Hashcube: A Data Structure for Space- and Query-Efficient Skycube Compression

Kenneth S. Bøgh, Sean Chester, Darius Sidlauskas, Ira Assent

Abstract: The skyline operator returns records in a dataset that provide optimal trade-offs of multiple dimensions. It is an expensive operator whose query performance can greatly benefit from materialization. However, a skyline can be executed over any subspace of dimensions, and the materialization of all subspace skylines, called the skycube, dramatically multiplies data size. Existing methods for skycube compression sacrifice too much query performance; so, we present a novel hashing- and bitstring-based compressed data structure that supports orders of magnitude faster query performance.