Task scheduling method, device, platform, server and storage medium

Abstract

The embodiment of the invention provides a task scheduling method, a device, a platform, a server and a storage medium. The method comprises the steps of obtaining historical task data generated whena business system executes a historical task according to a first task scheduling parameter; at least according to the historical task data, predicting a task scheduling updating parameter which maximizes the resource utilization rate of the to-be-processed task executed by the service system; updating the first task scheduling parameter into a second task scheduling parameter based on the task scheduling updating parameter; and according to the second task scheduling parameter, allocating resources of the service system to the to-be-processed task, thereby improving the task scheduling efficiency.

Description

technical field [0001] The embodiments of the present invention relate to the field of search technology, and in particular to a task scheduling method, device, platform, server and storage medium. Background technique [0002] In the IT (Internet Technology, Internet Technology) system, the task scheduling platform can implement a planned automatic start request, so as to execute at a specified time point, or repeat the corresponding operation at regular intervals. Usually, this part of the automatically initiated request is called Tasks, and the platform that automatically initiates tasks is called a task scheduling platform. [0003] On a distributed task scheduling platform, a third-party task scheduling framework usually allocates business system resources (such as CPU, memory, and time) to tasks based on task scheduling parameters, so that tasks occupy the allocated resources to implement task execution. However, since the task scheduling parameters of the third-party...

AI Technical Summary

Problems solved by technology

However, since the task scheduling parameters of the third-party task scheduling framework depend on human’s advance configuration, these pre-configured task scheduling parameters may not be compatible with the operating conditions of the business system, resulting in low efficiency of task scheduling, which in turn makes the business system machine usage is low

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