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Question
Formatted question description: https://leetcode.ca/all/146.html
146 LRU Cache
Design and implement a data structure for Least Recently Used (LRU) cache.
It should support the following operations: get and set.
get(key) - Get the value (will always be positive) of the key if the key exists in the cache, otherwise return -1.
set(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.
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
Follow up:
Could you do both operations in O(1) time complexity?
@tag-design
Algorithm
Solution
Create a class MyNode
, which contains data fields int key
, int value
, Node prev
and Node next
. That is, each node of type MyNode
has a key and a value, and have references to its previous node and the next node.
In class LRUCache
, data fields include int capacity
that stores the capacity of the cache, Map<Integer, MyNode> map
that maps each key to its node, MyNode head
and Node tail
that represents the head node and the tail node respectively. For Least Recently Used cache, the most recently used node is the head node and the least recently used node is the tail node.
In the constructor, initialize capacity
with the given capacity
.
In get(key)
, if key
is not in map
, then key
is not in the cache, so return -1. If key
is in map
, obtain the node and its value
, remove the node and set the node to be the head, and return value
.
In put(key, value)
, if map
contains key
, then obtain the node and update its value
, remove the node, and set the node to be the head. If map
does not contain key
, then create a new node using key
and value
, and set the new node to be the head. If the size of map
is greater than or equal to capacity
, then remove the node tail
and remove the corresponding entry in map
. Add a new entry of the new node into the map.
Two supplementary methods are needed.
- Method
remove(MyNode node)
. ObtainMyNode
’s previous node and next node, and update their references to other nodes accordingly. IfMyNode
ishead
ortail
, then updatehead
ortail
accordingly. - Method
setHead(MyNode node)
. SetMyNode
to be the new head and set the previous head’s reference accordingly. Iftail
isnull
, then updatetail
as well.
Code
Java
-
class LRUCache { int capacity; Map<Integer, MyNode> map = new HashMap<Integer, MyNode>(); // key => Node[key,val] MyNode head = null; MyNode tail = null; public LRUCache(int capacity) { this.capacity = capacity; } public int get(int key) { MyNode node = map.get(key); if (node == null) { return -1; } else { remove(node); setHead(node); return node.value; } } public void put(int key, int value) { if (map.containsKey(key)) { MyNode node = map.get(key); node.value = value; remove(node); setHead(node); } else { MyNode node = new MyNode(key, value); setHead(node); map.put(key, node); if (map.size() >= capacity) { // @note: also = , after if will add one more map.remove(tail.key); remove(tail); } } } public void remove(MyNode node) { MyNode prev = node.prev; MyNode next = node.next; // process previous node if (prev != null) prev.next = next; else head = next; // process next node if (next != null) next.prev = prev; else tail = prev; } public void setHead(MyNode node) { node.next = head; node.prev = null; if (head != null) head.prev = node; head = node; if (tail == null) tail = head; } } class MyNode { int key; int value; MyNode prev; MyNode next; public MyNode(int key, int value) { this.key = key; this.value = value; } } /** * 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); */
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// OJ: https://leetcode.com/problems/lru-cache // Time: // LRUCache: O(1) // get: O(1) // put: O(1) // Space: O(N) class LRUCache { int capacity; list<pair<int, int>> data; unordered_map<int, list<pair<int, int>>::iterator> m; void moveToFront(int key) { auto node = m[key]; data.splice(data.begin(), data, node); m[key] = data.begin(); } public: LRUCache(int capacity) : capacity(capacity) {} int get(int key) { // get node given key, put the node at the beginning of the list, return the value in the node if (m.count(key)) { moveToFront(key); return m[key]->second; } return -1; } void put(int key, int value) { // if key exists in the map, get node given key, put the node at the beginning of the list and update the value in the node // otherwise, put a new node at the beginning of the list with the <key, value> and update the map. If capacity exceeded, remove the last node from the list and map. if (m.count(key)) { moveToFront(key); m[key]->second = value; } else { data.emplace_front(key, value); m[key] = data.begin(); if (data.size() > capacity) { m.erase(data.rbegin()->first); data.pop_back(); } } } };
