Achieving a Sequenced, Relational Query Language with Log-Segmented Timestamps

In a relational temporal database, typically each row of each table has a period timestamp to indicate the lifetime of that row. In order to evaluate a query in a temporal database, sequenced semantics comes into play. The semantics stipulates that the query must be evaluated simultaneously in each time instant using the data rows available at that point of time. Existing researches have proposed changes in the query evaluation engine to achieve sequenced semantics. In this paper we show a way to support sequenced semantics without modifying the query engine. We propose a noble construction log-segmented label to represent the lifetime and replace the period timestamp from each row with a log-segmented label that signifies when the tuple is alive. Then we translate a sequenced query to a non-temporal query by utilizing the properties of log-segmented label. The translated query has only operations already available in a typical relational database making the query readily executable in an unaltered installation of the database. Thus the sequenced query inevitably runs and retrieve data without changing query evaluation engine. Finally our implementation using Java language, ANTLR parser generator and PostgreSQL database demonstrates the feasibility of the proposed mechanism, which, to the best of our knowledge, has not been previously shown

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

Translating Temporal SQL to Nested SQL

Sequenced and nonsequenced semantics are the two previously researched semantics for the evaluation of an operation in a temporal database such as a query or data modification. Sequenced semantics evaluates an operation in each time instant using only the data alive at that time. Nonsequenced semantics, in contrast, means that an operation explicitly references and manipulates the timestamps in the data. In this thesis we propose a new framework that shows both semantics are variants of a general temporal semantics. We present the general semantics and show how additional semantics, such as preceding semantics can be realized. The semantics are specified using annotations. The primary contribution of this theses is the translation from temporal SQL to nested SQL. We focus on SQL\u27s SELECT statement, which is used to query data. Temporal SQL is SQL annotated with temporal semantics. Nested SQL is SQL for non-1NF data, with additional operations, such as COGROUP and FLATTEN to create and un-nest, respectively, bags of tuples (non-1NF data). This thesis develops a denotational semantics for translating from temporal to nested SQL. We implemented the denotational semantics for an SQLite ANTLR grammar, and the thesis also reports on the implementation

28th International Symposium on Temporal Representation and Reasoning (TIME 2021)

The 28th International Symposium on Temporal Representation and Reasoning (TIME 2021) was planned to take place in Klagenfurt, Austria, but had to move to an online conference due to the insecurities and restrictions caused by the pandemic. Since its frst edition in 1994, TIME Symposium is quite unique in the panorama of the scientifc conferences as its main goal is to bring together researchers from distinct research areas involving the management and representation of temporal data as well as the reasoning about temporal aspects of information. Moreover, TIME Symposium aims to bridge theoretical and applied research, as well as to serve as an interdisciplinary forum for exchange among researchers from the areas of artifcial intelligence, database management, logic and verifcation, and beyond