基于嵌入式SQL的Datalog演绎规则解释器的设计

文章提出了一个建立在传统关系数据库基础上的能支持ANSISQL与嵌入式SQL的演绎规则解释器。利用这个解释器,用户能够定义一个蕴含关系并可以像在演绎数据库中使用Datalog规则一样来提出查询。其方法是把演绎规则和查询翻译成嵌入式SQL程序,该程序在执行查询时能被调用。这个解释器可以被认为是扩充RDBMS演绎查询功能的一个前端工具。     

A Distribution Design Methodology for Object DBMS

The design of distributed databases involves making decisions on the fragmentation and placement of data and programs across the sites of a computer network. The first phase of the distribution design in a top-down approach is the fragmentation phase, which clusters in fragments the information accessed simultaneously by applications. Most distribution design algorithms propose a horizontal or vertical class fragmentation. However, the user has no assistance in the choice between these techniques. In this work we present a detailed methodology for the design of distributed object databases that includes: (i) an analysis phase, to indicate the most adequate fragmentation technique to be applied in each class of the database schema; (ii) a horizontal class fragmentation algorithm, and (iii) a vertical class fragmentation algorithm. Basically, the analysis phase is responsible for driving the choice between the horizontal and the vertical partitioning techniques, or even the combination of both, in order to assist distribution designers in the fragmentation phase of object databases. Experiments using our methodology have resulted in fragmentation schemas offering a high degree of parallelism together with an important reduction of irrelevant data.     

Fragmenting relations horizontally using a knowledge-based approach

In distributed DBMSs, one major issue in developing a horizontal fragmentation technique is what criteria to use to guide the fragmentation. The authors propose to use, in addition to typical user queries, particular knowledge about the data itself. Use of this knowledge allows revision of typical user queries into more precise forms. The revised query expressions produce better estimations of user reference clusters to the database than the original query expressions. The estimated user reference clusters form a basis to partition relations horizontally. In the proposed approach, an ordinary many-sorted language is extended to represent the queries and knowledge compatibly. This knowledge is identified in terms of five axiom schemata. An inference procedure is developed to apply the knowledge to the queries deductively     

分布式空间数据分片与跨边界拓扑连接优化方法

研究分布式空间数据库(distributed spatial database,简称DSDB)中数据按区域分片时的跨边界片段拓扑连接查询问题,并提出相应的优化方法.首先研究了分布式环境下的空间数据的分片与分布,提出了空间数据分片的扩展原则:空间聚集性、空间对象的不分割性、逻辑无缝保持性.然后,将区域分割分片环境下的片段连接分为跨边界和非跨边界两类;同时,将拓扑关系分为两类,重点研究跨边界的两类片段拓扑连接.提出了跨边界空间片段拓扑连接优化的两个定理,并给出了证明.以此为基础,给出了跨边界空间拓扑连接优化规则,包括连接去除规则和连接优化转化规则.最后设计了详细的实验,对自然连接策略、半连接策略以及所提出的连接策略进行效率比较,结果表明,所提出的方法对跨边界连接优化有明显优势.因此,所提出的理论和方法可以用于分布式跨边界拓扑关系查询的优化.     

Querying fragmented relations in a distributed database

Summary The paper discusses the query optimization problem in a distributed database system supporting a complex fragmentation schema, in which different fragments can share the same set of data. The fragmentation and the distribution of data are assumed to be transparent to the user, who queries the database in terms of the global relations. The optimization of queries stated on a single fragmented relation is considered, and a method for its solution is presented. The method is based on an algorithm which calculates a set of virtual fragments that can alternatively be used to answer the query.     

