Sql server 2008 r2 SQL Server正在计算每天有多少实例

我有一个包含ID、开始日期和结束日期的表

Start_date  End_Date    ID
2016-03-01 06:30:00.000 2016-03-07 17:30:00.000 782772
2016-03-01 09:09:00.000 2016-03-07 10:16:00.000 782789
2016-03-01 11:17:00.000 2016-03-08 20:10:00.000 782882
2016-03-01 12:22:00.000 2016-03-21 19:40:00.000 782885
2016-03-01 13:15:00.000 2016-03-24 13:37:00.000 783000
2016-03-01 13:23:00.000 2016-03-07 19:15:00.000 782964
2016-03-01 13:55:00.000 2016-03-14 15:45:00.000 782972
2016-03-01 14:05:00.000 2016-03-07 20:32:00.000 783065
2016-03-01 18:06:00.000 2016-03-09 12:42:00.000 782988
2016-03-01 19:05:00.000 2016-04-01 20:00:00.000 782942
2016-03-01 19:15:00.000 2016-03-10 13:30:00.000 782940
2016-03-01 19:15:00.000 2016-03-07 18:00:00.000 783111
2016-03-01 20:10:00.000 2016-03-08 14:05:00.000 783019
2016-03-01 22:15:00.000 2016-03-24 12:46:00.000 782979
2016-03-02 08:00:00.000 2016-03-08 09:02:00.000 783222
2016-03-02 09:31:00.000 2016-03-15 09:16:00.000 783216
2016-03-02 11:04:00.000 2016-03-19 18:49:00.000 783301
2016-03-02 11:23:00.000 2016-03-14 19:49:00.000 783388
2016-03-02 11:46:00.000 2016-03-08 18:10:00.000 783368
2016-03-02 12:03:00.000 2016-03-23 08:44:00.000 783246
2016-03-02 12:23:00.000 2016-03-11 14:45:00.000 783302
2016-03-02 12:24:00.000 2016-03-12 15:30:00.000 783381
2016-03-02 12:30:00.000 2016-03-09 13:58:00.000 783268
2016-03-02 13:00:00.000 2016-03-10 11:30:00.000 783391
2016-03-02 13:35:00.000 2016-03-17 04:40:00.000 783309
2016-03-02 15:05:00.000 2016-04-04 11:52:00.000 783295
2016-03-02 15:08:00.000 2016-03-15 16:15:00.000 783305
2016-03-02 15:32:00.000 2016-03-08 14:20:00.000 783384
2016-03-02 16:49:00.000 2016-03-08 11:40:00.000 783367
2016-03-02 16:51:00.000 2016-03-11 16:00:00.000 783387
2016-03-02 18:00:00.000 2016-03-10 17:00:00.000 783242
2016-03-02 18:37:00.000 2016-03-25 13:30:00.000 783471
2016-03-02 18:45:00.000 2016-03-11 20:15:00.000 783498
2016-03-02 19:41:00.000 2016-03-17 12:34:00.000 783522
2016-03-02 20:08:00.000 2016-03-22 15:30:00.000 783405
2016-03-02 20:16:00.000 2016-03-31 12:30:00.000 783512
2016-03-02 21:45:00.000 2016-03-15 12:25:00.000 783407
2016-03-03 09:59:00.000 2016-03-09 15:00:00.000 783575
2016-03-03 11:18:00.000 2016-03-16 10:30:00.000 783570
2016-03-03 11:27:00.000 2016-03-15 17:28:00.000 783610
2016-03-03 11:36:00.000 2016-03-11 16:05:00.000 783572
2016-03-03 11:55:00.000 2016-03-10 20:15:00.000 783691
2016-03-03 12:10:00.000 2016-03-09 19:50:00.000 783702
2016-03-03 12:11:00.000 2016-03-15 14:08:00.000 783611
2016-03-03 12:55:00.000 2016-03-10 11:50:00.000 783571
2016-03-03 13:20:00.000 2016-04-20 20:37:00.000 783856
2016-03-03 14:08:00.000 2016-03-10 16:00:00.000 783728
2016-03-03 15:10:00.000 2016-03-10 17:00:00.000 783727
2016-03-03 15:20:00.000 2016-03-17 15:14:00.000 783768
2016-03-03 16:55:00.000 2016-03-09 14:09:00.000 783812
2016-03-03 17:00:00.000 2016-03-12 12:33:00.000 783978
2016-03-03 17:17:00.000 2016-03-10 16:00:00.000 783729
2016-03-03 17:42:00.000 2016-03-10 12:13:00.000 783975
2016-03-03 18:23:00.000 2016-03-09 17:00:00.000 783820
2016-03-03 18:31:00.000 2016-03-11 14:00:00.000 783891
2016-03-03 18:59:00.000 2016-03-10 17:00:00.000 783772
2016-03-03 19:48:00.000 2016-03-11 17:30:00.000 783724
2016-03-03 19:50:00.000 2016-03-09 18:00:00.000 783829
2016-03-03 20:48:00.000 2016-03-11 11:04:00.000 783745
2016-03-03 23:00:00.000 2016-03-13 10:59:00.000 783983
2016-03-04 02:50:00.000 2016-03-10 10:45:00.000 783991
2016-03-04 11:25:00.000 2016-03-14 14:50:00.000 784102
2016-03-04 11:28:00.000 2016-03-18 16:21:00.000 784011
2016-03-04 12:01:00.000 2016-03-11 13:20:00.000 784014
2016-03-04 12:15:00.000 2016-03-11 08:00:00.000 784004
2016-03-04 13:06:00.000 2016-03-11 15:00:00.000 784012
2016-03-04 13:37:00.000 2016-03-10 18:00:00.000 784200
2016-03-04 13:52:00.000 2016-04-22 21:30:00.000 784132
2016-03-04 14:11:00.000 2016-03-14 19:00:00.000 784136
2016-03-04 14:17:00.000 2016-03-11 16:52:00.000 784176
2016-03-04 14:42:00.000 2016-03-13 15:25:00.000 784070
2016-03-04 16:00:00.000 2016-03-11 17:30:00.000 784655
2016-03-04 16:30:00.000 2016-03-10 23:30:00.000 784652
2016-03-04 17:25:00.000 2016-03-22 14:00:00.000 784028
2016-03-04 19:50:00.000 2016-03-10 12:42:00.000 784303
2016-03-04 20:00:00.000 2016-03-10 16:13:00.000 784006
2016-03-04 21:30:00.000 2016-03-10 18:00:00.000 784042
2016-03-04 22:25:00.000 2016-04-02 19:40:00.000 784044
2016-03-04 22:40:00.000 2016-03-15 17:30:00.000 784276
2016-03-04 22:55:00.000 2016-03-13 13:50:00.000 784257
2016-03-04 23:10:00.000 2016-03-15 13:19:00.000 784266
2016-03-05 10:30:00.000 2016-03-11 07:45:00.000 784295
2016-03-05 10:30:00.000 2016-03-16 19:00:00.000 784305
2016-03-05 11:05:00.000 2016-03-17 15:26:00.000 784320
2016-03-05 12:30:00.000 2016-03-14 11:25:00.000 784368
2016-03-05 12:50:00.000 2016-03-17 13:27:00.000 784419
2016-03-05 13:01:00.000 2016-03-11 17:00:00.000 784298
2016-03-05 14:34:00.000 2016-03-11 19:00:00.000 784286
2016-03-05 14:45:00.000 2016-04-07 12:01:00.000 784316
2016-03-05 16:00:00.000 2016-03-24 17:00:00.000 784334
2016-03-05 19:22:00.000 2016-04-12 15:56:00.000 784335
2016-03-05 19:25:00.000 2016-03-14 11:59:00.000 784346
2016-03-05 19:25:00.000 2016-03-11 16:10:00.000 784399
2016-03-05 20:15:00.000 2016-03-15 16:20:00.000 784362
2016-03-05 20:26:00.000 2016-03-12 15:03:00.000 784347
2016-03-05 23:30:00.000 2016-03-17 16:45:00.000 784476
2016-03-06 11:57:00.000 2016-03-15 21:00:00.000 784524
2016-03-06 13:17:00.000 2016-03-29 08:09:00.000 784472
2016-03-06 14:07:00.000 2016-03-15 13:55:00.000 784497
2016-03-06 15:00:00.000 2016-03-16 12:24:00.000 784474

