How to make calculation on time intervals?

Question

I have a problem ,i solve it but i have written a long procedure and i can\'t be sure that it covers all the possible cases .

The problem:

If i have a

Answer 1

I've updated my answer with your data example and I'm adding another example for an employee 248 that uses case 2 and 5 from your graph.

--load example data for emply 547
select CONVERT(int, 547) emp_num, 
    Convert(datetime, '2015-4-1') day_date, 
    Convert(datetime, '2015-4-1 08:00') work_st,
    Convert(datetime, '2015-4-1 16:00') work_end, 
    Convert(datetime, '2015-4-1 07:45') check_in, 
    Convert(datetime, '2015-4-1 12:10') check_out, 
    'W' day_state
into #SecondaryIntervals
insert into #SecondaryIntervals select 547, '2015-4-1', '2015-4-1 08:00', '2015-4-1 16:00', '2015-4-1 12:45', '2015-4-1 17:24', 'W'
insert into #SecondaryIntervals select 547, '2015-4-2', '2015-4-2 00:00', '2015-4-2 00:00', '2015-4-2 07:11', '2015-4-2 13:11', 'E'

select CONVERT(int, 547) emp_num, 
    Convert(datetime, '2015-4-1') day_date, 
    Convert(datetime, '2015-4-1 15:00') mission_in,
    Convert(datetime, '2015-4-1 21:30') mission_out
into #MainIntervals
insert into #MainIntervals select 547, '2015-4-2', '2015-4-2 8:00', '2015-4-2 14:00'

--load more example data for an employee 548 with overlapping secondary intervals
insert into #SecondaryIntervals select 548, '2015-4-1', '2015-4-1 06:00', '2015-4-1 11:00', '2015-4-1 9:00', '2015-4-1 10:00', 'W'
insert into #SecondaryIntervals select 548, '2015-4-1', '2015-4-1 06:00', '2015-4-1 11:00', '2015-4-1 10:30', '2015-4-1 12:30', 'W'
insert into #SecondaryIntervals select 548, '2015-4-1', '2015-4-1 06:00', '2015-4-1 11:00', '2015-4-1 13:15', '2015-4-1 16:00', 'W'

insert into #MainIntervals select 548, '2015-4-1', '2015-4-1 8:00', '2015-4-1 14:00'

--Populate your Offline table with the intervals in #SecondaryIntervals
select 
    ROW_NUMBER() over (Order by emp_num, day_date, StartDateTime, EndDateTime) Rownum,
    emp_num,
    day_date,
    StartDateTime, 
    EndDateTime
into #Offline
from 
    (select emp_num,
        day_date,
        work_st StartDateTime, 
        work_end EndDateTime
    from #SecondaryIntervals
    where day_state = 'W'
    Group by emp_num,
        day_date,
        work_st, 
        work_end
    union
    select 
        emp_num,
        day_date,
        check_in StartDateTime, 
        check_out EndDateTime
    from #SecondaryIntervals
    Group by emp_num,
        day_date,
        check_in, 
        check_out
    ) SecondaryIntervals


--Populate your Online table
select 
    ROW_NUMBER() over (Order by emp_num, day_date, mission_in, mission_out) Rownum,
    emp_num,
    day_date,
    mission_in StartDateTime, 
    mission_out EndDateTime
into #Online
from #MainIntervals
group by emp_num,
    day_date,
    mission_in,
    mission_out


-------------------------------
--find overlaping offline times
-------------------------------
declare @Finished as tinyint
set @Finished = 0

while @Finished = 0
Begin
    update #Offline
    set #Offline.EndDateTime = OverlapEndDates.EndDateTime
    from #Offline
    join
        (
        select #Offline.Rownum,
            MAX(Overlap.EndDateTime) EndDateTime
        from #Offline
        join #Offline Overlap
        on #Offline.emp_num = Overlap.emp_num
            and #Offline.day_date = Overlap.day_date
            and Overlap.StartDateTime between #Offline.StartDateTime and #Offline.EndDateTime
            and #Offline.Rownum <= Overlap.Rownum
        group by #Offline.Rownum
        ) OverlapEndDates
    on #Offline.Rownum = OverlapEndDates.Rownum

    --Remove Online times completely inside of online times
    delete #Offline
    from #Offline
    join #Offline Overlap
    on #Offline.emp_num = Overlap.emp_num
        and #Offline.day_date = Overlap.day_date
        and #Offline.StartDateTime between Overlap.StartDateTime and Overlap.EndDateTime
        and #Offline.EndDateTime between Overlap.StartDateTime and Overlap.EndDateTime
        and #Offline.Rownum > Overlap.Rownum