A comprehensive approach to horizontal class fragmentation in a Distributed Object Based System

Optimal application performance on a Distributed Object Based System (DOBS) requires class fragmentation and the development of allocation schemes to place fragments at distributed sites so data transfer is minimized. Fragmentation enhances application performance by reducing the amount of irrelevant data accessed and the amount of data transferred unnecessarily between distributed sites. Algorithms for effecting horizontal and vertical fragmentation ofrelations exist, but fragmentation techniques for class objects in a distributed object based system are yet to appear in the literature. This paper first reviews a taxonomy of the fragmentation problem in a distributed object base. The paper then contributes by presenting a comprehensive set of algorithms for horizontally fragmenting the four realizable class models on the taxonomy. The fundamental approach is top-down, where the entity of fragmentation is the class object. Our approach consists of first generating primary horizontal fragments of a class based on only applications accessing this class, and secondly generating derived horizontal fragments of the class arising from primary fragments of its subclasses, its complex attributes (contained classes), and/or its complex methods classes. Finally, we combine the sets of primary and derived fragments of each class to produce the best possible fragments. Thus, these algorithms account for inheritance and class composition hierarchies as well as method nesting among objects, and are shown to be polynomial time. Recommended by: Patrick Valduriez     

Controlled generation of intensional answers

Intensional answers are conditions that tuples of values must satisfy to belong to the usual extensional answer of a query addressed to a deductive database. The authors review the concept of intensional answers and introduce a general method for generating them as logical consequences of the query and of deduction rules. The authors show how integrity constraints can filter out inadequate answers and produce simpler and more informative answers. An efficient organization for the combination of answers and constraints is described. The introduction of negation in queries and in the body of deduction rules is discussed. Beyond the mechanics of answer generation, the interest of the approach also depends on a strategy for selecting answers to a user submitting a query. This requires techniques for user modeling and dialogue management similar to those required for expert systems     

Query language approach based on the deductive object-oriented database paradigm

The integration of data-oriented (structural), behavioral and deductive aspects is necessary in next generation information systems. The deductive object-oriented database paradigm offers a very promising starting point for the implementation of these kinds of information systems. So far in the context of this paradigm a big problem has been the lack of a query language suitable to an ordinary end user. Typically in existing proposals for deductive object-oriented databases the user has to master well both logic-based rule formulation and object-oriented programming. In this paper we introduce a set of high-level querying primitives which increases the degree of declarativeness compared to the deductive object-oriented query languages proposed so far. In terms of these primitives it is possible to offer for end users such application-specific concepts and structures whose interpretation is obvious to users but whose specification is too demanding for them. By combining these primitives in queries the user can integrate data-oriented, behavioral and deductive aspects with each other in a concept-oriented way. Our query language approach is based on the incorporation of deductive aspects to object-orientation. Among others this means that deductive aspects of objects are inherited in the specialization/generalization hierarchy like any other properties of objects.     

A model-driven workflow fragmentation framework for collaborative workflow architectures and systems

This paper focuses on a workflow distribution methodology for rationally deploying workflow models onto a distributed workflow system running on cloud computing environments, and we particularly lay a stress upon that those workflow systems operable on cloud computing environments are dubbed collaborative workflow systems, which are not only built upon the collaborative workflow architectures proposed in the paper, but pursuing the so-called collaborative computing paradigm characterized by focusing collaboration over cloud computing environments. The essential idea of the workflow distribution methodology is about how to fragment a workflow model and how to allocate its fragments to each of the architectural components configuring the underlying collaborative workflow architecture and system. As a reasonable solution to realize the essential idea, the paper proposes a model-driven workflow fragmentation framework, which provides a series of fragmentation algorithms that semantically fragmentate a workflow model by considering the semantic factors - performer, role, control-flow, data-flow, etc. - of the ICN-based workflow model as fragmentation criteria. The algorithms are classified into the vertical fragmentation approach, the horizontal fragmentation approach, and the hybrid approach of both. Conclusively, this paper conceives a possible set of collaborative workflow architectures embedding the collaborative computing paradigm, and describes the detailed formalism of the framework and about how the framework works on those collaborative workflow architectures and systems.     

Formal reasoning in intelligent database systems

Expert database systems were proposed to solve the difficulties encountered in traditional database systems. Prolog provides a fast prototyping tool for building such database systems. However, an intelligent database system implemented in Prolog faces a major restriction that only Horn rules are allowed in the knowledge base. We propose a theorem prover which can make inference for non-Horn intelligent database systems. Conclusions can be deduced from the facts and rules stored in a knowledge base. For a knowledge base with a finite domain, the prover can provide correct answers to queries, derive logical consequences of the database, and provide help in detecting inconsistencies or locating bugs in the database. The theorem prover is efficient in deriving conclusions from large knowledge bases which might swamp most of the other deductive systems. The theorem prover is also useful in solving heuristically the satisfiability problem related to a database with an infinite domain. A truth maintenance mechanism is provided to help eliminate repetitious work for the same goals.Supported by National Science Council under grant NSC 81-0408-E-110-9.     

