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This article mainly explains "what is CAP Theorem". The content of the explanation is simple and clear, and it is easy to learn and understand. Please follow Xiaobian's train of thought to study and learn "what is CAP Theorem".

CAP principle, also known as CAP theorem, refers to that in a distributed system, Consistency (consistency), Availability (availability) and Partition tolerance (partition fault tolerance) can not be obtained at the same time.

Distributed systems (distributed system) are becoming more and more important, and large websites are almost all distributed.

The biggest difficulty of distributed system is how to synchronize the state of each node. CAP theorem is not only the basic theorem in this aspect, but also the starting point for understanding distributed systems.

Three indicators of distributed system

In 1998, Eric Brewer, a computer scientist at the University of California, proposed that there are three indicators for distributed systems.

Consistency

Availability

Partition tolerance

Their first letters are C, An and P, respectively.

Eric Brewer says it is impossible to achieve all three indicators at the same time. This conclusion is called CAP theorem.

Partition tolerance

Let's take a look at Partition tolerance, which is called "partition fault tolerance" in Chinese.

Most distributed systems are distributed in multiple subnetworks. Each subnetwork is called a partition. Partition fault tolerance means that interval communication may fail. For example, if one server is in China and the other is in the United States, these are the two zones that may not be able to communicate with each other.

In the figure above, G1 and G2 are two servers that span regions. G1 sends a message to G2, which may not be received. This situation must be taken into account when designing the system.

Generally speaking, partition fault tolerance is unavoidable, so it can be considered that the P of CAP is always true. The CAP theorem tells us that the rest of C and A cannot be done at the same time.

Consistency

Consistency is called "consistency" in Chinese. It means that this value must be returned for the read operation after the write operation. For example, if a record is v0, the user initiates a write operation to G1 and changes it to v1.

Next, the user's read operation will get v1. It's called consistency.

The problem is that it is possible for the user to initiate a read to G2 and return v0 because the value of G2 has not changed. The results of G1 and G2 read operations are inconsistent, which is not consistent.

In order to change G2 to v1, it is necessary to ask G1 to send a message to G2 during the G1 write operation, asking G2 to also change to v1.

In this way, the user can also get v1 by initiating a read operation to G2.

Availability

Availability is called "availability" in Chinese, which means that as soon as a user's request is received, the server must respond.

The user can choose to initiate a read operation to G1 or G2. No matter which server it is, as long as it receives a request, it must tell the user whether it is v0 or v1, otherwise it will not meet the availability.

The contradiction between Consistency and Availability

Why can't consistency and availability be established at the same time? The answer is simple because communication may fail (that is, partition fault tolerance occurs).

If the consistency of G2 is guaranteed, G1 must lock the read and write operations of G2 during write operations. Only after data synchronization can read and write be reopened. During lock-up, G2 cannot read or write, and there is no availability.

If the availability of G2 is guaranteed, it is inevitable that G2 cannot be locked, so consistency is not established.

Thank you for your reading, the above is the content of "what is the CAP Theorem", after the study of this article, I believe you have a deeper understanding of what the CAP Theorem is, and the specific use needs to be verified in practice. Here is, the editor will push for you more related knowledge points of the article, welcome to follow!

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