RHist: adaptive summarization over continuous data streams
Proceedings of the eleventh international conference on Information and knowledge management
Query distribution estimation and predictive caching in mobile ad hoc networks
Proceedings of the Seventh ACM International Workshop on Data Engineering for Wireless and Mobile Access
Stratified reservoir sampling over heterogeneous data streams
SSDBM'10 Proceedings of the 22nd international conference on Scientific and statistical database management
Adaptive stratified reservoir sampling over heterogeneous data streams
Information Systems
| Hi-index | 0.00 |
The ability to provide accurate and efficient result estimations of user queries is very important for the query optimizer in database systems. In this paper, we show that the traditional estimation techniques with data reduction points of view do not produce satisfiable estimation results if the query patterns are dynamically changing. We further show that to reduce query estimation error, instead of accurately capturing the data distribution, it is more effective to capture the user query patterns. In this paper, we propose query estimation techniques that can adapt to user query patterns for more accurate estimates of the size of selection or range queries over databases.