Online association rule mining
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Informix under CONTROL: Online Query Processing
Data Mining and Knowledge Discovery
Large-Sample and Deterministic Confidence Intervals for Online Aggregation
SSDBM '97 Proceedings of the Ninth International Conference on Scientific and Statistical Database Management
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Aggregation in traditional database systems is performed in batch mode: a query is submitted, the system processes a large volume of data over a long period of time, and an accurate answer is returned. Batch mode processing has long been unacceptable to users. In this paper we describe the need for online aggregation processing, in which aggregation operators provide ongoing feedback, and are controllable during processing. We explore a number of issues, including both user interface needs and database technology required to support those needs. We describe new usability and performance goals for online aggregation processing, and present techniques for enhancing current relational database systems to support online aggregation.