Question

我有以下查询按日期对“打开销售报价”记录进行分组，并且我添加了一些CASE表达式以将总公开报价金额分成4个附加列：

SELECT 
    DATE(quotes.created_at) AS date, 
    COUNT(DISTINCT quotes.entity_id) AS quote_open, 
    SUM(quote_items.row_total) AS quote_open_mrc, 
    CASE WHEN quotes.percentage_to_close >= 0 < 50 THEN COUNT(DISTINCT quotes.entity_id) END AS quote_open_50, 
    CASE WHEN quotes.percentage_to_close >= 50 < 75 THEN COUNT(DISTINCT quotes.entity_id) END AS quote_open_5075, 
    CASE WHEN quotes.percentage_to_close >= 75 THEN COUNT(DISTINCT quotes.entity_id) END AS quote_open_75,
    CASE WHEN quotes.percentage_to_close IS NULL THEN COUNT(DISTINCT quotes.entity_id) END AS quote_open_noclose

FROM `sales_quote_item` AS `quote_items`

INNER JOIN `sales_quote` AS `quotes` 
    ON quotes.entity_id = quote_items.quote_id 

WHERE (quote_items.sku like '05-%') 
    AND (quotes.is_quotation = 1) 
    AND (quotes.quote_status NOT IN ('won', 'lost', 'expired')) 
    AND (quotes.quote_type = 'prod_serv_base_rec') 

GROUP BY 
    `date`
;

但这并没有返回正确的结果：

+------------+------------+----------------+---------------+-----------------+---------------+--------------------+
| date       | quote_open | quote_open_mrc | quote_open_50 | quote_open_5075 | quote_open_75 | quote_open_noclose |
+------------+------------+----------------+---------------+-----------------+---------------+--------------------+
| 2014-09-25 |          2 |       209.9000 |             2 |               2 |          NULL |               NULL |
| 2014-09-29 |          1 |        95.4300 |             1 |               1 |          NULL |               NULL |
| 2014-09-30 |          5 |       943.4500 |             5 |               5 |          NULL |               NULL |
| 2014-10-02 |          1 |        70.9700 |             1 |               1 |          NULL |               NULL |
| 2014-10-03 |          1 |       105.8300 |             1 |               1 |          NULL |               NULL |
| 2014-10-06 |          1 |       197.3800 |             1 |               1 |          NULL |               NULL |
| 2014-10-07 |          2 |      1430.1800 |             2 |               2 |          NULL |               NULL |
| 2014-10-08 |          4 |      1185.5100 |             4 |               4 |          NULL |               NULL |
| 2014-10-09 |          1 |        57.4800 |             1 |               1 |          NULL |               NULL |
| 2014-10-13 |          1 |        73.1000 |             1 |               1 |          NULL |               NULL |
| 2014-10-14 |          2 |       326.6800 |             2 |               2 |             2 |               NULL |
| 2014-10-15 |          2 |      1294.8300 |             2 |               2 |          NULL |               NULL |
+------------+------------+----------------+---------------+-----------------+---------------+--------------------+

我不确定如何正确使用CASE，但实际上我想要的是在同一结果集中看到quote_open跨差异“桶”的传播。因此，4个存储桶列应在每条记录上加起来quote_open。

Answer 1

您的CASE WHEN语法错误。尝试：

   COUNT(DISTINCT CASE 
                    WHEN quotes.percentage_to_close >= 0 
                         AND quotes.percentage_to_close < 50 
                    THEN quotes.entity_id 
                  END) AS quote_open_50, 
   COUNT(DISTINCT CASE 
                    WHEN quotes.percentage_to_close >= 0 
                         AND quotes.percentage_to_close < 50 
                    THEN quotes.entity_id 
                  END) AS quote_open_50, 
   COUNT(DISTINCT CASE 
                    WHEN quotes.percentage_to_close >= 50 
                         AND quotes.percentage_to_close < 75 
                    THEN quotes.entity_id 
                  END) AS quote_open_5075, 
   COUNT(DISTINCT CASE 
                    WHEN quotes.percentage_to_close >= 75 
                    THEN quotes.entity_id 
                  END) AS quote_open_75, 
   COUNT(DISTINCT CASE 
                    WHEN quotes.percentage_to_close IS NULL 
                    THEN quotes.entity_id 
                  END) AS quote_open_noclose

请参阅this simplified fiddle。

Answer 2

你的逻辑写得不好：

CASE WHEN quotes.percentage_to_close >= 0 < 50

这将被解析为更像

CASE WHEN quotes.percentage_to_close >= (0 < 50)
CASE WHEN quotes.percentage_to_close >= (true)
CASE WHEN quotes.percentage_to_close >= 1

你不能写这样的多重比较，尝试更像

的东西

CASE WHEN (a >= 0) AND (a <= 50)

代替。

使用MySQL CASE表达式进行聚合

2 个答案: