使用可选列匹配连接2个表

Question

一直在做一些MySQL的东西，发现一个棘手的情况需要解决。

这是2个MySQL表

import numpy as np 
from sklearn import preprocessing 
input_data = np.array([[5.1, -2.9, 3.3], 
                       [-1.2, 7.8, -6.1], 
                       [3.9, 0.4, 2.1], 
                       [7.3, -9.9, -4.5]]) 
# Binarize data  
data_binarized = preprocessing.Binarizer(threshold=2.1).transform(input_data) 
print("\nBinarized data:\n", data_binarized) 

我正在尝试查找与Table1: user_fav fav_id | brand_id | Keyword 1 | 0 | test 2 | 67 | test1 3 | 68 | Table 2: products p_id | p_brand | p_name 1 | 67 | test1 shoes 2 | 68 | test shoes 表匹配的产品数量，如下所示：

• 如果user_fav为0，则将brand_id与keyword
匹配
• 如果p_name＆gt; 0和brand_id然后在两个条件下加入
• 如果keyword != ''＆gt; 0和brand_id然后加入keyword == ''

总的来说，我需要查找与brand_id and p_brand行匹配的产品数量。

尝试过此查询，但确实只包含一个条件：

user_fav

有任何解决此问题的建议吗？

谢谢！

Answer 1

<强> SQL DEMO

SELECT u.*, count(p.p_id) as pcount
FROM user_fav u
JOIN products p
  ON ( u.`brand_id` = 0 and p.`p_name` Like CONCAT('%',  u.`Keyword`, '%'))
  OR ( u.`Keyword` = '' and u.`brand_id` = p.`p_brand`)  
  OR (  u.`brand_id` > 0 and u.`Keyword` <> '' and 
        ( u.`brand_id` = p.`p_brand` AND p.`p_name` Like CONCAT('%',  u.`Keyword`, '%'))
      ) group by u.fav_id

<强>输出

| fav_id | brand_id | Keyword | pcount |
|--------|----------|---------|--------|
|      1 |        0 |    test |      2 |
|      2 |       67 |   test1 |      1 |
|      3 |       68 |         |      1 |

Answer 2

您的加入条件并非一对一，因此您可以对条件进行分组，因为每个规则集都不包含下一个规则集。

select 
    `uf`.`fav_id`, 
    count(`p`.`p_id`) AS `pcount` 
from 
    `user_fav` `uf` 
left join 
    `products` `p` 
    ON (
       `uf`.`brand_id` = 0
       AND `uf`.`Keyword` = `p`.`p_name`
    )
    OR (
        `uf`.`brand_id` > 0
       AND `uf`.`Keyword` != ''
       AND `uf`.`Keyword` = `p`.`p_name`
       AND `uf`.`brand_id` = `p`.`p_id`
    )
    OR (
        `uf`.`brand_id` > 0
       AND `uf`.`Keyword` = ''
       AND `uf`.`brand_id` = `p`.`p_id`
    )
group by `uf`.`fav_id`