Patent attributes
A method is provided for generating a classification model configured to select an optimal execution combination for query processing. The method provides, to a processor, training queries and different execution combinations for executing the training queries. Each different execution combination involves a respective different query engine and a respective different runtime. The method extracts, from a set of Directed Acyclic Graphs (DAGs) using a set of Cost-Based Optimizers (CBOs), a set of feature vectors for each of the plurality of training queries. The method adds, by the processor to each of merged feature vectors a respective label indicative of the optimal execution combination based on actual respective execution times of the plurality of different execution combinations, to obtain a set of labels. The method trains, by the processor, the classification model by learning the set of merged feature vectors with the set of labels.
