dubbo负载均衡的地址：http://dubbo.io/books/dubbo-user-book/demos/loadbalance.html
随机策略：
public class RandomLoadBalance extends AbstractLoadBalance {
public static final String NAME = "random";
private final Random random = new Random();
protected <T> Invoker<T> doSelect(List<Invoker<T>> invokers, URL url, Invocation invocation) {
int length = invokers.size(); // 总个数
int totalWeight = 0; // 总权重
boolean sameWeight = true; // 权重是否都一样
for (int i = 0; i < length; i++) {
int weight = getWeight(invokers.get(i), invocation);
totalWeight += weight; // 累计总权重
if (sameWeight && i > 0
&& weight != getWeight(invokers.get(i - 1), invocation)) {
sameWeight = false; // 计算所有权重是否一样
}
}
if (totalWeight > 0 && !sameWeight) {
// 如果权重不相同且权重大于0则按总权重数随机
int offset = random.nextInt(totalWeight);
// 并确定随机值落在哪个片断上
for (int i = 0; i < length; i++) {
offset -= getWeight(invokers.get(i), invocation);
if (offset < 0) {
return invokers.get(i);
}
}
}
// 如果权重相同或权重为0则均等随机
return invokers.get(random.nextInt(length));
}
}
由此判断出，Random是线程安全的！ 轮训策略：
public class RoundRobinLoadBalance extends AbstractLoadBalance {
public static final String NAME = "roundrobin";
private final ConcurrentMap<String, AtomicPositiveInteger> sequences = new ConcurrentHashMap<String, AtomicPositiveInteger>();
protected <T> Invoker<T> doSelect(List<Invoker<T>> invokers, URL url, Invocation invocation) {
String key = invokers.get(0).getUrl().getServiceKey() + "." + invocation.getMethodName();
int length = invokers.size(); // 总个数
int maxWeight = 0; // 最大权重
int minWeight = Integer.MAX_VALUE; // 最小权重
final LinkedHashMap<Invoker<T>, IntegerWrapper> invokerToWeightMap = new LinkedHashMap<Invoker<T>, IntegerWrapper>();
int weightSum = 0;
for (int i = 0; i < length; i++) {
int weight = getWeight(invokers.get(i), invocation);
maxWeight = Math.max(maxWeight, weight); // 累计最大权重
minWeight = Math.min(minWeight, weight); // 累计最小权重
if (weight > 0) {
invokerToWeightMap.put(invokers.get(i), new IntegerWrapper(weight));
weightSum += weight;
}
}
AtomicPositiveInteger sequence = sequences.get(key);
if (sequence == null) {
sequences.putIfAbsent(key, new AtomicPositiveInteger());
sequence = sequences.get(key);
}
int currentSequence = sequence.getAndIncrement();
if (maxWeight > 0 && minWeight < maxWeight) { // 权重不一样
int mod = currentSequence % weightSum;
for (int i = 0; i < maxWeight; i++) {
for (Map.Entry<Invoker<T>, IntegerWrapper> each : invokerToWeightMap.entrySet()) {
final Invoker<T> k = each.getKey();
final IntegerWrapper v = each.getValue();
if (mod == 0 && v.getValue() > 0) {
return k;
}
if (v.getValue() > 0) {
v.decrement();
mod--;
}
}
}
}
// 取模轮循
return invokers.get(currentSequence % length);
}
private static final class IntegerWrapper {
private int value;
public IntegerWrapper(int value) {
this.value = value;
}
public int getValue() {
return value;
}
public void setValue(int value) {
this.value = value;
}
public void decrement() {
this.value--;
}
}
}
这里要用ConcurrentMap记录每个invokers list 对应一个记数，记数每次调用加1，然后取模来算出调用哪一个invoker。
最少活跃数策略：
public class LeastActiveLoadBalance extends AbstractLoadBalance {
public static final String NAME = "leastactive";
private final Random random = new Random();
protected <T> Invoker<T> doSelect(List<Invoker<T>> invokers, URL url, Invocation invocation) {
int length = invokers.size(); // 总个数
int leastActive = -1; // 最小的活跃数
int leastCount = 0; // 相同最小活跃数的个数
int[] leastIndexs = new int[length]; // 相同最小活跃数的下标
int totalWeight = 0; // 总权重
int firstWeight = 0; // 第一个权重，用于于计算是否相同
boolean sameWeight = true; // 是否所有权重相同
for (int i = 0; i < length; i++) {
