LeetCode 382 Linked List Random Node

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Given a singly linked list, return a random node’s value from the linked list. Each node must have the same probability of being chosen.

Follow up:
What if the linked list is extremely large and its length is unknown to you? Could you solve this efficiently without using extra space?

Example:

// Init a singly linked list [1,2,3].ListNode head = new ListNode(1);head.next = new ListNode(2);head.next.next = new ListNode(3);Solution solution = new Solution(head);// getRandom() should return either 1, 2, or 3 randomly. Each element should have equal probability of returning.solution.getRandom();

大意是说给你一个链表,长度未知,等概率随机选出一个。这就需要蓄水池算法。
蓄水池算法用于解决在N个元素中等概率随机选出k个(0<k<N).N可以未知或者很大。
具体做法如下:
1 给N个元素标号为1-N
2 遍历,将前k个元素加入候选集合
3 当标号大于k时,假设为i,如果元素只有i个,那么每个元素被选中的概率应该是k/i,为此做如下操作:
对第i个元素,以k/i的概率将i号元素加入候选集合,以1/k的概率从候选集合中移除一个原来元素。如果每个元素留在集合的概率是i/k那么算法就正确。
证明(数学归纳法):
3.1 当i=k+1时,第i个元素加入候选集合的概率是1/i,前i个元素被留下概率是1-(k/(k+1))*(1/k)=k/(k+1)
3.2 当i>k时,假设前i个元素每一个被加入候选集合的概率是k/i
3.3 当i=i+1时,前i个元素每一个被加入候选集合的概率是(k/i)*(1-(k/(i+1))*(1/k)),化简可得k/(i+1),第i+1个显然也是k/(i+1)
3.4 得证
具体到这个题只要把k换成1就行了。代码如下:

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  public static void main(String[] args) {        // TODO Auto-generated method stub        Random ran = new Random();        System.out.println(ran.nextInt(1));    }    public class ListNode {        int val;        ListNode next;         ListNode(int x) {            val = x;        }    }     ListNode head;    Random ran;     public Solution_382(ListNode head) {        this.head = head;        ran = new Random();    }     /** Returns a random node's value. */    public int getRandom() {        ListNode node = head;        int current = 0;        for (int i = 1; node != null; i++) {            current = ran.nextInt(i) == 0 ? node.val : current;            node=node.next;        }        return current;    }
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