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feat: azl397985856#460 lfu cache (azl397985856#69)
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240 changes: 240 additions & 0 deletions problems/460.lfu-cache.md
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## 题目地址
https://leetcode.com/problems/lfu-cache/

## 题目描述

```
Design and implement a data structure for Least Frequently Used (LFU) 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 reaches its capacity, it should invalidate the least frequently used item before inserting a new item. For the purpose of this problem, when there is a tie (i.e., two or more keys that have the same frequency), the least recently used key would be evicted.
Follow up:
Could you do both operations in O(1) time complexity?
Example:
LFUCache cache = new LFUCache( 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.get(3); // returns 3.
cache.put(4, 4); // evicts key 1.
cache.get(1); // returns -1 (not found)
cache.get(3); // returns 3
cache.get(4); // returns 4
```

## 思路
[LFU(Least frequently used)](https://www.wikiwand.com/en/Least_frequently_used) 但内存容量满的情况下,有新的数据进来,需要更多空间的时候,就需要删除被访问频率最少的元素。

举个例子,比如说cache容量是 3,按顺序依次放入 `1,2,1,2,1,3`, cache已存满 3 个元素 (1,2,3), 这时如果想放入一个新的元素 4 的时候,就需要腾出一个元素空间。
用 LFU,这里就淘汰 3, 因为 3 的次数只出现依次, 1 和 2 出现的次数都比 3 多。


题中 `get``put` 都是 `O(1)`的时间复杂度,那么删除和增加都是`O(1)`,可以想到用双链表,和`HashMap`,用一个`HashMap, nodeMap,` 保存当前`key`,和 `node{key, value, frequent} `的映射。
这样`get(key)`的操作就是`O(1)`. 如果要删除一个元素,那么就需要另一个`HashMap,freqMap,`保存元素出现次数`(frequent)`和双链表`(DoublyLinkedlist)` 映射,
这里双链表存的是frequent相同的元素。每次`get``put`的时候,`frequent+1`,然后把`node`插入到双链表的`head node, head.next=node`
每次删除`freqent`最小的双链表的`tail node, tail.prev`

用给的例子举例说明:
```
1. put(1, 1),
- 首先查找nodeMap中有没有key=1对应的value,
没有就新建node(key, value, freq) -> node1(1, 1, 1), 插入 nodeMap,{[1, node1]}
- 查找freqMap中有没有freq=1 对应的value,
没有就新建doublylinkedlist(head, tail), 把node1 插入doublylinkedlist head->next = node1.
如下图,
```
![460.lfu-cache-1](../assets/problems/460.lfu-cache-1.jpg)
```
2. put(2, 2),
- 首先查找nodeMap中有没有key=2对应的value,
没有就新建node(key, value, freq) -> node2(2, 2, 1), 插入 nodeMap,{[1, node1], [2, node2]}
- 查找freqMap中有没有freq=1 对应的value,
没有就新建doublylinkedlist(head, tail), 把node2 插入doublylinkedlist head->next = node2.
如下图,
```
![460.lfu-cache-2](../assets/problems/460.lfu-cache-2.jpg)
```
3. get(1),
- 首先查找nodeMap中有没有key=1对应的value,nodeMap:{[1, node1], [2, node2]},
找到node1,把node1 freq+1 -> node1(1,1,2)
- 更新freqMap,删除freq=1,node1
- 更新freqMap,插入freq=2,node1
如下图,
```
![460.lfu-cache-3](../assets/problems/460.lfu-cache-3.jpg)
```
4. put(3, 3),
- 判断cache的capacity,已满,需要淘汰使用次数最少的元素,找到最小的freq=1,删除双链表tail node.prev
如果tailnode.prev != null, 删除。然后从nodeMap中删除对应的key。
- 首先查找nodeMap中有没有key=3对应的value,
没有就新建node(key, value, freq) -> node3(3, 3, 1), 插入 nodeMap,{[1, node1], [3, node3]}
- 查找freqMap中有没有freq=1 对应的value,
没有就新建doublylinkedlist(head, tail), 把node3 插入doublylinkedlist head->next = node3.
如下图,
```
![460.lfu-cache-4](../assets/problems/460.lfu-cache-4.jpg)
```
5. get(2)
- 查找nodeMap,如果没有对应的key的value,返回 -1。
6. get(3)
- 首先查找nodeMap中有没有key=3对应的value,nodeMap:{[1, node1], [3, node3]},
找到node3,把node3 freq+1 -> node3(3,3,2)
- 更新freqMap,删除freq=1,node3
- 更新freqMap,插入freq=2,node3
如下图,
```
![460.lfu-cache-5](../assets/problems/460.lfu-cache-5.jpg)
```
7. put(4, 4),
- 判断cache的capacity,已满,需要淘汰使用次数最少的元素,找到最小的freq=1,删除双链表tail node.prev
如果tailnode.prev != null, 删除。然后从nodeMap中删除对应的key。
- 首先查找nodeMap中有没有key=4对应的value,
没有就新建node(key, value, freq) -> node4(4, 4, 1), 插入 nodeMap,{[4, node4], [3, node3]}
- 查找freqMap中有没有freq=1 对应的value,
没有就新建doublylinkedlist(head, tail), 把 node4 插入doublylinkedlist head->next = node4.
如下图,
```
![460.lfu-cache-6](../assets/problems/460.lfu-cache-6.jpg)
```
8. get(1)
- 查找nodeMap,如果没有对应的key的value,返回 -1。
9. get(3)
- 首先查找nodeMap中有没有key=3对应的value,nodeMap:{[4, node4], [3, node3]},
找到node3,把node3 freq+1 -> node3(3,3,3)
- 更新freqMap,删除freq=2,node3
- 更新freqMap,插入freq=3,node3
如下图,
```
![460.lfu-cache-7](../assets/problems/460.lfu-cache-7.jpg)
```
10. get(4)
- 首先查找nodeMap中有没有key=4对应的value,nodeMap:{[4, node4], [3, node3]},
找到node4,把node4 freq+1 -> node4(4,4,2)
- 更新freqMap,删除freq=1,node4
- 更新freqMap,插入freq=2,node4
如下图,
```
![460.lfu-cache-8](../assets/problems/460.lfu-cache-8.jpg)

