University of Maryland
|Topic:||Improving the Performance of Heterogeneous Databases|
|Date:||Tuesday, March 20, 2001|
|Place:||Gould-Simpson, Room 701|
My work focuses on optimizing the performance of servers that access multiple networked heterogeneous data sources and that process a large number of concurrent submitted queries. In particular, I have developed techniques that address the following three problems: (1) Given a networked query that accesses heterogeneous data sources, how do we compute its cost? (2) Given a set of queries spanning heterogeneous networked data sources, how do we merge these queries together so as to reduce the workload on the server? and (3) Given a set of queries, how can we partition this set of queries into clusters so that the queries in each cluster may be merged using the techniques of (2) above? Specifically, I will summarize our solutions to problems (1) and (2) and describe algorithms which partition a large number of concurrent queries into components of small size (e.g. 10 to 50) so that each component's queries can be merged using techniques we developed to solve problem (2). I will also provide experimental results that justify the scalability of our approach.