    --LOOK IF THERE ARE ANY MORE CHAINS LEFT    
    IF NOT EXISTS(
            select #Offline.Rownum,
                MAX(Overlap.EndDateTime) EndDateTime
            from #Offline
            join #Offline Overlap
            on #Offline.emp_num = Overlap.emp_num
                and #Offline.day_date = Overlap.day_date
                and Overlap.StartDateTime between #Offline.StartDateTime and #Offline.EndDateTime
                and #Offline.Rownum < Overlap.Rownum
            group by #Offline.Rownum
            )
        SET @Finished = 1
END

-------------------------------
--Modify Online times with offline ranges
-------------------------------

--delete any Online times completely inside offline range
delete #Online 
from #Online
join #Offline
on #Online.emp_num = #Offline.emp_num
    and #Online.day_date = #Offline.day_date
    and #Online.StartDateTime between #Offline.StartDateTime and #Offline.EndDateTime
    and #Online.EndDateTime between #Offline.StartDateTime and #Offline.EndDateTime

--Find Online Times with offline range at the beginning
update #Online
set #Online.StartDateTime = #Offline.EndDateTime
from #Online
join #Offline
on #Online.emp_num = #Offline.emp_num
    and #Online.day_date = #Offline.day_date
    and #Online.StartDateTime between #Offline.StartDateTime and #Offline.EndDateTime
    and #Online.EndDateTime >= #Offline.EndDateTime

--Find Online Times with offline range at the end
update #Online
set #Online.EndDateTime = #Offline.StartDateTime
from #Online
join #Offline
on #Online.emp_num = #Offline.emp_num
    and #Online.day_date = #Offline.day_date
    and #Online.StartDateTime <= #Offline.StartDateTime
    and #Online.EndDateTime between #Offline.StartDateTime and #Offline.EndDateTime

--Find Online Times with offline range punched in the middle
select #Online.Rownum, 
    #Offline.Rownum OfflineRow,
    #Offline.StartDateTime,
    #Offline.EndDateTime,
    ROW_NUMBER() over (Partition by #Online.Rownum order by #Offline.Rownum Desc) OfflineHoleNumber
into #OfflineHoles
from #Online
join #Offline
on #Online.emp_num = #Offline.emp_num
    and #Online.day_date = #Offline.day_date
    and #Offline.StartDateTime between #Online.StartDateTime and #Online.EndDateTime
    and #Offline.EndDateTime between #Online.StartDateTime and #Online.EndDateTime

declare @HoleNumber as integer
select @HoleNumber = isnull(MAX(OfflineHoleNumber),0) from #OfflineHoles

--Punch the holes out of the online times
While @HoleNumber > 0
Begin
    insert into #Online 
    select
        -1 Rownum,
        #Online.emp_num,
        #Online.day_date,
        #OfflineHoles.EndDateTime StartDateTime,
        #Online.EndDateTime EndDateTime
    from #Online
    join #OfflineHoles
    on #Online.Rownum = #OfflineHoles.Rownum
    where OfflineHoleNumber = @HoleNumber

    update #Online
    set #Online.EndDateTime = #OfflineHoles.StartDateTime
    from #Online
    join #OfflineHoles
    on #Online.Rownum = #OfflineHoles.Rownum
    where OfflineHoleNumber = @HoleNumber

    set @HoleNumber=@HoleNumber-1
end

--Output total hours
select emp_num, day_date, 
    SUM(datediff(second,StartDateTime, EndDateTime)) / 3600.0 TotalHr, 
    SUM(datediff(second,StartDateTime, EndDateTime)) / 60.0 TotalMin
from #Online
group by emp_num, day_date
order by 1, 2

--see how it split up the online intervals
select emp_num, day_date, StartDateTime, EndDateTime
from #Online
order by 1, 2, 3, 4

Output is:

emp_num     day_date                TotalHr                                 TotalMin
----------- ----------------------- --------------------------------------- ---------------------------------------
547         2015-04-01 00:00:00.000 4.100000                                246.000000
547         2015-04-02 00:00:00.000 0.816666                                49.000000
548         2015-04-01 00:00:00.000 0.750000                                45.000000

(3 row(s) affected)

emp_num     day_date                StartDateTime           EndDateTime
----------- ----------------------- ----------------------- -----------------------
547         2015-04-01 00:00:00.000 2015-04-01 17:24:00.000 2015-04-01 21:30:00.000
547         2015-04-02 00:00:00.000 2015-04-02 13:11:00.000 2015-04-02 14:00:00.000
548         2015-04-01 00:00:00.000 2015-04-01 12:30:00.000 2015-04-01 13:15:00.000

(3 row(s) affected)

I left my other answer posted because it's more generic in case someone else wants to snag it. I see you added a bounty to this question. Let me know if there's something specific about my answer that doesn't satisfy you and I'll try to help you out. I process thousands of intervals with this method and it returns in just a few seconds.