我想做的是，每天我都能计算出有多少条目出现

示例输出

date        Instances
01/03/2016  113
02/03/2016  100
03/03/2016  106
04/03/2016  127
05/03/2016  81
06/03/2016  59
07/03/2016  115
08/03/2016  104
09/03/2016  92
10/03/2016  105
11/03/2016  128
12/03/2016  71
13/03/2016  64
14/03/2016  99
15/03/2016  106
16/03/2016  101
17/03/2016  96
18/03/2016  127
19/03/2016  75
20/03/2016  62
21/03/2016  93
22/03/2016  109
23/03/2016  102
24/03/2016  104
25/03/2016  85
26/03/2016  87
27/03/2016  72
28/03/2016  61
29/03/2016  86
30/03/2016  90
31/03/2016  122

这是我正在使用的查询

with [dates] as (
    select convert(datetime, '2016-01-01') as [date] --start
    union all
    select dateadd(day, 1, [date])
    from [dates]
    where [date] < GETDATE() --end
)
select [date]
    ,Sum (Case when [date] between ws._start_dttm and Case when Cast(ws.End_DTTM as date) is null then [date]
                                                 else Cast(ws._End_DTTM as date) end then 1 else 0 end)  
from [dates]
Join [STAYS] ws on Case when Cast(ws.End_DTTM as date) is null then GETDATE()-1 
                                                 else Cast(ws.End_DTTM as date) end = dates.date
where END_DTTM between '2016-01-01' and GETDATE()
Group BY date
Order by [date]
option (maxrecursion 0)

根据Op评论更新：
下一行的摘要

Start_date               End_Date                 ID 
2016-03-01 06:30:00.000 2016-03-07 17:30:00.000 782772

预期产出将是：

01/03/2016  1 
02/03/2016  1 
03/03/2016  1 
04/03/2016  1 
05/03/2016  1 
06/03/2016  1 
07/03/2016  1

像这样，我要计算每个日期的所有行

select convert(varchar(10),startdate,103) as datee,count(*) as occurences
from table
group by convert(varchar(10),startdate,103)

更新： 试试这个

---

不是我在寻找什么，我所追求的是每天有多少次停留。也就是说，开始日期结束日期ID 2016-03-01 06:30:00.000 2016-03-07 17:30:00.000 782772将是2016年03月01日1 02/03/2016年03月03日1 04/03/2016 1 05/03/2016 1 06/03/2016 1 07/03/2016 1谢谢你的帮助，我在这里找到了答案

select convert(varchar(10),startdate,103) as datee,count(*) as occurences
from table
group by convert(varchar(10),startdate,103)

;with cte
as
(
select 
startdate,enddate
datediff(day,enddate,startdate) as cnt
from
table
)
select 
convert(varchar(10),startdate,103)as date,
sum(cnt)
from
cte
group by 
convert(varchar(10),startdate,103)