61 research outputs found
On Data Representation and Use In A Temporal Relational DBMS
Numerous proposals for extending the relational data model to incorporate the temporal
dimension of data have appeared over the past decade. It has long been known that these
proposals have adopted one of two basic approaches to the incorporation of time into the
extended relational model. Recent work formally contrasted the expressive power of these two
approaches, termed temporally ungrouped and temporally grouped, and demonstrated that the
temporally grouped models are more expressive. IN the temporally ungrouped models, the
temporal dimension is added through the addition of some number of distinguished attributes to
the schema of each relation, and each tuple is "stamped" with temporal values for these attributes.
By contrast, in temporally grouped models the temporal dimension is added to the types of values
that serve as the domain of each ordinary attribute, and the application's schema is left intact.
The recent appearance of TSQL2, a temporal extension to the SQL-92 standard based upon the
temporally ungrouped paradigm, means that it is likely that commercial DBMS's will be extended
to support time in this weaker way. Thus the distinction between these two approaches - and its
impact on the day-to-day user of a DBMS - is of increasing relevance to the database practitioner
and the database user community. In this paper we address this issue from the practical
perspective of such a user. Through a series of example queries and updates, we illustrate the
differences between these two approaches and demonstrate that the temporally grouped approach
more adequately captures the semantics of historical data.Information Systems Working Papers Serie
On the Semantics of "Now" in Databases
While "now" is expressed in SQL as CURRENT-TIMESTAMP within queries, this value cannot be
stored in the database. However, this notion of an ever-increasing current-time value has been
reflected in some temporal data models by inclusion of database-resident variables, such as
"now," "until-changed," "â," "@" and "-." Time variables are very desirable, but their use
also leads to a new type of database, consisting of tuples with variables, termed a variable
database.
This paper proposes a framework for defining the semantics of the variable databases of temporal
relational data models. A framework is presented because several reasonable meanings
may be given to databases that use some of the specific temporal variables that have appeared
in the literature. Using the framework, the paper defines a useful semantics for such databases.
Because situations occur where the existing time variables are inadequate, two new types of
modeling entities that address these shortcomings, timestamps which we call now-relative and
now-relative indeterminate, are introduced and defined within the framework. Moreover, the paper
provides a foundation, using algebraic bind operators, for the querying of variable databases
via existing query languages. This transition to variable databases presented here requires minimal
change to the query processor. Finally, to underline the practical feasibility of variable
databases, we show that database variables can be precisely specified and efficiently implemented
in conventional query languages, such as SQL, and in temporal query languages, such
as TSQL2.Information Systems Working Papers Serie
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