HINTA: A Linearization Algorithm for Physical Clustering of Complex OLAP Hierarchies.
Roland Pieringer, Volker Markl, Frank Ramsak, Rudolf Bayer · 2001
Hierarchies are an important means to categorize data stored in OLAP systems. OLAP queries follow the drill/slice/dice-paradigm and therefore exhibit navigation patterns that follow the hierarchy of a dimension. In real-world applications, hierarchies are often unbalanced and share levels, resulting in complex hierarchy structures. So far, encoding methods for simple structured hierarchies have been introduced to handle hierarchies efficiently for query processing. In this paper we propose the HINTA algorithm to compute the clustering order for complex hierarchies by linearization. The physical clustering of OLAP data computed by HINTA significantly improves the performance of OLAP queries. HINTA enables clustering of complex hierarchies that can share hierarchy levels in several classifications over one dimension.