Dynamic queries for information exploration: an implementation and evaluation
CHI '92 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Visual information seeking: tight coupling of dynamic query filters with starfield displays
CHI '94 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Processing queries for first-few answers
CIKM '96 Proceedings of the fifth international conference on Information and knowledge management
ACM SIGMOD Record
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
On saying “Enough already!” in SQL
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
On optimizing an SQL-like nested query
ACM Transactions on Database Systems (TODS)
Dataflow query execution in a parallel main-memory environment
PDIS '91 Proceedings of the first international conference on Parallel and distributed information systems
Database Management Systems
Reducing the Braking Distance of an SQL Query Engine
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Evaluating Top-k Selection Queries
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Online Feedback for Nested Aggregate Queries with Multi-Threading
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
On Getting Some Answers Quickly, and Perhaps More Later
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Nondeterministic Queries in a Relational Grid Information Service
Proceedings of the 2003 ACM/IEEE conference on Supercomputing
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Traditionally, the answer to a database query is construed as 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 驴getting some answers quickly, and perhaps more later.驴 From a decision-maker's perspective, such a strategy is optimal for coping with information overload and makes economic sense (when used in conjunction with a micropayment mechanism). These new requirements present new opportunities for database query optimization. In this paper, we propose a progressive query processing strategy that exploits this behavior to conserve system resources and to minimize query response time and user waiting time. This is accomplished by the heuristic decomposition of user queries into subqueries that can be evaluated on demand. To illustrate the practicality of the proposed methods, we describe the architecture of a prototype system that provides a nonintrusive implementation of our approach. Finally, we present experimental results obtained from an empirical study conducted using an Oracle Server that demonstrate the benefits of the progressive query processing strategy.