试试这个

WITH cte
     AS (SELECT *
         FROM   (VALUES (1,10,NULL),
                        (2,15,NULL),
                        (3,17,NULL),
                        (4,NULL,14.00),
                        (5,NULL,15.33),
                        (6,NULL,15.44),
                        (7,NULL,14.93)) tc (month, act, fore))
SELECT mon,avg(res) 
FROM   cte a
       CROSS apply (SELECT TOP 3 ( COALESCE(a.act, a.fore) ) AS res,
                                 b.month                     AS mon
                    FROM   cte b
                    WHERE  a.month < b.month
                    ORDER  BY a.month DESC) cs
GROUP  BY mon
ORDER  BY mon

或Sql Server 2012+使用此

SELECT
    [month]=[month]+1,
    forecast=CAST(AVG(COALESCE(act,fore)) OVER (ORDER BY [month] ROWS BETWEEN 3 PRECEDING  AND CURRENT row  ) AS DECIMAL(28,2))
FROM
    cte

使用递归CTE计算预测平均值

2 个答案: