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MYSQL数据库查询按日期分组统计详细代码

2024-01-30 15:44:16 作者：嘉禾嘉宁papa

这篇文章主要给大家介绍了关于MYSQL数据库查询按日期分组统计的相关资料,按日期分组是指按照时间维度对数据进行分类汇总统计,常用于查询分析具有时间属性的数据,例如订单量、用户活跃等,需要的朋友可以参考下

一、按日分组

1.1、dayofyear、dayofmonth、dayofweek

dayofyear(date) 函数返回日期位于所在年份的第几天，范围是1 ~ 366
dayofmonth(date) 函数返回日期位于所在月份的第几天，范围是1 ~ 31
dayofweek(date) 函数返回日期位于所在周的第几天，范围是1 ~ 7

查询语句

select 
	dayofmonth(transtime) as transDay,
	count(*) as transNum
from tb_inf_otherbiz 
where transtime between '2016-10-01 00:00:00' and '2016-10-31 23:59:59'
group by transDay
order by transDay asc;

查询结果

+----------+----------+
| transDay | transNum |
+----------+----------+
| 1 | 1704 |
| 2 | 985 |
| 3 | 723 |
| 4 | 606 |
| 5 | 581 |
| 6 | 1051 |
| 7 | 1257 |
| 8 | 637 |
| 9 | 1049 |
| 10 | 559 |
| 11 | 724 |
| 12 | 964 |
| 13 | 1139 |
| 14 | 2542 |
| 15 | 5957 |
| 16 | 3185 |
| 17 | 543 |
| 18 | 507 |
| 19 | 854 |
| 20 | 849 |
| 21 | 2216 |
| 22 | 3788 |
| 23 | 2498 |
| 24 | 693 |
| 25 | 597 |
| 26 | 756 |
| 27 | 854 |
| 28 | 1583 |
| 29 | 2180 |
| 30 | 1855 |
| 31 | 744 |
+----------+----------+
31 rows in set (0.05 sec)

需要注意的是，如果是 dayofmonth 或者 dayofweek 时间跨月或者周，多月或者多周数据会合并到一起，如果希望分开，则可以采用下面的格式化方法。

1.2、格式化函数

DATE_FORMAT(date, ‘%Y-%m-%d’) 函数按指定表达返回格式化后的日期，包含年月日

查询语句

select 
	DATE_FORMAT(transtime, '%Y-%m-%d') as transDay,
	count(*) as transNum
from tb_inf_otherbiz 
where transtime between '2016-10-01 00:00:00' and '2016-10-31 23:59:59'
group by transDay
order by transDay asc;

查询结果

+------------+----------+
| transDay | transNum |
+------------+----------+
| 2016-10-01 | 1704 |
| 2016-10-02 | 985 |
| 2016-10-03 | 723 |
| 2016-10-04 | 606 |
| 2016-10-05 | 581 |
| 2016-10-06 | 1051 |
| 2016-10-07 | 1257 |
| 2016-10-08 | 637 |
| 2016-10-09 | 1049 |
| 2016-10-10 | 559 |
| 2016-10-11 | 724 |
| 2016-10-12 | 964 |
| 2016-10-13 | 1139 |
| 2016-10-14 | 2542 |
| 2016-10-15 | 5957 |
| 2016-10-16 | 3185 |
| 2016-10-17 | 543 |
| 2016-10-18 | 507 |
| 2016-10-19 | 854 |
| 2016-10-20 | 849 |
| 2016-10-21 | 2216 |
| 2016-10-22 | 3788 |
| 2016-10-23 | 2498 |
| 2016-10-24 | 693 |
| 2016-10-25 | 597 |
| 2016-10-26 | 756 |
| 2016-10-27 | 854 |
| 2016-10-28 | 1583 |
| 2016-10-29 | 2180 |
| 2016-10-30 | 1855 |
| 2016-10-31 | 744 |
+------------+----------+
31 rows in set (0.08 sec)

二、按周分组

2.1、week函数

week(date) 函数返回日期是本年的第几周，每周是从周日开始，取值范围是0 ~ 53

查询语句

select 
	week(transtime) as transWeek,
	count(*) as transNum
from tb_inf_otherbiz 
where transtime between '2016-01-01 00:00:00' and '2016-12-31 23:59:59'
group by transWeek
order by transWeek asc;

查询结果

+-----------+----------+
| transWeek | transNum |
+-----------+----------+
| 0 | 2 |
| 1 | 8 |
| 2 | 9 |
| 3 | 1 |
| 4 | 4 |
| 5 | 7 |
| 6 | 4 |
| 7 | 9 |
| 8 | 7 |
| 9 | 2 |
| 10 | 21 |
| 11 | 18 |
| 12 | 19 |
| 13 | 34 |
| 14 | 31 |
| 15 | 17 |
| 16 | 130 |
| 17 | 261 |
| 18 | 230 |
| 19 | 494 |
| 20 | 452 |
| 21 | 485 |
| 22 | 590 |
| 23 | 684 |
| 24 | 580 |
| 25 | 620 |
| 26 | 370 |
| 27 | 155 |
| 28 | 721 |
| 29 | 747 |
| 30 | 659 |
| 31 | 775 |
| 32 | 843 |
| 33 | 897 |
| 34 | 926 |
| 35 | 975 |
| 36 | 975 |
| 37 | 1048 |
| 38 | 393 |
| 39 | 4145 |
| 40 | 5840 |
| 41 | 12934 |
| 42 | 11942 |
| 43 | 9161 |
| 44 | 9102 |
| 45 | 8284 |
| 46 | 6150 |
| 47 | 5825 |
| 48 | 6374 |
| 49 | 6929 |
| 50 | 4366 |
| 51 | 3858 |
| 52 | 5855 |
+-----------+----------+
53 rows in set (0.12 sec)

2.2、weekofyear函数

weekofyear(date) 函数返回日期是本年的第几周，每周是从周一开始，取值范围是1 ~ 53

查询语句

select 
	weekofyear(transtime) as transWeek,
	count(*) as transNum
from tb_inf_otherbiz 
where transtime between '2016-01-01 00:00:00' and '2016-12-31 23:59:59'
group by transWeek
order by transWeek asc;

查询结果

+-----------+----------+
| transWeek | transNum |
+-----------+----------+
| 1 | 11 |
| 2 | 6 |
| 4 | 5 |
| 5 | 6 |
| 6 | 5 |
| 7 | 9 |
| 8 | 7 |
| 9 | 1 |
| 10 | 22 |
| 11 | 17 |
| 12 | 23 |
| 13 | 34 |
| 14 | 28 |
| 15 | 16 |
| 16 | 199 |
| 17 | 194 |
| 18 | 299 |
| 19 | 510 |
| 20 | 458 |
| 21 | 492 |
| 22 | 571 |
| 23 | 709 |
| 24 | 546 |
| 25 | 640 |
| 26 | 278 |
| 27 | 257 |
| 28 | 723 |
| 29 | 720 |
| 30 | 710 |
| 31 | 786 |
| 32 | 813 |
| 33 | 921 |
| 34 | 957 |
| 35 | 1002 |
| 36 | 932 |
| 37 | 1032 |
| 38 | 327 |
| 39 | 5064 |
| 40 | 5904 |
| 41 | 15070 |
| 42 | 11255 |
| 43 | 8518 |
| 44 | 9203 |
| 45 | 7836 |
| 46 | 5448 |
| 47 | 6608 |
| 48 | 5934 |
| 49 | 6639 |
| 50 | 4160 |
| 51 | 3887 |
| 52 | 5173 |
| 53 | 3 |
+-----------+----------+
52 rows in set (0.12 sec)

2.3、weekday函数

weekday(date) 返回周几，注意，周一是0，周二是1，。。。周日是6

查询语句

select 
	weekday(transtime) as transWeek,
	count(*) as transNum
from tb_inf_otherbiz 
where transtime between '2016-10-01 00:00:00' and '2016-10-31 23:59:59'
group by transWeek
order by transWeek asc;

查询结果

+-----------+----------+
| transWeek | transNum |
+-----------+----------+
| 0 | 3262 |
| 1 | 2434 |
| 2 | 3155 |
| 3 | 3893 |
| 4 | 7598 |
| 5 | 14266 |
| 6 | 9572 |
+-----------+----------+
7 rows in set (0.05 sec)

同时如果觉得不直观，你想获取名称，可以使用 dayname(date) 替代 weekday(date) ，结果如下

2.4、dayname函数

dayname(date) 返回星期几：MONDAY，TUESDAY…SUNDAY

查询语句

select 
	dayname(transtime) as transWeek,
	count(*) as transNum
from tb_inf_otherbiz 
where transtime between '2016-10-01 00:00:00' and '2016-10-31 23:59:59'
group by transWeek
order by transWeek asc;

查询结果

+-----------+----------+
| transWeek | transNum |
+-----------+----------+
| Friday | 7598 |
| Monday | 3262 |
| Saturday | 14266 |
| Sunday | 9572 |
| Thursday | 3893 |
| Tuesday | 2434 |
| Wednesday | 3155 |
+-----------+----------+
7 rows in set (0.08 sec)

