Java 和 Python 程序的相同一致哈希算法实现

我们有一个应用程序，Python模块将数据写入redis分片，Java模块将从redis分片读取数据，所以我需要为Java和Python实现完全相同的一致哈希算法，以确保可以找到数据。

我用谷歌搜索了几个实现，但发现Java和Python的实现总是不同的，不能用来聚集。需要您的帮助。

编辑，我尝试过的在线实现：Java：
http://weblogs.java.net/blog/tomwhite/archive/2007/11/consistent_hash.html
Python：http://techspot.zzzeek.org/2012/07/07/the-absolutely-simplest-consistent-hashing-example/
http://amix.dk/blog/post/19367

编辑，附加Java（使用Google Guava lib）和我写的Python代码。代码基于上述文章。

import java.util.Collection;
import java.util.SortedMap;
import java.util.TreeMap;
import com.google.common.hash.HashFunction;

public class ConsistentHash<T> {
    private final HashFunction hashFunction;
    private final int numberOfReplicas;
    private final SortedMap<Long, T> circle = new TreeMap<Long, T>();

    public ConsistentHash(HashFunction hashFunction, int numberOfReplicas,
            Collection<T> nodes) {
        this.hashFunction = hashFunction;
        this.numberOfReplicas = numberOfReplicas;

        for (T node : nodes) {
            add(node);
        }
    }

    public void add(T node) {
        for (int i = 0; i < numberOfReplicas; i++) {
            circle.put(hashFunction.hashString(node.toString() + i).asLong(),
                    node);
        }
    }

    public void remove(T node) {
        for (int i = 0; i < numberOfReplicas; i++) {
            circle.remove(hashFunction.hashString(node.toString() + i).asLong());
        }
    }

    public T get(Object key) {
        if (circle.isEmpty()) {
            return null;
        }
        long hash = hashFunction.hashString(key.toString()).asLong();
        if (!circle.containsKey(hash)) {
            SortedMap<Long, T> tailMap = circle.tailMap(hash);
            hash = tailMap.isEmpty() ? circle.firstKey() : tailMap.firstKey();
        }
        return circle.get(hash);
    }
}

测试代码：

        ArrayList<String> al = new ArrayList<String>(); 
        al.add("redis1");
        al.add("redis2");
        al.add("redis3");
        al.add("redis4");

        String[] userIds = 
        {"-84942321036308",
        "-76029520310209",
        "-68343931116147",
        "-54921760962352"
        };
        HashFunction hf = Hashing.md5();

        ConsistentHash<String> consistentHash = new ConsistentHash<String>(hf, 100, al); 
        for (String userId : userIds) {
            System.out.println(consistentHash.get(userId));
        }

Python 代码：

import bisect
import md5

class ConsistentHashRing(object):
    """Implement a consistent hashing ring."""

    def __init__(self, replicas=100):
        """Create a new ConsistentHashRing.

        :param replicas: number of replicas.

        """
        self.replicas = replicas
        self._keys = []
        self._nodes = {}

    def _hash(self, key):
        """Given a string key, return a hash value."""

        return long(md5.md5(key).hexdigest(), 16)

    def _repl_iterator(self, nodename):
        """Given a node name, return an iterable of replica hashes."""

        return (self._hash("%s%s" % (nodename, i))
                for i in xrange(self.replicas))

    def __setitem__(self, nodename, node):
        """Add a node, given its name.

        The given nodename is hashed
        among the number of replicas.

        """
        for hash_ in self._repl_iterator(nodename):
            if hash_ in self._nodes:
                raise ValueError("Node name %r is "
                            "already present" % nodename)
            self._nodes[hash_] = node
            bisect.insort(self._keys, hash_)

    def __delitem__(self, nodename):
        """Remove a node, given its name."""

        for hash_ in self._repl_iterator(nodename):
            # will raise KeyError for nonexistent node name
            del self._nodes[hash_]
            index = bisect.bisect_left(self._keys, hash_)
            del self._keys[index]

    def __getitem__(self, key):
        """Return a node, given a key.

        The node replica with a hash value nearest
        but not less than that of the given
        name is returned.   If the hash of the
        given name is greater than the greatest
        hash, returns the lowest hashed node.

        """
        hash_ = self._hash(key)
        start = bisect.bisect(self._keys, hash_)
        if start == len(self._keys):
            start = 0
        return self._nodes[self._keys[start]]

测试代码：

import ConsistentHashRing

if __name__ == '__main__':
    server_infos = ["redis1", "redis2", "redis3", "redis4"];
    hash_ring = ConsistentHashRing()
    test_keys = ["-84942321036308",
        "-76029520310209",
        "-68343931116147",
        "-54921760962352",
        "-53401599829545"
        ];

    for server in server_infos:
        hash_ring[server] = server

    for key in test_keys:
        print str(hash_ring[key])