SQL LEFT JOIN 关键字

LEFT JOIN 关键字从左表（table1）返回所有的行，即使右表（table2）中没有匹配。如果右表中没有匹配，则结果为 NULL。

SQL LEFT JOIN 语法

SELECT column_name(s)
FROM table1
LEFT JOIN table2
ON table1.column_name=table2.column_name;

SELECT column_name(s)
FROM table1
LEFT OUTER JOIN table2
ON table1.column_name=table2.column_name;

演示数据库

在本教程中，我们将使用 RUNOOB 样本数据库。

下面是选自 "Websites" 表的数据：

+----+--------------+---------------------------+-------+---------+
| id | name         | url                       | alexa | country |
+----+--------------+---------------------------+-------+---------+
| 1  | Google       | https://www.google.cm/    | 1     | USA     |
| 2  | 淘宝          | https://www.taobao.com/   | 13    | CN      |
| 3  | 芝麻教程      | http://www.web3.xin/    | 4689  | CN      |
| 4  | 微博          | http://weibo.com/         | 20    | CN      |
| 5  | Facebook     | https://www.facebook.com/ | 3     | USA     |
| 7  | stackoverflow | http://stackoverflow.com/ |   0 | IND     |
+----+---------------+---------------------------+-------+---------+

mysql> SELECT * FROM access_log;
+-----+---------+-------+------------+
| aid | site_id | count | date       |
+-----+---------+-------+------------+
|   1 |       1 |    45 | 2016-05-10 |
|   2 |       3 |   100 | 2016-05-13 |
|   3 |       1 |   230 | 2016-05-14 |
|   4 |       2 |    10 | 2016-05-14 |
|   5 |       5 |   205 | 2016-05-14 |
|   6 |       4 |    13 | 2016-05-15 |
|   7 |       3 |   220 | 2016-05-15 |
|   8 |       5 |   545 | 2016-05-16 |
|   9 |       3 |   201 | 2016-05-17 |
+-----+---------+-------+------------+
9 rows in set (0.00 sec)

SQL LEFT JOIN 实例

下面的 SQL 语句将返回所有网站及他们的访问量（如果有的话）。

以下实例中我们把 Websites 作为左表，access_log 作为右表：

实例

SELECT Websites.name, access_log.count, access_log.date
FROM Websites
LEFT JOIN access_log
ON Websites.id=access_log.site_id
ORDER BY access_log.count DESC; 

mysql> SELECT Websites.name, access_log.count, access_log.date
    -> FROM Websites
    -> LEFT JOIN access_log
    -> ON Websites.id=access_log.site_id
    -> ORDER BY access_log.count DESC;
+---------------+-------+------------+
| name          | count | date       |
+---------------+-------+------------+
| Facebook      |   545 | 2016-05-16 |
| Google        |   230 | 2016-05-14 |
| 芝麻教程      |   220 | 2016-05-15 |
| Facebook      |   205 | 2016-05-14 |
| 芝麻教程      |   201 | 2016-05-17 |
| 芝麻教程      |   100 | 2016-05-13 |
| Google        |    45 | 2016-05-10 |
| 微博          |    13 | 2016-05-15 |
| 淘宝          |    10 | 2016-05-14 |
| stackoverflow |  NULL | NULL       |
+---------------+-------+------------+
10 rows in set (0.00 sec)