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COMPRESSING DATA CUBE IN PARALLEL OLAP SYSTEMS
| Content Provider | CiteSeerX |
|---|---|
| Author | Eavis, Todd Dehne, Frank Liang, Boyong |
| Abstract | This paper proposes an efficient algorithm to compress the cubes in the progress of the parallel data cube generation. This low overhead compression mechanism provides block-by-block and record-by-record compression by using tuple difference coding techniques, thereby maximizing the compression ratio and minimizing the decompression penalty at run-time. The experimental results demonstrate that the typical compression ratio is about 30:1 without sacrificing running time. This paper also proposes two data cube computation algorithms based on the proposed compressed data structure. Moreover, my work demonstrates that the compression method is also suitable for Hilbert Space Filling Curve, a mechanism widely used in multi-dimensional indexing. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Record-by-record Compression Tuple Difference Low Overhead Compression Mechanism Efficient Algorithm Data Cube Computation Algorithm Data Structure Compression Ratio Parallel Data Cube Generation Decompression Penalty Hilbert Space Filling Curve Multi-dimensional Indexing Compression Method Typical Compression Ratio Experimental Result |
| Content Type | Text |
| Resource Type | Article |