三、按月分组

3.1、month函数

month(date) 函数返回日期对应的月份，范围1～12

查询语句

select 
	month(transtime) as transMonth,
	count(*) as transNum
from tb_inf_otherbiz 
where transtime between '2016-01-01 00:00:00' and '2016-12-31 23:59:59'
group by transMonth
order by transMonth asc;

查询结果

+------------+----------+
| transMonth | transNum |
+------------+----------+
| 1 | 25 |
| 2 | 27 |
| 3 | 83 |
| 4 | 449 |
| 5 | 1893 |
| 6 | 2611 |
| 7 | 2411 |
| 8 | 3811 |
| 9 | 5334 |
| 10 | 44180 |
| 11 | 30140 |
| 12 | 24004 |
+------------+----------+
12 rows in set (0.12 sec)

同时如果你想获取名字，可以使用 MONTHNAME(date) 替代 month(date) ，结果如下：

+------------+----------+
| transMonth | transNum |
+------------+----------+
| April | 449 |
| August | 3811 |
| December | 24004 |
| February | 27 |
| January | 25 |
| July | 2411 |
| June | 2611 |
| March | 83 |
| May | 1893 |
| November | 30140 |
| October | 44180 |
| September | 5334 |
+------------+----------+
12 rows in set (0.20 sec)

需要注意的是，如果是跨年了，多年的数据会合并到一起，就不知道每一年的某月是多少了，如果希望分开，则可以采用下面的格式化方法。

3.2、DATE_FORMAT函数

DATE_FORMAT(date, ‘%Y-%m’) 函数按指定表达返回格式化后的日期，包含年月

查询语句

select 
	DATE_FORMAT(transtime, '%Y-%m') as transMonth,
	count(*) as transNum
from tb_inf_otherbiz 
where transtime between '2016-01-01 00:00:00' and '2016-12-31 23:59:59'
group by transMonth
order by transMonth asc;

查询结果

+------------+----------+
| transMonth | transNum |
+------------+----------+
| 2016-01 | 25 |
| 2016-02 | 27 |
| 2016-03 | 83 |
| 2016-04 | 449 |
| 2016-05 | 1893 |
| 2016-06 | 2611 |
| 2016-07 | 2411 |
| 2016-08 | 3811 |
| 2016-09 | 5334 |
| 2016-10 | 44180 |
| 2016-11 | 30140 |
| 2016-12 | 24004 |
+------------+----------+
12 rows in set (0.20 sec)

四、按季分组

4.1、quarter函数

quarter(date) 函数返回日期对应的季度，范围为1～4

查询语句

select 
	quarter(transtime) as quarterNo,
	count(*) as transNum
from tb_inf_otherbiz 
where transtime between '2016-01-01 00:00:00' and '2016-12-31 23:59:59'
group by quarterNo
order by quarterNo asc;

查询结果

+-----------+----------+
| quarterNo | transNum |
+-----------+----------+
| 1 | 135 |
| 2 | 4953 |
| 3 | 11556 |
| 4 | 98324 |
+-----------+----------+
4 rows in set (0.12 sec)

五、按年分组

5.1、year函数

year(date) 函数返回日期对应的年份

查询语句

select 
	year(transtime) as transYear,
	count(*) as transNum
from tb_inf_otherbiz 
where transtime between '2015-01-01 00:00:00' and '2022-12-31 23:59:59'
group by transYear
order by transYear asc;

查询结果

+-----------+----------+
| transYear | transNum |
+-----------+----------+
| 2015 | 6 |
| 2016 | 114968 |
| 2017 | 66703 |
| 2018 | 2738 |
| 2019 | 1853 |
| 2020 | 651 |
| 2021 | 40 |
+-----------+----------+
7 rows in set (0.19 sec)

5.2、DATE_FORMAT函数

DATE_FORMAT(date, ‘%Y’) 函数按指定表达返回格式化后的日期，包含年

查询语句

select 
	DATE_FORMAT(transtime, '%Y') as transYear,
	count(*) as transNum
from tb_inf_otherbiz 
where transtime between '2015-01-01 00:00:00' and '2022-12-31 23:59:59'
group by transYear
order by transYear asc;

查询结果

+-----------+----------+
| transYear | transNum |
+-----------+----------+
| 2015 | 6 |
| 2016 | 114968 |
| 2017 | 66703 |
| 2018 | 2738 |
| 2019 | 1853 |
| 2020 | 651 |
| 2021 | 40 |
+-----------+----------+
7 rows in set (0.19 sec)

其他

格式转换

select from_unixtime(create_time / 1000, '%Y-%m-%d %H:%i:%S') create_time
from t_content

结语

本文的操作都是基于mysql8.0的版本，搞懂mysql的函数这些查询都会变得简单。

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