哈哈, 代码是最好的注释,???
/*
/**
* ConsistentHash From Dubbo
* 一致性hash算法
*/
public class ConsistentHashLoadBalance extends AbstractLoadBalance {
public static final String NAME = "consistenthash";
private final ConcurrentMap<String, ConsistentHashSelector<?>> selectors = new ConcurrentHashMap<String, ConsistentHashSelector<?>>();
@SuppressWarnings("unchecked")
@Override
// 负载方法
protected <T> Invoker<T> doSelect(List<Invoker<T>> invokers, URL url, Invocation invocation) {
// 获取方法名
String methodName = RpcUtils.getMethodName(invocation);
// 使用第一个参数的url 生成key
String key = invokers.get(0).getUrl().getServiceKey() + "." + methodName;
// 生成Invokers列表的hashCode值
int identityHashCode = System.identityHashCode(invokers);
// 使用key, 从selectors获取selector
ConsistentHashSelector<T> selector = (ConsistentHashSelector<T>) selectors.get(key);
// 第一次获取一定为 null, 或者invokers列表成员发生变化了。
if (selector == null || selector.identityHashCode != identityHashCode) {
// 创建ConsistentHashSelector时会生成所有虚拟结点
selectors.put(key, new ConsistentHashSelector<T>(invokers, methodName, identityHashCode));
// 获取 selector
selector = (ConsistentHashSelector<T>) selectors.get(key);
}
// select
return selector.select(invocation);
}
private static final class ConsistentHashSelector<T> {
// 存储虚拟节点
private final TreeMap<Long, Invoker<T>> virtualInvokers;
// 存储的副本
private final int replicaNumber;
// hashcode
private final int identityHashCode;
// 参数 索引数组
private final int[] argumentIndex;
ConsistentHashSelector(List<Invoker<T>> invokers, String methodName, int identityHashCode) {
// TreeMap 来维护 key有序
this.virtualInvokers = new TreeMap<Long, Invoker<T>>();
this.identityHashCode = identityHashCode;
// 获取url
URL url = invokers.get(0).getUrl();
// 获取所配置的结点数,如没有设置则使用默认值160
this.replicaNumber = url.getMethodParameter(methodName, "hash.nodes", 160);
String[] index = Constants.COMMA_SPLIT_PATTERN.split(url.getMethodParameter(methodName, "hash.arguments", "0"));
argumentIndex = new int[index.length];
for (int i = 0; i < index.length; i++) {
argumentIndex[i] = Integer.parseInt(index[i]);
}
// 对每个invoker 默认生成 160个 虚拟节点, 存入TreeMap
// 避免数据倾斜
for (Invoker<T> invoker : invokers) {
String address = invoker.getUrl().getAddress();
for (int i = 0; i < replicaNumber / 4; i++) {
byte[] digest = md5(address + i);
for (int h = 0; h < 4; h++) {
long m = hash(digest, h);
virtualInvokers.put(m, invoker);
}
}
}
}
// select 一个 invoker
public Invoker<T> select(Invocation invocation) {
// 获取key
String key = toKey(invocation.getArguments());
// key对应的md5 字节数组
byte[] digest = md5(key);
return selectForKey(hash(digest, 0));
}
private String toKey(Object[] args) {
StringBuilder buf = new StringBuilder();
for (int i : argumentIndex) {
if (i >= 0 && i < args.length) {
buf.append(args[i]);
}
}
return buf.toString();
}
private Invoker<T> selectForKey(long hash) {
// ceilingEntry 找 比hash值大的第一个entry
Map.Entry<Long, Invoker<T>> entry = virtualInvokers.ceilingEntry(hash);
// 如果是 hash轮的最后一个key, 返回第一个entry
if (entry == null) {
entry = virtualInvokers.firstEntry();
}
return entry.getValue();
}
// hash算法, 和effective Java 里面讲的 hash方法异曲同工之妙
private long hash(byte[] digest, int number) {
return (((long) (digest[3 + number * 4] & 0xFF) << 24)
| ((long) (digest[2 + number * 4] & 0xFF) << 16)
| ((long) (digest[1 + number * 4] & 0xFF) << 8)
| (digest[number * 4] & 0xFF))
& 0xFFFFFFFFL;
}
// md5 算法
private byte[] md5(String value) {
MessageDigest md5;
try {
md5 = MessageDigest.getInstance("MD5");
} catch (NoSuchAlgorithmException e) {
throw new IllegalStateException(e.getMessage(), e);
}
md5.reset();
byte[] bytes = value.getBytes(StandardCharsets.UTF_8);
md5.update(bytes);
return md5.digest();
}
}
}