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  • dubbo调用负载均衡

    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。
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  • 原文地址:https://www.cnblogs.com/killbug/p/8328022.html
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