Name
Abstract | ||
|---|---|---|
Dwarf is a highly compressed structure, which compresses the cube by eliminating the semantic redundancies while computing a data cube. Although it has high compression ratio, Dwarf is slower in querying and more difficult in updating due to its structure characteristics. So we propose two novel clustering methods for query optimization: the recursion clustering method for point queries and the hierarchical clustering method for range queries. To facilitate the implementation, we design a partition strategy and a logical clustering mechanism. Experimental results show our methods can effectively improve the query performance on data cubes, and the recursion clustering method is suitable for both point queries and range queries. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-74553-2_16 | DaWaK |
Keywords | DocType | Volume |
clustered dwarf structure,query optimization,query performance,recursion clustering method,hierarchical clustering method,point query,structure characteristic,range query,data cubes,dwarf structure,data cube,logical clustering mechanism,hierarchical clustering,compression ratio | Journal | 1 |
Issue | ISSN | ISBN |
2 | 0302-9743 | 3-540-74552-1 |
Citations | PageRank | References |
1 | 0.37 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fangling Leng | 1 | 24 | 4.13 |
| Yubin Bao | 2 | 80 | 16.78 |
| Daling Wang | 3 | 207 | 41.35 |
| Ge YU | 4 | 1313 | 175.88 |