Rekursive/hierarchische Abfrage mit Postgres

[Diese Antwort basiert auf Gordons]

Ich habe arr_time und dep_time in TIME geändert Datentypen, was Berechnungen erleichtert. Außerdem wurden Ergebnisspalten für total_time und wait_time hinzugefügt. Hinweis :Wenn im Diagramm Schleifen möglich sind, müssen Sie diese vermeiden (möglicherweise mithilfe eines Arrays zum Speichern des Pfads)

WITH RECURSIVE segs AS (
  SELECT f0.flight_num::text as flight
            , src_city, dest_city
            , dep_time AS departure
            , arr_time AS arrival
            , airfare, mileage
            , 1 as hops
            , (arr_time - dep_time)::interval AS total_time
            , '00:00'::interval as waiting_time
  FROM flight f0
  WHERE src_city = 'SLC' -- <SRC_CITY>
  UNION ALL
  SELECT s.flight || '-->' || f1.flight_num::text as flight
            , s.src_city, f1.dest_city
            , s.departure AS departure
            , f1.arr_time AS arrival
            , s.airfare + f1.airfare as airfare
            , s.mileage + f1.mileage as mileage
            , s.hops + 1 AS hops
            , s.total_time + (f1.arr_time - f1.dep_time)::interval AS total_time
            , s.waiting_time + (f1.dep_time - s.arrival)::interval AS waiting_time
  FROM segs s
     JOIN flight f1
       ON f1.src_city = s.dest_city
       AND f1.dep_time > s.arrival -- you can't leave until you are there
)
SELECT *
FROM segs
WHERE dest_city = 'LA' -- <DEST_CITY>
ORDER BY airfare desc
    ;

FYI:die Änderungen an der Tabellenstruktur:

create table flight
  ( flight_num BIGSERIAL PRIMARY KEY
  , src_city varchar
  , dest_city varchar
  , dep_time TIME
  , arr_time TIME
  , airfare INTEGER
  , mileage INTEGER
);

Und zu den Daten:

insert into flight VALUES
  (101,    'Montreal',          'NY',                   '05:30',     '06:45',    180,      170),
  (102,    'Montreal',          'Washington',           '01:00',     '02:35',    100,      180),
  (103,    'NY',                'Chicago',              '08:00',     '10:00',    150,      300),
  (105,    'Washington',        'KansasCity',           '06:00',     '08:45',    200,      600),
  (106,    'Washington',        'NY',                   '12:00',     '13:30',     50,       80),
  (107,    'Chicago',           'SLC',                  '11:00',     '14:30',    220,      750),
  (110,    'KansasCity',        'Denver',               '14:00',     '15:25',    180,      300),
  (111,    'KansasCity',        'SLC',                  '13:00',     '15:30',    200,      500),
  (112,    'SLC',               'SanFran',              '18:00',     '19:30',     85,      210),
  (113,    'SLC',               'LA',                   '17:30',     '19:00',    185,      230),
  (115,    'Denver',            'SLC',                  '15:00',     '16:00',     75,      300),
  (116,    'SanFran',           'LA',                   '22:00',     '22:30',     50,       75),
  (118,    'LA',                'Seattle',              '20:00',     '21:00',    150,      450);