Invoker<T> invoker = invokers.get(i);
int active = RpcStatus.getStatus(invoker.getUrl(), invocation.getMethodName()).getActive(); // 活跃数
int weight = invoker.getUrl().getMethodParameter(invocation.getMethodName(), Constants.WEIGHT_KEY, Constants.DEFAULT_WEIGHT); // 权重
if (leastActive == -1 || active < leastActive) { // 发现更小的活跃数，重新开始
leastActive = active; // 记录最小活跃数
leastCount = 1; // 重新统计相同最小活跃数的个数
leastIndexs[0] = i; // 重新记录最小活跃数下标
totalWeight = weight; // 重新累计总权重
firstWeight = weight; // 记录第一个权重
sameWeight = true; // 还原权重相同标识
} else if (active == leastActive) { // 累计相同最小的活跃数
leastIndexs[leastCount++] = i; // 累计相同最小活跃数下标
totalWeight += weight; // 累计总权重
// 判断所有权重是否一样
if (sameWeight && i > 0
&& weight != firstWeight) {
sameWeight = false;
}
}
}
// assert(leastCount > 0)
if (leastCount == 1) {
// 如果只有一个最小则直接返回
return invokers.get(leastIndexs[0]);
}
if (!sameWeight && totalWeight > 0) {
// 如果权重不相同且权重大于0则按总权重数随机
int offsetWeight = random.nextInt(totalWeight);
// 并确定随机值落在哪个片断上
for (int i = 0; i < leastCount; i++) {
int leastIndex = leastIndexs[i];
offsetWeight -= getWeight(invokers.get(leastIndex), invocation);
if (offsetWeight <= 0)
return invokers.get(leastIndex);
}
}
// 如果权重相同或权重为0则均等随机
return invokers.get(leastIndexs[random.nextInt(leastCount)]);
}
}
一致性hash策略：
public class ConsistentHashLoadBalance extends AbstractLoadBalance {
public static final String NAME = "consistenthash";
private final ConcurrentMap<String, ConsistentHashSelector<?>> selectors = new ConcurrentHashMap<String, ConsistentHashSelector<?>>();
@SuppressWarnings("unchecked")
@Override
protected <T> Invoker<T> doSelect(List<Invoker<T>> invokers, URL url, Invocation invocation) {
String key = invokers.get(0).getUrl().getServiceKey() + "." + invocation.getMethodName();
int identityHashCode = System.identityHashCode(invokers);
ConsistentHashSelector<T> selector = (ConsistentHashSelector<T>) selectors.get(key);
if (selector == null || selector.identityHashCode != identityHashCode) {
selectors.put(key, new ConsistentHashSelector<T>(invokers, invocation.getMethodName(), identityHashCode));
selector = (ConsistentHashSelector<T>) selectors.get(key);
}
return selector.select(invocation);
}
private static final class ConsistentHashSelector<T> {
private final TreeMap<Long, Invoker<T>> virtualInvokers;
private final int replicaNumber;
private final int identityHashCode;
private final int[] argumentIndex;
ConsistentHashSelector(List<Invoker<T>> invokers, String methodName, int identityHashCode) {
this.virtualInvokers = new TreeMap<Long, Invoker<T>>();
this.identityHashCode = identityHashCode;
URL url = invokers.get(0).getUrl();
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]);
}
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);
}
}
}
}
public Invoker<T> select(Invocation invocation) {
String key = toKey(invocation.getArguments());
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) {
Invoker<T> invoker;
Long key = hash;
if (!virtualInvokers.containsKey(key)) {
SortedMap<Long, Invoker<T>> tailMap = virtualInvokers.tailMap(key);
if (tailMap.isEmpty()) {
key = virtualInvokers.firstKey();
} else {
key = tailMap.firstKey();
}
}
invoker = virtualInvokers.get(key);
return invoker;
}
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;
}
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;
try {
bytes = value.getBytes("UTF-8");
} catch (UnsupportedEncodingException e) {
throw new IllegalStateException(e.getMessage(), e);
}
md5.update(bytes);
return md5.digest();
}
}
}
这个一致性hash放节点的时候的key用的是ip地址，在查询的时候使用调用方法的参数集合，这里可能会有问题，不建议使用。