Getting datetime count range in SQL Server

Question

I try to get the date range between the data changes in SQL Server my query is

select count(1) as qty, Info, convert(char,dFError,100) dErr
from TableData
group by Info, convert(char,dFError,100) 
order by dErr asc

I have this qty has the number of reques to a server, info are the servers ip and the date it's when a request it's sended to another server.

qty	Info	dErr
1	1.97	Aug 11 2021 9:01AM
1	1.97	Aug 11 2021 9:06AM
88	1.33	Dec 21 2021 2:04PM
1	1.95	Dec 22 2021 9:44PM
9	1.95	Dec 22 2021 9:45PM
1	1.33	Dec 22 2021 9:51PM
19	1.33	Dec 22 2021 9:52PM
3	1.33	Dec 22 2021 9:53PM
6	1.33	Dec 27 2021 7:10PM
17	1.33	Dec 27 2021 7:11PM
15	1.95	Dec 27 2021 7:17PM
8	1.95	Dec 27 2021 7:18PM

and I want this, in Aug 11 at 9:06AM all are going to 1.97, at Dec 21 at 2:04PM all are going to 1.33, that means the date and the info

qty	Info	dErr
2	1.97	Aug 11 2021 9:06AM
88	1.33	Dec 21 2021 2:04PM
10	1.95	Dec 22 2021 9:45PM
46	1.33	Dec 27 2021 7:11PM
23	1.95	Dec 27 2021 7:18PM

in the same day can be the same group of numbers on distinct hour

qty	Info	dErr
1	1.97	Jan 24 2022 9:39AM
1	1.97	Jan 24 2022 9:51AM
1	1.97	Jan 24 2022 9:58AM
4	1.97	Jan 24 2022 10:08AM
1	1.97	Jan 24 2022 10:12AM
8	1.95	Jan 24 2022 10:24AM
2	1.95	Jan 24 2022 10:32AM
10	1.33	Jan 24 2022 10:33AM
1	1.33	Jan 24 2022 11:37AM
8	1.95	Jan 24 2022 11:59AM
1	1.95	Jan 24 2022 12:00PM
2	1.95	Jan 24 2022 12:08PM

and need to be displayed like

qty	Info	dErr
8	1.97	Jan 24 2022 10:12AM
10	1.95	Jan 24 2022 10:32AM
11	1.33	Jan 24 2022 11:37AM
11	1.95	Jan 24 2022 12:08PM

Answer 1

A double row_number can be used to calculate a ranking.
Then the ranking can be used in the aggregation to solve this Gaps-And-Islands type of problem.

select sum(qty) as qty, Info, max(dFError) as dErr
from (
  select Info, dFError, qty
  , convert(date, dFError) as dErrorDate
  , Rnk = row_number() over (order by dFError)
  + row_number() over (partition by Info order by dFError desc)
  from TableData
) q
group by Info, Rnk
order by dErr;

qty	Info	dErr
2	1.97	2021-08-11 09:06:00.000
88	1.33	2021-12-21 14:04:00.000
10	1.95	2021-12-22 21:45:00.000
46	1.33	2021-12-27 19:11:00.000
23	1.95	2021-12-27 19:18:00.000
8	1.97	2022-01-24 10:12:00.000
10	1.95	2022-01-24 10:32:00.000
11	1.33	2022-01-24 11:37:00.000
11	1.95	2022-01-24 12:08:00.000

Demo on db<>fiddle here