试一试

按年(record_date)，月(record_date)分组

这里还有一种方法。这使用[MySQL的LAST_DAY()函数][1]将每个时间戳映射到它的月份。如果在record_date上有索引，它还能够通过有效的范围扫描按年进行过滤。

  SELECT LAST_DAY(record_date) month_ending, COUNT(*) record_count
    FROM stats
   WHERE record_date >= '2000-01-01'
     AND record_date <  '2000-01-01' + INTERVAL 1 YEAR
   GROUP BY LAST_DAY(record_date) 

如果希望按天计算结果，请使用DATE(record_date)。

如果您希望按日历季度获得结果，请使用YEAR(record_date)， quarter (record_date)。

这是一个记录。https://www.plumislandmedia.net/mysql/sql-reporting-time-intervals/ [1]: https://dev.mysql.com/doc/refman/8.0/en/date-and-time-functions.html # function_last-day

GROUP BY YEAR(record_date), MONTH(record_date)

查看MySQL中的日期和时间函数。

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.

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。)

．．．． group by to_char(date， 'YYYY')——> 1989

．．．． group by to_char(date，'MM')——>05

．．．． 3 .用to_char(date，'DD')——>

．．．． group by to_char(date，'MON')——>

．．．． 9 . group by to_char(date，'YY')——>