Periodic data play a major role in many application domains, spanning from manufacturing to office automation, from scheduling to data broadcasting. In many of such domains, the huge number of repetitions make the goal of extesiolly storing and accessing such data very challenging. In this paper, we propose a new methodology, based on an intensiol representation of periodic data. The representation model we propose captures the notion of periodic granularity provided by the temporal database glossary, and is an extension of the TSQL2 temporal relatiol data model. We define the algebraic operators, and introduce access algorithms to cope with them, proving that they are correct with respect to the traditiol extesiol approach.We also provide an experimental evaluation of our approach.
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