数据库加速引擎中数据垂直分片技术研究

探讨了企业级数据库加速引擎（EDAE）中数据分布器（DDT）的实现。DDT基于两种分片技术：Hash散列水平分片和垂直分片。提出了一种基于图形技术的垂直分片算法VFG，它能很好地适用于OLTP应用。最后在理论和实验上对引擎的分片方案进行了分析和研究。     

A new vertical fragmentation algorithm based on ant collective behavior in distributed database systems

Considering the existing massive volumes of data processed nowadays and the distributed nature of many organizations, there is no doubt how vital the need is for distributed database systems. In such systems, the response time to a transaction or a query is highly affected by the distribution design of the database system, particularly its methods for fragmentation, replication, and allocation data. According to the relevant literature, from the two approaches to fragmentation, namely horizontal and vertical fragmentation, the latter requires the use of heuristic methods due to it being NP-Hard. Currently, there are a number of different methods of providing vertical fragmentation, which normally introduce a relatively high computational complexity or do not yield optimal results, particularly for large-scale problems. In this paper, because of their distributed and scalable nature, we apply swarm intelligence algorithms to present an algorithm for finding a solution to vertical fragmentation problem, which is optimal in most cases. In our proposed algorithm, the relations are tried to be fragmented in such a way so as not only to make transaction processing at each site as much localized as possible, but also to reduce the costs of operations. Moreover, we report on the experimental results of comparing our algorithm with several other similar algorithms to show that ours outperforms the other algorithms and is able to generate a better solution in terms of the optimality of results and computational complexity.     

Algebraic optimization of recursive queries

Over the past few years, much attention has been paid to deductive databases. They offer a logic-based interface, and allow formulation of complex recursive queries. However, they do not offer appropriate update facilities, and do not support existing applications. To overcome these problems an SQL-like interface is required besides a logic-based interface.

In the PRISMA project we have developed a tightly-coupled distributed database, on a multiprocessor machine, with two user interfaces: SQL and PRISMAlog. Query optimization is localized in one component: the relational query optimizer. Therefore, we have defined an eXtended Relational Algebra that allows recursive query formulation and can also be used for expressing executable schedules, and we have developed algebraic optimization strategies for recursive queries. In this paper we describe an optimization strategy that rewrites regular (in the context of formal grammars) mutually recursive queries into standard Relational Algebra and transitive closure operations. We also describe how to push selections into the resulting transitive closure operations.

The reason we focus on algebraic optimization is that, in our opinion, the new generation of advanced database systems will be built starting from existing state-of-the-art relational technology, instead of building a completely new class of systems.     

Query by class,rule, and concept

The ideal query language for a knowledge base will probably never be found: easy formulation and easy evaluation of queries are two conflicting goals. Easy formulation asks for a flexible, expressive language near to human language or gestures. Easy evaluation of queries requires an effective mapping to machine code, which computes the correct answer in a finite number of steps. This article approaches the problem by a query language with three faces. The first projects queries to concepts of the knowledge representation language KL-One for easy formulation and readability. The second presents queries as rules of a deductive database with fixpoint semantics. The third presents queries as classes whose instances are the materialized answer (view) to the query. The methods for maintaining and updating the views are compiled from their deductive interpretation.     

An overview of cooperative answering

Databases and information systems are often hard to use because they do not explicitly attempt to cooperate with their users. Direct answers to database and knowledge base queries may not always be the best answers. Instead, an answer with extra or alternative information may be more useful and less misleading to a user. This paper surveys foundational work that has been done toward endowing intelligent information systems with the ability to exhibit cooperative behavior. Grice's maxims of cooperative conversation, which provided a starting point for the field of cooperative answering, are presented along with relevant work in natural language dialogue systems, database query answering systems, and logic programming and deductive databases. The paper gives a detailed account of cooperative techniques that have been developed for considering users' beliefs and expectations, presuppositions, and misconceptions. Also, work in intensional answering and generalizing queries and answers is covered. Finally, the Cooperative Answering System at Maryland, which is intended to be a general, portable platform for supporting a wide spectrum of cooperative answering techniques, is described.     

