distribution tech system principle ( one )

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本文介绍了分布式系统的颁础笔理论，强调一致性、可用性和分区容忍性之间的权衡。它讨论了在设计分布式系统时如何在不完全一致的情况下实现可用性和容错性，并提到了基于不同模型的应用实例。最后，文中提到了笔补虫辞蝉和搁补蹿迟等共识算法的重要性。

CAP
一个分布式系统最多只能同时满足：
●
一致性（ Consistency ）
●
可用性（ Availability ）
●
分区容忍性（ Partition Tolerance ）
这三项中的两项。

C
●
一致性
指“所有节点同时看到相同的数据”，
即更新操作成功并返回客户端完成后，
所有节点在同一时间的数据完全一致，
等同于所有节点拥有数据的最新版本。

A
●
可用性
“ 任何时候，读写都是成功的”，
即服务一直可用，
而且是正常响应时间。

P
●
分区容忍性
“ 当部分节点出现消息丢失或者分区故障的时候，
分布式系统仍然能够继续运行”，
即系统容忍网络出现分区，
遇到某节点或网络分区之间网络不可达的情况下，
仍然能够对外提供满足一致性或可用性的服务。

CAP
●
在分布式系统中， P 是确定的。
CAP 应用模型就是 CP 架构和 AP 架构。
●
分布式系统所关注的，就是在分区容忍的前提下，如何
实现更好的 A 和更稳定的 C 。

CAP
●
工程上来说，放弃强一致性
（这里说的一致性是强一致性），
追求分区容错性和可用性，
这是很多分布式系统设计时的选择

BASE
●
基本可用
不追求 CAP 中的「任何时候，读写都是成功
的」，而是系统能够基本运行，一直提供服务。基
本可用强调了分布式系统在出现不可预知故障的时
候，允许损失部分可用性，相比正常的系统，可能
是响应时间延长，或者是服务被降级。

BASE
●
软状态
可以对应 ACID 事务中的原子性，实现的是强制一致性，要么全做要
么不做，所有用户看到的数据一致。
其中的原子性要求多个节点的数据副本都是一致的，强调数据一致性。
原子性可以理解为一种“硬状态”，
软状态则是允许系统中的数据存在中间状态，并认为该状态不影响系统
的整体可用性，即允许系统在多个不同节点的数据副本存在数据延时。

BASE
●
最终一致性
数据不可能一直是软状态，
必须在一个时间期限后达到各节点的一致
性，在期限过后，应当保证所有副本保持数
据一致性，也就是达到数据的最终一致性。

Zookeeper
●
Zab
ZooKeeper
Atomic
Broadcast

Zookeeper
●
消息广播阶段
●
崩溃恢复阶段 (epoch,Zxid,serverid)
整个 ZooKeeper 集群的一致性保证就是
在上面两个状态之前切换

ETCD
●
Raft
●
数据，类似的两阶段提交
●
选举，每节点内部都有计时器

罢别苍驳颈苍别是基于狈驳颈苍虫的高效、安全平台，旨在提升奥别产应用的性能与稳定性，通过动态模块加载和安全防护措施实现灵活扩展与高效服务。该文档介绍了罢别苍驳颈苍别的应用案例、开发细节及未来发展方向，包括负载均衡、安全性增强和内容优化等功能。罢别苍驳颈苍别的开源历程也体现了持续改进和与多个公司合作的愿景。

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