ConvMADE: Convolution Makes Cardinality Estimation Stronger

ConvMADE: Convolution Makes Cardinality Estimation Stronger

Cardinality estimation is critical for optimizing database queries, and accurate results are essential for a good query plan. Traditional models use statistical principles but struggle with complex data associations. Learning-based methods solve these problems but need to improve accuracy and reduce...

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Bibliographic Details
Main Authors: Chao Gao, Jiong Yu, Zhenzhen He, Xiaoqiao Xiong
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Autoregression model
cardinality estimation
convolution
database management system
query optimizer
Online Access:https://ieeexplore.ieee.org/document/10239358/

Internet

https://ieeexplore.ieee.org/document/10239358/

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