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Об оценке коммуникационных затрат при обработке фрагментированного отношения для равномерного распределения

Authors: Gubin, M. V.; Sokolinky, L. B.;

Об оценке коммуникационных затрат при обработке фрагментированного отношения для равномерного распределения

Abstract

При обработке запросов в параллельных системах баз данных без совместного использования ресурсов в общем случае не удается избежать пересылок кортежей между процессорными узлами. В статье доказывается теорема, позволяющая получить оценку количества пересылаемых кортежей при обработке фрагментированного отношения для случая, когда функция пересылки функционально зависит от атрибута, значения которого распределены равномерно относительно атрибута фрагментации. Query processing in the shared-nothing parallel database systems demands a data exchange between processor nodes. In the paper, we present a theorem, which gives estimation for the amount of tuples which have to be transferred during processing partitioned relation. We consider the case when the transfer function is functionally dependent on an attribute, which is uniformly distributed relative to the partitioning attribute. M.V. Gubin, South Ural State University (Zlatoust, Russian Federation), L.B. Sokolinky, South Ural State University (Chelyabinsk, Russian Federation)

Keywords

partitioning parallelism, архитектура без совместного использования ресурсов, shared-nothing architecture, УДК 004.22, parallel database system, фрагментный параллелизм, УДК 004.75.032.24, ГРНТИ 50.41, параллельные системы баз данных, коммуникационные затраты, communication overhead

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green