Method and device for uniformly distributing data

Abstract

The invention provides a method and a device for uniformly distributing data, and relates to the big data technology, and the method comprises the steps: taking a geographic position as a first calculation factor, and carrying out the primary classification of customer data through a clustering algorithm; determining a customer transaction relevance characteristic value according to the customer transaction historical information; on the basis of the primary classification result, using the customer transaction relevance characteristic value as a second calculation factor, and utilizing a clustering algorithm to perform secondary classification on the customer data; determining an attribute characteristic value and a customer transaction behavior characteristic value according to the customer transaction historical information; and according to the attribute feature values and the customer transaction behavior feature values, uniformly distributing the results of the secondary classification to a data center. According to the invention, client data and resources can be uniformly distributed among the data centers and in the data centers, uniform transaction hotspots of the data centers are ensured, and the transaction performance is improved.

Description

technical field [0001] The invention relates to the technical field of computer data processing, in particular to a method and device for evenly distributing data. Background technique [0002] This section is intended to provide a background or context for implementations of the invention that are recited in the claims. The descriptions herein are not admitted to be prior art by inclusion in this section. [0003] Most of the existing banking systems are deployed in a centralized manner. The data is concentrated in a center across the country, and data backups are established in the same city or in different places. Under the distributed architecture, most banking systems allocate customers according to provinces or according to the total number of customers / The number of data centers is allocated to customers. In this allocation method, the data and resource allocation rules are relatively simple, and the even distribution of data and resources cannot be guaranteed. ...

AI Technical Summary

Problems solved by technology

If customer information and resources cannot be evenly distributed in each data center, it may lead to a situation where a data center is overheated and a data center has a low transaction volume in a high-concurrency scenario. In this case, it not only causes a waste of hardware resources , which also leads to a large number of transaction bottleneck resources in the overheated data center, which leads to a decrease in system processing performance

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