如何将列相乘,然后将具有类似记录(例如客户名称)的行相加?

mysqlmysqli database

为了理解这一点,让我们创建一个包含 ID、客户名称、商品、价格等字段的表。我们首先将商品与价格相乘。之后,将添加具有类似记录(即相同的客户名称)的行。

首先我们创建一个表:

mysql> create table DemoTable
(
   CustomerId int NOT NULL AUTO_INCREMENT PRIMARY KEY,
   CustomerName varchar(100),
   CustomerItems int,
   CustomerPrice int
);
Query OK, 0 rows affected (0.54 sec)

下面是使用 insert 命令在表中插入一些记录的查询:

mysql> insert into DemoTable(CustomerName,CustomerItems,CustomerPrice)values('Larry',3,450);
Query OK, 1 row affected (0.24 sec)
mysql> insert into DemoTable(CustomerName,CustomerItems,CustomerPrice)values('Mike',2,550);
Query OK, 1 row affected (0.42 sec)
mysql> insert into DemoTable(CustomerName,CustomerItems,CustomerPrice)values('Larry',4,1000);
Query OK, 1 row affected (0.12 sec)
mysql> insert into DemoTable(CustomerName,CustomerItems,CustomerPrice)values('Larry',1,100);
Query OK, 1 row affected (0.12 sec)
mysql> insert into DemoTable(CustomerName,CustomerItems,CustomerPrice)values('Mike',5,200);
Query OK, 1 row affected (0.71 sec)

以下是使用 select 命令显示表中记录的查询:

mysql> select *from DemoTable;

这将产生以下输出 −

+------------+--------------+---------------+---------------+
| CustomerId | CustomerName | CustomerItems | CustomerPrice |
+------------+--------------+---------------+---------------+
|          1 | Larry        |             3 |           450 |
|          2 | Mike         |             2 |           550 |
|          3 | Larry        |             4 |          1000 |
|          4 | Larry        |             1 |           100 |
|          5 | Mike         |             5 |           200 |
+------------+--------------+---------------+---------------+
5 rows in set (0.00 sec)

以下查询用于将列 (Items * Price) 相乘,然后对具有相似记录的行求和:

mysql> SELECT CustomerName, SUM( CustomerItems* CustomerPrice) AS TOTAL_PRICE FROM DemoTable
GROUP BY CustomerName;

这将产生以下输出 −

+--------------+-------------+
| CustomerName | TOTAL_PRICE |
+--------------+-------------+
| Larry        | 5450        |
| Mike         | 2100        |
+--------------+-------------+
2 rows in set (0.05 sec)

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