Comment on page
LRU-cache
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.
The cache is initialized with a positive capacity.
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
Make use of Java library, LinkedHashMap, ordered and keep track of map size.
- when insert into new (key,value) into map, check map already reach capacity or not:
- if reach capacity, then remove last value from map, insert (key, value) into head of map
- if not reach capacity, insert into head of map
- when fetch value by key, check whether key in map or not:
- if key not in map, return -1
- if key in map, get value by key, remove current key from map, insert current key into head of map
Time Complexity:
O(N)Space Complexity:
O(M)- N - N operation times
- M - M is the capacity
class LRUCache {
private LinkedHashMap<Integer, Integer> map;
private int capacity;
public LRUCache(int capacity) {
map = new LinkedHashMap<>(capacity);
this.capacity = capacity;
}
public int get(int key) {
if (!map.containsKey(key)) return -1;
int value = map.remove(key);
map.put(key, value);
return value;
}
public void put(int key, int value) {
if (map.containsKey(key)) {
map.remove(key);
} else if (map.size() >= capacity) {
map.remove(map.keySet().iterator().next());
}
map.put(key, value);
}
}
public class LRUCache {
private Map<Integer, DoubleLinkedList> map;
private int capacity;
private DoubleLinkedList head;
private DoubleLinkedList tail;
public LRUCache(int capacity) {
map = new HashMap<>(capacity);
this.capacity = capacity;
}
public int get(int key) {
// if key not in map, return -1
if (!map.containsKey(key)) return -1;
// if key in map, remove current node, insert current node into head
DoubleLinkedList node = map.get(key);
remove(node);
setHead(node);
return node.val;
}
public void put(int key, int value) {
// if key in map, remove current node, and insert into head
if (map.containsKey(key)) {
DoubleLinkedList node = map.get(key);
remove(node);
node.val = value;
setHead(node);
} else {
// key not in map, check current map is already reach capacity,
// if yes, then remove last node, and insert current node into head
// if not, insert current node into head
// put current node into map
DoubleLinkedList newNode = new DoubleLinkedList(key, value);
if (map.size() >= capacity) {
map.remove(tail.key);
remove(tail);
}
setHead(newNode);
map.put(key, newNode);
}
}
private void remove(DoubleLinkedList node) {
if (node.pre != null) {
node.pre.next = node.next;
} else {
head = node.next;
}
if (node.next != null) {
node.next.pre = node.pre;
} else {
tail = node.pre;
}
}
private void setHead(DoubleLinkedList node) {
node.pre = null;
node.next = head;
if (head != null) {
head.pre = node;
}
head = node;
if (tail == null) {
tail = head;
}
}
class DoubleLinkedList {
int key;
int val;
DoubleLinkedList pre;
DoubleLinkedList next;
public DoubleLinkedList(int key, int val) {
this.key = key;
this.val = val;
}
}
}
Last modified 3yr ago