Hi all,

I need some help constructing a query... Short version is that I need to group time-slots together into larger ones.

Say I have the following rows, each representing a one-hour slot in a booking system (these are manufactured by a function, pulling data from underlying tables, and this is a simplified example):

aircraft_reg |       slot_begin       |        slot_end        | booking_id | booking_priority | owner_uid
--------------+------------------------+------------------------+------------+------------------+-----------
EI-MCG       | 2026-08-22 09:00:00+01 | 2026-08-22 10:00:00+01 |        361 |                1 | rod EI-MCG       | 2026-08-22 10:00:00+01 | 2026-08-22 11:00:00+01 |        361 |                1 | rod EI-MCG       | 2026-08-22 11:00:00+01 | 2026-08-22 12:00:00+01 |        361 |                1 | rod EI-MCG       | 2026-08-22 12:00:00+01 | 2026-08-22 13:00:00+01 |        217 |                1 | jbloggs EI-MCG       | 2026-08-22 12:00:00+01 | 2026-08-22 13:00:00+01 |        361 |                2 | rod EI-MCG       | 2026-08-22 13:00:00+01 | 2026-08-22 14:00:00+01 |        217 |                1 | jbloggs EI-MCG       | 2026-08-22 13:00:00+01 | 2026-08-22 14:00:00+01 |        361 |                2 | rod EI-MCG       | 2026-08-22 14:00:00+01 | 2026-08-22 15:00:00+01 |        361 |                1 | rod EI-MCG       | 2026-08-22 15:00:00+01 | 2026-08-22 16:00:00+01 |        361 |                1 | rod EI-MCG       | 2026-08-22 16:00:00+01 | 2026-08-22 17:00:00+01 |        361 |                1 | rod EI-MCG       | 2026-08-22 17:00:00+01 | 2026-08-22 18:00:00+01 |        361 |                1 | rod EI-MCG       | 2026-08-22 18:00:00+01 | 2026-08-22 19:00:00+01 |        361 |                1 | rod

(In the case of the slots at 12:00 and 13:00, the slot owner is user "jbloggs", and user "rod" is queuing in the hope that jbloggs cancels - the booking_priority column indicates who has the active booking and who is queued.)

My question is: how do I group together adjacent slots into larger time-slices, so that (for example) I can tell user "rod" that his booking with ID 361 looks like this? -

 * 09:00 - 12:00: active booking
 * 12:00 - 14:00: queued booking
 * 14:00 - 19:00: active booking

...i.e. reduce all the row above into just three rows.

For context, the bookings are stored in an underlying table which uses a tstzrange column for the booking time. When bookings overlap the overlapping period is queued behind booking(s) made earlier - hence the booking for user "rod" in the example above has the same booking ID for all its hour slots.

Here's an example of what I've tried. The function get_slots_demo() in the CTE breaks the overall time-period covered into hour-long slots, as returned in the first example above.

  with slots as (
      select * from get_slots_demo(
          (select lower(booking_time) from bookings_demo where booking_id = 361),           (select upper(booking_time) from bookings_demo where booking_id = 361)
      )
      where booking_id = 361
      order by slot_begin, booking_priority
  )
  select
      s1.booking_id,
      s1.aircraft_reg,
      min(s1.slot_begin) as booking_begin,
      max(s2.slot_end) as booking_end,
      s1.booking_priority
  from slots s1
  inner join slots s2 on (s1.slot_end = s2.slot_begin)
  group by s1.booking_id, s1.aircraft_reg, s1.booking_priority;

However, this just returns two rows - one for the entire period and one for the queued period. This is presumably to be expected, as I suppose what I really need is some grouping column which will be different for each of the three periods I want to return... However, I don't have one, and I can't think of a way to manufacture one. I could do it procedurally, writing a function which detects the boundary between active and queued slots and creates the required grouping column that way, but I'd like to try and do it in "proper SQL" if possible - for the learning exercise at least!

Any pointers or guidance will be very much appreciated.... Thanks in advance.

Ray.

--
Ray O'Donnell // Galway // Ireland
[email protected]

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