Looking at the problem of effectively and efficiently partitioning data warehouses, most of state-of-the-art approaches, which are very often heuristic-based, are static, since they assume the existence of an a-priori known set of queries. Contrary to this, in real-life applications, queries may change dynamically and fragmentation heuristics need to integrate these changes. Following this main consideration, in this paper we propose and experimentally assess an incremental approach for selecting data warehouse fragmentation schemes using genetic algorithms. © 2013 Springer-Verlag Berlin Heidelberg.
Incremental algorithms for selecting horizontal schemas of data warehouses: The dynamic case
Cuzzocrea Alfredo;
2013
Abstract
Looking at the problem of effectively and efficiently partitioning data warehouses, most of state-of-the-art approaches, which are very often heuristic-based, are static, since they assume the existence of an a-priori known set of queries. Contrary to this, in real-life applications, queries may change dynamically and fragmentation heuristics need to integrate these changes. Following this main consideration, in this paper we propose and experimentally assess an incremental approach for selecting data warehouse fragmentation schemes using genetic algorithms. © 2013 Springer-Verlag Berlin Heidelberg.File in questo prodotto:
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