Distributed task scheduling method and system and computer readable storage medium

Abstract

The invention discloses a distributed task scheduling method and system and a computer readable storage medium. The distributed task scheduling system comprises a scheduling information management module and a scheduling center module which are connected with each other, and the scheduling information management module is suitable for receiving distributed task configuration information input by auser so as to configure and manage distributed tasks; and the scheduling center module is suitable for receiving and analyzing the distributed task configuration information and sending an executionmessage corresponding to the distributed task configuration information to an application system at regular time. By applying the distributed task scheduling system, the development cost, the operation and maintenance cost and the system overhead of the distributed timed tasks can be reduced.

Description

technical field [0001] Embodiments of the present invention relate to the field of computer application technologies, and in particular, to a distributed task scheduling method and system, and a computer-readable storage medium. Background technique [0002] In software application systems, there are distributed timing tasks. Distributed timing tasks refer to deploying the same set of application codes on multiple node servers, and tasks that complete the same logic will not be executed repeatedly by each node at the same time. In a distributed environment, when a node fails, the failure can be automatically transferred, and other nodes automatically replace the failed node to perform scheduled tasks normally. [0003] In existing application systems, for distributed timing tasks, each application system needs to develop task modules independently, and at the same time use distributed locks or control business logic to avoid repeated task execution to ensure business correc...

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Problems solved by technology

For example, data needs to be queried for processing in scheduled tasks. Although the correctness of data processing can be guaranteed through the database optimistic locking mechanism, since each node is performing the same operation at the same time, it will increase the overhead and burden of the database.

In addition, when the application system is online, if you want to modify the scheduled task execution plan or suspend the scheduled task, you need to log in to all the servers where the system is deployed, shut down the application system first, then modify the execution plan of the scheduled task of the application system, and finally restart the application If the system is hard-coded, it is necessary to recompile the application system, and then log in to the server to re-publish, resulting in more complicated operation and maintenance, and higher system overhead

[0005] Therefore, the existing distributed task scheduling scheme has high development cost and large system overhead, which affects system performance

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