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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/14194
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| Title: | On the Semantics of "Now" in Databases |
| Authors: | Clifford, James
Dyreson, Curtis
Isakowitz, Tomas
Jensen, Christian S.
Snodgrass, Richard T. |
| Issue Date: | Jun-1996 |
| Publisher: | Stern School of Business, New York University |
| Series/Report no.: | IS-96-03 |
| Abstract: | 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. |
| URI: | http://hdl.handle.net/2451/14194 |
| Appears in Collections: | IOMS: Information Systems Working Papers
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