|
mysql> select * from t_order;
+---------+-----+-------+--------+---------------------+------+
| orderid | uid | uname | amount | time | year |
+---------+-----+-------+--------+---------------------+------+
| 20 | 1 | brand | 91.23 | 2018-08-20 17:22:21 | 2018 |
| 21 | 1 | brand | 87.54 | 2019-07-16 09:21:30 | 2019 |
| 22 | 1 | brand | 166.88 | 2019-04-04 12:23:55 | 2019 |
| 23 | 2 | helyn | 93.73 | 2019-09-15 10:11:11 | 2019 |
| 24 | 2 | helyn | 102.32 | 2019-01-08 17:33:25 | 2019 |
| 25 | 2 | helyn | 106.06 | 2019-12-24 12:25:25 | 2019 |
| 26 | 2 | helyn | 73.42 | 2020-04-03 17:16:23 | 2020 |
| 27 | 3 | sol | 55.55 | 2019-08-05 19:16:23 | 2019 |
| 28 | 3 | sol | 69.96 | 2020-09-16 19:23:16 | 2020 |
| 29 | 4 | weng | 199.99 | 2020-06-08 19:55:06 | 2020 |
+---------+-----+-------+--------+---------------------+------+
10 rows in set
单字段分组
即对付某个字段举办分组，好比针对用户举办分组，输出他们的用户Id，订单数目和总额：
mysql> select uid,count(uid),sum(amount) from t_order group by uid;
+-----+------------+-------------+
| uid | count(uid) | sum(amount) |
+-----+------------+-------------+
| 1 | 3 | 345.65 |
| 2 | 4 | 375.53 |
| 3 | 2 | 125.51 |
| 4 | 1 | 199.99 |
+-----+------------+-------------+
4 rows in set
多字段分组
即对付多个字段举办分组，好比针对用户举办分组，再对他们差异年份的订单数据举办分组，输出订单数目和斲丧总额：
mysql> select uid,count(uid) as nums,sum(amount) as totalamount,year from t_order group by uid,year;
+-----+------+-------------+------+
| uid | nums | totalamount | year |
+-----+------+-------------+------+
| 1 | 1 | 91.23 | 2018 |
| 1 | 2 | 254.42 | 2019 |
| 2 | 3 | 302.11 | 2019 |
| 2 | 1 | 73.42 | 2020 |
| 3 | 1 | 55.55 | 2019 |
| 3 | 1 | 69.96 | 2020 |
| 4 | 1 | 199.99 | 2020 |
+-----+------+-------------+------+
7 rows in set
分组前的前提过滤：where
这个很简朴，就是再分组（group by）之前通过where要害字举办前提过滤，取出我们必要的数据，假设我们只要列出2019年8月之后的数据，源数据只有6条及格的，有两条年份一样被分组的：
mysql> select uid,count(uid) as nums,sum(amount) as totalamount,year from t_order where time > '2019-08-01' group by uid,year;
+-----+------+-------------+------+
| uid | nums | totalamount | year |
+-----+------+-------------+------+
| 2 | 2 | 199.79 | 2019 |
| 2 | 1 | 73.42 | 2020 |
| 3 | 1 | 55.55 | 2019 |
| 3 | 1 | 69.96 | 2020 |
| 4 | 1 | 199.99 | 2020 |
+-----+------+-------------+------+
5 rows in set
分组后的前提过滤：having
偶然辰我们必要再分组之后再对数据举办过滤，这时辰就必要行使having要害字举办数据过滤，再上述前提下，我们必要取出斲丧次数高出一次的数据：
mysql> select uid,count(uid) as nums,sum(amount) as totalamount,year from t_order where time > '2019-08-01' group by uid,year having nums>1;
+-----+------+-------------+------+
| uid | nums | totalamount | year |
+-----+------+-------------+------+
| 2 | 2 | 199.79 | 2019 |
+-----+------+-------------+------+
1 row in set
这边必要留意区分where和having：
where是在分组（聚合）前对记录举办筛选，而having是在分组竣事后的功效里筛选，最后返回过滤后的功效。
可以把having领略为两级查询，即含having的查询操纵先得到不含having子句时的sql查询功效表，然后在这个功效表上行使having前提筛选出切合的记录，最后返回这些记录，因此，having后是可以跟聚合函数的，而且这个聚积函数不必与select后头的聚积函数沟通。
分组后的排序处理赏罚
order前提接在group by后头，也就是统计出每个用户的斲丧总额和斲丧次数后，对用户的斲丧总额举办降序排序的进程。
mysql> select uid,count(uid) as nums,sum(amount) as totalamount from t_order group by uid;
+-----+------+-------------+
| uid | nums | totalamount |
+-----+------+-------------+
| 1 | 3 | 345.65 |
| 2 | 4 | 375.53 |
| 3 | 2 | 125.51 |
| 4 | 1 | 199.99 |
+-----+------+-------------+
4 rows in set （编辑：湖南网）
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