Frederic Dumonceaux presented a part of his Ph.D work at BDA’2014 (journées Bases de Données Avancées), entitled Materializing Data Cubes as Partitions of Sets of Tuples.

Abstract : In the last decade, several partition-based algorithms were introduced to summarize data cubes in a multidimensional modeling context. Summarization process contains in itself many critical issues occurring when querying a data warehouse. One concrete example is the ability to group similar queries to set up a materialization/caching policy improving re- sponse time whenever the result of a query is broadly close from a precomputed result. Indeed, while the number of in- volved dimensions linearly increases, data complexity of the query then grows exponentially and stored some views sum- marizing tuples aggregates is likely to speed up the overall query. The cornerstone is therefore the ability to handle aggre- gates of cells as well as a dedicated algebra which reflects navigation within a cube and query processing using de- scriptors and filtering. Moreover, although lots of frame- work were proposed to efficiently manage and process OLAP queries in many different ways, none of those handle their results as first-class objects to be managed and queried. In this paper, we propose an algebra whose base objects are partitions defined over the set of facts gathered in a data warehouse. We will annotate them to leave a contextual in- formation to express at once the result of many multidimensional queries. We will also outline its benefits in the whole building and querying process.

 

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