Cross-Model Conjunctive Queries over Relation and Tree-structured Data

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Chen , Y , Uotila , V , Lu , J , Liu , Z H & Das , S 2022 , Cross-Model Conjunctive Queries over Relation and Tree-structured Data . in Database Systems for Advanced Applications. DASFAA 2022. . Lecture Notes in Computer Science , vol. 13245 , Springer , Cham , International Conference on Database Systems for Advanced Applications , Hyderabad , India , 11/04/2022 . https://doi.org/10.1007/978-3-031-00123-9_2

Title: Cross-Model Conjunctive Queries over Relation and Tree-structured Data
Author: Chen, Yuxing; Uotila, Valter; Lu, Jiaheng; Liu, Zhen Hua; Das, Souripriya
Contributor organization: Unified DataBase Management System research group / Jiaheng Lu
Department of Computer Science
Publisher: Springer
Date: 2022-04-08
Language: eng
Number of pages: 16
Belongs to series: Database Systems for Advanced Applications. DASFAA 2022.
Belongs to series: Lecture Notes in Computer Science
ISBN: 978-3-031-00123-9
DOI: https://doi.org/10.1007/978-3-031-00123-9_2
URI: http://hdl.handle.net/10138/345969
Abstract: Conjunctive queries are the most basic and central class of database queries. With the continued growth of demands to manage and process the massive volume of different types of data, there is little research to study the conjunctive queries between relation and tree data. In this paper, we study Cross-Model Conjunctive Queries (CMCQs) over relation and tree-structured data (XML and JSON). To efficiently process CMCQs with bounded intermediate results we first encode tree nodes with position information. With tree node original label values and encoded position values, it allows our proposed algorithm CMJoin to join relations and tree data simultaneously, avoiding massive intermediate results. CMJoin achieves worst-case optimality in terms of the total result of label values and encoded position values. Experimental results demonstrate the efficiency and scalability of the proposed techniques to answer a CMCQ in terms of running time and intermediate result size.
Subject: 113 Computer and information sciences
Peer reviewed: Yes
Rights: unspecified
Usage restriction: openAccess
Self-archived version: acceptedVersion


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