We present a domain-independent model of hierarchical software system design and construction that is based on interchangeable software components and largescale reuse. The model unifies the conceptualizations of two independent projects, Genesis and Avoca, that are successful examples of software component/building-block technologies and domain modeling. Building-block technologies exploit large-scale reuse, rely on open architecture software, and elevate the granularity of programming to the subsystem level. Domain modeling formalizes the similarities and differences among systems of a domain. We believe our model is a blue-print for achieving software component technologies in many domains.

Efficient methods of processing unanticipated queries are a crucial prerequisite for the success of generalized database management systems. A wide variety of approaches to improve the performance of query evaluation algorithms have been proposed: logic-based and semantic transformations, fast implementations of basic operations, and combinatorial or heuristic algorithms for generating alternative access plans and choosing among them. These methods are presented in the framework of a general query evaluation procedure using the relational calculus representation of queries. In addition, nonstandard query optimization issues such as higher level query evaluation, query optimization in distributed databases, and use of database machines are addressed. The focus, however, is on query optimization in centralized database systems.

The paper considers two decision problems on hypergraphs, hypergraph saturation and recognition of the transversal hypergraph, and discusses their significance for several search problems in applied computer science. Hypergraph saturation, i.e., given a hypergraph H, decide if every subset of vertices is contained in or contains some edge of H, is shown to be co-NP-complete. A certain subproblem of hypergraph saturation, the saturation of simple hypergraphs, is shown to be computationally equivalent to transversal hypergraph recognition, i.e., given two hypergraphs H 1; H 2, decide if the sets in H 2 are all the minimal transversals of H 1. The complexity of the search problem related to the recognition of the transversal hypergraph, the computation of the transversal hypergraph, is an open problem. This task needs time exponential in the input size, but it is unknown whether an output-polynomial algorithm exists for this problem. For several important subcases, for instance if an upper or lower bound is imposed on the edge size or for acyclic hypergraphs, we present output-polynomial algorithms. Computing or recognizing the minimal transversals of a hypergraph is a frequent problem in practice, which is pointed out by identifying important applications in database theory, Boolean switching theory, logic, and AI, particularly in model-based diagnosis.

Mobile computers and wireless networks are emerging technologies that will soon be available to a wide variety of computer users. Unlike earlier generations of laptop computers, the new generation of mobile computers can be an integrated part of a distributed computing environment, one in which users change physical location frequently. The result is a new computing paradigm, nomadic computing. This paradigm will affect the design of much of our current systems software, including that of database systems. This paper discusses in some detail the impact of nomadic computing on a number of traditional database system concepts. In particular, we point out how the reliance on short-lived batteries changes the cost assumptions underlying query processing. In these systems, power consumption competes with resource utilization in the definition of cost metrics. We also discuss how the likelihood of temporary disconnection forces consideration of alternative transaction processing pr...

Thii paper describes the techniques used to optimize relational queries in the SDD-1 distributed database system. Queries are submitted to SDD-1 in a high-level procedural language called Datalan-guage. Optimization begins by translating each Datalanguage query into a relational calculus form called an envelope, which is essentially an aggregate-free QUEL query. This paper is primarily concerned with the optimization of envelopes. Envelopes are processed in two phases. The first phase executes relational operations at various sites of the distributed database in order to delimit a subset of the database that contains all data relevant to the envelope. This subset is called a reduction of the database. The second phase transmits the reduction to one designated site, and the query is executed locally at that site. The critical optimization problem is to perform the reduction phase efficiently. Success depends on designing a good repertoire of operators to use during this phase, and an effective algorithm for deciding which of these operators to use in processing a given envelope against a given database. The principal reduction operator that we employ is called a

