CARDINALITY ESTIMATION METHOD AND DEVICE FOR SKYLINE QUERY BASED ON DEEP LEARNING

A cardinality estimation method for Skyline query based on deep learning comprises: parsing historical query log information of a database to obtain Skyline query on a given target dataset and its corresponding cardinality to construct a training set; constructing and training respective data distribution learning models according to distribution information of the target dataset and the training set; using model parameters of the trained data distribution learning models as initialization parameter of the cardinality estimation model, and training the cardinality estimation model according to the training set; inputting query points to obtain final cardinality estimates according to the trained cardinality estimation model. The present disclosure provides a solution for cardinality estimation for Skyline query variants, and ensures the monotonic nature of cardinality estimation for Skyline query variants, and proposes an efficient and accurate cardinality estimation method.