负载均衡 ribbon

最新推荐文章于 2024-04-25 16:54:23 发布

原创最新推荐文章于 2024-04-25 16:54:23 发布 · 233 阅读

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#spring cloud ribbon

本文深入探讨了Ribbon负载均衡器中两种核心策略：随机选择与轮询选择。通过源码分析，揭示了如何从服务器列表中筛选出符合条件的服务器，并采用随机或轮询方式选择目标服务器的过程。

ribbon-loadbalacer.-2.2.2.jar

抽象类：public abstract class AbstractServerPredicate

//随机策略

public Optional<Server> chooseRandomlyAfterFiltering(List<Server> servers) {
    List<Server> eligible = this.getEligibleServers(servers);
    return eligible.size() == 0?Optional.absent():Optional.of(eligible.get(this.random.nextInt(eligible.size())));
}

//重复轮询策略（nextIndex自增后，服务器的个数取模）
public Optional<Server> chooseRoundRobinAfterFiltering(List<Server> servers) {
    List<Server> eligible = this.getEligibleServers(servers);
    return eligible.size() == 0?Optional.absent():Optional.of(eligible.get(this.nextIndex.getAndIncrement() % eligible.size()));
}

//随机策略
public Optional<Server> chooseRandomlyAfterFiltering(List<Server> servers, Object loadBalancerKey) {
    List<Server> eligible = this.getEligibleServers(servers, loadBalancerKey);
    return eligible.size() == 0?Optional.absent():Optional.of(eligible.get(this.random.nextInt(eligible.size())));
}

//重复轮询策略（nextIndex自增后，服务器的个数取模）

public Optional<Server> chooseRoundRobinAfterFiltering(List<Server> servers, Object loadBalancerKey) {
    List<Server> eligible = this.getEligibleServers(servers, loadBalancerKey);
    return eligible.size() == 0?Optional.absent():Optional.of(eligible.get(this.nextIndex.getAndIncrement() % eligible.size()));
}