java实现：http://www.oschina.net/code/snippet_730640_22941
参考：http://amix.dk/blog/post/19367
python实现:
import md5
class HashRing(object):
def __init__(self, nodes=None, replicas=3):
"""Manages a hash ring.
`nodes` is a list of objects that have a proper __str__ representation.
`replicas` indicates how many virtual points should be used pr. node,
replicas are required to improve the distribution.
"""
self.replicas = replicas
self.ring = dict()
self._sorted_keys = []
if nodes:
for node in nodes:
self.add_node(node)
def add_node(self, node):
"""Adds a `node` to the hash ring (including a number of replicas).
"""
for i in xrange(0, self.replicas):
key = self.gen_key('%s:%s' % (node, i))
self.ring[key] = node
self._sorted_keys.append(key)
self._sorted_keys.sort()
def remove_node(self, node):
"""Removes `node` from the hash ring and its replicas.
"""
for i in xrange(0, self.replicas):
key = self.gen_key('%s:%s' % (node, i))
del self.ring[key]
self._sorted_keys.remove(key)
def get_node(self, string_key):
"""Given a string key a corresponding node in the hash ring is returned.
If the hash ring is empty, `None` is returned.
"""
return self.get_node_pos(string_key)[0]
def get_node_pos(self, string_key):
"""Given a string key a corresponding node in the hash ring is returned
along with it's position in the ring.
If the hash ring is empty, (`None`, `None`) is returned.
"""
if not self.ring:
return None, None
key = self.gen_key(string_key)
nodes = self._sorted_keys
for i in xrange(0, len(nodes)):
node = nodes[i]
if key <= node:
return self.ring[node], i
return self.ring[nodes[0]], 0
def get_nodes(self, string_key):
"""Given a string key it returns the nodes as a generator that can hold the key.
The generator is never ending and iterates through the ring
starting at the correct position.
"""
if not self.ring:
yield None, None
node, pos = self.get_node_pos(string_key)
for key in self._sorted_keys[pos:]:
yield self.ring[key]
while True:
for key in self._sorted_keys:
yield self.ring[key]
def gen_key(self, key):
"""Given a string key it returns a long value,
this long value represents a place on the hash ring.
md5 is currently used because it mixes well.
"""
m = md5.new()
m.update(key)
return long(m.hexdigest(), 16)
memcache_servers = ['192.168.1.1:11212','192.168.1.2:11212']
ring = HashRing(memcache_servers)
server = ring.get_node('my_key')
print server
java实现:
package util;
import java.util.Arrays;
import java.util.Collection;
import java.util.SortedMap;
import java.util.TreeMap;
/**
* 一致性Hash算法
* 算法详解：http://blog.csdn.net/sparkliang/article/details/5279393
* 算法实现：https://weblogs.java.net/blog/2007/11/27/consistent-hashing
* @author xiaoleilu
*
* @param <T> 节点类型
*/
public class ConsistentHash<T> {
/** Hash计算对象，用于自定义hash算法 */
HashFunc hashFunc;
/** 复制的节点个数 */
private final int numberOfReplicas;
/** 一致性Hash环 */
private final SortedMap<Integer, T> circle = new TreeMap<Integer, T>();
/**
* 构造，使用Java默认的Hash算法
* @param numberOfReplicas 复制的节点个数，增加每个节点的复制节点有利于负载均衡
* @param nodes 节点对象
*/
public ConsistentHash(int numberOfReplicas, Collection<T> nodes) {
this.numberOfReplicas = numberOfReplicas;
this.hashFunc = new HashFunc() {
@Override
public Integer hash(Object key) {
String data = key.toString();
//默认使用FNV1hash算法
final int p = 16777619;
int hash = (int) 2166136261L;
for (int i = 0; i < data.length(); i++)
hash = (hash ^ data.charAt(i)) * p;
hash += hash << 13;
hash ^= hash >> 7;
hash += hash << 3;
hash ^= hash >> 17;
hash += hash << 5;
return hash;
}
};
//初始化节点
for (T node : nodes) {
add(node);
}
}
/**
* 构造
* @param hashFunc hash算法对象
* @param numberOfReplicas 复制的节点个数，增加每个节点的复制节点有利于负载均衡
* @param nodes 节点对象
*/
public ConsistentHash(HashFunc hashFunc, int numberOfReplicas, Collection<T> nodes) {
this.numberOfReplicas = numberOfReplicas;
this.hashFunc = hashFunc;
//初始化节点
for (T node : nodes) {
add(node);
}
}
/**
* 增加节点<br>
* 每增加一个节点，就会在闭环上增加给定复制节点数<br>
* 例如复制节点数是2，则每调用此方法一次，增加两个虚拟节点，这两个节点指向同一Node
* 由于hash算法会调用node的toString方法，故按照toString去重
* @param node 节点对象
*/
public void add(T node) {
for (int i = 0; i < numberOfReplicas; i++) {
circle.put(hashFunc.hash(node.toString() + i), node);
}
}
/**
* 移除节点的同时移除相应的虚拟节点
* @param node 节点对象
*/
public void remove(T node) {
for (int i = 0; i < numberOfReplicas; i++) {
circle.remove(hashFunc.hash(node.toString() + i));
}
}
/**
* 获得一个最近的顺时针节点
* @param key 为给定键取Hash，取得顺时针方向上最近的一个虚拟节点对应的实际节点
* @return 节点对象
*/
public T get(Object key) {
if (circle.isEmpty()) {
return null;
}
int hash = hashFunc.hash(key);
if (!circle.containsKey(hash)) {
SortedMap<Integer, T> tailMap = circle.tailMap(hash); //返回此映射的部分视图，其键大于等于 hash
hash = tailMap.isEmpty() ? circle.firstKey() : tailMap.firstKey();
}
//正好命中
return circle.get(hash);
}
/**
* Hash算法对象，用于自定义hash算法
* @author xiaoleilu
*
*/
public interface HashFunc {
public Integer hash(Object key);
}
public static void main(String[] args) {
ConsistentHash<String> hash = new ConsistentHash<String>(3, Arrays.asList("192.168.1.1:11211", "192.168.1.2:11211"));
System.out.println(hash.get("test"));
}
}