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This article mainly introduces "what is java distributed CAP Theorem". In daily operation, I believe that many people have doubts about what java distributed CAP Theorem is. Xiaobian consulted all kinds of data and sorted out simple and easy-to-use operation methods. I hope it will be helpful for you to answer the doubt of "what is java distributed CAP Theorem?" Next, please follow the editor to study!

CAP Theorem, also known as Brewer Theorem, is proposed by Eric brewer, a computer scientist, and is a theorem in the field of distributed systems. If you want to design a distributed architecture system, it is essential to master this theorem.

C is Consistency, that is, consistency, and in CAP is strong consistency. An is Availability, availability. P is Partition tolerance, partition fault tolerance. In a distributed system, you can't have all three, you can only choose two. This is the CAP theorem. For example, if you guarantee consistency and partition fault tolerance, you can't guarantee availability.

Consistency

The consistency here is strong consistency, which means that, for example, node A updates the data, and node B can update it at the same time, so that the client gets the latest data every time it reads. But our usual network delay is ignored in the theorem. In reality, network delay is still unavoidable, so we can only achieve final consistency, but the goal is still close to strong consistency, that is, try our best to reduce the delay time.

Availability

Availability means that a non-failure node needs to return a reasonable response at a reasonable time. A reasonable response means no error, no timeout failure. For example, node A updates the data and publishes it to node B at the same time, but the intermediate transmission cable is broken by the excavator, and the user accesses node B. at this time, node B should return the old data and should not report an error. This is usability. Make the user feel that the system still works.

Partition tolerance

Partition fault tolerance refers to the normal operation and response of the system when the network is partitioned. For example, node An and node B can not communicate, you have to consider how the system should be at this time. Although the probability of network partitioning is low and the time is short, this can happen. Therefore, in theory, it is necessary to sacrifice C or APowerP.

For example, throw P away. So at this time the system needs to ensure CA, and then the network partition occurs, nodes An and B can not communicate, at this time the client wants to write data to node A, but because the data cannot be synchronized to node B. Therefore, consistency can only be guaranteed by ensuring that A does not write. If you don't let the client write data to A, you can only report an error and return it to the client, saying that you can't write at this time. Is that a violation of usability?

Therefore, P must be guaranteed in the distributed system. So this is how CP,AP works in a distributed system.

What about CA? Please note that there are only two of the three CAP mentioned by CAP, so CA can be matched. That is, when there is no P in the system, CA collocation. In other words, it is necessary to meet C and A when there is no partition in the system, and abandon C or An according to the situation when the partition occurs in the system.

Be careful

CAP theory is not at the system level, but at the data level. What do you mean?

In other words, when there is a network partition, you can comply with CP for part of the data and AP for part of the data. For example, user registration scenarios can go to CP to ensure the success of login after user registration. And users change avatars on AP, after all, the impact of using old data will not be very great.

Therefore, we have to choose different solutions according to different business scenarios. CAP can be matched flexibly.

At this point, the study of "what is the CAP Theorem of java distribution" is over. I hope to be able to solve your doubts. The collocation of theory and practice can better help you learn, go and try it! If you want to continue to learn more related knowledge, please continue to follow the website, the editor will continue to work hard to bring you more practical articles!

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