漫谈分布式系统：基本概念
0x00 前言
MIT 6.824课程第一节的部分内容，加上自己参考了一些书一起整理而得。
资源共享是构造分布式系统的主要动机！ —— 《分布式系统：概念与设计》 第一章
0x01 什么是分布式系统
分布式的定义有很多，我们从两本书中摘来两个比较权威的定义来看，就不翻译中文了。
其一：
A distributed system is a model in which components located on networked computers communicate and coordinate their actions by passing messages. The components interact with each other in order to achieve a common goal.
其二：
A distributed system is a collection of independent computers that appears to its users as a single coherent system.
重要特性
分布式系统有一些特殊特性，这些特殊的性质也是我们在设计分布式系统需要考虑的主要问题。对这些问题的认知程度，直接影响到我们是否能理解为什么那么多分布式系统要被设计出来，它们到底要解决什么问题，每个系统在设计的时候有什么优点，然后它们做了什么取舍。
- 组件并发性（concurrency of components）
- 缺乏全局时钟（lack of a global clock）
- 组件故障的独立性（independent failure of components）
反正我是感觉第三条占得分量挺重的。
为什么要用分布式系统？
- to connect physically separate entities
- to achieve security via isolation
- to tolerate faults via replication
- to scale up throughput via parallel CPUs/mem/disk/net
- 为了连接物理上相互分离的实体
- 为了通过隔离(isolation)实现安全性
- 为了通过复制(replication)实现容错
- 为了使CPUs/mem/disk/net可以实现扩容
有什么难题
困难当然很多，总的来讲会有这几点：
- complex: many concurrent parts
- must cope with partial failure
- tricky to realize performance potential
- 复杂性: 多个并发的部分
- 必须处理部分失败的情况
- 难以实现的性能潜力
这些困难怎么体现？
0x02 几个话题
围绕前面列的问题，我们来分别讨论几个话题：一致性、错误容忍、性能。这几个点的解决往往会引入新的问题，比如说为了避免集群中一台服务器挂掉导致丢数据，我们会使用多备份的机制，但是已引入多备份就又引入了数据不一致的问题。而为了保证数据一致性，就要多加入更多的处理逻辑，这就会导致性能的下降。
那么怎么样能设计一个完美的分布式系统呢？ 这个我也不知道，先学着吧......
1. consistency（一致性）
Consistency is an issue for both replicated objects and transactions involving related updates to different objects (recall ACID properties)
一致性问题主要会集中在多备份和分布式事务中。
Achieving good behavior is hard!
- "Replica" servers are hard to keep identical.
- Clients may crash midway through multi-step update.
- Servers crash at awkward moments, e.g. after executing but before replying.
- Network may make live servers look dead; risk of "split brain".
Consistency and performance are enemies.
- Consistency requires communication, e.g. to get latest Put().
- "Strong consistency" often leads to slow systems.
- High performance often imposes "weak consistency" on - applications.
People have pursued many design points in this spectrum.
2. fault tolerance
1000s of servers, complex net -> always something broken. We'd like to hide these failures from the application.
What we want:
- Availability -- app can keep using its data despite failures
- Durability -- app's data will come back to life when failures are repaired
How: replicated servers.
If one server crashes, client can proceed using the other(s).
3. Performance
What we want: scalable throughput.
Nx servers -> Nx total throughput via parallel CPU, disk, net. So handling more load only requires buying more computers.
But Scaling gets harder as N grows. Why?
- Load im-balance, stragglers. (Some node is much more slower than others. 慢节点)
- Non-parallelizable code: initialization, interaction.
- Bottlenecks from shared resources, e.g. network.
0XFF 总结
列了一些基本概念。不想搞成中文了，发现看英文挺能理解的，翻译中文，怎么都别扭。
参考
作者：dantezhao |简书 | CSDN | GITHUB
个人主页：http://dantezhao.com
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