Abstract
Column-oriented database systems offer decision-makers the most appropriate model for data warehouse storage. However, in the absence of on-line analytical operators, the only, very costly, way of constructing OLAP cubes involves using the UNION operator for group by queries in order to obtain all the Group By required to compute the OLAP cube. To solve this problem, in this article we propose a new aggregation operator, called C-CUBE (Columnar-CUBE), which allows data cubes to be computed using column-oriented data warehouses. We implemented the C-CUBE operator within the column-oriented DBMS, MonetDB and conducted experiments on the benchmark SSBM (Star Schema Benchmark). Thus we have shown that C-CUBE has OLAP cubes computation times reduced by up to 60% compared with the SQL Server CUBE operator in a 1TB warehouse.
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Dehdouh, K., Bentayeb, F., Boussaid, O., Kabachi, N. (2014). Towards an OLAP Environment for Column-Oriented Data Warehouses. In: Bellatreche, L., Mohania, M.K. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2014. Lecture Notes in Computer Science, vol 8646. Springer, Cham. https://doi.org/10.1007/978-3-319-10160-6_20
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DOI: https://doi.org/10.1007/978-3-319-10160-6_20
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