A Survey of Query Evaluation under Updates

PhD Qualifying Examination


Title: "A Survey of Query Evaluation under Updates"

by

Mr. Binyang DAI


Abstract:

In the big data era, many applications and services have evolved to 
continuously consume data from upstream sources and require rapid updates to 
query results. This underscores the need for efficient query evaluation 
under updates. In industry, this has driven the development of open-source 
stream processing frameworks. In academia, this is known as the incremental 
view maintenance (IVM) problem, with numerous IVM techniques and prototype 
systems developed in recent years.

This survey provides an overview of IVM techniques, focusing on their 
worst-case update time complexity. It examines established lower bound 
results and identifies conditions enabling constant-time updates. 
Furthermore, it reviews approximate query processing (AQP) techniques widely 
used in query evaluation under updates. Finally, it explores promising 
research directions and open challenges in this field.


Date:                   Wednesday, 11 June 2025

Time:                   3:00pm - 5:00pm

Venue:                  Room 3494
                        Lifts 25/26

Committee Members:      Prof. Ke Yi (Supervisor)
                        Prof. Dimitris Papadias (Chairperson)
                        Prof. Qiong Luo