Business data concurrent processing method, device thereof and system

Abstract

The invention provides a business data concurrent processing method, a device thereof and a system, belongs to the technical field of cloud computing, and can be applied to the financial field or other fields. The business data concurrent processing method comprises the steps of obtaining business input parameters, and determining rules corresponding to the input parameters and element information of elements corresponding to the rules; sending the element information of each element to a corresponding cluster client, so that each cluster client obtains an element value of each element information in parallel; and concurrently executing the rule corresponding to each element value according to each element value from each cluster client to obtain each execution result. The system expansibility, the operation stability and the service data processing efficiency can be improved, and related service requirements can be quickly responded.

Description

technical field [0001] The present invention relates to the technical field of cloud computing, in particular to a method, device and system for concurrently processing business data. Background technique [0002] With the rise of the wave of Internet finance, the online business volume of inclusive finance and personal loans is increasing day by day, and the demand for time-sensitive data processing is getting stronger and stronger. In this situation, it is necessary to put higher requirements on the system's real-time data processing capabilities. However, at the technical level, due to the microservice transformation and service group splitting caused by system upgrades, data is scattered in various libraries along with the splitting of business domains. , business personnel expect to obtain index data from different data sources, or even external index data from third parties outside the industry to achieve comprehensive data control, which greatly reduces the efficiency...

AI Technical Summary

Problems solved by technology

In this situation, it is necessary to put higher requirements on the system's real-time data processing capabilities. However, at the technical level, due to the microservice transformation and service group splitting caused by system upgrades, data is scattered in various libraries along with the splitting of business domains. , business personnel expect to obtain index data from different data sources, or even external index data from third parties outside the industry to achieve comprehensive data control, which greatly reduces the efficiency of system element value extraction; in addition, the decision engine system adapts to different business needs. The rule models are constantly being added, and multiple rule models (such as common rules, rule sets, and scorecard rules) are used in one scenario at the same time, which affects the execution performance of the decision engine for rules, which makes it difficult for the system to meet the millisecond level of business Respond to demand in real time

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