SQL HAVING
SQL HAVING子句
HAVING 子句
在 SQL 中增加 HAVING 子句原因是,WHERE 关键字无法与聚合函数一起使用。
HAVING 子句可以让我们筛选分组后的各组数据。
SQL HAVING 语法
SELECT column_name, aggregate_function(column_name)
FROM table_name
WHERE column_name operator value
GROUP BY column_name
HAVING aggregate_function(column_name) operator value;
FROM table_name
WHERE column_name operator value
GROUP BY column_name
HAVING aggregate_function(column_name) operator value;
演示数据库
在本教程中,我们将使用 php 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 | php中文网 | http://www.php.cn/ | 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 |
+----+---------------+---------------------------+-------+---------+
| id | name | url | alexa | country |
+----+--------------+---------------------------+-------+---------+
| 1 | Google | https://www.google.cm/ | 1 | USA |
| 2 | 淘宝 | https://www.taobao.com/ | 13 | CN |
| 3 | php中文网 | http://www.php.cn/ | 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 |
+----+---------------+---------------------------+-------+---------+
下面是 "access_log" 网站访问记录表的数据:
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)
+-----+---------+-------+------------+
| 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 HAVING 实例
现在我们想要查找总访问量大于 200 的网站。
我们使用下面的 SQL 语句:
实例
SELECT Websites.name, Websites.url, SUM(access_log.count) AS nums FROM
(access_log
INNER JOIN Websites
ON access_log.site_id=Websites.id)
GROUP BY Websites.name
HAVING SUM(access_log.count) > 200;
INNER JOIN Websites
ON access_log.site_id=Websites.id)
GROUP BY Websites.name
HAVING SUM(access_log.count) > 200;
执行以上 SQL 输出结果如下:
现在我们想要查找总访问量大于 200 的网站,并且 alexa 排名小于 200。
我们在 SQL 语句中增加一个普通的 WHERE 子句:
实例
SELECT Websites.name, SUM(access_log.count) AS nums FROM
Websites
INNER JOIN access_log
ON Websites.id=access_log.site_id
WHERE Websites.alexa < 200
GROUP BY Websites.name
HAVING SUM(access_log.count) > 200;
INNER JOIN access_log
ON Websites.id=access_log.site_id
WHERE Websites.alexa < 200
GROUP BY Websites.name
HAVING SUM(access_log.count) > 200;
执行以上 SQL 输出结果如下: