Overview of Our Research

Database Access Methods

Indexing techniques can significantly improve query efficiency. We use machine learning techniques to optimize various index structure based on the data distribution and workload patterns.


Query Optimization

Query optimizer is at the core of a data management system. Traditional query optimizer requires a huge amount of work to build, and yet performs sub-optimally. We explore opportunities to enhance query optimizers with learning-based techniques, e.g., leared cardinalitiy estimation, multi-query optimization.


ML4DB Foundation

The foundation of applying machine learning to problems like cardinality estimation/ query optimization is to have an effective representation of the query plans.


Database Testing and Tools

There are plenty of other application of machine learning in data management systems. For example, we studied database generation from query workloads, which enables cloud database benchmarking and stress testing.


List of Projects