Name
Abstract | ||
|---|---|---|
Processing of large amounts of data in data warehouses is increasingly being done in cluster architectures to achieve scalability. In this paper we look into the problem of ad hoc star join query processing in clusters architectures. We propose a new technique, the Star Hash Join (SHJ), which exploits a combination of multiple bit filter strategies in such architectures. SHJ is a generalization of the Pushed Down Bit Filters for clusters. The objectives of the technique are to reduce (i) the amount of data communicated, (ii) the amount of data spilled to disk during the execution of intermediate joins in the query plan, and (iii) amount of memory used by auxiliary data structures such as bit filters. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11546849_20 | DaWaK |
Keywords | Field | DocType |
multiple bit filter strategy,data warehouse,bit filters,auxiliary data structure,large amount,query plan,cluster architecture,query processing,bit filter,new technique,clusters architecture,data structure | Data warehouse,Hash join,Data mining,Data structure,Joins,Star schema,Fact table,Computer science,Database,Scalability,Query plan | Conference |
Volume | ISSN | ISBN |
3589 | 0302-9743 | 3-540-28558-X |
Citations | PageRank | References |
2 | 0.37 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Josep Aguilar-Saborit | 1 | 86 | 8.01 |
| Victor Muntés-Mulero | 2 | 204 | 22.79 |
| Calisto Zuzarte | 3 | 260 | 31.97 |
| Josep-L. Larriba-Pey | 4 | 162 | 17.44 |