一致性雜湊演算法的原理與實現

/**
 * @author: https://kefeng.wang
 * @date: 2018-08-10 11:08
 **/
public class ConsistentHashing {
// 物理節點
private Set<String> physicalNodes = new TreeSet<String>() {
{
add("192.168.1.101");
add("192.168.1.102");
add("192.168.1.103");
add("192.168.1.104");
}
};

//虛擬節點
private final int VIRTUAL_COPIES = 1048576; // 物理節點至虛擬節點的複製倍數
private TreeMap<Long, String> virtualNodes = new TreeMap<>(); // 雜湊值 => 物理節點

// 32位的 Fowler-Noll-Vo 雜湊演算法
// https://en.wikipedia.org/wiki/Fowler–Noll–Vo_hash_function
private static Long FNVHash(String key) {
final int p = 16777619;
Long hash = 2166136261L;
for (int idx = 0, num = key.length(); idx < num; ++idx) {
hash = (hash ^ key.charAt(idx)) * p;
}
hash += hash << 13;
hash ^= hash >> 7;
hash += hash << 3;
hash ^= hash >> 17;
hash += hash << 5;

if (hash < 0) {
hash = Math.abs(hash);
}
return hash;
}

// 根據物理節點，構建虛擬節點對映表
public ConsistentHashing() {
for (String nodeIp : physicalNodes) {
addPhysicalNode(nodeIp);
}
}

// 新增物理節點
public void addPhysicalNode(String nodeIp) {
for (int idx = 0; idx < VIRTUAL_COPIES; ++idx) {
long hash = FNVHash(nodeIp + "#" + idx);
virtualNodes.put(hash, nodeIp);
}
}

// 刪除物理節點
public void removePhysicalNode(String nodeIp) {
for (int idx = 0; idx < VIRTUAL_COPIES; ++idx) {
long hash = FNVHash(nodeIp + "#" + idx);
virtualNodes.remove(hash);
}
}

// 查詢物件對映的節點
public String getObjectNode(String object) {
long hash = FNVHash(object);
SortedMap<Long, String> tailMap = virtualNodes.tailMap(hash); // 所有大於 hash 的節點
Long key = tailMap.isEmpty() ? virtualNodes.firstKey() : tailMap.firstKey();
return virtualNodes.get(key);
}

// 統計物件與節點的對映關係
public void dumpObjectNodeMap(String label, int objectMin, int objectMax) {
// 統計
Map<String, Integer> objectNodeMap = new TreeMap<>(); // IP => COUNT
for (int object = objectMin; object <= objectMax; ++object) {
String nodeIp = getObjectNode(Integer.toString(object));
Integer count = objectNodeMap.get(nodeIp);
objectNodeMap.put(nodeIp, (count == null ? 0 : count + 1));
}

// 列印
double totalCount = objectMax - objectMin + 1;
System.out.println("======== " + label + " ========");
for (Map.Entry<String, Integer> entry : objectNodeMap.entrySet()) {
long percent = (int) (100 * entry.getValue() / totalCount);
System.out.println("IP=" + entry.getKey() + ": RATE=" + percent + "%");
}
}

public static void main(String[] args) {
ConsistentHashing ch = new ConsistentHashing();

// 初始情況
ch.dumpObjectNodeMap("初始情況", 0, 65536);

// 刪除物理節點
ch.removePhysicalNode("192.168.1.103");
ch.dumpObjectNodeMap("刪除物理節點", 0, 65536);

// 新增物理節點
ch.addPhysicalNode("192.168.1.108");
ch.dumpObjectNodeMap("新增物理節點", 0, 65536);
}
}

======== 初始情況 ========
IP=192.168.1.101: RATE=45%
IP=192.168.1.102: RATE=3%
IP=192.168.1.103: RATE=28%
IP=192.168.1.104: RATE=22%
======== 刪除物理節點 ========
IP=192.168.1.101: RATE=45%
IP=192.168.1.102: RATE=3%
IP=192.168.1.104: RATE=51%
======== 新增物理節點 ========
IP=192.168.1.101: RATE=45%
IP=192.168.1.102: RATE=3%
IP=192.168.1.104: RATE=32%
IP=192.168.1.108: RATE=18%

======== 初始情況 ========
IP=192.168.1.101: RATE=29%
IP=192.168.1.102: RATE=21%
IP=192.168.1.103: RATE=25%
IP=192.168.1.104: RATE=23%
======== 刪除物理節點 ========
IP=192.168.1.101: RATE=39%
IP=192.168.1.102: RATE=37%
IP=192.168.1.104: RATE=23%
======== 新增物理節點 ========
IP=192.168.1.101: RATE=35%
IP=192.168.1.102: RATE=20%
IP=192.168.1.104: RATE=23%
IP=192.168.1.108: RATE=20%

======== 初始情況 ========
IP=192.168.1.101: RATE=24%
IP=192.168.1.102: RATE=24%
IP=192.168.1.103: RATE=25%
IP=192.168.1.104: RATE=25%
======== 刪除物理節點 ========
IP=192.168.1.101: RATE=33%
IP=192.168.1.102: RATE=33%
IP=192.168.1.104: RATE=33%
======== 新增物理節點 ========
IP=192.168.1.101: RATE=25%
IP=192.168.1.102: RATE=24%
IP=192.168.1.104: RATE=24%
IP=192.168.1.108: RATE=24%