43. Merge Sorted Array && LRU Cache

Merge Sorted Array

OJ: https://oj.leetcode.com/problems/merge-sorted-array/

Given two sorted integer arrays A and B, merge B into A as one sorted array.

Note: You may assume that A has enough space (size that is greater or equal to m + n) to hold additional elements from B. The number of elements initialized in A and B are m and n respectively.

思想：因为 A 很大， 所以从最大值开始插入， 即从 A 的 m+n 位置开始插入数据。避免了冗余的移动。

class Solution {
public:
    void merge(int A[], int m, int B[], int n) {
        int end = m+n-1;
        int iA = m-1, iB = n-1;
        while(iB >= 0) {
            if(iA < 0 || A[iA] <= B[iB])  A[end--] = B[iB--];
            else A[end--] = A[iA--];
        }
    }
};

LRU Cache

OJ: https://oj.leetcode.com/problems/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.

思想：

1. 由于要 O(1) 时间确定某 key 是不是在 Cache 中，所以用 Hash_map (<key, node*>), 从而能够O(1)找到结点地址，返回对应的 value。

2. 由于要 O(1) 时间插入、删除某项， 所以各项之间的存储不能用单链表（删除时要O(n)查找前面的结点），不能用顺序表(插入、删除都 O(n)), 故存储使用双链表。

综上分析，查找、插入、删除都是 O(1)时间。（代码尚可优化）

typedef struct node {
	node *pre, *next;
	int key;
	int value;
	node() : pre(NULL), next(NULL), key(0), value(0) {}
	node(int k, int v) : pre(NULL), next(NULL), key(k), value(v) {}
} DoubleLinkList;

class LRUCache{
public:
	LRUCache(int capacity) : _capacity(capacity), cnt(0), front(NULL), tail(NULL) {}

	int get(int key) {
		unordered_map<int, node*>::iterator it = _map.find(key);
		if(it == _map.end()) return -1;

		node* s = it->second;
		if(s != front) {
			if(s == tail) {
			    tail = s->pre;
			    s->pre = NULL;
			    tail->next = NULL;
				front->pre = s;
				s->next = front;
				front = s;
			}else {
				s->pre->next = s->next;
				s->next->pre = s->pre;
				s->next = front;
				front->pre = s;
				front = s;
			}
		}
		return it->second->value;
	}
	void set(int key, int value) {
		unordered_map<int, node*>::iterator it = _map.find(key);
		if(it == _map.end()) {
			if(++cnt > _capacity) {
				if(front == tail) {
					_map.erase(tail->key);
					front = tail = NULL;

				}else{
					node *s = tail;
					tail = tail->pre;
					tail->next = NULL;
					_map.erase(s->key);
					free(s);
					--cnt;
				}
			}
			node *p = new node(key, value);
			if(front == NULL) {
				front = tail = p;
			}else {
				p->next = front;
				front->pre = p;
				front = p;
			}
			_map.insert(pair<int, node*>(key, p));
		}else {
			it->second->value = value;
			node *s = it->second;
			if(s == front) {
				return;
			}else if(s == tail) {
			    tail = s->pre;
			    s->pre = NULL;
				tail->next = NULL;
				s->next = front;
				front->pre = s;
				front = s;
			}else {
				s->pre->next = s->next;
				s->next->pre = s->pre;
				s->pre = NULL;
				s->next = front;
				front->pre = s;
				front = s;
			}
		}
	}
	unordered_map<int, node*> _map;
	DoubleLinkList *front, *tail;
	int _capacity;
	int cnt;
};