A multi-service interface execution time prediction method for big data platform considering busyness
A technology of big data platform and execution time, applied in the direction of electric digital data processing, error detection/correction, instrument, etc., can solve the problems of poor practicality, no consideration of platform, and difficulty in accurately predicting the execution time of service interface, so as to ensure the accuracy , Improving the effect of service efficiency and quality
Active Publication Date: 2020-03-27
SHANDONG UNIV
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For the execution time prediction of IoT interface services, traditional time prediction methods do not take into account the actual operating environment of the platform, so they are not practical and highly subjective, making it difficult to accurately predict the execution time of service interfaces. Therefore, effective data analysis and processing technologies are urgently needed. Accurately predict the execution time of the service interface, thereby improving the accuracy of the service execution time prediction model, making full use of platform resources, improving the overall performance of the platform, and also facilitating the management of IoT services and promoting the development of IoT
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[0038] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0039] It should be pointed out that the following detailed description is exemplary and intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
[0040] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinatio...
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The invention discloses a multi-service interface execution time prediction method for a big data platform considering a busyness degree. The method comprises the steps that parameters in the execution process of an internet-of-things interface service are defined; the value of a data volume, the size of a data block, the IO performance of a database and the number of free containers are obtainedfrom historical execution information of the interface service and monitoring information of the platform, and a primary prediction model of service execution time is established according to the obtained information; the primary prediction model is fitted according to the function type of the interface service to obtain a corrected prediction model of the service execution time; according to different services and different running time periods, the prediction execution time of the corrected prediction model of the service execution time is solved. According the method, the prediction model is corrected according to the busyness degree of the platform, and the purpose of improving the accuracy of the prediction model of the service running time is achieved.
Description
technical field [0001] The invention relates to a method for predicting the execution time of a multi-service interface on a big data platform considering the degree of busyness. Background technique [0002] With the development of Internet technology and the maturity of service-oriented architecture technology, the service-based interface application technology has been widely applied to IoT. In the service management layer in IoT, upgrading the traditional data interface to interface service not only facilitates the management of the interface, simplifies the process of data transmission, but also greatly improves the quality of data transmitted by the interface, and improves the user's understanding of data and applications. Product satisfaction. However, for the platform, in the face of numerous interface services, how to accurately predict the execution time of the interface services, not only meet the user's data needs, but also make full use of the resources of the ...
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IPC IPC(8): G06F11/34
CPCG06F11/3409G06F11/3457
Inventor 史玉良王新军张世栋孔兰菊闫中敏
Owner SHANDONG UNIV