This part, PART IIF [6], concludes the document HIGH-SPEED TOOLS FOR GLOBAL INFORMATION MANAGEMENT. II. Specifications and Uses of the Transparent Query Language (TQL) [1–6]. It describes novel applications of TQL, the key data structures, and contains a dictionary of Transparent Query Language terms. PART IIF references PART IIA [1], PART IIB [2], PART IIC [3], PART IID [4], and PART IIE [5] and contains Conclusions and Acknowledgements. 相似文献
We propose a new algorithm, called Stripe-join, for performing a join given a join index. Stripe-join is inspired by an algorithm called ‘Jive-join’ developed by Li and Ross. Stripe-join makes a single sequential pass through each input relation, in addition to one pass through the join index and two passes through a set of temporary files that contain tuple identifiers but no input tuples. Stripe-join performs this efficiently even when the input relations are much larger than main memory, as long as the number of blocks in main memory is of the order of the square root of the number of blocks in the participating relations. Stripe-join is particularly efficient for self-joins. To our knowledge, Stripe-join is the first algorithm that, given a join index and a relation significantly larger than main memory, can perform a self-join with just a single pass over the input relation and without storing input tuples in intermediate files. Almost all the I/O is sequential, thus minimizing the impact of seek and rotational latency. The algorithm is resistant to data skew. It can also join multiple relations while still making only a single pass over each input relation. Using a detailed cost model, Stripe-join is analyzed and compared with competing algorithms. For large input relations, Stripe-join performs significantly better than Valduriez's algorithm and hash join algorithms. We demonstrate circumstances under which Stripe-join performs significantly better than Jive-join. Unlike Jive-join, Stripe-join makes no assumptions about the order of the join index. 相似文献
Deriving local cost models for query optimization in a dynamic multidatabase system (MDBS) is a challenging issue. In this paper, we study how to evolve a query cost model to capture a slowly-changing dynamic MDBS environment so that the cost model is kept up-to-date all the time. Two novel evolutionary techniques, i.e., the shifting method and the block-moving method, are proposed. The former updates a cost model by taking up-to-date information from a new sample query into consideration at each step, while the latter considers a block (batch) of new sample queries at each step. The relevant issues, including derivation of recurrence updating formulas, development of efficient algorithms, analysis and comparison of complexities, and design of an integrated scheme to apply the two methods adaptively, are studied. Our theoretical and experimental results demonstrate that the proposed techniques are quite promising in maintaining accurate cost models efficiently for a slowly changing dynamic MDBS environment. Besides the application to MDBSs, the proposed techniques can also be applied to the automatic maintenance of cost models in self-managing database systems.Received: 25 November 2002, Accepted: 20 May 2003, Published online: 30 September 2003Edited by: L. LiuResearch supported by the US National Science Foundation under Grant # IIS-9811980 and The University of Michigan under OVPR and UMD grants. 相似文献
Some categorical methods used in developing computer programs are considered. Relevant theorems are proved.
Translated from Kibernetika i Sistemnyi Analiz, No. 4, pp. 3–11, July–August, 2000. 相似文献
We consider basic conceptual graphs, namely simple conceptual graphs (SGs), which are equivalent to the existential conjunctive positive fragment of first-order logic. The fundamental problem, deduction, is performed by a graph homomorphism called projection. The existence of a projection from a SG Q to a SG G means that the knowledge represented by Q is deducible from the knowledge represented by G. In this framework, a knowledge base is composed of SGs representing facts and a query is itself a SG. We focus on the issue of querying SGs, which highlights another fundamental problem, namely query answering. Each projection from a query to a fact defines an answer to the query, with an answer being itself a SG. The query answering problem asks for all answers to a query.
This paper introduces atomic negation into this framework. Several understandings of negation are explored, which are all of interest in real world applications. In particular, we focus on situations where, in the context of incomplete knowledge, classical negation is not satisfactory because deduction can be proven but there is no answer to the query. We show that intuitionistic deduction captures the notion of an answer and can be solved by projection checking. Algorithms are provided for all studied problems. They are all based on projection. They can thus be combined to deal with several kinds of negation simultaneously. Relationships with problems on conjunctive queries in databases are recalled and extended. Finally, we point out that this discussion can be put in the context of semantic web databases. 相似文献