Jedis中的一致性hash
本文仅供大家参考,不保证正确性,有问题请及时指出
一致性hash就不多说了,网上有很多说的很好的文章,这里说说Jedis中的Shard是如何使用一致性hash的,也为大家在实现一致性hash提供些思路。
首先是hash函数,在Jedis中有两种Hash算法可供选择,分别是MurMurHash和MD5. 按照Jedis的说法MurMur Hash更快,效果更好些。
MurmurHash.java
package redis.clients.util;
import java.nio.ByteBuffer;
import java.nio.ByteOrder;
publicclass MurmurHash implements Hashing {
publicstaticint hash(byte[] data, int seed) {
return hash(ByteBuffer.wrap(data), seed);
}
publicstaticint hash(byte[] data, int offset, int length, int seed) {
return hash(ByteBuffer.wrap(data, offset, length), seed);
}
publicstaticint hash(ByteBuffer buf, int seed) {
ByteOrder byteOrder = buf.order();
buf.order(ByteOrder.LITTLE_ENDIAN);
int m = 0x5bd1e995;
int r = 24;
int h = seed ^ buf.remaining();
int k;
while (buf.remaining() >= 4) {
k = buf.getInt();
k *= m;
k ^= k >>> r;
k *= m;
h *= m;
h ^= k;
}
if (buf.remaining() > 0) {
ByteBuffer finish = ByteBuffer.allocate(4).order(
ByteOrder.LITTLE_ENDIAN);
finish.put(buf).rewind();
h ^= finish.getInt();
h *= m;
}
h ^= h >>> 13;
h *= m;
h ^= h >>> 15;
buf.order(byteOrder);
return h;
}
publicstaticlong hash64A(byte[] data, int seed) {
return hash64A(ByteBuffer.wrap(data), seed);
}
publicstaticlong hash64A(byte[] data, int offset, int length, int seed) {
return hash64A(ByteBuffer.wrap(data, offset, length), seed);
}
publicstaticlong hash64A(ByteBuffer buf, int seed) {
ByteOrder byteOrder = buf.order();
buf.order(ByteOrder.LITTLE_ENDIAN);
long m = 0xc6a4a7935bd1e995L;
int r = 47;
long h = seed ^ (buf.remaining() * m);
long k;
while (buf.remaining() >= 8) {
k = buf.getLong();
k *= m;
k ^= k >>> r;
k *= m;
h ^= k;
h *= m;
}
if (buf.remaining() > 0) {
ByteBuffer finish = ByteBuffer.allocate(8).order(
ByteOrder.LITTLE_ENDIAN);
finish.put(buf).rewind();
h ^= finish.getLong();
h *= m;
}
h ^= h >>> r;
h *= m;
h ^= h >>> r;
buf.order(byteOrder);
return h;
}
publiclong hash(byte[] key) {
return hash64A(key, 0x1234ABCD);
}
publiclong hash(String key) {
return hash(SafeEncoder.encode(key));
}
}
而MD5从java提供的类中即可获得,但是需要将MD5值转换为long类型的常量。
publicinterface Hashing {
publicstaticfinal Hashing MURMUR_HASH = new MurmurHash();
public ThreadLocal
publicstaticfinal Hashing MD5 = new Hashing() {
publiclong hash(String key) {
return hash(SafeEncoder.encode(key));
}
publiclong hash(byte[] key) {
try {
if (md5Holder.get() == null) {
md5Holder.set(MessageDigest.getInstance("MD5"));
}
} catch (NoSuchAlgorithmException e) {
thrownew IllegalStateException("++++ no md5 algorythm found");
}
MessageDigest md5 = md5Holder.get();
md5.reset();
md5.update(key);
byte[] bKey = md5.digest();
long res = ((long) (bKey[3] & 0xFF) << 24)
| ((long) (bKey[2] & 0xFF) << 16)
| ((long) (bKey[1] & 0xFF) << 8) | (long) (bKey[0] & 0xFF);
return res;
}
};
}
MD5中使用了ThreadLocal,这个就不多说了,网上也有很多相关的blog。或者查看我《如何写性能测试程序》那篇博客。
下面主要说说,Jedis中的一致性Hash部分。
Shard中定义了如下属性:
private TreeMap
privatefinal Hashing algo;
privatefinal Map
nodes属性类型为TreeMap
algo是hash算法,是MurMur或者MD5.
resources 完成主机信息和实际链接(Jedis)间的映射。
初始化主机hash如下:
privatevoid initialize(List shards) {
nodes = new TreeMap
for (int i = 0; i != shards.size(); ++i) {
final S shardInfo = shards.get(i);
if (shardInfo.getName() == null)
for (int n = 0; n < 160 * shardInfo.getWeight(); n++) {
nodes.put(this.algo.hash("SHARD-" + i + "-NODE-" + n), shardInfo);
}
else
for (int n = 0; n < 160 * shardInfo.getWeight(); n++) {
nodes.put(this.algo.hash(shardInfo.getName() + "*" + shardInfo.getWeight() + n), shardInfo);
}
resources.put(shardInfo, shardInfo.createResource());
}
}
在for循环中,遍历主机列表(shards.get(i)),之后对每个主机按照单权重160的比例计算shard值,将shard值和主机信息(shardInfo)放到nodes中,将主机信息(shardInfo)和其对应的链接资源(Jedis)映射放入到resources中。
Weight是权重,用于调节单个主机被映射值个数,如果weight为1,那么当前主机将被映射为160个值,weight为2,当前主机将被映射为320个值,因此weight为2的节点被访问到的概率就会高一些。
获取某个key对应的主机链接:
public S getShardInfo(byte[] key) {
SortedMap
if (tail.isEmpty()) {
returnnodes.get(nodes.firstKey());
}
return tail.get(tail.firstKey());
}
在获取key时,先根据key做hash(algo.hash(key)),然后获取node中值大于algo.hash(key)的子树,子树的头结点即为整个子树的最小值,因此选中这个节点做为key的映射节点,取出key值对应的value(hostInfo),之后根据hostInfo,通过resources,获取最终的链接。
public R getShard(byte[] key) {
returnresources.get(getShardInfo(key));
}
当然,一致性hash在存储时,一个key可以对应多个节点,一般这多个节点都是在nodes(MapTree)中连续的,因此,也可以改进这个算法,以便实现多节点存储同一个key的方式。
参考:jedis-2.1.0.jar