1,685 research outputs found

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

    Get PDF
    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

    Get PDF
    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

    An Inflationary Fixed Point Operator in XQuery

    Full text link
    We introduce a controlled form of recursion in XQuery, inflationary fixed points, familiar in the context of relational databases. This imposes restrictions on the expressible types of recursion, but we show that inflationary fixed points nevertheless are sufficiently versatile to capture a wide range of interesting use cases, including the semantics of Regular XPath and its core transitive closure construct. While the optimization of general user-defined recursive functions in XQuery appears elusive, we will describe how inflationary fixed points can be efficiently evaluated, provided that the recursive XQuery expressions exhibit a distributivity property. We show how distributivity can be assessed both, syntactically and algebraically, and provide experimental evidence that XQuery processors can substantially benefit during inflationary fixed point evaluation.Comment: 11 pages, 10 figures, 2 table

    Bounds on series-parallel slowdown

    Full text link
    We use activity networks (task graphs) to model parallel programs and consider series-parallel extensions of these networks. Our motivation is two-fold: the benefits of series-parallel activity networks and the modelling of programming constructs, such as those imposed by current parallel computing environments. Series-parallelisation adds precedence constraints to an activity network, usually increasing its makespan (execution time). The slowdown ratio describes how additional constraints affect the makespan. We disprove an existing conjecture positing a bound of two on the slowdown when workload is not considered. Where workload is known, we conjecture that 4/3 slowdown is always achievable, and prove our conjecture for small networks using max-plus algebra. We analyse a polynomial-time algorithm showing that achieving 4/3 slowdown is in exp-APX. Finally, we discuss the implications of our results.Comment: 12 pages, 4 figure

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

    Get PDF
    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..

    Efficient parallel computation on multiprocessors with optical interconnection networks

    Get PDF
    This dissertation studies optical interconnection networks, their architecture, address schemes, and computation and communication capabilities. We focus on a simple but powerful optical interconnection network model - the Linear Array with Reconfigurable pipelined Bus System (LARPBS). We extend the LARPBS model to a simplified higher dimensional LAPRBS and provide a set of basic computation operations. We then study the following two groups of parallel computation problems on both one dimensional LARPBS\u27s as well as multi-dimensional LARPBS\u27s: parallel comparison problems, including sorting, merging, and selection; Boolean matrix multiplication, transitive closure and their applications to connected component problems. We implement an optimal sorting algorithm on an n-processor LARPBS. With this optimal sorting algorithm at disposal, we study the sorting problem for higher dimensional LARPBS\u27s and obtain the following results: • An optimal basic Columnsort algorithm on a 2D LARPBS. • Two optimal two-way merge sort algorithms on a 2D LARPBS. • An optimal multi-way merge sorting algorithm on a 2D LARPBS. • An optimal generalized column sort algorithm on a 2D LARPBS. • An optimal generalized column sort algorithm on a 3D LARPBS. • An optimal 5-phase sorting algorithm on a 3D LARPBS. Results for selection problems are as follows: • A constant time maximum-finding algorithm on an LARPBS. • An optimal maximum-finding algorithm on an LARPBS. • An O((log log n)2) time parallel selection algorithm on an LARPBS. • An O(k(log log n)2) time parallel multi-selection algorithm on an LARPBS. While studying the computation and communication properties of the LARPBS model, we find Boolean matrix multiplication and its applications to the graph are another set of problem that can be solved efficiently on the LARPBS. Following is a list of results we have obtained in this area. • A constant time Boolean matrix multiplication algorithm. • An O(log n)-time transitive closure algorithm. • An O(log n)-time connected components algorithm. • An O(log n)-time strongly connected components algorithm. The results provided in this dissertation show the strong computation and communication power of optical interconnection networks

    A constant time parallel algorithm for the triangularization of a sparse matrix using CD-PARBS

    Get PDF
    An algorithm for the triangularization of a matrix whose graph is a directed acyclic graph, popularly known as dag, is presented. One of the algorithms for obtaining this special form has been given by Sargent and Westerberg. Their approach is practically good but sequential in nature and cannot be parallelised easily. In this work we present a parallel algorithm which is based on the observation that, if we find the transitive closure matrix of a directed acyclic graph, count the number of entries in each row, sort them in the ascending order of their values and rank them accordingly, we get a lower triangular matrix. We show that all these operations can be done using 3-d CD- PARBS(Complete Directed PARBS) in constant time. The same approach can be used for the block cases, producing the same relabelling as produced by Tarjan’s algorithm, in constant time. To the best of our knowledge, it is the first approach to solve such problems using directed PARBS

    Service oriented transitive closure solution

    Get PDF
    The goal of this project is a service based solution that utilizes parallel and distributed processing algorithms to solve the transitive closure problem for a large dataset. A dataset may be view conceptually as a table in a database, with a physical structure representing a file containing a sequence of records and fields. Two records are said to be transitively related if and only if they are directly related due to sharing of one or more specific fields, or a sequence may be made from one record to the other under the condition that all intermediate entries are related the immediate previous and subsequent entry. The transitive closure problem is to cluster the records in a dataset into groups such that all transitively related records are in one group. An approach to solve this problem is to divide the task into two separate problems. The first of these problems is the processing of the dataset, and thus generating a set of pairs. Each of these pairs would include two record identifiers, and these pairs would exist if and only if these two records were directly related. The second of these problems is to use the record pairs to cluster the records into transitive closures. The current software solution solves this second sub problem through the reading of record pairs, produced by a different software solution, and writes the completed results of the transitive closure problem to a file. This thesis studies how to enhance the current software solution in such a way that it becomes a service . The study includes designing, implementing, testing, and evaluating the enhanced solution. The service model identifies an aspect that would potentially benefit from restructuring or addition of functionality. A current issue is the lack of an ability to fetch transitive closure from within the solution upon the completion of a job, and is thus limited in itsdirect use with other processes or applications
    • …
    corecore