Resource assessment method and device, computer equipment and storage medium

A computer program and resource technology, applied in the field of big data, can solve problems such as inaccurate evaluation methods, inability to quantitatively analyze and evaluate the usage of the entire queue or the entire cluster, etc.
CN109800975AActive Publication Date: 2019-05-24亚信科技(中国)有限公司
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
亚信科技(中国)有限公司
Publication Date
2019-05-24

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Abstract

The invention relates to a resource assessment method and system, computer equipment and a storage medium. The method comprises the following steps: obtaining cluster index information to be evaluated, determining cluster job average delay and a cluster resource utilization rate according to the to-be-evaluated cluster index information; according to the cluster index information to be evaluated,trunking operation average delay and trunking resource utilization rate are increased; determining a queue operation average delay standard deviation and a queue resource utilization rate standard deviation; According to at least one of the cluster job average delay, the cluster resource utilization rate, the queue job average delay standard deviation and the queue resource utilization rate standard deviation, resource assessment is carried out, so that quantitative analysis on the use condition of the whole queue or the whole cluster is realized, and the assessment method is more accurate.
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Description

technical field

[0001] The present application relates to the technical field of big data, in particular to a resource evaluation method, device, computer equipment and storage medium. Background technique

[0002] In the field of big data processing, with the increase of data and servers in the data center, there are higher requirements for the allocation of data and resources. Due to the increase in cluster size and the increase in program resource utilization requirements, the ability to monitor the cluster status in real time and provide timely feedback on the cluster and running jobs will greatly affect the overall functions and jobs of the entire big data platform. efficiency.

[0003] In the traditional method, for the resource usage of big data clusters, it is often only possible to analyze and evaluate the resource usage of a single job, and cannot effectively conduct quantitative analysis and evaluation of the usage of the entire queue or the entire cluster, and t...

Claims

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