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思路：用map+链表实现，map用来提高查询速度，链表用来存放元素。链表头放入最新的元素，表尾为最老元素。访问cache命中，或者cache满写入时都需要对链表内容和map进行调整。
JDK里面有一个LinkedHashMap就是基于这个思路实现的。
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.
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public class LRUCache {
static class Node {
int key;
int value;
@Override
public String toString() {
return "Node{" +
"key=" + key +
", value=" + value +
'}';
}
}
static private LinkedList<Node> cache;
static private int cap;
static private Node indexMap[];
public LRUCache(int capacity) {
cache = new LinkedList<Node>();
indexMap = new Node[100000];
cap = capacity;
}
static public boolean isFull() {
return cache.size() == cap;
}
static public Node find(int key) {
if (cache.isEmpty())
return null;
Node tar = null;
if ((tar = indexMap[key]) == null)
return null;
cache.remove(tar);
cache.addFirst(tar);
return tar;
}
public int get(int key) {
Node node = find(key);
if (node == null) {
return -1;
}
return node.value;
}
public void set(int key, int value) {
Node node = null;
if ((node = find(key)) != null) {
node.value = value;
return;
}
//not find the element
if (isFull()) {
indexMap[cache.getLast().key] = null;
cache.removeLast();
}
Node newNode = new Node();
newNode.key = key;
newNode.value = value;
cache.addFirst(newNode);
indexMap[key] = newNode;
}
}