## 关键点分析
用两个`Map`分别保存 `nodeMap {key, node}``freqMap{frequent, DoublyLinkedList}`
实现`get``put`操作都是`O(1)`的时间复杂度。

可以用Java自带的一些数据结构,比如HashLinkedHashSet,这样就不需要自己自建Node,DoublelyLinkedList。
可以很大程度的缩减代码量。

## 代码(Java code)
```java
public class LC460LFUCache {
class Node {
int key, val, freq;
Node prev, next;

Node(int key, int val) {
this.key = key;
this.val = val;
freq = 1;
}
}

class DoubleLinkedList {
private Node head;
private Node tail;
private int size;

DoubleLinkedList() {
head = new Node(0, 0);
tail = new Node(0, 0);
head.next = tail;
tail.prev = head;
}

void add(Node node) {
head.next.prev = node;
node.next = head.next;
node.prev = head;
head.next = node;
size++;
}

void remove(Node node) {
node.prev.next = node.next;
node.next.prev = node.prev;
size--;
}

// always remove last node if last node exists
Node removeLast() {
if (size > 0) {
Node node = tail.prev;
remove(node);
return node;
} else return null;
}
}

// cache capacity
private int capacity;
// min frequent
private int minFreq;
Map<Integer, Node> nodeMap;
Map<Integer, DoubleLinkedList> freqMap;
public LC460LFUCache(int capacity) {
this.minFreq = 0;
this.capacity = capacity;
nodeMap = new HashMap<>();
freqMap = new HashMap<>();
}

public int get(int key) {
Node node = nodeMap.get(key);
if (node == null) return -1;
update(node);
return node.val;
}

public void put(int key, int value) {
if (capacity == 0) return;
Node node;
if (nodeMap.containsKey(key)) {
node = nodeMap.get(key);
node.val = value;
update(node);
} else {
node = new Node(key, value);
nodeMap.put(key, node);
if (nodeMap.size() == capacity) {
DoubleLinkedList lastList = freqMap.get(minFreq);
nodeMap.remove(lastList.removeLast().key);
}
minFreq = 1;
DoubleLinkedList newList = freqMap.getOrDefault(node.freq, new DoubleLinkedList());
newList.add(node);
freqMap.put(node.freq, newList);
}
}

private void update(Node node) {
DoubleLinkedList oldList = freqMap.get(node.freq);
oldList.remove(node);
if (node.freq == minFreq && oldList.size == 0) minFreq++;
node.freq++;
DoubleLinkedList newList = freqMap.getOrDefault(node.freq, new DoubleLinkedList());
newList.add(node);
freqMap.put(node.freq, newList);
}
}
```

## 参考(References)
1. [LFU(Least frequently used) Cache](https://www.wikiwand.com/en/Least_frequently_used)
2. [Leetcode discussion mylzsd](https://leetcode.com/problems/lfu-cache/discuss/94547/Java-O(1)-Solution-Using-Two-HashMap-and-One-DoubleLinkedList)
3. [Leetcode discussion aaaeeeo](https://leetcode.com/problems/lfu-cache/discuss/94547/Java-O(1)-Solution-Using-Two-HashMap-and-One-DoubleLinkedList)

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