We propose to extend database systems by a Skyline operation. This operation filters out a set of interesting points from a potentially large set of data points. A point is interesting if it is not dominated by any other point. For example, a hotel might be interesting for somebody traveling to Nassau if no other hotel is both cheaper and closer to the beach. We show how SQL can be extended to pose Skyline queries, present and evaluate alternative algorithms to implement the Skyline operation, and show how this operation can be combined with other database operations (e.g., join and Top N).

Algebraic transformation and optimization tech-niques have been the method of choice in relational query execution, but applying them in OODBMS is difficult due to the complexity of object-oriented query languages. This paper demonstrates that the problem can be simplified by mapping an OO data model to the binary ralational model implemented by Monet, a state-of-the-art database kernel. We present a generic mapping scheme to flatten data models and study the case of a straightforward object-oriented model. We show how flattening enabled us to implement a query algebra, using only a very limited set of simple oper-ations. The required primitives and query execution strategies are discussed, and their performance is eval-uated on the 1GB TPC-D benchmark, showing that our divide-and-conquer approach yields excellent results. 1

Decision support queries typically involve several joins, a grouping with aggregation, and/or sorting of the result tuples. We propose two new classes of query evaluation algorithms that can be used to speed up the execution of such queries. The algorithms are based on (1) early sorting and (2) early partitioning--- or a combination of both. The idea is to push the sorting and/or the partitioning to the leaves, i. e., the base relations, of the query evaluation plans (QEPs) and thereby avoid sorting or partitioning large intermediate results generated by the joins. Both, early sorting and early partitioning are used in combination with hash-based algorithms for evaluating the join(s) and the grouping. To enable early sorting, the sort order generated at an early stage of the query evaluation plan is retained through an arbitrary number of socalled order-preserving hash joins (OHJs). To make early partitioning applicable to a large class of decision support queries, we generalize the s...

This paper describes an architecture for building distributed information systems from existing information resources, based on software agent and distributed object technologies. An agent-based architecture is used, with messages exchanged via the FIPA agent communication language (ACL). Novel features of this system include the use of standards from the object-oriented programming community such as the Common Object Request Broker Architecture (CORBA) (as a communications infrastructure), the Unified Modeling Language (used as an ontology representation language), the Object Data Management Group’s Object Query Language (used for queries) and the Object Management Group’s Meta Object Facility (used as the basis for an ontology repository agent). ‘Stringified ’ object references may be returned as the content of ACL messages, allowing query results to be made available via a variety of CORBA interfaces.

. Inter-object references are one of the key concepts of object-relational and object-oriented database systems. In this work, we investigate alternative techniques to implement inter-object references and make the best use of them in query processing, i.e., in evaluating functional joins. We will give a comprehensive overview and performance evaluation of all known techniques for simple (singlevalued) as well as multi-valued functional joins. Furthermore, we will describe special order-preserving functionaljoin techniques that are particularly attractive for decision support queries that require ordered results. While most of the presentation of this paper is focused on object-relational and object-oriented database systems, some of the results can also be applied to plain relational databases because index nested-loop joins along key/foreign-key relationships, as they are frequently found in relational databases, are just one particular way to execute a functional join. Key words: O...

In query optimization, a given query will be transformed by rewrite rules into an equivalent execution plan that is cheaper than the straightforwardly assigned plan according to some cost model. Finding the cheapest of all equivalent execution plans is a challenge since the rewriting of complex queries on the basis of a large set of rewriting rules may potentially span a very large space of equivalent plans. Consequently, one has to either use search strategies to explore (parts of) the search space or some heuristics to prune this space thus making it efficiently traversable. This paper presents the use of search strategies in the CROQUE project. The adaptation of some common strategies led to the development of a simple but powerful heuristics which is demonstrated by examples executed in the CROQUE prototype. The proposed heuristics can support any random--based search strategy or can be used stand--alone. It may be integrated seamlessly into most of the present query optimizers w...

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This paper describes an algebra for use with parallel object databases, and in particular ODMG compliant databases with OQL. Although there have been many proposals for parallel relational database systems, there has been much less work on parallel object databases, and on parallel query processing for object databases. The parallel algebra presented in this paper is an extension of an existing physical algebra for OQL, and has an important role during query optimization, and for describing execution plans. The paper presents not only the algebra, but also its role in the architecture of a parallel database.

The advanced data models for PAS that make these systems superior to their table-oriented antecedents (RDBMS) have an impact on the formalisms that are needed to capture these models and their appropiate query languages (eg. ODMG's OQL). Queries that are nested to arbitrary depth, path expressions, and complex predicates pose challenges on the query translation process. The work package RT2.1 will identify generic (algebraic) operators that allow the efficient translation of such queries. These operators will account for the various bulk types the data models feature. Optimisation techniques have to be found, adapted, and validated. PAS query languages allow to mix operations on bulk types and scalars (just like programming languages). Monad calculi treat bulk and scalar types in a uniform way, and allow for reasoning about arithmetics and general computation. This ooeers the perspective of a hybrid approach to query translation and optimisation, combining the power of algebra and calcu...