第五周 技术选型（1）作业

package com.company.gitdemo;
import java.util.*;
public class ConsistenceHash {
    public ConsistenceHash() {
    }
    public ConsistenceHash(int viretalNums) {
        this.viretalNums = viretalNums;
    }
    // 物理节点集合
    private List<String> realNodes = new ArrayList<>();
    // 虚拟节点数，用户指定
    private int viretalNums = 100;
    // 物理节点存储数据数量
    private Map<String,Integer> nodeKvCount = new HashMap<>();
    // 排序存储结构红黑树，key是虚拟节点的hash值，value是物理节点
    private SortedMap<Long,String> sortedMap = new TreeMap<>();
    //添加服务器节点
    public void addNode(String node) {
        String vnode = null;
        int i = 0;
        for (int count = 0; count < viretalNums; ) {
            i++;
            vnode = node + "_" + i;
            long hasValue = hash(vnode);
            if(!this.sortedMap.containsKey(hasValue)){
                count++;
                sortedMap.put(hasValue, node);
            }
        }
        nodeKvCount.put(node,0);
        this.realNodes.add(node);
    }
    //获取服务器节点
    public String getNode(String key) {
        long hash = hash(key);
        SortedMap<Long, String> map = this.sortedMap.tailMap(hash);
        String node;
        if (map.isEmpty()) {
            node= this.sortedMap.get(sortedMap.firstKey());
        } else {
            node= map.get(map.firstKey());
        }
        nodeKvCount.put(node,nodeKvCount.get(node)+1);
        return node;
    }
    //获取服务器节点数据分布标准差
    public double getStandardDeviation(int sumCount) {
        //平均值
        double avg=sumCount/realNodes.size();
        //方差
        int total = 0;
        for (Map.Entry<String, Integer> entry : nodeKvCount.entrySet()) {
            total += (entry.getValue() - avg) * (entry.getValue() - avg);
        }
        //标准差
        double standardDeviation = Math.sqrt(total / realNodes.size());
        return standardDeviation;
    }
    /**
     * 使用FNV1_32_HASH
     */
    private   long hash(String  key) {
        final int p = 16777619;
        int hash = (int) 2166136261L;
        for (int i = 0; i < key.length(); i++) {
            hash = (hash ^ key.charAt(i)) * p;
        }
        hash += hash << 13;
        hash ^= hash >> 7;
        hash += hash << 3;
        hash ^= hash >> 17;
        hash += hash << 5;
        // 如果算出来的值为负数则取其绝对值
        if (hash < 0) {
            hash = Math.abs(hash);
        }
        return hash;
    }
}

package com.company.gitdemo;
public class Main {
    public static void main(String[] args) {
        ConsistenceHash consistenceHash = new ConsistenceHash(150);
        consistenceHash.addNode("193.168.1.9");
        consistenceHash.addNode("193.168.1.11");
        consistenceHash.addNode("193.168.1.53");
        consistenceHash.addNode("193.168.1.13");
        consistenceHash.addNode("193.168.1.14");
        consistenceHash.addNode("193.168.1.77");
        consistenceHash.addNode("193.168.1.26");
        consistenceHash.addNode("193.168.1.36");
        consistenceHash.addNode("193.168.1.45");
        consistenceHash.addNode("193.168.1.14");
        //存储
        int  sumCount=1000000;
        for (int i = 0; i < sumCount; i++) {
            consistenceHash.getNode("a" + i);
        }
        double standardDeviation=consistenceHash.getStandardDeviation(sumCount);
        System.out.println("标准差：" + standardDeviation);
    }
}