SQL 別名

我們可以使用別名（Alias）來對(duì)數(shù)據(jù)表或者列進(jìn)行臨時(shí)命名。

使用別名意味著要用特定的 SQL 語句對(duì)表進(jìn)行重命名。重命名是臨時(shí)的，數(shù)據(jù)庫(kù)中表的實(shí)際名字并不會(huì)改變。

對(duì)于特定的 SQL 查詢，需要使用列別名來對(duì)表中的列進(jìn)行重命名。

語法：

表別名的基本語法如下：

SELECT column1, column2....
FROM table_name AS alias_name
WHERE [condition];

列別名的基本語法如下：

SELECT column_name AS alias_name
FROM table_name
WHERE [condition];

示例：

考慮下面兩個(gè)數(shù)據(jù)表，（a）CUSTOMERS 表，如下：

+----+----------+-----+-----------+----------+
| ID | NAME     | AGE | ADDRESS   | SALARY   |
+----+----------+-----+-----------+----------+
|  1 | Ramesh   |  32 | Ahmedabad |  2000.00 |
|  2 | Khilan   |  25 | Delhi     |  1500.00 |
|  3 | kaushik  |  23 | Kota      |  2000.00 |
|  4 | Chaitali |  25 | Mumbai    |  6500.00 |
|  5 | Hardik   |  27 | Bhopal    |  8500.00 |
|  6 | Komal    |  22 | MP        |  4500.00 |
|  7 | Muffy    |  24 | Indore    | 10000.00 |
+----+----------+-----+-----------+----------+

（b）另一個(gè)是 ORDERS 表，如下所示：

+-----+---------------------+-------------+--------+
|OID  | DATE                | CUSTOMER_ID | AMOUNT |
+-----+---------------------+-------------+--------+
| 102 | 2009-10-08 00:00:00 |           3 |   3000 |
| 100 | 2009-10-08 00:00:00 |           3 |   1500 |
| 101 | 2009-11-20 00:00:00 |           2 |   1560 |
| 103 | 2008-05-20 00:00:00 |           4 |   2060 |
+-----+---------------------+-------------+--------+

下面是表別名的用法：

SQL> SELECT C.ID, C.NAME, C.AGE, O.AMOUNT 
        FROM CUSTOMERS AS C, ORDERS AS O
        WHERE  C.ID = O.CUSTOMER_ID;

上面語句的運(yùn)行結(jié)果如下所示：

+----+----------+-----+--------+
| ID | NAME     | AGE | AMOUNT |
+----+----------+-----+--------+
|  3 | kaushik  |  23 |   3000 |
|  3 | kaushik  |  23 |   1500 |
|  2 | Khilan   |  25 |   1560 |
|  4 | Chaitali |  25 |   2060 |
+----+----------+-----+--------+

下面是列別名的用法：

SQL> SELECT  ID AS CUSTOMER_ID, NAME AS CUSTOMER_NAME
     FROM CUSTOMERS
     WHERE SALARY IS NOT NULL;

其運(yùn)行結(jié)果如下所示：

+-------------+---------------+
| CUSTOMER_ID | CUSTOMER_NAME |
+-------------+---------------+
|           1 | Ramesh        |
|           2 | Khilan        |
|           3 | kaushik       |
|           4 | Chaitali      |
|           5 | Hardik        |
|           6 | Komal         |
|           7 | Muffy         |
+-------------+---------------+