标签：区间 date 示例 from group by 关键字 strong es2017 src
示例表A:
| author_id | author_name |
| 1 | Kimmy |
| 2 | Abel |
| 3 | Bill |
| 4 | Berton |
示例表B:
| book_id | author_id | start_date | end_date |
| 9 | 1 | 2017-09-25 21:16:04 | 2017-09-25 21:16:06 |
| 10 | 3 | ||
| 11 | 2 | 2017-09-25 21:21:46 | 2017-09-25 21:21:47 |
| 12 | 1 | ||
| 13 | 8 |
示例表C:
| order_id | book_id | price | order_date |
| 1 | 9 | 0.2 | 2017-09-24 21:21:46 |
| 2 | 9 | 0.6 | 2017-09-25 21:16:04 |
| 3 | 11 | 0.1 | 2017-09-25 21:21:46 |
在以上表中执行AB表关联
SELECT `authors`.*, `books`.book_id FROM `authors` LEFT JOIN `books` ON `authors`.author_id = `books`.author_id
结果
| author_id | author_name | book_id |
| 1 | Kimmy | 9 |
| 3 | Bill | 10 |
| 2 | Abel | 11 |
| 1 | Kimmy | 12 |
| 4 | Berton |
结果出现了2条author_id为1的记录，因为右表中存在了两条关联author_id=1的行
右边出现N条关联左边的记录，结果就会相应出现N条关联了右表出现的记录
在以上表中执行ABC表关联
SELECT `authors`.*, `books`.book_id, `orders`.order_id, `orders`.price FROM `authors` LEFT JOIN `books` ON `authors`.author_id = `books`.author_id LEFT JOIN `orders` ON `books`.book_id = `orders`.book_id
结果
| author_id | author_name | book_id | order_id | order_price |
| 1 | Kimmy | 9 | 1 | 0.2 |
| 1 | Kimmy | 9 | 2 | 0.6 |
| 2 | Abel | 11 | 3 | 0.1 |
| 3 | Bill | 10 | ||
| 1 | Kimmy | 12 | ||
| 4 | Berton |
结果出现了3条author_id=1的记录，因为authors第一次关联了books表book_id为9和12的book关联了author_id为1的作者，而book_id为9的书本则关联了两个orders记录，所以结果集包含3条author_id为1的记录
可以运用
count(),sum()
等函数通过
group by
来统计结果
SELECT `authors`.*, sum(`orders`.price) FROM `authors` LEFT JOIN `books` ON `authors`.author_id = `books`.author_id LEFT JOIN `orders` ON `books`.book_id = `orders`.book_id GROUP BY `books`.book_id
结果集会基于book_id来统计每一本书的订单总额
| author_id | author_name | book_id | sum(order_price) |
| 4 | Berton | ||
| 1 | Kimmy | 9 | 0.80 |
| 3 | Bill | 10 | |
| 2 | Abel | 11 | 0.10 |
| 1 | Kimmy | 12 |
book_id为9的订单总额为0.80，并且9的记录从多条合并为1条
运用
having
对那些WHERE 关键字无法与合计函数一起使用进行一些筛选查询
SELECT `authors`.*, `books`.book_id, sum(`orders`.price)AS prices FROM `authors` LEFT JOIN `books` ON `authors`.author_id = `books`.author_id LEFT JOIN `orders` ON `books`.book_id = `orders`.book_id GROUP BY `books`.book_id HAVING prices > 0.1
这时只有sum为0.8的结果被选中
| author_id | author_name | book_id | sum(order_price) |
| 1 | Kimmy | 9 | 0.80 |
对于组合其他语法查询，也是没问题的
SELECT `authors`.*, `books`.book_id, sum(`orders`.price)AS prices FROM `authors` LEFT JOIN `books` ON `authors`.author_id = `books`.author_id LEFT JOIN `orders` ON `books`.book_id = `orders`.book_id GROUP BY `books`.book_id HAVING prices >= 0.1 ORDER BY prices asc LIMIT 1,1
多条件join
SELECT `authors`.*, `books`.book_id, `orders`.order_id, sum(`orders`.price) FROM `authors` LEFT JOIN `books` ON `authors`.author_id = `books`.author_id LEFT JOIN `orders` ON `books`.book_id = `orders`.book_id AND `orders`.order_date >= `books`.start_date AND `orders`.order_date <= `books`.end_date GROUP BY `books`.book_id
选取在一定时间区间范围内的order订单，可以看到订单order_id为1的订单不再纳入book_id为9的统计当中，因为它的时间区间不符合join条件
| author_id | author_name | book_id | order_id | sum(`order`.price) |
| 4 | Berton | |||
| 1 | Kimmy | 9 | 2 | 0.60 |
| 3 | Bill | 10 | ||
| 2 | Abel | 11 | 3 | 0.10 |
| 1 | Kimmy | 12 |
标签：区间 date 示例 from group by 关键字 strong es2017 src
原文地址：http://www.cnblogs.com/yiyide266/p/7594058.html
