Processing OLAP queries in hierarchically clustered databases

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


On-Line Analytical Processing (OLAP) is a technology that encompasses applications requiring a multidimensional and hierarchical view of data. OLAP applications often require fast response time to complex grouping/aggregation queries on enormous quantities of data. Commercial relational database management systems use mainly multiple one-dimensional indexes to process OLAP queries that restrict multiple dimensions. However, in many cases, multidimensional access methods outperform one-dimensional indexing methods. We present an architecture for multidimensional databases that are clustered with respect to multiple hierarchical dimensions. It is based on the star schema and is called CSB star. We focus on processing OLAP queries over this schema using multidimensional access methods. Users can still formulate their queries over a traditional star schema, which are then rewritten by the query processor over the CSB star. We exploit the different clustering features of the CSB star to efficiently process a class of typical OLAP queries. We detect cases where the construction of an evaluation plan can be simplified, and other cases where additional processing techniques can be applied.

Original languageEnglish (US)
Pages (from-to)205-224
Number of pages20
JournalData and Knowledge Engineering
Issue number2
StatePublished - May 2003
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Information Systems and Management


  • Grouping and aggregation query
  • Hierarchical clustering
  • Multidimensional database
  • On-Line Analytical Processing
  • Star schema


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