Name
Abstract | ||
|---|---|---|
We discuss the usage of the paradigms of rough sets and granular computing in the core components of the Infobright's database engine. Having data stored in the form of compressed blocks of attribute values, our query execution methods utilize compact information about those blocks' contents instead of brute-force data decompression. The paper contains examples of algorithms implemented with the aim to minimize the need of accessing the compressed data in such operations as filtering, joining and aggregating. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/GrC.2010.177 | Granular Computing |
Keywords | Field | DocType |
infobright analytic database engine,database engine,attribute value,rough sets,rough set,granular computing,brute-force data decompression,query execution method,core component,compact information,relational databases,engines,data storage,rough set theory,data compression,databases,attribute values,computer architecture | Data mining,Relational database,Computer science,Computer data storage,Filter (signal processing),Rough set,Database engine,Granular computing,Data compression | Conference |
ISBN | Citations | PageRank |
978-1-4244-7964-1 | 4 | 0.45 |
References | Authors | |
9 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ślȩzak, D. | 1 | 4 | 0.45 |
| Piotr Synak | 2 | 481 | 45.13 |
| Jakub Wroblewski | 3 | 353 | 30.77 |
| Graham Toppin | 4 | 20 | 2.62 |