Efficient OLAP Queries on In-memory Databases with Frequent Updates

In this project, we will collaborate with Actenum our industry partner tackle the challenges of online analytics processing (OLAP) queries on in-memory databases that are updated frequently. Specifically, we will address the technical research issues about how to conduct effective and efficient OLAP on frequently updated data stored in a large in-memory database, and retain the query answering time within a millisecond scale. We will explore effective query syntax, informative query result presentation, and efficient query answering algorithms. The research outcome will benefit our industry partner immediately.

Faculty Supervisor:

Dr. Jian Pei

Student:

Xiaoning Xu & TBD

Partner:

Actenum Corporation

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Simon Fraser University