Satisfiability, implication, and equivalence problems involving conjunctive inequalities are important and widely encountered database problems that need to be efficiently and effectively processed. In this article we consider two popular types of arithmetic inequalities, (X op Y) and (X op C), where X and Y are attributes, C is a constant of the domain or X, and op � {�, �, �, �, �, �}. These inequalities are most frequently used in a database system, inasmuch as the former type of inequality represents a �—join, and the latter is a selection. We study the satisfiability and implication problems under the integer domain and the real domain, as well as under two different operator sets ({�, �, �, �, �} and {�,�,�,�,�,�}). Our results show that solutions under different domains and/or different operator sets are quite different. Out of these eight cases, excluding two cases that had been shown to be NP-hard, we either report the first necessary and sufficient conditions for these problems as well as their efficient algorithms with complexity analysis (for four cases), or provide an improved algorithm (for two cases). These iff conditions and algorithms are essential to database designers, practitioners, and researchers. These algorithms have been implemented and an experimental study comparing the proposed algorithms and those previously known is conducted. Our experiments show that the proposed algorithms are more efficient than previously known algorithms even for small input. Categories and Subject Descriptors: H.2.4 [Database Management]: Systems—query processing;

Data Caching at local clients plays an important role in improving the performance of client-server systems. In this paper, we introduce a novel caching scheme which is called semantic caching. Unlike the traditional page caching, tuple caching etc., the semantic cache is defined and accessed based on the queries submitted by the client. Both the predicates and the resulting tuples of queries are cached. When a new query is requested, the partial or whole result may be obtained through query processing on the semantic cache. With the advantages of low overhead, efficiency and flexibility, the semantic caching scheme can be used in the mobile computing environment,heterogeneous systems and general client-server systems. The formal definition of the semantic cache and related concepts are first given in this report, we then discuss the semantic cache management issues. At last, we investigate the semantic caching query processing techniques. Keywords: Semantic Cache, Semantic Segment, Query, Query Trimming, Coalescing, Cache Replacement, Satisfiability, Implicity.

Abstract. The correctness of the data managed by database systems is vital to any application that utilizes data for business, research, and decision-making purposes. To guard databases against erroneous data not reflecting real-world data or business rules, semantic integrity constraints can be specified during database design. Current commercial database management systems provide various means to implement mechanisms to enforce semantic integrity constraints at database run-time. In this paper, we give an overview of the semanticintegrity support in the most recent SQL-standard SQL:1999, and we show to what extent the different concepts and language constructs proposed in this standard can be found in major commercial (object-)relational database management systems. In addition, we discuss general design guidelines that point out how the semanticintegrity features provided by these systems should be utilized in order to implement an effective integrity enforcing subsystem for a database. Keywords: Semanticintegrity constraints – SQL:1999 – Object-relational databases – Constraint enforcement

The need to search for complex and recurring patterns in database sequences is shared by many applications. In this work, we discuss how to express and support efficiently sophisticated sequential pattern queries in relational database systems. Thus, we first

this paper, we investigate the design and optimization of a query language capable of expressing and supporting efficiently the search for complex sequential patterns in database systems. Thus, we first introduce SQL-TS, an extension of SQL to express these patterns, and then we study how to optimize the queries for this language. We take the optimal text search algorithm of Knuth, Morris and Pratt, and generalize it to handle complex queries on sequences. Our algorithm exploits the interdependencies between the elements of a pattern to minimize repeated passes over the same data. Experimental results on typical sequence queries, such as double bottom queries, confirm that substantial speedups are achieved by our new optimization techniques

Semantic caching is particularly attractive for use in a mobile computing environment due to the reduced wireless network trac and the fact that it provides more autonomy for the mobile clients. Previous work either does not provide a formal semantic caching model, or lacks efficient query processing strategies. This paper extends the existing research in three ways: formal de nitions associated with semantic caching are presented, query processing strategies are investigated, and the performance of the semantic cache model is examined through a detailed simulation study, which shows its effectiveness in mobile computing.

On-line analytical processing (OLAP) queries can take hours or even days to execute on very large data warehouses. Therefore, there is a need to employ techniques that can facilitate efficient execution of these queries. Data partitioning concept that has been studied in the context of relational databases aims to reduce query execution time and facilitate the parallel execution of queries. In this paper, we develop a framework for applying the partitioning technique on DW schema (star schema) to reduce the total query execution cost. We develop an analytical cost model for executing a set of OLAP queries on a partitioned star schema. We conduct experiments to evaluate the utility of partitioning in efficiently executing OLAP queries. Finally,we show how partitioning can be used to facilitate parallel execution of OLAP queries. 1