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本章是这本书最酣畅淋漓的一章，涉及到了一致性和共识问题的方方面面，知识点多而不失条理。第一部分先讲了 Linearizability, 为后面的知识点做铺垫。到了 “Ordering Guarantees” 这一小节，从因果关系的带来的 “Happened Before” 的关系开始讲起，讲到了序列号和 Lamport Timestamp，提出来 Lamport Timestamp 的一个缺点：无法在某事件发生时判断是否有冲突，然后引出了全序关系广播，在全序关系广播中又讲到了和 Linearizable 之间的等价关系，最后引出共识算法。太精彩了，值得反复阅读！ Consistency Guarantees Most replicated databases provide at least eventual consistency, which means that if you stop writing to the database and wait for some unspecified length of time, then eventually all read requests will return the same value. A better name for eventual consistency may be convergence, as we expect all replicas to eventually converge to the same value. ...

Faults and Partial Failures An individual computer with good software is usually either fully functional or entirely broken, but not something in between. Thus, computers hide the fuzzy physical reality on which they are implemented and present an idealized system model that operates with mathematical perfection. In a distributed system, there may well be some parts of the system that are broken in some unpredictable way, even though other parts of the system are working fine. This is known as a partial failure. The difficulty is that partial failures are nondeterministic: if you try to do anything involving multiple nodes and the network, it may sometimes work and sometimes unpredictably fail. ...

A transaction is a way for an application to group several reads and writes together into a logical unit. Transactions are not a law of nature; they were created with a purpose, namely to simplify the programming model for applications accessing a database. 相当于数据库提供了一层重要的抽象，在编写应用程序时不用再去考虑那些能被事务处理的错误与问题了。 The Meaning of ACID The safety guarantees provided by transactions are often described by the well known acronym ACID, which stands for Atomicity, Consistency, Isolation, and Durability. ...

The main reason for wanting to partition data is scalability. Normally, partitions are defined in such a way that each piece of data (each record, row, or document) belongs to exactly one partition. Partitioning and Replication Partitioning is usually combined with replication so that copies of each partition are stored on multiple nodes. This means that, even though each record belongs to exactly one partition, it may still be stored on several different nodes for fault tolerance. ...

Replication Versus Partitioning There are two common ways data is distributed across multiple nodes: Replication Keeping a copy of the same data on several different nodes, potentially in different locations. Replication provides redundancy and can also help improve performance. Partitioning Splitting a big database into smaller subsets called partitions so that different partitions can be assigned to different nodes (also known as sharding). These are separate mechanisms, but they often go hand in hand: ...