Adaptive data clustering for databases

Abstract

The present disclosure provides a method for generating a classification model in a database system. The method comprises generating a plurality of database tables by performing data clustering on a database, acquiring a plurality of queries associated with information from the database, generating training data by executing each of the plurality of queries on the plurality of database tables, and training a classification model using the training data, wherein the classification model is used to select a database table for a query based on corresponding performance information associated with the query on the database during executing of the query. The present disclosure also provides a method for executing a query on a database using a classification model. The method comprises obtaining the classification model, obtaining a database query, generating a target table by inputting the database query into the classification model, and executing the database query on the target table. In addition, the present disclosure provides database systems and non-transitory computer-readable media for generating a classification model or executing a query on a database using a classification model.