I think I got it:
dt <- cc[rep(1:.N, installments)][, Indx := 1:.N, by = .(period, customer, installments)] dt[, period := period + Indx - 1] dt[, inst_pay := purchase/installments] dt[, spending := sum(inst_pay), by = .(period, customer)] setorder(dt, customer, period) print(dt)
period customer purchase installments Indx inst_pay spending 1: 1 1 90 3 1 30 30 2: 2 1 90 3 2 30 40 3: 2 1 20 2 1 10 40 4: 3 1 90 3 3 30 50 5: 3 1 20 2 2 10 50 6: 3 1 10 1 1 10 50 7: 1 2 50 2 1 25 25 8: 2 2 50 2 2 25 55 9: 2 2 60 2 1 30 55 10: 3 2 60 2 2 30 40 11: 3 2 10 1 1 10 40

Just out of curiosity I've taken a look at what happens under the hood, and I've used [dtruss/strace][1] on each test.
C++
./a.out < in Saw 6512403 lines in 8 seconds. Crunch speed: 814050
syscalls `sudo dtruss -c ./a.out < in`
CALL COUNT __mac_syscall 1 <snip> open 6 pread 8 mprotect 17 mmap 22 stat64 30 read_nocancel 25958

Python
./a.py < in Read 6512402 lines in 1 seconds. LPS: 6512402
syscalls `sudo dtruss -c ./a.py < in`
CALL COUNT __mac_syscall 1 <snip> open 5 pread 8 mprotect 17 mmap 21 stat64 29
[1]: http://en.wikipedia.org/wiki/Strace