May 2020
Beginner to intermediate
319 pages
7h 3m
Chinese
Content preview from 数据库系统内幕
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179
第
10
章
领导者选举
同步的代价可能会非常大：如果算法的每一个步骤都需要联系其他参与者，那么结果一
定是产生相当显著的通信开销。在大型且地理分布的网络中尤其如此。为了减少同步开
销和达成决定所需消息的往返次数，一些算法依赖于
领导者
（有时称为
协调者
）进程的
存在，该进程负责执行或协调分布式算法的各个步骤。
一般来说，分布式系统中的进程是对等的，任何进程都可以接管领导者的角色。进程可
以长期担任领导者，但这不是一个永久的角色。通常情况下，进程可以一直担任领导者
直到崩溃为止。崩溃后，任何其他进程都可以开始新一轮的选举，如果其当选，就可以
担任领导者并继续执行上个领导者遗留的工作。
选举算法的
活动性
（liveness）保证了
大多数时候
会有一个领导者，选举最终会完成（即
系统不应该无限期地处于选举状态）。
理想情况下，我们也希望获得
安全性
，保证一次
最多只能有一个
领导者，并完全消除
脑
裂
（两个目的相同的领导者被选举出来，但彼此不知情）的可能性。然而在实践中，许
多领导者选举算法违反了这一协定。
可以使用领导者进程来实现广播中消息的全序。领导者收集并保存全局状态，接收消
息，并将消息分发给各个进程。它还可以用于协调发生在系统故障后、初始化期间或重
要状态变更时的系统重组。
系统初始化时将会触发选举，第一次选择领导者。当上一个领导者崩溃或通信失败时也
会触发选举。选举必须是确定性的：选举过程中必须只产生一个领导者。这一决定需要
对所有参与者都有效。
尽管领导者选举和分布式锁（即对共享资源的独占所有权）从理论角度看可能很相似
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.