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Space-Query Tradeoffs in Range Subgraph Counting and Listing

Authors Shiyuan Deng, Shangqi Lu, Yufei Tao

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Author Details

Shiyuan Deng
  • The Chinese University of Hong Kong, China
Shangqi Lu
  • The Chinese University of Hong Kong, China
Yufei Tao
  • The Chinese University of Hong Kong, China

Funding

Supported in part by GRF Projects 14207820, 14203421, and 14222822 from HKRGC.

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Shiyuan Deng, Shangqi Lu, and Yufei Tao. Space-Query Tradeoffs in Range Subgraph Counting and Listing. In 26th International Conference on Database Theory (ICDT 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 255, pp. 6:1-6:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.ICDT.2023.6

Abstract

This paper initializes the study of range subgraph counting and range subgraph listing, both of which are motivated by the significant demands in practice to perform graph analytics on subgraphs pertinent to only selected, as opposed to all, vertices. In the first problem, there is an undirected graph G where each vertex carries a real-valued attribute. Given an interval q and a pattern Q, a query counts the number of occurrences of Q in the subgraph of G induced by the vertices whose attributes fall in q. The second problem has the same setup except that a query needs to enumerate (rather than count) those occurrences with a small delay. In both problems, our goal is to understand the tradeoff between space usage and query cost, or more specifically: (i) given a target on query efficiency, how much pre-computed information about G must we store? (ii) Or conversely, given a budget on space usage, what is the best query time we can hope for? We establish a suite of upper- and lower-bound results on such tradeoffs for various query patterns.

Subject Classification

ACM Subject Classification
  • Theory of computation → Graph algorithms analysis
Keywords
  • Subgraph Pattern Counting
  • Subgraph Pattern Listing
  • Conjunctive Queries

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