Deductive Data Warehouses and Aggregate (Derived) Tables

نویسندگان

  • Kornelije Rabuzin
  • Mirko Malekovic
  • Mirko Cubrilo
چکیده

In one of our previous papers, the idea of deductive data warehouses has been introduced. It was shown how to use Datalog rules to perform Online Analytical Processing (OLAP) analysis on data. In this paper, we show how to use Datalog rules to specify the data warehouse model (data mart) as well as how to add rules that produce aggregate and derived tables that are normally used to speed up the process of retrieving data. Since it is good to have aggregate and derived tables (to speed up queries), the main drawback is that they require extra storage. Consequently implicit definition of such tables may seem interesting.

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تاریخ انتشار 2014