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RIGHT JOIN返回右表中的所有行,即使左表中没有匹配项也不会影响右表中的结果。这意味着如果 ON 子句匹配左表中的 0 条记录;仍将在结果中返回一行,但在左表的每一列中都为 NULL。
这意味着 RIGHT JOIN 返回右表中的所有值,加上左表中匹配的值,或者在没有匹配项的情况下返回 NULL。
RIGHT JOIN的基本语法如下。
SELECT table1.column1, table2.column2...
FROM table1
RIGHT JOIN table2
ON table1.common_field = table2.common_field;
现在我们看如下的两张表
+----+----------+-----+-----------+----------+
| 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 |
+----+----------+-----+-----------+----------+
+-----+---------------------+-------------+--------+
|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 |
+-----+---------------------+-------------+--------+
现在,让我们使用 RIGHT JOIN 连接这两个表,如下所示。
SQL> SELECT ID, NAME, AMOUNT, DATE
FROM CUSTOMERS
RIGHT JOIN ORDERS
ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID;
结果如下
+------+----------+--------+---------------------+
| ID | NAME | AMOUNT | DATE |
+------+----------+--------+---------------------+
| 3 | kaushik | 3000 | 2009-10-08 00:00:00 |
| 3 | kaushik | 1500 | 2009-10-08 00:00:00 |
| 2 | Khilan | 1560 | 2009-11-20 00:00:00 |
| 4 | Chaitali | 2060 | 2008-05-20 00:00:00 |
+------+----------+--------+---------------------+
但是这里我们看到并没有左表字段为NULL的行,所以我们再给ORDERS表加一条记录
INSERT INTO ORDERS VALUES (104,'2008-05-21 00:00:00',9,2160);
我们新加的这条记录的CUSTOMER_ID的值在 CUSTOMERS 表中并不存在,现在我们再使用 RIGHT JOIN语句进行查询,看一下什么结果
SQL> SELECT ID, NAME, AMOUNT, DATE
FROM CUSTOMERS
RIGHT JOIN ORDERS
ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID;
结果如下
+------+----------+--------+---------------------+
| ID | NAME | AMOUNT | DATE |
+------+----------+--------+---------------------+
| 3 | kaushik | 1500 | 2009-10-08 00:00:00 |
| 3 | kaushik | 1560 | 2009-11-20 00:00:00 |
| 3 | kaushik | 3000 | 2009-10-08 00:00:00 |
| 4 | Chaitali | 2060 | 2008-05-20 00:00:00 |
| NULL | NULL | 2160 | 2008-05-21 00:00:00 |
+------+----------+--------+---------------------+
示例图
现在我们看左表出现了NULL的情况。