GraphQL response data volume prediction based on Code2Vec and AutoML
International Journal of Web Information Systems
ISSN: 1744-0084
Article publication date: 8 March 2024
Issue publication date: 30 April 2024
Abstract
Purpose
GraphQL is a new Open API specification that allows clients to send queries and obtain data flexibly according to their needs. However, a high-complexity GraphQL query may lead to an excessive data volume of the query result, which causes problems such as resource overload of the API server. Therefore, this paper aims to address this issue by predicting the response data volume of a GraphQL query statement.
Design/methodology/approach
This paper proposes a GraphQL response data volume prediction approach based on Code2Vec and AutoML. First, a GraphQL query statement is transformed into a path collection of an abstract syntax tree based on the idea of Code2Vec, and then the query is aggregated into a vector with the fixed length. Finally, the response result data volume is predicted by a fully connected neural network. To further improve the prediction accuracy, the prediction results of embedded features are combined with the field features and summary features of the query statement to predict the final response data volume by the AutoML model.
Findings
Experiments on two public GraphQL API data sets, GitHub and Yelp, show that the accuracy of the proposed approach is 15.85% and 50.31% higher than existing GraphQL response volume prediction approaches based on machine learning techniques, respectively.
Originality/value
This paper proposes an approach that combines Code2Vec and AutoML for GraphQL query response data volume prediction with higher accuracy.
Keywords
Acknowledgements
Funding: This research was supported by the Education Ministry Humanities and Social Science Research Planning Fund Project of China (23YJAZH192), National Key R&D Program of China (2022ZD0119501), NSFC (52374221), and Natural Science Foundation of Shandong Province of China (ZR2021QG038, ZR2020MF044).
Citation
Zhang, F., Wei, Y. and Feng, T. (2024), "GraphQL response data volume prediction based on Code2Vec and AutoML", International Journal of Web Information Systems, Vol. 20 No. 3, pp. 268-288. https://doi.org/10.1108/IJWIS-12-2023-0246
Publisher
:Emerald Publishing Limited
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