Data Management

Compression of High-Dimensional Data Spaces Using Non-Differential Augmented Vector Quantization

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Executive Summary

Most data-intensive applications are confronted with the problems of I/O bottleneck, poor query processing times and space requirements. Database compression alleviates this bottleneck, reduces disk space usage, improves disk access speed, speeds up query response time, reduces overall retrieval time and increases the effective I/O bandwidth. However, random access to individual tuples in a compressed database is very difficult to achieve with most of the available compression techniques. This paper reports a lossless compression technique called non-differential augmented vector quantization. The technique is applicable to a collection of tuples and especially effective for tuples with numerous low to medium cardinality fields.

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