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Topic

Tuple

About: Tuple is a research topic. Over the lifetime, 6513 publications have been published within this topic receiving 146057 citations. The topic is also known as: tuple & ordered tuplet.


Papers
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Journal ArticleDOI
01 Mar 1997
TL;DR: A methodology for integrating schema translation and data conversion for converting relational to object-oriented database system to improve productivity and flexibility is described.
Abstract: As object-oriented model becomes the trend of database technology, there is a need to convert relational to object-oriented database system to improve productivity and flexibility. The changeover includes schema translation, data conversion and program conversion. This paper describes a methodology for integrating schema translation and data conversion. Schema translation involves semantic reconstruction and the mapping of relational schema into object-oriented schema. Data conversion involves unloading tuples of relations into sequential files and reloading them into object-oriented classes files. The methodology preserves the constraints of the relational database by mapping the equivalent data dependencies.

61 citations

Journal ArticleDOI
TL;DR: This work presents several alternative extensions and decompositions of access support relations for a given path expression, the best of which has to be determined according to the application-specific database usage profile.

61 citations

Proceedings ArticleDOI
26 Mar 2012
TL;DR: A representation system for relational data based on algebraic factorisation using distributivity of product over union and commutativity of product and union is introduced and two characterisations of conjunctive queries based on factorisations of their results whose nesting structure is defined by so-called factorisation trees.
Abstract: We introduce a representation system for relational data based on algebraic factorisation using distributivity of product over union and commutativity of product and union.We give two characterisations of conjunctive queries based on factorisations of their results whose nesting structure is defined by so-called factorisation trees.The first characterisation concerns sizes of factorised representations. For any query, we derive a size bound that is asymptotically tight within our class of factorisations.We also characterise the queries by tight bounds on the readability of the provenance of result tuples and define syntactically the class of queries with bounded readability.

61 citations

Patent
02 Mar 2009
TL;DR: In this article, the authors present techniques for managing memory usage in a processing system using a query plan that was generated for a continuous query applied to the multiple tuples in the data stream.
Abstract: Techniques for managing memory usage in a processing system are provided. This may be achieved by receiving a data stream including multiple tuples and determining a query plan that was generated for a continuous query applied to the multiple tuples in the data stream. The query plan may include one or more operators. Before scheduling an operator in the query plan, it is determined when an eviction is to be performed based a level of free memory of the processing system. An eviction candidate is determined and a page associated with the eviction candidate is evicted from the memory to a persistent storage.

60 citations

Journal ArticleDOI
01 Sep 2010
TL;DR: This paper develops novel, more efficient factorization algorithms that directly construct the read-once expression for a result tuple Boolean formula (if one exists), for a large subclass of queries (specifically, conjunctive queries without self-joins).
Abstract: Probabilistic databases hold promise of being a viable means for large-scale uncertainty management, increasingly needed in a number of real world applications domains. However, query evaluation in probabilistic databases remains a computational challenge. Prior work on efficient exact query evaluation in probabilistic databases has largely concentrated on query-centric formulations (e.g., safe plans, hierarchical queries), in that, they only consider characteristics of the query and not the data in the database. It is easy to construct examples where a supposedly hard query run on an appropriate database gives rise to a tractable query evaluation problem. In this paper, we develop efficient query evaluation techniques that leverage characteristics of both the query and the data in the database. We focus on tuple-independent databases where the query evaluation problem is equivalent to computing marginal probabilities of Boolean formulas associated with the result tuples. This latter task is easy if the Boolean formulas can be factorized into a form that has every variable appearing at most once (called read-once). However, a naive approach that directly uses previously developed Boolean formula factorization algorithms is inefficient, because those algorithms require the input formulas to be in the disjunctive normal form (DNF). We instead develop novel, more efficient factorization algorithms that directly construct the read-once expression for a result tuple Boolean formula (if one exists), for a large subclass of queries (specifically, conjunctive queries without self-joins). We empirically demonstrate that (1) our proposed techniques are orders of magnitude faster than generic inference algorithms for queries where the result Boolean formulas can be factorized into read-once expressions, and (2) for the special case of hierarchical queries, they rival the efficiency of prior techniques specifically designed to handle such queries.

60 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023203
2022459
2021210
2020285
2019306
2018266