This might be done by comparing matrices of sales and returns. The function below seems to be close to what you want. It doesn't exactly match your example, but your example has cases where returns are made before the transactions. Was this intentional?
The code should run faster than a looping solution. Code: NB. hui progressive index NB. http://code.jsoftware.com/wiki/Essays/Progressive_Index-Of oc=: i.~ (] - {) /:@/: pi=: #@[ ({. i.&(,.oc) }.) [ i. , NB. argument is 3-col table of seq,key,qty NB. result is the unmatched transactions matchtrans=: 3 : 0 msk=. 0<{:"1 y sales=. msk#y returns=. (-.msk)#y ndx=. (}."1 sales) pi | }."1 returns cancels=. ndx<#sales ((<<<cancels#ndx){sales),(-.cancels)#returns ) Example: dat=: ".;._2 (0 : 0) 1 1 1 2 1 _1 3 1 1 4 2 1 5 2 1 6 2 3 7 2 _1 8 2 _1 9 3 5 10 3 _2 11 3 2 ) matchtrans dat 3 1 1 6 2 3 9 3 5 On Wed, Apr 12, 2017 at 9:35 AM, Joe Bogner <[email protected]> wrote: > I have a problem I'm trying to solve in different languages. I have a > solution in SQL and also in kdb which largely resembles the SQL solution. > I'm curious what a J solution would look like. More specifically, I'm > interested in picking the brains of others here to see if this type of > problem can be solved without looping (some form of scan?). > > EDIT: Initially I wrote this up thinking the J solution would difficult, > but it was actually fairly straightforward -- about 15 minutes, but still > would like to see if there are alternatives. If nothing else, maybe an > interesting problem to share. > > Example data: > > A store has a transaction log with a sequence for each transaction. The > transaction log records a key for a unique customer/item combination. The > transaction log records how many units were purchased or returned. > > Goal: > Attempt to match up related transactions and cancel out instances when the > customer/item combination is returned at the same quantity as a previous > transaction > > Examples: > > Joe buys 1 blue pen, which is defective, then returns the 1 defective blue > pen, then buys another blue pen. EXPECTED: cancel out first two > transactions and leave the the last one for 1 pen > > Bob buys 2 red pens in two separate transactions. He then buys 3 more. He > returns the first two purchases as two separate return transactions. > EXPECTED: cancel out all transactions except the one for qty 3 > > Jane buys 5 purple pens and subsequently returns two of them. She buys two > more. EXPECTED: No transactions match exactly, so nothing is cancelled out > > > Data: > > data=: 0 : 0 > seq key qty > 1 1 1 > 2 1 _1 > 3 1 1 > 4 2 1 > 5 2 1 > 6 2 3 > 7 2 _1 > 8 2 _1 > 9 3 5 > 10 3 _2 > 11 3 2 > ) > tbl =: ,. ' ' cut every cutLF data > 'seqs keys qtys' =: |: ". every }. tbl > > > Goal: > > goals =: 0 : 0 > > goal > > cancelled > > credit > > ok > > cancelled > > cancelled > > ok > > credit > > credit > > ok > > ok > > ok > > ) > > > > > tbl,.(cutLF goals) > > +---+---+---+---------+ > > |seq|key|qty|goal | > > +---+---+---+---------+ > > |1 |1 |1 |cancelled| > > +---+---+---+---------+ > > |2 |1 |_1 |credit | > > +---+---+---+---------+ > > |3 |1 |1 |ok | > > +---+---+---+---------+ > > |4 |2 |1 |cancelled| > > +---+---+---+---------+ > > |5 |2 |1 |cancelled| > > +---+---+---+---------+ > > |6 |2 |3 |ok | > > +---+---+---+---------+ > > |7 |2 |_1 |credit | > > +---+---+---+---------+ > > |8 |2 |_1 |credit | > > +---+---+---+---------+ > > |9 |3 |5 |ok | > > +---+---+---+---------+ > > |10 |3 |_2 |ok | > > +---+---+---+---------+ > > |11 |3 |2 |ok | > > +---+---+---+---------+ > > > > One approach: > > applycredits =: 3 : 0 > > goals=.(<'goal') > > creditids=.0 > > for_i. (i. # seqs) do. > > key=.i{keys > > seq=.i{seqs > > qty=.i{qtys > > nextcredit =.| {. qtys #~ ((key=keys)*(seqs>seq)*(qtys<0)) > > if. nextcredit = qty do. > > goals=.goals,<'cancelled' > > creditids =. creditids, seqs #~ ((key=keys)*(seqs>seq)*(qtys<0)) > > elseif. creditids e.~ seq do. > > goals=.goals,<'credit' > > elseif. do. > > goals=.goals,<'ok' > > end. > > end. > > goals > > ) > > tbl ,. ( applycredits 0 ) > > > +---+---+---+---------+ > > |seq|key|qty|goal | > > +---+---+---+---------+ > > |1 |1 |1 |cancelled| > > +---+---+---+---------+ > > |2 |1 |_1 |credit | > > +---+---+---+---------+ > > |3 |1 |1 |ok | > > +---+---+---+---------+ > > |4 |2 |1 |cancelled| > > +---+---+---+---------+ > > |5 |2 |1 |cancelled| > > +---+---+---+---------+ > > |6 |2 |3 |ok | > > +---+---+---+---------+ > > |7 |2 |_1 |credit | > > +---+---+---+---------+ > > |8 |2 |_1 |credit | > > +---+---+---+---------+ > > |9 |3 |5 |ok | > > +---+---+---+---------+ > > |10 |3 |_2 |ok | > > +---+---+---+---------+ > > |11 |3 |2 |ok | > > +---+---+---+---------+ > > > > (cutLF goals) -: ( applycredits 0 ) > > 1 > > > thanks for any input > ---------------------------------------------------------------------- > For information about J forums see http://www.jsoftware.com/forums.htm ---------------------------------------------------------------------- For information about J forums see http://www.jsoftware.com/forums.htm
