07212 Abstracts Collection -- Constraint Databases, Geometric Elimination ang Geographic Information Systems

From 20.05. to 25.05., the Dagstuhl Seminar 07212 ``Constraint Databases, Geometric Elimination and Geographic Information Systems\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

MLPQ: A LINEAR CONSTRAINT DATABASE SYSTEM WITH AGGREGATE OPERATORS

In this project report, I will discuss a Multiple Linear Programming Query (MLPQ) system and the theoretical background of this system.The MPLQ system is developed to solve some realistic problems involving both linear programming (UP) techniques and linear constraint databases (LCDBs) theory. The MLPQ system is aimed at providing a mechanism of bridging these two important areas. system basically consists of three parts which are a linear constraint database, an LP solver, and an interface between the LCDB and the LP solver. The LCDB of the MLPQ system contains multiple linear programming problems. The LP solver used in the MPLQ is an implementation Of the SIMPLEX method. An important feature of the MLPQ system is that it can handle the SQL aggregate Operators, such as minimum Min, maximum Max, summation Sum, and average Avg. The MLPQ system provides an efficient way of evaluation of aggregate operators for linear constraint databases

Towards Practical Constraint Databases (Extended Abstract)

) St ephane Grumbach I.N.R.I.A. Rocquencourt BP 105 78153 Le Chesnay, France [email protected] Jianwen Su Computer Science Department University of California Santa Barbara, California 93106, USA [email protected] Abstract We develop a framework for (real) constraint databases based on finite precision arithmetic which fulfills the main requirements of practical constraint databases. First, it allows the manipulation of approximate values, standard in scientific applications. More importantly, it permits the extension of the relational calculus with aggregate functions, while preserving the fundamental property of closed form evaluation with PTIME data complexity. This is an important step since the initial model of [KKR90] cannot be extended to aggregate functions. Moreover, finite precision computation plays a central role in efficient query processing. We introduce the finite precision semantics of queries and prove expressive power results concerning it. We then prese..