是否可以做一个简单的查询来计算我在一个确定的时间段内有多少记录,比如一年,一个月,或者一天,有一个TIMESTAMP字段,比如:
SELECT COUNT(id)
FROM stats
WHERE record_date.YEAR = 2009
GROUP BY record_date.YEAR
甚至:
SELECT COUNT(id)
FROM stats
GROUP BY record_date.YEAR, record_date.MONTH
每月进行统计。
谢谢!
是否可以做一个简单的查询来计算我在一个确定的时间段内有多少记录,比如一年,一个月,或者一天,有一个TIMESTAMP字段,比如:
SELECT COUNT(id)
FROM stats
WHERE record_date.YEAR = 2009
GROUP BY record_date.YEAR
甚至:
SELECT COUNT(id)
FROM stats
GROUP BY record_date.YEAR, record_date.MONTH
每月进行统计。
谢谢!
当前回答
如果你想在MySQL中按日期分组,那么使用下面的代码:
SELECT COUNT(id)
FROM stats
GROUP BY DAYOFMONTH(record_date)
希望这为那些要找到这个帖子的人节省了一些时间。
其他回答
如果你的搜索已经超过几年了,你仍然想每月分组,我建议:
版本1:
SELECT SQL_NO_CACHE YEAR(record_date), MONTH(record_date), COUNT(*)
FROM stats
GROUP BY DATE_FORMAT(record_date, '%Y%m')
版本#2(更有效):
SELECT SQL_NO_CACHE YEAR(record_date), MONTH(record_date), COUNT(*)
FROM stats
GROUP BY YEAR(record_date)*100 + MONTH(record_date)
我在一个大表上比较了这些版本,有1,357,918行(innodb), 第二个版本的效果似乎更好。
版本1(平均执行10次):1.404秒 版本2(平均执行10次):0.780秒
(增加SQL_NO_CACHE键,防止MySQL对查询进行缓存。)
我试着使用上面的“WHERE”语句,我认为它是正确的,因为没有人纠正它,但我错了;经过一些搜索,我发现这是WHERE语句的正确公式,所以代码变成这样:
SELECT COUNT(id)
FROM stats
WHERE YEAR(record_date) = 2009
GROUP BY MONTH(record_date)
完整而简单的解决方案,具有类似的性能,但更短,更灵活的替代方案,目前活跃:
SELECT COUNT(*) FROM stats
-- GROUP BY YEAR(record_date), MONTH(record_date), DAYOFMONTH(record_date)
GROUP BY DATE_FORMAT(record_date, '%Y-%m-%d')
你可以在GROUP BY中简单的使用Mysql DATE_FORMAT()函数。在某些情况下,您可能希望添加一个额外的列以增加清晰度,例如记录跨越数年,而同一个月出现在不同的年份。这里有很多选项,你可以自定义。开始前请先读一下。希望对你有帮助。下面是示例查询,以帮助您理解
SELECT
COUNT(id),
DATE_FORMAT(record_date, '%Y-%m-%d') AS DAY,
DATE_FORMAT(record_date, '%Y-%m') AS MONTH,
DATE_FORMAT(record_date, '%Y') AS YEAR
FROM
stats
WHERE
YEAR = 2009
GROUP BY
DATE_FORMAT(record_date, '%Y-%m-%d ');
GROUP BY DATE_FORMAT(record_date, '%Y%m')
Note (primarily, to potential downvoters). Presently, this may not be as efficient as other suggestions. Still, I leave it as an alternative, and a one, too, that can serve in seeing how faster other solutions are. (For you can't really tell fast from slow until you see the difference.) Also, as time goes on, changes could be made to MySQL's engine with regard to optimisation so as to make this solution, at some (perhaps, not so distant) point in future, to become quite comparable in efficiency with most others.