Dubbo 的负载均衡策略：随机策略

public class RandomLoadBalance extends AbstractLoadBalance {

    public static final String NAME = "random";

    private final Random random = new Random();

    @Override
    protected <T> Invoker<T> doSelect(List<Invoker<T>> invokers, URL url, Invocation invocation) {
        // 待选择的被调用服务的实例数量
        int length = invokers.size(); // Number of invokers
        // 统计总权重
        int totalWeight = 0; // The sum of weights
        // 标识：每个被调用服务的实例的权重是否相同
        boolean sameWeight = true; // Every invoker has the same weight?
        // 遍历每个被调用服务，获取每个被调用服务的权重，统计所有权重之和，并判断每个调用服务的权重是否相同
        for (int i = 0; i < length; i++) {
            int weight = getWeight(invokers.get(i), invocation);
            totalWeight += weight; // Sum
            if (sameWeight && i > 0
                    && weight != getWeight(invokers.get(i - 1), invocation)) {
                // 有不相同的权重，则标识 sameWeight 为 false
                sameWeight = false;
            }
        }

        // 总权重大于 0 且 被调用服务权重有不相同的，则随机产生一个 0 到 totalWeight-1 的数，定位到该数是在哪个被调用方的范围内
        if (totalWeight > 0 && !sameWeight) {
            // If (not every invoker has the same weight & at least one invoker's weight>0), select randomly based on totalWeight.
            int offset = random.nextInt(totalWeight);
            // Return a invoker based on the random value.
            for (int i = 0; i < length; i++) {
                offset -= getWeight(invokers.get(i), invocation);
                if (offset < 0) {
                    return invokers.get(i);
                }
            }
        }

        // 所有的被调用服务的权重相同，则随机产生一个 0 到 length-1 的数，返回对应的被调用服务
        // If all invokers have the same weight value or totalWeight=0, return evenly.
        return invokers.get(random.nextInt(length));
    }

}