CareerCup

This is nothing but LRU cache.

What are we designing for? Space? Time?

If space is available and we can keep all data:

Solution #1
 - Simple solution keep sorted list O(nlogn)
 - return proper slice of list for the queried time O(logN)

Solution #2
 - Create BST and insert into tree O(logN)
 - return subtree whos time is less than the queried time O(logN)

If for space, assume were feed the hashtags one at time

Solution #1
 - N = 10
 - Create three sorted bins of size N elements. For 1min, 10min, 1hr
 - create helper function refresh:
   - In bin1Min, remove expired items, and bubble up to bin10Min or bin1hr  if applicable
   - in bin10Min, remove expired items, and bubble up to bin1hr if applicable
   - in bin1hr, remove expired items.
 - on insert
   - call refresh()
   - insert new item into proper bin based on current time difference
    - find insert position( selection sort since N is small )
    - if over threshold of elements, insert new item in front, and pop last
    - if poped, bubble up if applicable

Do you guys think the above solution would work? Would love some feedback.