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This document presents a novel cardinality estimation model for complex database systems using a TreeLSTM neural network, which addresses the limitations of traditional methods by accurately capturing correlations between multiple tables. The proposed model incorporates a sampling method and a hybrid loss function to enhance estimation accuracy, particularly for complex SQL queries. Experimental results demonstrate that this model significantly outperforms existing cardinality estimation techniques in terms

Author

Laradj CHELLAMA

Language

EN