Task data processing method and device, readable storage medium and electronic equipment

Abstract

The embodiment of the invention discloses a task data processing method and device, a readable storage medium and electronic equipment. The method comprises the following steps: determining a currentpressure attribute of a target object and a matching characteristic value of each piece of task information corresponding to the target object, determining a target diffusion threshold according to the current pressure attribute, and allocating each piece of task information according to the target diffusion threshold and the matching characteristic value of each piece of task information. According to the embodiment of the invention, the target diffusion threshold for task classification can be dynamically determined according to the pressure condition of the current target object, so that the classified task information is distributed in different distribution modes, the task receiving rate of the task information corresponding to the target object is ensured, and the task processing efficiency of a system is further improved.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a task data processing method, device, readable storage medium and electronic equipment. Background technique [0002] Currently, in the task processing process in the Internet field, the task scheduling platform will classify the multiple acquired tasks, so as to assign tasks to each type of task in different ways. However, in the actual application process, the classification rules for tasks on the task scheduling platform are pre-set rules, which cannot be adjusted flexibly when faced with different task situations. Therefore, in special situations such as a sudden increase in the amount of tasks and a sharp increase in the difficulty of task processing, the probability of tasks being picked up will decrease due to the use of the task allocation rules under normal conditions, which will affect the overall task processing efficiency of the system. Contents of the in...

AI Technical Summary

Problems solved by technology

However, in the actual application process, the task scheduling platform's classification rules for tasks are pre-set rules, which cannot be flexibly adjusted in the face of different task situations

Therefore, in the case of special situations such as a sudden increase in the amount of tasks and a sharp increase in the difficulty of task processing, the probability of tasks being picked up will decrease due to the use of the task allocation rules in the normal state, which will affect the overall task processing efficiency of the system

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