Abstract
Horizontal Data Partitioning is an optimization technique well suited to optimize star-join queries in Relational Data Warehouses. Most works focus on a static selection of a fragmentation schema. However, due to the evolution of data warehouses and the ad hoc nature of queries, the development of incremental algorithms for fragmentation schema selection has become a necessity. In this work, we present a Partitioning Algebra containing all operators needed to update a schema when a new query arrives. To identify queries which should trigger a schema update, we introduce the notion of query profiling.
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Bouchakri, R., Bellatreche, L., Faget, Z. (2014). Algebra-Based Approach for Incremental Data Warehouse Partitioning. In: Decker, H., Lhotská, L., Link, S., Spies, M., Wagner, R.R. (eds) Database and Expert Systems Applications. DEXA 2014. Lecture Notes in Computer Science, vol 8645. Springer, Cham. https://doi.org/10.1007/978-3-319-10085-2_40
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DOI: https://doi.org/10.1007/978-3-319-10085-2_40
Publisher Name: Springer, Cham
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