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A Method for Partial Top-k/Bottom-k Queries in On-line Analytical Processing (2006)
| Content Provider | CiteSeerX |
|---|---|
| Author | Chung, Yon Dohn Yang, Woo Suk Kim, Myoung Ho |
| Abstract | Abstract—Online analytical processing (OLAP) is a widely used technology for facilitating decision support applications. In the paper we consider partial aggregation queries, especially for partial top-k/bottom-k, which retrieve top/bottom k records among the specified cells of the given query. For efficient processing of partial ranking queries, this paper proposes a set of algorithms using the RD-Tree that was previously proposed data structure for partial max/min queries. Through experiments with real data, we show the efficiency, robustness, and low storage overhead of the proposed method. O Index Terms—Aggregation, OLAP, Partial Ranking Queries, RD-Tree, Top-k/Bottom-k. |
| File Format | |
| Publisher Date | 2006-01-01 |
| Access Restriction | Open |
| Subject Keyword | Partial Top-k Bottom-k Query On-line Analytical Processing Partial Ranking Query Low Storage Overhead Top-k Bottom-k Efficient Processing Decision Support Application Partial Max Min Query Top Bottom Record Partial Aggregation Query Abstract Online Analytical Processing Specified Cell Partial Top-k Bottom-k Index Term Aggregation |
| Content Type | Text |
| Resource Type | Article |