This paper deals with the evaluation of acyclic Boolean conjunctive queries in relational databases. By well-known results of Yannakakis [1981], this problem is solvable in polynomial time; its precise complexity, however, has not been pinpointed so far. We show that the problem of evaluating acyclic Boolean conjunctive queries is complete for LOGCFL, the class of decision problems that are logspace-reducible to a context-free language. Since LOGCFL is contained in AC 1 and NC 2, the evaluation problem of acyclic Boolean conjunctive queries is highly parallelizable. We present a parallel database algorithm solving this problem with a logarithmic number of parallel join operations. The algorithm is generalized to computing the output of relevant classes of non-Boolean queries. We also show that the acyclic versions of the following well-known database and AI problems are all LOGCFL-complete: The Query Output Tuple problem for conjunctive queries, Conjunctive Query Containment, Clause Subsumption, and Constraint Satisfaction. The LOGCFL-completeness result is extended to the class of queries of bounded treewidth and to other relevant query classes which are more general than the acyclic queries.

. Object-Relational and Object-Oriented DBMSs allow users to invoke time-consuming ("expensive") methods in their queries. When queries containing these expensive methods are run on data with duplicate values, time is wasted redundantly computing methods on the same value. This problem has been studied in the context of programming languages, where "memoization" is the standard solution. In the database literature, sorting has been proposed to deal with this problem. We compare these approachesalong with a third solution, a variant of unary hybrid hashing which we call Hybrid Cache. We demonstrate that Hybrid Cache always dominates memoization, and significantly outperforms sorting in many instances. This provides new insights into the tradeoff between hashing and sorting for unary operations. Additionally, our Hybrid Cache algorithm includes some new optimizations for unary hybrid hashing, which can be used for other applications such as grouping and duplicate elimination. We conclude...

Peer-to-peer (P2P) architectures are commonly used for file-sharing applications. The reasons for P2P's popularity in file sharing -- fault tolerance, scalability, and ease of deployment -- also make it a good model for distributed data management. In this paper, we introduce a scalable P2P framework for distributed data management applications using mutant query plans: XML serializations of algebraic query plan graphs that can include verbatim XML data, references to resource locations (URLs), and abstract resource names (URNs). We show how we can build distributed catalogs based on multihierarchic namespaces that can efficiently handle content indexing and query routing. We also discuss how peers can convey the currency and coverage of their data, and how queries can use this information to manage the inherent tradeoffs between answer completeness, timeliness, and latency.

Several techniques that compute the join between two spatial datasets have been proposed during the last decade. Among these methods, some consider existing indices for the joined inputs, while others treat datasets with no index, providing solutions for the case where at least one input comes as an intermediate result of another database operator. In this paper we analyze previous work on spatial joins and propose a novel algorithm, called slot index spatial join (SISJ), that efficiently computes the spatial join between two inputs, only one of which is indexed by an R-tree. Going one step further, we show how SISJ and other spatial join algorithms can be implemented as operators in a database environment that joins more than two spatial datasets. We study the differences between relational and spatial multiway joins, and propose a dynamic programming algorithm that optimizes the execution of complex spatial queries. Keywords Spatial Joins, Spatial Query Processing, Query Optimizati...

We define the magic-sets transformation for traditional relational systems (with duplicates, aggregation and grouping), as well as for relational systems extended with recursion. We compare the magic-sets rewriting to traditional optimization techniques for nonrecursive queries, and use performance experiments to argue that the magic-sets transformation is often a better optimization technique. 1 Introduction "Magic-sets" is the name of a query transformation algorithm ([BMSU86]) (and now a class of algorithms Part of this work was done at the IBM Almaden Research Center. Work at Stanford was supported by an NSF grant IRI87 -22886, an Air Force grant AFOSR-88-0266, and a grant of IBM Corporation. y Author's current affiliation: Tandem Computers. z Part of this work was done while the author was visiting IBM Almaden Research Center. Work at Wisconsin was supported by an IBM Faculty Development Award and an NSF grant IRI-8804319. --- Generalized Magic-sets of [BR87], Magic Tem...