2020
DOI: 10.1155/2020/6620528
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Dominance-Partitioned Subgraph Matching on Large RDF Graph

Abstract: Subgraph matching on a large graph has become a popular research topic in the field of graph analysis, which has a wide range of applications including question answering and community detection. However, traditional edge-cutting strategy destroys the structure of indivisible knowledge in a large RDF graph. On the premise of load-balancing on subgraph division, a dominance-partitioned strategy is proposed to divide a large RDF graph without compromising the knowledge structure. Firstly, a dominance-connected p… Show more

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Cited by 2 publications
(1 citation statement)
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“…Withtherapidgrowthofdatainrecentyears,thetraditionalreverseskylinequeryalgorithm basedonsinglemachine (Rajba,2021)processingmodeisnolongerpractical.Therefore,itisvitalto improveandapplytheReverseSkylinequeryalgorithminadistributedenvironment (Gajetal.,2013). TheMapReduce (Dean&Ghemawat,2008)designpatterneffectivelyimplementsparallelprocessing ofbigdataunderdistributedenvironmentbyusingtheideaofpartition (Ning,Sun,Zhao,Xing,&Li, 2020).However,MapReducewasdesignedtostorethedatawithoutmoving (Ramanathan&Latha, 2019),aswellasthesubsequentdatamanipulation.Eachquerywillinevitablyresultintheoverall traversalofthedata.QuantitiesofIOtransmissionintheshuffleprocesswillconsequentlyruinthe queryefficiency.Therefore,howtotakeadvantageofMapReduceandavoidtraversalisamatter ofhighimportancetodesignandimplementanefficient,stable,universal,andwell-suitedreverse skylinequeryalgorithmfordistributedenvironmentsinthecontemporarybigdataenvironment.…”
Section: Introductionmentioning
confidence: 99%
“…Withtherapidgrowthofdatainrecentyears,thetraditionalreverseskylinequeryalgorithm basedonsinglemachine (Rajba,2021)processingmodeisnolongerpractical.Therefore,itisvitalto improveandapplytheReverseSkylinequeryalgorithminadistributedenvironment (Gajetal.,2013). TheMapReduce (Dean&Ghemawat,2008)designpatterneffectivelyimplementsparallelprocessing ofbigdataunderdistributedenvironmentbyusingtheideaofpartition (Ning,Sun,Zhao,Xing,&Li, 2020).However,MapReducewasdesignedtostorethedatawithoutmoving (Ramanathan&Latha, 2019),aswellasthesubsequentdatamanipulation.Eachquerywillinevitablyresultintheoverall traversalofthedata.QuantitiesofIOtransmissionintheshuffleprocesswillconsequentlyruinthe queryefficiency.Therefore,howtotakeadvantageofMapReduceandavoidtraversalisamatter ofhighimportancetodesignandimplementanefficient,stable,universal,andwell-suitedreverse skylinequeryalgorithmfordistributedenvironmentsinthecontemporarybigdataenvironment.…”
Section: Introductionmentioning
confidence: 99%