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Container scheduling method, electronic equipment and storage medium

A scheduling method and container technology, which is applied in the directions of multi-program device, climate sustainability, program start/switching, etc., can solve the problems of low batch scheduling efficiency of business operations, improve scheduling efficiency, alleviate resource competition, and improve matching degree of effect

Active Publication Date: 2022-08-02
ZTE CORP
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

See Figure 3, big data or artificial intelligence operations often include Different tasks, the existing batch scheduling method needs to traverse the resource requirements of all tasks in a big data or artificial intelligence job when making a scheduling decision, resulting in low batch scheduling efficiency of business jobs in the prior art

Method used

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  • Container scheduling method, electronic equipment and storage medium
  • Container scheduling method, electronic equipment and storage medium
  • Container scheduling method, electronic equipment and storage medium

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Embodiment Construction

[0035] It should be understood that the specific implementations described herein are only used to explain the present invention, and to limit the present invention.

[0036] In the following description, suffixes such as "module", "component" or "unit" used to denote elements are only used to facilitate the description of the present invention, and have no special meaning by themselves, therefore, "module", "component" Or "units" can be mixed.

[0037] The batch scheduling method represented by Volcano in the prior art schedules all tasks contained in a big data and artificial intelligence job to the same node as much as possible. Since these tasks may require the same resource type, this batch scheduling method Problems that easily lead to node resource competition, such as Figure 4 As shown, at present, the existing batch scheduling method only improves the scheduling efficiency of big data and artificial intelligence jobs to a certain extent, but there are still problems...

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Abstract

The embodiment of the invention provides a container scheduling method, electronic equipment and a storage medium. The method comprises the steps of dividing a task container corresponding to a business job to at least one custom description resource object according to a task type; determining the fitness and bearing capacity of each cluster node to the task container in the custom description resource object; and configuring a scheduling relationship between the cluster node and the task container according to the fitness and the bearing capacity. According to the embodiment of the invention, batch scheduling of the task containers is realized, the container scheduling efficiency can be improved, the task containers are allocated to different cluster nodes according to the fitness and the bearing capacity, the matching degree of the task containers and the cluster nodes can be improved, and the problem of resource competition of the cluster nodes is relieved.

Description

technical field [0001] The invention relates to the technical field of computer applications, and in particular, to a container scheduling method, an electronic device and a storage medium. Background technique [0002] In recent years, big data and artificial intelligence technologies have developed rapidly, and data mining, data collection, data processing, data aggregation and deep learning have become the mainstream types of operations in current cloud data centers. These different types of data jobs all need to be divided into interdependent tasks to run together. [0003] With the development of container virtualization technology, users tend to encapsulate tasks and their dependencies into lightweight containers to run. Existing container deployment solutions create their own corresponding container operations for each task in big data and artificial intelligence jobs. Since big data and artificial intelligence jobs often contain multiple tasks, a big data and artifi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/455G06F9/48G06F9/50
CPCG06F9/45558G06F9/4881G06F9/5061G06F9/5038G06F2009/4557Y02D10/00
Inventor 屠要峰刘子捷牛家浩高洪张登银王德政
Owner ZTE CORP
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