LRU 缓存机制

题目

运用你所掌握的数据结构,设计和实现一个  LRU (最近最少使用) 缓存机制 。
实现 LRUCache 类:

LRUCache(int capacity) 以正整数作为容量 capacity 初始化 LRU 缓存
int get(int key) 如果关键字 key 存在于缓存中,则返回关键字的值,否则返回 -1
void put(int key, int value) 如果关键字已经存在,则变更其数据值;如果关键字不存在,则插入该组「关键字-值」。当缓存容量达到上限时,它应该在写入新数据之前删除最久未使用的数据值,从而为新的数据值留出空间。

题解

哈希表

class ListNode {
  constructor(key, value) {
    this.key = key
    this.value = value
    this.next = null
    this.prev = null
  }
}

class LRUCache {
  constructor(capacity) {
    this.capacity = capacity
    this.hashTable = {}
    this.count = 0
    this.dummyHead = new ListNode()
    this.dummyTail = new ListNode()
    this.dummyHead.next = this.dummyTail
    this.dummyTail.prev = this.dummyHead
  }

  get(key) {
    let node = this.hashTable[key]
    if (node == null) return -1
    this.moveToHead(node)
    return node.value
  }

  put(key, value) {
    let node = this.hashTable[key]
    if (node == null) {
      let newNode = new ListNode(key, value)
      this.hashTable[key] = newNode
      this.addToHead(newNode)
      this.count++
      if (this.count > this.capacity) {
        this.removeLRUItem()
      }
    } else {
      node.value = value
      this.moveToHead(node)
    }
  }

  moveToHead(node) {
    this.removeFromList(node)
    this.addToHead(node)
  }

  removeFromList(node) {
    let tempForPrev = node.prev
    let tempForNext = node.next
    tempForPrev.next = tempForNext
    tempForNext.prev = tempForPrev
  }

  addToHead(node) {
    node.prev = this.dummyHead
    node.next = this.dummyHead.next
    this.dummyHead.next.prev = node
    this.dummyHead.next = node
  }

  removeLRUItem() {
    let tail = this.popTail()
    delete this.hashTable[tail.key]
    this.count--
  }

  popTail() {
    let tailItem = this.dummyTail.prev
    this.removeFromList(tailItem)
    return tailItem
  }
}

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