LRU Cache
Created: November 11, 2018 by [lek-tin]
Last updated: November 11, 2018
Design and implement a data structure for Least Recently Used (LRU) cache. It should support the following operations: get and put.
get(key) - Get the value (will always be positive) of the key if the key exists in the cache, otherwise return -1.
put(key, value) - Set or insert the value if the key is not already present. When the cache reached its capacity, it should invalidate the least recently used item before inserting a new item.
Follow up:
Could you do both operations in O(1) time complexity?
Example:
LRUCache cache = new LRUCache( 2 /* capacity */ );
cache.put(1, 1);
cache.put(2, 2);
cache.get(1); // returns 1
cache.put(3, 3); // evicts key 2
cache.get(2); // returns -1 (not found)
cache.put(4, 4); // evicts key 1
cache.get(1); // returns -1 (not found)
cache.get(3); // returns 3
cache.get(4); // returns 4
Solution:
import java.util.LinkedHashMap;
import java.util.Map;
public class LRUCache {
private Map<Integer, Integer> cache;
private int capacity;
public LRUCache(int capacity) {
this.capacity = capacity;
cache = new LinkedHashMap<Integer, Integer>(capacity);
}
public int get(int key) {
Integer val = cache.get(key);
if (val == null) return -1;
cache.remove(key);
cache.put(key, val);
return val;
}
public void put(int key, int val) {
cache.remove(key);
cache.put(key, val);
if (cache.size() > capacity) {
cache.remove(cache.entrySet().iterator().next().getKey());
}
}
}
/**
* Your LRUCache object will be instantiated and called as such:
* LRUCache obj = new LRUCache(capacity);
* int param_1 = obj.get(key);
* obj.put(key,value);
*/
Dynamic Link Library / Double linked list, used for insertion and deletion
# Dictionary stores keys with values of nodes. Nodes form
# double linked list containing key, value pairs. DLL is in
# order of use with least recent at head and most recent at tail.
# Time - O(1)
# Space - O(n) set and get: hashmap and linked-list
class Node:
def __init__(self, key, value):
self.key = key
self.value = value
self.prev = None
self.next = None
class DLL:
# head <--> key_1 <--> key_2 <--> key_3 <--> ... <-->tail
def __init__(self):
self.head = Node(None, None) # least recently used, remove at head
self.tail = Node(None, None) # most recently used, add and update at tail
self.head.next = self.tail
self.tail.prev = self.head
def appendToTail(self, node):
# tail is always a placeholder
# head - 1 - 2 - 3 - 4 - 5 - 6 ------ tail
# ↖ node ↗
node.prev = self.tail.prev
self.tail.prev.next = node
node.next = self.tail
self.tail.prev = node
def removeAtHead(self):
# head is always a placeholder
# head - 1 - 2 - 3 - 4 - 5 - 6 - tail
# node
node = self.head.next
node.next.prev = self.head
self.head.next = self.head.next.next
key = node.key
del node
return key
def update(self, node):
# take out from current position
node.prev.next = node.next
node.next.prev = node.prev
# put back at tail
self.appendToTail(node)
class LRUCache(object):
def __init__(self, capacity):
"""
:type capacity: int
"""
self.capacity = capacity
self.queue = DLL()
self.map = {}
def get(self, key):
"""
:rtype: int
"""
if key not in self.map:
return -1
node = self.map[key]
self.queue.update(node)
return node.value
def put(self, key, value):
"""
:type key: int
:type value: int
:rtype: nothing
"""
# Key exists, so we update value and append node to tail
if key in self.map:
node = self.map[key]
node.value = value
self.queue.update(node)
return
else:
# new key
node = Node(key, value)
self.map[key] = node
self.queue.appendToTail(node)
if self.capacity == 0:
# cache is full, remove the oldest
removed_key = self.queue.removeAtHead()
del self.map[removed_key]
else:
# decrement capacity
self.capacity -= 1
Linked Hashmap
from collections import OrderedDict
class LRUCache(OrderedDict):
def __init__(self, capacity: int):
"""
:type capacity: int
"""
self.capacity = capacity
def get(self, key):
"""
:type key: int
:rtype: int
"""
if key not in self:
return - 1
self.move_to_end(key)
return self[key]
def put(self, key, value):
"""
:type key: int
:type value: int
:rtype: void
"""
if key in self:
self.move_to_end(key)
self[key] = value
if len(self) > self.capacity:
self.popitem(last = False)
# Your LRUCache object will be instantiated and called as such:
# obj = LRUCache(capacity)
# param_1 = obj.get(key)
# obj.put(key,value)