Updated version

Based on feedback from OP. This is not just a simple min/max situation, it’s a gaps and islands problem. In this case, we have to deal with multiple “on_rent” records and potentially multiple “off_rent” records as well as gaps in between “off_rent” and “on_rent”.

This is my solution so far (see bottom of response to populate sample data table):

WITH cte AS (
    -- Collapse groups to get the start and end rent dates for each
    SELECT x.tag, x.GroupID
        , DateOnRent  = MIN(IIF(x.on_rent_status = 1, x.[date_on-off_rent], NULL)) -- Using min because we want the FIRST time  on_rent was logged
        , DateOffRent = MIN(IIF(x.on_rent_status = 0, x.[date_on-off_rent], NULL)) -- Using min because we want the FIRST time off_rent was logged
    FROM (
        SELECT x.tag, x.[date_on-off_rent], x.on_rent_status
            -- If the status changed from off_rent to on_rent, then we know a new group has started
            -- Returning 1 to the running total will generate a grouping ID that keeps sequential rent_status records together
            , GroupID = SUM(IIF(x.on_rent_status = 1 AND x.prev_on_rent_status = 0, 1, 0)) OVER (PARTITION BY x.tag ORDER BY x.position)
        FROM (
            SELECT tag, on_rent_status, [date_on-off_rent], position
                -- Getting the previous value will help us later determine whether the status changed
                , prev_on_rent_status = LAG(on_rent_status) OVER (PARTITION BY tag ORDER BY position)
            FROM #rent_history
        ) x
    ) x
    GROUP BY x.tag, x.GroupID
)
SELECT x.tag
    , FirstDateOnRent = MIN(x.DateOnRent)
    , LastDateOffRent = MAX(x.LastDateOffRent) -- NULL if still on_rent
    , DaysOnRent      = SUM(x.DaysOnRent)
    , DaysOffRent     = DATEDIFF(DAY, MAX(x.LastDateOffRent), GETDATE()) -- NULL if still on_rent
FROM (
    SELECT x.tag, x.DateOnRent, x.DateOffRent
        -- We want the most recent state of DateOffRent, rather than MAX, which means if they are still on_rent, it should return null
        , LastDateOffRent = LAST_VALUE(x.DateOffRent) OVER (PARTITION BY x.tag ORDER BY x.DateOnRent)
        -- Number of DaysOnrent needs to be calc'd at the group level so we don't accidentally include gaps
        , DaysOnRent  = DATEDIFF(DAY, x.DateOnRent, COALESCE(x.DateOffRent, GETDATE()))
    FROM cte x
) x
GROUP BY x.tag;

I tried to comment the code as best I could, so I won’t completely dive into how this works line by line.

But the basic idea is…calculate some sort of grouping ID that can keep sequential events together. In this case I relied on both LAG() and SUM({state change logic}) OVER() to generate that ID.

Then from there it’s just a lot of extra grouping and aggregation to get the final output.

This new query version will support multiple on_rent records, multiple off_rent records as well as gaps between off_rent and on_rent.

Old/Original reply

Based on your explanation, you have a table/dataset called “Rent History”, which represents the top dataset in your screenshot.

And you want a query against that dataset whose output matches the second dataset in your screenshot labeled “Final Result”.

Assuming that’s true, this is what I’ve come up with…problem is, I’m making a bunch of assumptions around business logic that may not be correct, even if it does match your output table…

SELECT x.tag, x.DateOnRent, x.DateOffRent
    , DaysOnRent  = DATEDIFF(DAY, x.DateOnRent, COALESCE(x.DateOffRent, GETDATE()))
    , DaysOffRent = DATEDIFF(DAY, x.DateOffRent, GETDATE())
FROM (
    SELECT tag
        , DateOnRent  = MIN(IIF(on_rent_status = 1, [date_on-off_rent], NULL))
        , DateOffRent = MAX(IIF(on_rent_status = 0, [date_on-off_rent], NULL))
    FROM #rent_history
    GROUP BY tag
) x

I also don’t know how large the underlying datasets are this is running against, so I have no idea how efficient it would be.

The concept seems pretty simple though…grab the earliest “on_rent” date and the oldest “off_rent” date. Then do the datediff calculations using those?

For anyone who wants the script I used to generate the sample data…

CREATE TABLE #rent_history (
    tag                         nvarchar(20) NOT NULL,
    progress_complete_date_time datetime     NOT NULL,
    create_date                 datetime     NOT NULL,
    required_until_date         datetime     NOT NULL,
    modify_date                 datetime     NOT NULL,
    on_rent_status              bit          NOT NULL,
    [date_on-off_rent]          datetime     NOT NULL,
    position                    int          NOT NULL,
    [first_time_on-off_rent]    datetime         NULL,
    [RANK]                      int          NOT NULL,
);

INSERT INTO #rent_history
VALUES ('TAG-000479', '08/12/21 00:00', '11/06/23 19:31', '01/31/24 00:00', '11/06/23 19:31', 1, '08/12/21 00:00', 1, '08/12/21 00:00', 1)
     , ('TAG-000479', '08/12/21 00:00', '11/06/23 19:31', '01/31/24 00:00', '11/06/23 19:31', 1, '11/06/23 00:00', 2, NULL            , 1)
     , ('TAG-000479', '08/12/21 00:00', '11/06/23 19:31', '01/31/24 00:00', '11/06/23 19:31', 1, '11/06/23 00:00', 3, NULL            , 1)
     , ('TAG-000479', '08/12/21 00:00', '11/06/23 19:31', '04/01/24 00:00', '04/04/24 05:00', 0, '04/04/24 00:00', 4, NULL            , 4)
     , ('TAG-000479', '08/12/21 00:00', '11/06/23 19:31', '04/01/24 00:00', '04/04/24 05:00', 1, '04/04/24 00:00', 5, NULL            , 5)
     , ('TAG-000479', '08/12/21 00:00', '11/06/23 19:31', '12/31/24 00:00', '04/30/24 15:11', 1, '04/30/24 00:00', 6, NULL            , 6)
     , ('TAG-000479', '08/12/21 00:00', '11/06/23 19:31', '12/31/24 00:00', '06/10/24 17:02', 0, '06/10/24 00:00', 7, NULL            , 7)
     , ('TAG-001832', '03/28/24 00:00', '01/17/24 15:41', '03/31/24 00:00', '03/28/24 03:32', 1, '03/28/24 00:00', 1, '03/28/24 00:00', 1)
     , ('TAG-003420', '06/24/24 00:00', '06/24/24 18:55', '12/15/24 00:00', '06/25/24 15:18', 1, '06/24/24 00:00', 1, '06/24/24 00:00', 1);