Consistency maintenance system and methods for distributed-type data

Abstract

Provided is a consistency maintenance system and methods for distributed-type data in a distributed-type cluster system. The consistency maintenance system and methods for distributed-type data is composed of a cluster management node, a global lock management node and a plurality of data maintenance nodes which are scattered in the system, wherein the data maintenance nodes are the isomorphic nodes suitable for storing one or more data replicas. The data maintenance nodes are provided with three modules of monitoring events, maintaining data consistency and sending events. The global lock management node is responsible for storing and managing update locks of all the data in a system, and storing all information of the data maintenance nodes. The global lock management node is provided with three modules of receiving and sending massage, the update locks requesting queue, and the information management for data maintenance nodes. The cluster management node is responsible for managing the latest information of all the nodes in the system, and testing the state of each node in the system periodically. The consistency maintenance system and methods for distributed-type data have the advantages of being reliable and flexible in work methods. Besides, a client can develop a data update towards a plurality of targets at the same time. The consistency maintenance system and methods for distributed-type data have a simple operation, a less communication overhead, a short updating time delay, and a promising application prospects.

Description

technical field [0001] The invention relates to a system and method for maintaining consistency of distributed data, belonging to the technical field of computers. Background technique [0002] A distributed system is a system that performs distributed processing tasks on an architecture of multiprocessors interconnected by a communication network. Because each piece of data in the distributed cluster system is stored in multiple nodes in the distributed cluster, when the data on one of the cluster nodes is updated, how to realize and guarantee the data on the remaining nodes in the cluster system The copy can also perform the same update operation, so that all copies of each data in the entire cluster system are guaranteed to be consistent, which is a focus of attention of technical personnel in the industry. [0003] There are mainly the following five existing technologies for solving distributed data consistency methods, but each of them has different disadvantages. Th...

AI Technical Summary

Problems solved by technology

Its disadvantages are: the update message must be sent to all data nodes in the shortest possible time. If it cannot be sent in a short time, the system will generate outdated data; moreover, once the node where the primary data is located fails, the data copy Nodes will not get update messages

Its disadvantage is: mirror data is read-only and cannot be written, and there are certain restrictions

The disadvantage of this method is: when a transaction update fails, it will cause an increase in the frequency of transaction restarts, and when the local transaction and the global transaction are executed at the same time, it is easy to cause data update inconsistencies

[0009] In short, in the process of data updating, the above-mentioned data consistency updating method in the prior art has imperfections in terms of possible node failure and network communication failure.

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