Query Optimization using Machine and Deep Learning
In this project we will investigate and develop novel techniques that employ Machine Learning (ML) and Deep Learning (DL) for the optimal execution of queries in a relational DBMS. The research will be conducted with close collaboration with the team of IBM that develops Db2, the well-known relational DBMS of IBM. The goal is to integrate the produced ‘learned’ optimizer in Db2. The students that will work on the project will extract information from queries and execution plans and use this information in order design, develop, and evaluate ML/DL-based approaches that learn the current optimizer’s cost inaccuracies. Furthermore, they will design a technique that enables the query optimizer to incorporate such information into the decision making process towards the selection of the best query execution plan.
Voir la description complète du projetVasiliki Kantere
IBM Canada Ltd
Computer science
Agriculture; Information and cultural industries; Manufacturing; Professional, scientific and technical services
University of Ottawa
Accelerate
