How can I group flight legs together into routes for counting? - sql

Question

I have a person's flight history and want to find their most frequent route. All flights are stored as a single row in a table, even return trips where a->b will be in one row and b->a will be in another.
I need to identify where two legs equate to a route; for example:
This person has flown 16 times in total
New York to Paris 2 times (Flight key: JFKCDG)
Paris to New York 2 times (Flight Key: CDGJFK)
New York to London 3 times (Flight Key: JFKLHR)
Currently I don't know a way to group the first two above as a 'Route' and therefore any query I write considers JFKLHR to be the most frequent route (6 times between NY and London) even though I can see from the data that this person has flown between NY and Paris a total of 10 times
Sample Table:
User ID¦Flight Key
-------------------
1 ¦JFKCDG
1 ¦JFKCDG
1 ¦CDGJFK
1 ¦CDGJFK
1 ¦JFKLHR
1 ¦JFKLHR
1 ¦JFKLHR
Expected Output
User ID¦Flight Key¦Count
------------------------
1 ¦JFKCDGJFK ¦4

Answer 1

Building on the clever idea in the answer by #fancyPants. You can use string functions to compare each leg of a route and patch together a full return trip.
I believe this query should work. The first part of the common table expression turns those flights that are round trips into three parts (src-dst-src) and the second part returns those that are one way (as src-dst).
with flights_cte as (
select
USERID,
case when left(flightkey,3) > right(flightkey,3)
then concat(flightkey, left(flightkey,3))
else concat(right(flightkey,3), flightkey)
end as flightkey,
count(*) count
from flights f
where exists (
select 1 from flights where right(f.flightkey,3) = left(flightKey,3)
)
group by
userid,
case
when left(flightkey,3) > right(flightkey,3)
then concat(flightkey, left(flightkey,3))
else concat(right(flightkey,3), flightkey)
end
union all
select userid, FlightKey, count(*)
from flights f
where not exists (
select 1 from flights where right(f.flightkey,3) = left(flightKey,3)
)
group by UserID, FlightKey
)
select flights_cte.userid, flights_cte.flightkey, flights_cte.count
from flights_cte
join (select userid, max(count) _max_count from flights_cte group by userid) _max
on flights_cte.UserID=_max.UserID and flights_cte.count = _max_count
A sample SQL Fiddle gives this output:
| USERID | FLIGHTKEY | COUNT |
|--------|-----------|-------|
| 1 | JFKCDGJFK | 4 |

Answer 2

Assuming routes are not a single row, otherwise you wouldn't be asking.. (although I would guess that the whole route is in some other table, maybe reservation-related)
Guessing the first step is to group this data by person and flights that compose a 'route'. I have an article called T-SQL: Identify bad dates in a time series where the time series can be modified to detect gaps between legs of over a day (guess) to differentiate routes. Second step would be to convert legs into route, i.e. JFK-CDG and CDG-JFK to single value JFK-CDG-JFK.
Then it would be a single query, counting the above single value route, and ORDER BY that count.
Good luck.