Demythization of structural XML query processing: Comparison of holistic and binary approaches

dc.contributor.authorLukáš, Petr
dc.contributor.authorBača, Radim
dc.contributor.authorKrátký, Michal
dc.contributor.authorLing, Tok Wang
dc.date.accessioned2021-06-23T09:04:02Z
dc.date.available2021-06-23T09:04:02Z
dc.date.issued2021
dc.description.abstractXML queries can be modeled by twig pattern queries (TPQs) specifying predicates on XML nodes and XPath relationships satisfied between them. A lot of TPQ types have been proposed; this paper takes into account a TPQ model extended by a specification of output and non-output query nodes since it complies with the XQuery semantics and, in many cases, it leads to a more efficient query processing. In general, there are two types of approaches to process a TPQ: holistic joins and binary joins. Whereas the binary join approach builds a query plan as a tree of interconnected binary operators, the holistic join approach evaluates a whole query using one operator (i.e., using one complex algorithm). Surprisingly, a thorough analytical and experimental comparison is still missing despite an enormous research effort in this area. In this paper, we try to fill this gap; we analytically and experimentally show that the binary joins used in a fully-pipelined plan (i.e., the plan where each join operation does not wait for the complete result of the previous operation and no explicit sorting is used) can often outperform the holistic joins, especially for TPQs with a higher ratio of non-output query nodes. The main contributions of this paper can be summarized as follows: (i) we introduce several improvements of existing binary join approaches allowing to build a fully-pipelined plan for a TPQ considering non-output query nodes, (ii) we prove that for a certain class of TPQs such a plan has the linear time complexity with respect to the size of the input and output as well as the linear space complexity with respect to the XML document depth (i.e., the same complexity as the holistic join approaches), (iii) we show that our improved binary join approach outperforms the holistic join approaches in many situations, and (iv) we propose a simple combined approach that utilizes advantages of both types of approaches.cs
dc.description.firstpage1439cs
dc.description.issue4cs
dc.description.lastpage1452cs
dc.description.sourceWeb of Sciencecs
dc.description.volume33cs
dc.identifier.citationIEEE Transactions on Knowledge and Data Engineering. 2021, vol. 33, issue 4, p. 1439-1452.cs
dc.identifier.doi10.1109/TKDE.2019.2946157
dc.identifier.issn1041-4347
dc.identifier.issn1558-2191
dc.identifier.urihttp://hdl.handle.net/10084/143107
dc.identifier.wos000626617900008
dc.language.isoencs
dc.publisherIEEEcs
dc.relation.ispartofseriesIEEE Transactions on Knowledge and Data Engineeringcs
dc.relation.urihttps://doi.org/10.1109/TKDE.2019.2946157cs
dc.rights© 2019 IEEEcs
dc.subjectXMLcs
dc.subjectquery processingcs
dc.subjectsemanticscs
dc.subjectsortingcs
dc.subjecttime complexitycs
dc.subjectimpedance matchingcs
dc.subjectstructural XML query processingcs
dc.subjecttwig pattern querycs
dc.subjectholistic joinscs
dc.subjectbinary joinscs
dc.subjectXPathcs
dc.subjectXQuerycs
dc.titleDemythization of structural XML query processing: Comparison of holistic and binary approachescs
dc.typearticlecs
dc.type.statusPeer-reviewedcs

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