Polymorphic queries for P2P systems

When a query is posed on a centralized database, if it refers to attributes that are not defined in the database, the user is warranted to get either an error or an empty set. In contrast, when a query is posed on a peer in a P2P system and refers to attributes not found in the local database, the query should not be simply rejected if the relevant information is available at other peers. This paper proposes a query model for unstructured P2P systems to answer such queries. (a) We introduce a class of polymorphic queries, a revision of conjunctive queries by incorporating type variables to accommodate attributes not defined in the local database. (b) We define the semantics of polymorphic queries in terms of horizontal and vertical object expansions, to find attributes and tuples, respectively, missing from the local database. We show that both expansions can be conducted in a uniform framework. (c) We develop a top-K algorithm to approximately answer polymorphic queries. (d) We also provide a method to merge tuples collected from various peers, based on matching keys specified in polymorphic queries. Our experimental study verifies that polymorphic queries are able to find more sensible information than traditional queries supported by P2P systems, and that these queries can be evaluated efficiently.     

Efficient evaluation for a subset of recursive queries

We consider the efficient evaluation of recursive queries in logic databases where the queries are expressed using a Datalog program (function-free Horn-clause program) that contains only regularly or linearly recursive predicates. Using well-known results on graph traversal, we develop an efficient algorithm for evaluating relations defined by a binary-chain program. We also present a transformation by which the evaluation of a subset of queries involving nonbinary relations can be reduced to the evaluation of binary-chain queries. This transformation is guided by the choice of bound arguments in the query, and the bindings are propagated through the program so that in the evaluation of the transformed program the bindings will be used to restrict the set of database facts consulted.     

The query clustering problem: a set partitioning approach

In this research, we address the query clustering problem which involves determining globally optimal execution strategies for a set of queries. The need to process a set of queries together often arises in deductive database systems, scientific database systems, large bibliographic retrieval systems and several other database applications. We address the optimization problem from the perspective of overlaps in data requirements, and model the batched operations using a set-partitioning approach. In this model, we first consider the case of m queries each involving a two-way join operation. We develop a recursive methodology to determine all the processing strategies in this case. Next, we establish certain dominance properties among the strategies, and develop exact as well as heuristic algorithms for selecting an appropriate strategy. We extend this analysis to a clustering approach, and outline a framework for optimizing multiway joins. The results show that the proposed approach is viable and efficient, and can easily be incorporated into the query processing component of most database systems     

Removing redundant join operations in queries involving views

Views are understood as a good means to tailor base relations individually to the needs of each user. However, if a user formulates his queries in terms of views he often has no chance to express these queries without joins. In terms of base relations many of these joins would not be necessary, and therefore the advantages of the view concept are payed for with a reduced performance. This study shows that this performance reduction can be avoided by automatically transforming a certain class of queries formulated in terms of views into equivalent queries on their base relations. This transformation is performed on the source level of SQL and uses the functional dependencies of the base relations to remove redundant join operations. Performance measurements in a real application of System/R show that this method is very efficient.     

Enhanced Schemes for Data Fragmentation,Allocation, and Replication in Distributed Database Systems

With the growth of information technology and computer networks, there is a vital need for optimal design of distributed databases with the aim of performance improvement in terms of minimizing the round-trip response time and query transmission and processing costs. To address this issue, new fragmentation, data allocation, and replication techniques are required. In this paper, we propose enhanced vertical fragmentation, allocation, and replication schemes to improve the performance of distributed database systems. The proposed fragmentation scheme clusters highly-bonded attributes (i.e., normally accessed together) into a single fragment in order to minimize the query processing cost. The allocation scheme is proposed to find an optimized allocation to minimize the round-trip response time. The replication scheme partially replicates the fragments to increase the local execution of queries in a way that minimizes the cost of transmitting replicas to the sites. Experimental results show that, on average, the proposed schemes reduce the round-trip response time of queries by 23% and query processing cost by 15%, as compared to the related work.