1 research outputs found
Keeping Interval-Based Functional Dependencies Up-to-Date
In the temporal database literature, every fact stored in a
database may be equipped with two temporal dimensions: the valid time,
which describes the time when the fact is true in the modeled reality, and
the transaction time, which describes the time when the fact is current
in the database and can be retrieved. Temporal functional dependencies
(TFDs) add valid time to classical functional dependencies (FDs)
in order to express database integrity constraints over the flow of time.
Currently, proposals dealing with TFDs adopt a point-based approach,
where tuples hold at specific time points, to express integrity constraints
such as \u201cfor each month, the salary of an employee depends only on his
role\u201d. To the best of our knowledge, there are no proposals dealing with
interval-based temporal functional dependencies (ITFDs), where the associated
valid time is represented by an interval and there is the need
of representing both point-based and interval-based data dependencies.
In this paper, we propose ITFDs based on Allen\u2019s interval relations and
discuss their expressive power with respect to other TFDs proposed in
the literature: ITFDs allow us to express interval-based data dependencies,
which cannot be expressed through the existing point-based TFDs.
ITFDs allow one to express constraints such as \u201cemployees starting to
work the same day with the same role get the same salary\u201d or \u201cemployees
with a given role working on a project cannot start to work with the same
role on another project that will end before the first one\u201d. Furthermore,
we propose new algorithms based on B-trees to e!ciently verify the satisfaction
of ITFDs in a temporal database. These algorithms guarantee
that, starting from a relation satisfying a set of ITFDs, the updated
relation still satisfies the given ITFDs