Relational database compression using augmented vector quantization
- 19 November 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 540-549
- https://doi.org/10.1109/icde.1995.380352
Abstract
Data compression is one way to alleviate the I/O bottleneck problem faced by I/O-intensive applications such as databases. However, this approach is not widely used because of the lack of suitable database compression techniques. In this paper, we design and implement a novel database compression technique based on vector quantization (VQ). VQ is a data compression technique with wide applicability in speech and image coding, but it is not directly suitable for databases because it is lossy. We show how one may use a lossless version of vector quantization to reduce database space storage requirements and improve disk I/O bandwidth.Keywords
This publication has 9 references indexed in Scilit:
- A physical storage model for efficient statistical query processingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Data compression and database performancePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Disk system architectures for high performance computingProceedings of the IEEE, 1989
- Data Compression in Scientific and Statistical DatabasesIEEE Transactions on Software Engineering, 1985
- Vector quantizationIEEE ASSP Magazine, 1984
- Vector quantization: A pattern-matching technique for speech codingIEEE Communications Magazine, 1983
- An Algorithm for Vector Quantizer DesignIEEE Transactions on Communications, 1980
- A new technique for compression and storage of dataCommunications of the ACM, 1974
- Run-length encodings (Corresp.)IEEE Transactions on Information Theory, 1966