29 research outputs found

    Set-Oriented Mining for Association Rules in Relational Databases

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    Describe set-oriented algorithms for mining association rules. Such algorithms imply performing multiple joins and may appear to be inherently less efficient than special-purpose algorithms. We develop new algorithms that can be expressed as SQL queries, and discuss the optimization of these algorithms. After analytical evaluation, an algorithm named SETM emerges as the algorithm of choice. SETM uses only simple database primitives, viz. sorting and merge-scan join. SETM is simple, fast and stable over the range of parameter values. The major contribution of this paper is that it shows that at least some aspects of data mining can be carried out by using general query languages such as SQL, rather than by developing specialized black-box algorithms. The set-oriented nature of SETM facilitates the development of extension

    Algebraic optimization of recursive queries

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    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.\ud \ud 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.\ud \ud 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

    A survey of parallel execution strategies for transitive closure and logic programs

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    An important feature of database technology of the nineties is the use of parallelism for speeding up the execution of complex queries. This technology is being tested in several experimental database architectures and a few commercial systems for conventional select-project-join queries. In particular, hash-based fragmentation is used to distribute data to disks under the control of different processors in order to perform selections and joins in parallel. With the development of new query languages, and in particular with the definition of transitive closure queries and of more general logic programming queries, the new dimension of recursion has been added to query processing. Recursive queries are complex; at the same time, their regular structure is particularly suited for parallel execution, and parallelism may give a high efficiency gain. We survey the approaches to parallel execution of recursive queries that have been presented in the recent literature. We observe that research on parallel execution of recursive queries is separated into two distinct subareas, one focused on the transitive closure of Relational Algebra expressions, the other one focused on optimization of more general Datalog queries. Though the subareas seem radically different because of the approach and formalism used, they have many common features. This is not surprising, because most typical Datalog queries can be solved by means of the transitive closure of simple algebraic expressions. We first analyze the relationship between the transitive closure of expressions in Relational Algebra and Datalog programs. We then review sequential methods for evaluating transitive closure, distinguishing iterative and direct methods. We address the parallelization of these methods, by discussing various forms of parallelization. Data fragmentation plays an important role in obtaining parallel execution; we describe hash-based and semantic fragmentation. Finally, we consider Datalog queries, and present general methods for parallel rule execution; we recognize the similarities between these methods and the methods reviewed previously, when the former are applied to linear Datalog queries. We also provide a quantitative analysis that shows the impact of the initial data distribution on the performance of methods

    Data fragmentation for parallel transitive closure strategies

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    Addresses the problem of fragmenting a relation to make the parallel computation of the transitive closure efficient, based on the disconnection set approach. To better understand this design problem, the authors focus on transportation networks. These are characterized by loosely interconnected clusters of nodes with a high internal connectivity rate. Three requirements that have to be fulfilled by a fragmentation are formulated, and three different fragmentation strategies are presented, each emphasizing one of these requirements. Some test results are presented to show the performance of the various fragmentation strategie

    Optimization of Spatial Joins Using Filters

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    When viewing present-day technical applications that rely on the use of database systems, one notices that new techniques must be integrated in database management systems to be able to support these applications efficiently. This paper discusses one of these techniques in the context of supporting a Geographic Information System. It is known that the use of filters on geometric objects has a significant impact on the processing of 2-way spatial join queries. For this purpose, filters require approximations of objects. Queries can be optimized by filtering data not with just one but with several filters. Existing join methods are based on a combination of filters and a spatial index. The index is used to reduce the cost of the filter step and to minimize the cost of retrieving geometric objects from disk. In this paper we examine n-way spatial joins. Complex n-way spatial join queries require solving several 2-way joins of intermediate results. In this case, not only the profit gained from using both filters and spatial indices but also the additional cost due to using these techniques are examined. For 2-way joins of base relations these costs are considered part of physical database design. We focus on the criteria for mutually comparing filters and not on those for spatial indices. Important aspects of a multi-step filter-based n-way spatial join method are described together with performance experiments. The winning join method uses several filters with approximations that are constructed by rotating two parallel lines around the object

    Implementation and Performance Evaluation of a Parallel Transitive Closure Algorithms on PRISMA/DB

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    This paper is one of the first to discuss actual implementation of and experimentation with parallel transitive closure operations on a full-fledged relational database system. It brings two research efforts together; the development of an efficient execution strategy for parallel computation of path problems, called Disconnection Set Approach, and the development and implementation of a parallel, main-memory DBMS, called PRISMA/DB. First, we report on the implementation of the disconnection set approach on PRISMA/DB, showing how the latter's design allowed us to easily extend the functionality of the system. Second, we investigate the disconnection set approach's parallel behavior and performance by means of extensive experimentation. It is shown that the parallel implementation of the disconnection set approach yields very good performance characteristics, and that (super)linear speedup w.r.t. a special implementation of semi-naive is achieved for regular, so-called linear fragmenta..

    Set-Oriented Mining for Association Rules in Relational Databases

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    Describe set-oriented algorithms for mining association rules. Such algorithms imply performing multiple joins and may appear to be inherently less efficient than special-purpose algorithms. We develop new algorithms that can be expressed as SQL queries, and discuss the optimization of these algorithms. After analytical evaluation, an algorithm named SETM emerges as the algorithm of choice. SETM uses only simple database primitives, viz. sorting and merge-scan join. SETM is simple, fast and stable over the range of parameter values. The major contribution of this paper is that it shows that at least some aspects of data mining can be carried out by using general query languages such as SQL, rather than by developing specialized black-box algorithms. The set-oriented nature of SETM facilitates the development of extension

    Data and Knowledge Base Management Systems: Data Model and Query Processing

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    Parallel hierarchical evaluation of transitive closure queries

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    Presents a new approach to parallel computation of transitive closure queries using a semantic data fragmentation. Tuples of a large base relation denote edges in a graph, which models a transportation network. A fragmentation algorithm is proposed which produces a partitioning of the base relation into several fragments such that any fragment corresponds to a subgraph. One fragment, called high-speed fragment, collects all edges which guarantee maximum speed. Thus, the fragmentation algorithm induces a hierarchical relationship between the high-speed fragment and all other fragments. With this fragmentation, any query about paths connecting two nodes can be answered by using just the fragments in which nodes are located and the high-speed fragment. In general, if each fragment is managed by a distinguished processor, then the query can be answered by three processors working in parallel. This schema can be applied recursively to generate an arbitrary number of hierarchical level

    Preface

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    This volume provides much-needed coverage of the technical background to the development of multimedia applications. Based on an advanced summer school run by the University of Twente, each chapter is written by an expert in a particular topic, including enabling technologies, operating systems, index structures for multimedia, and communication issues. There is also a comprehensive discussion of the factors which determine the success or failure of database applications in the real-world, based on new multimedia projects in Dutch industries and service companies. Multimedia Databases in Perspective is an advanced textbook aimed at final year undergraduate students, and MSc and PhD students studying databases, database management, information systems, and multimedia applications. It will also be of interest to researchers in the above areas, and DBMS developers working in the software industry
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