分布式CAP理论（英文版）

In a distant country, there is a place called the Distributed Kingdom. The residents here have unique talent and courage to work together to create a dynamic world. However, the kingdom faces a key problem in balancing the three key attributes of data consistency, availability, and partitioned fault tolerance in distributed systems.
In order to solve this problem, the residents of the kingdom started a heated discussion: In distributed systems, data replication is the key to maintaining data consistency. This process can lead to data inconsistencies. To solve this problem, the residents decided to adopt the zoning fault-tolerance strategy. This means that each service has multiple nodes, and even if one node fails, other nodes can still provide services. However, in cases where the network is not available, this strategy can cause availability to be compromised. In order to maintain service availability even when the network is unavailable, residents decide to introduce consistent hashing. With this technique, even if one node fails, other nodes can allocate requests to the working node based on a consistent hash algorithm, thus ensuring service availability.
In practice, residents of the distributed kingdom find that these three key attributes often need to be weighed against specific needs. To ensure data consistency, you need to sacrifice partial availability, such as delayed response. To ensure service availability, some data consistency, such as accepting outdated data, needs to be sacrificed.
Eventually, the inhabitants of the distributed kingdom found a way to balance these three key attributes. Applying this method to every corner of the kingdom, residents can take full advantage of partition fault tolerance while ensuring data consistency and service availability. The inhabitants of the kingdom proudly call this approach the Distributed Transaction CAP Theory.
Since then, the inhabitants of the distributed kingdom have always thought of CAP theory when solving problems. Learned tradeoffs between these three key attributes to achieve higher system performance and reliability. But this kingdom’s story, has also become in the Internet world section of eternal legend.
In the CAP theory of distributed transactions, CP (consistency, partition fault tolerance) and AP (availability, partition fault tolerance) are two important concepts. The CP indicates that a service needs to maintain data consistency across multiple nodes to prevent data inconsistency during replication. The AP emphasizes the ability of the system to respond quickly to reasonable requests on non-fault nodes in the face of zoning fault tolerance (that is, network failures).