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class Node: def __init__(self, key=0, val=0): self.key = key self.val = val self.prev = None self.next = None class LRUCache: def __init__(self, capacity: int): self.cache = {} self.head = Node() self.tail = Node() self.capacity = capacity self.size = 0 self.head.next = self.tail self.tail.prev = self.head def get(self, key: int) -> int: if key not in self.cache: return -1 node = self.cache[key] self.move_to_head(node) return node.val def put(self, key: int, value: int) -> None: if key in self.cache: node = self.cache[key] node.val = value self.move_to_head(node) else: node = Node(key, value) self.cache[key] = node self.add_to_head(node) self.size += 1 if self.size > self.capacity: node = self.remove_tail() self.cache.pop(node.key) self.size -= 1 def move_to_head(self, node): self.remove_node(node) self.add_to_head(node) def remove_node(self, node): node.prev.next = node.next node.next.prev = node.prev def add_to_head(self, node): node.next = self.head.next node.prev = self.head self.head.next = node node.next.prev = node def remove_tail(self): node = self.tail.prev self.remove_node(node) return node # Your LRUCache object will be instantiated and called as such: # obj = LRUCache(capacity) # param_1 = obj.get(key) # obj.put(key,value) ############ ''' example: >>> od = collections.OrderedDict() >>> >>> od[1]=1 >>> od[2]=2 >>> od[3]=3 >>> >>> od OrderedDict([(1, 1), (2, 2), (3, 3)]) >>> >>> od.move_to_end(1) >>> >>> od OrderedDict([(2, 2), (3, 3), (1, 1)]) >>> >>> od.get(1) 1 >>> >>> od.popitem() (1, 1) >>> >>> od OrderedDict([(2, 2), (3, 3)]) >>> >>> od[1]=1 >>> od OrderedDict([(2, 2), (3, 3), (1, 1)]) >>> >>> od.popitem(last=False) (2, 2) >>> od OrderedDict([(3, 3), (1, 1)]) ''' import collections class LRUCache: def __init__(self, capacity: 'int'): self.cache = collections.OrderedDict() self.remain = capacity def get(self, key: 'int') -> 'int': if key not in self.cache: return -1 self.cache.move_to_end(key) # meaning end is the most recently used return self.cache.get(key) def put(self, key: 'int', value: 'int') -> 'None': if key not in self.cache: if self.remain > 0: self.remain -= 1 else: self.cache.popitem(last=False) # pop start position else: self.cache.pop(key) self.cache[key] = value # add to end of dict, meaning most recently used ### below solution with no ordered-dict class DLinkedNode: def __init__(self, key=0, value=0): self.key = key self.val = value self.next = None self.prev = None class DLinkedList: def __init__(self): self.head = DLinkedNode() # dummy head, its next is real head self.tail = DLinkedNode() # dummy tail, its prev is real tail self.head.next, self.tail.prev = self.tail, self.head def add_node(self, node): # add to head node.prev, node.next = self.head, self.head.next node.next.prev, node.prev.next = node, node def remove_node(self, node): node.prev.next, node.next.prev = node.next, node.prev return node.key def remove_tail(self): return self.remove_node(self.tail.prev) # dummy tail's prev is real tail def move_to_head(self, node): self.remove_node(node) self.add_node(node) # def __repr__(self): # ans = [] # h = self.head # while h: # ans.append(str(h.val)) # h = h.next # return '<DLinkedList: {}>'.format('->'.join(ans)) class LRUCache: def __init__(self, capacity: int): self.capacity = capacity self.nodes_map = {} self.cache_list = DLinkedList() def get(self, key: int) -> int: node = self.nodes_map.get(key, None) if node: self.cache_list.move_to_head(node) return node.val else: return -1 def put(self, key: int, value: int) -> None: node = self.nodes_map.get(key, None) if not node: if self.capacity > 0: self.capacity -= 1 else: rm_key = self.cache_list.remove_tail() self.nodes_map.pop(rm_key) # note api new_node = DLinkedNode(key, value) self.nodes_map[key] = new_node self.cache_list.add_node(new_node) else: self.cache_list.move_to_head(node) node.val = value