Query Rewriting for SWIFT (First) Answers
IEEE Transactions on Knowledge and Data Engineering
Online Feedback for Nested Aggregate Queries with Multi-Threading
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Approximate Query Translation Across Heterogeneous Information Sources
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Limiting Result Cardinalities for Multidatabase Queries Using Histograms
BNCOD 18 Proceedings of the 18th British National Conference on Databases: Advances in Databases
Progressive evaluation of nested aggregate queries
The VLDB Journal — The International Journal on Very Large Data Bases
Approximate query mapping: Accounting for translation closeness
The VLDB Journal — The International Journal on Very Large Data Bases
Quality-driven query answering for integrated information systems
Quality-driven query answering for integrated information systems
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Traditionally, the answer to a database query is construed to be the set of all tuples that meet the criteria stated. Strict adherence to this notion in query evaluation is however increasingly unsatisfactory because decision makers are more prone to adopting an exploratory strategy for information search which we call ``getting some answers quickly, and perhaps more later.'' In this paper, we propose a progressive query processing strategy that exploits this behavior to conserve system resources and to minimize query response time. This is accomplished by the heuristic decomposition of user queries into subqueries that can be evaluated on demand. We also describe the architecture of a prototype system that provides a non-intrusive implementation of our approach. Finally, we present experimental results that demonstrate the benefits of the progressive query processing strategy.