Cache LRU (Least Recently Used) iotja l-element li ma kienx aċċessat għal aktar żmien meta tilħaq l-kapaċità. Id-disinn klassiku jgħaqqad hash map (lookup O(1)) ma doubly linked list (O(1) reordering), u jagħti O(1) get u put.
Disinn ta' żewġ strutturi
HashMap: key -> node DLL (recency order):
MRU <-> ... <-> LRU
get/put: map finds node move touched node to front (MRU)
in O(1); DLL splices it evict the tail (LRU) when full
to the front in O(1)
Code
from collections import OrderedDict
class LRUCache:
def __init__(self, capacity):
self.cap = capacity
self.cache = OrderedDict() # preserves access order
def get(self, key): # O(1)
if key not in self.cache:
return -1
self.cache.move_to_end(key) # mark as most recently used
return self.cache[key]
def put(self, key, value): # O(1)
if key in self.cache:
self.cache.move_to_end(key)
self.cache[key] = value
if len(self.cache) > self.cap:
self.cache.popitem(last=False) # evict least recently used
OrderedDict hu innifsu hash map flimkien ma doubly linked list, eżattament l-istruttura deskritta hawn fuq.
| Operazzjoni | Ħin |
|---|---|
| get | O(1) |
| put | O(1) |
| space | O(capacity) |
Għaliex doubly linked list
Douubly linked list ippermettik tneħħi node miċ-ċentru f'O(1) (għandek il-prev/next tiegħu), li huwa impossibbli ma singly linked list jew array mingħajr O(n) shift.
Għaliex huwa importanti
Cache LRU jiffunzjonaw quddiem databases, web servers, u CPU biex iżommu data sħun veloċi u memorja limitata.
Hi din il-problema pyesa standard fl-intervisti senior għaliex tittesta l-għaqda ta' żewġ strutturi sabiex ir-restrizzjoni ta' waħda tipprovditu minn oħra — skill essenzjali tad-disinn tas-sistema.