A = {1,2}
B = {3,4,5}
A×B={(1,3), (1,4), (1,5), (2,3), (2,4), (2,5) };
B×A={(3,1), (3,2), (4,1), (4,2), (5,1), (5,2) };
#第一种写法 SELECT table1.column1, table2.column2... FROM table1 CROSS JOIN table2 #第二种写法 SELECT table1.column1, table2.column2... FROM table1, table2第一种写法见名知意,是 SQL 标准推荐的写法。
+----+----------+-----+-----------+----------+ | 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 | +-----+---------------------+-------------+--------+
SQL> SELECT ID, NAME, AMOUNT, DATE FROM CUSTOMERS CROSS JOIN ORDERS;执行结果:
+----+----------+--------+---------------------+ | ID | NAME | AMOUNT | DATE | +----+----------+--------+---------------------+ | 1 | Ramesh | 3000 | 2009-10-08 00:00:00 | | 1 | Ramesh | 1500 | 2009-10-08 00:00:00 | | 1 | Ramesh | 1560 | 2009-11-20 00:00:00 | | 1 | Ramesh | 2060 | 2008-05-20 00:00:00 | | 2 | Khilan | 3000 | 2009-10-08 00:00:00 | | 2 | Khilan | 1500 | 2009-10-08 00:00:00 | | 2 | Khilan | 1560 | 2009-11-20 00:00:00 | | 2 | Khilan | 2060 | 2008-05-20 00:00:00 | | 3 | kaushik | 3000 | 2009-10-08 00:00:00 | | 3 | kaushik | 1500 | 2009-10-08 00:00:00 | | 3 | kaushik | 1560 | 2009-11-20 00:00:00 | | 3 | kaushik | 2060 | 2008-05-20 00:00:00 | | 4 | Chaitali | 3000 | 2009-10-08 00:00:00 | | 4 | Chaitali | 1500 | 2009-10-08 00:00:00 | | 4 | Chaitali | 1560 | 2009-11-20 00:00:00 | | 4 | Chaitali | 2060 | 2008-05-20 00:00:00 | | 5 | Hardik | 3000 | 2009-10-08 00:00:00 | | 5 | Hardik | 1500 | 2009-10-08 00:00:00 | | 5 | Hardik | 1560 | 2009-11-20 00:00:00 | | 5 | Hardik | 2060 | 2008-05-20 00:00:00 | | 6 | Komal | 3000 | 2009-10-08 00:00:00 | | 6 | Komal | 1500 | 2009-10-08 00:00:00 | | 6 | Komal | 1560 | 2009-11-20 00:00:00 | | 6 | Komal | 2060 | 2008-05-20 00:00:00 | | 7 | Muffy | 3000 | 2009-10-08 00:00:00 | | 7 | Muffy | 1500 | 2009-10-08 00:00:00 | | 7 | Muffy | 1560 | 2009-11-20 00:00:00 | | 7 | Muffy | 2060 | 2008-05-20 00:00:00 | +----+----------+--------+---------------------+
SQL> SELECT ID, NAME, AMOUNT, DATE FROM CUSTOMERS CROSS JOIN ORDERS ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID;或者
SQL> SELECT ID, NAME, AMOUNT, DATE FROM CUSTOMERS CROSS JOIN ORDERS WHERE CUSTOMERS.ID = ORDERS.CUSTOMER_ID;执行结果:
+----+----------+--------+---------------------+ | 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 | +----+----------+--------+---------------------+
SQL> SELECT ID, NAME, AMOUNT, DATE FROM CUSTOMERS INNER JOIN ORDERS ON CUSTOMERS.ID = ORDERS.CUSTOMER_ID;
10000 * 10000 = 10000 0000 = 1亿
条记录,数据库引擎将花费大量的时间和资源去创建和处理这个结果集。
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