An XML based scalable implementation of temporal databases using parametric model

A parametric model and a query language ParaSQL for temporal databases has been proposed in the past. As the attribute values in the model can vary in length, it is difficult to use existing relational storage technology. To address this, CanStoreX, our XML-based storage technology has been deployed in a prior implementation. In parallel, the storage technology as well as our style of implementation for database prototypes have gone through an evolution. This has necessitated the previous implementation to be revisited. In addition, a new parser has been developed using JavaCC. Furthermore, a larger subset of ParaSQL has been implemented. For testing, a utility to generate synthetic temporal relations has been developed. Conforming to the new style, the present implementation has been encapsulated in terms of high level commands. This allows end-users to system developers on one hand and various database prototypes on the other, to interact with a central storage system from a common GUI that facilitates execution of batches of commands. Our implementation has helped to identify pragmatic issues in temporal database implementation as well as as the storage technology more clearly

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

Disjunctively incomplete information in relational databases: modeling and related issues

In this dissertation, the issues related to the information incompleteness in relational databases are explored. In general, this dissertation can be divided into two parts. The first part extends the relational natural join operator and the update operations of insertion and deletion to I-tables, an extended relational model representing inclusively indefinite and maybe information, in a semantically correct manner. Rudimentary or naive algorithms for computing natural joins on I-tables require an exponential number of pair-up operations and block accesses proportional to the size of I-tables due to the combinatorial nature of natural joins on I-tables. Thus, the problem becomes intractable for large I-tables. An algorithm for computing natural joins under the extended model which reduces the number of pair-up operations to a linear order of complexity in general and in the worst case to a polynomial order of complexity with respect to the size of I-tables is proposed in this dissertation. In addition, this algorithm also reduces the number of block accesses to a linear order of complexity with respect to the size of I-tables;The second part is related to the modeling aspect of incomplete databases. An extended relational model, called E-table, is proposed. E-table is capable of representing exclusively disjunctive information. That is, disjunctions of the form P[subscript]1\mid P[subscript]2\mid·s\mid P[subscript]n, where ǁ denotes a generalized logical exclusive or indicating that exactly one of the P[subscript]i\u27s can be true. The information content of an E-table is precisely defined and relational operators of selection, projection, difference, union, intersection, and cartisian product are extended to E-tables in a semantically correct manner. Conditions under which redundancies could arise due to the presence of exclusively disjunctive information are characterized and the procedure for resolving redundancies is presented;Finally, this dissertation is concluded with discussions on the directions for further research in the area of incomplete information modeling. In particular, a sketch of a relational model, IE-table (Inclusive and Exclusive table), for representing both inclusively and exclusively disjunctive information is provided

Probabilistic Temporal Databases, I: Algebra

Dyreson and Snodgrass have drawn attention to the fact that in many temporal database applications, there is often uncertainty present about the start time of events, the end time of events, the duration of events, etc. When the granularity of time is small (e.g. milliseconds), a statement such as "Packet p was shipped sometime during the first 5 days of January, 1998" leads to a massive amount of uncertainty (5 times 24 times 60 times 60 times 1000) possibilities. As noted by Zaniolo et. al., past attempts to deal with uncertainty in databases have been restricted to relatively small amounts of uncertainty in attributes. Dyreson and Snodgrass have taken an important first step towards solving this problem. In this paper, we first introduce the syntax of Temporal-Probabilistic (TP) relations and then show how they can be converted to an explicit, significantly more space-consuming form called Annotated Relations. We then present a {\em Theoretical Annotated Temporal Algebra} (TATA). Being explicit, TATA is convenient for specifying how the algebraic operations should behave, but is impractical to use because annotated relations are overwhelmingly large. Next, we present a Temporal Probabilistic Algebra (TPA). We show that our definition of the TP-Algebra provides a correct implementation of TATA despite the fact that it operates on implicit, succinct TP-relations instead of the overwhelmingly large annotated relations. Finally, we report on timings for an implementation of the TP-Algebra built on top of ODBC. (Also cross-referenced as UMIACS-TR-99-09