research-article

Graphs-at-a-time: query language and access methods for graph databases

Authors:

Ambuj K. SinghAuthors Info & Claims

SIGMOD '08: Proceedings of the 2008 ACM SIGMOD international conference on Management of data

Pages 405 - 418

https://doi.org/10.1145/1376616.1376660

Published: 09 June 2008 Publication History

Abstract

With the prevalence of graph data in a variety of domains, there is an increasing need for a language to query and manipulate graphs with heterogeneous attributes and structures. We propose a query language for graph databases that supports arbitrary attributes on nodes, edges, and graphs. In this language, graphs are the basic unit of information and each query manipulates one or more collections of graphs. To allow for flexible compositions of graph structures, we extend the notion of formal languages from strings to the graph domain. We present a graph algebra extended from the relational algebra in which the selection operator is generalized to graph pattern matching and a composition operator is introduced for rewriting matched graphs. Then, we investigate access methods of the selection operator. Pattern matching over large graphs is challenging due to the NP-completeness of subgraph isomorphism. We address this by a combination of techniques: use of neighborhood subgraphs and profiles, joint reduction of the search space, and optimization of the search order. Experimental results on real and synthetic large graphs demonstrate that our graph specific optimizations outperform an SQL-based implementation by orders of magnitude.

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Cited By

Cao WMeng KLin ZTan G(2025)GLumin: Fast Connectivity Check Based on LUTs For Efficient Graph Pattern MiningProceedings of the 30th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming10.1145/3710848.3710889(455-468)Online publication date: 28-Feb-2025
https://dl.acm.org/doi/10.1145/3710848.3710889
Lu YZhang ZZheng W(2025)BⓈX: Subgraph Matching with Batch Backtracking SearchProceedings of the ACM on Management of Data10.1145/37096653:1(1-27)Online publication date: 11-Feb-2025
https://dl.acm.org/doi/10.1145/3709665
Cinquin O(2025)Steering veridical large language model analyses by correcting and enriching generated database queries: first steps toward ChatGPT bioinformaticsBriefings in Bioinformatics10.1093/bib/bbaf04526:1Online publication date: 6-Feb-2025
https://doi.org/10.1093/bib/bbaf045
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Index Terms

Graphs-at-a-time: query language and access methods for graph databases
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. Database query processing
    2. Query languages
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory
      1. Database query processing and optimization (theory)

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cover image ACM Conferences

SIGMOD '08: Proceedings of the 2008 ACM SIGMOD international conference on Management of data

June 2008

1396 pages

ISBN:9781605581026

DOI:10.1145/1376616

General Chairs:
Laks V. S. Lakshmanan
University of British Columbia, Canada
,
Raymond T. Ng
University of British Columbia, Canada
,
Dennis Shasha
New York University, USA

Copyright © 2008 ACM.

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Published: 09 June 2008

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SIGMOD/PODS '08

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SIGMOD/PODS '08: SIGMOD/PODS '08 - International Conference on Management of Data

June 9 - 12, 2008

Vancouver, Canada

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Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

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https://dl.acm.org/doi/10.1145/3710848.3710889
Lu YZhang ZZheng W(2025)BⓈX: Subgraph Matching with Batch Backtracking SearchProceedings of the ACM on Management of Data10.1145/37096653:1(1-27)Online publication date: 11-Feb-2025
https://dl.acm.org/doi/10.1145/3709665
Cinquin O(2025)Steering veridical large language model analyses by correcting and enriching generated database queries: first steps toward ChatGPT bioinformaticsBriefings in Bioinformatics10.1093/bib/bbaf04526:1Online publication date: 6-Feb-2025
https://doi.org/10.1093/bib/bbaf045
Chai YLi JZhang QGe JWang X(2025)ASM: Adaptive Subgraph Matching via Efficient Compression and Label FilterWeb and Big Data. APWeb-WAIM 2024 International Workshops10.1007/978-981-96-0055-7_3(30-42)Online publication date: 31-Jan-2025
https://doi.org/10.1007/978-981-96-0055-7_3
Yang X(2024)Improving the Relevance, Speed, and Computational Efficiency of Semantic Search through Database Indexing: A ReviewOptimization Algorithms - Classics and Recent Advances10.5772/intechopen.112232Online publication date: 10-Jul-2024
https://doi.org/10.5772/intechopen.112232
Sun YChen XChen HQi RNing B(2024)Categorical Multi-Query Subgraph Matching on Labeled GraphElectronics10.3390/electronics1321419113:21(4191)Online publication date: 25-Oct-2024
https://doi.org/10.3390/electronics13214191
Chen ZZhuang JWang XTang XYang KDu MZhou J(2024)Top-k Graph Similarity Search Algorithm Based on Chi-Square Statistics in Probabilistic GraphsElectronics10.3390/electronics1301019213:1(192)Online publication date: 1-Jan-2024
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Shin WSong SPark KHan W(2024)Cardinality Estimation of Subgraph Matching: A Filtering-Sampling ApproachProceedings of the VLDB Endowment10.14778/3654621.365463517:7(1697-1709)Online publication date: 1-Mar-2024
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Sharma AMehta DWu B(2024)Understanding High-Performance Subgraph Pattern Matching: A Systems PerspectiveProceedings of the 7th Joint Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)10.1145/3661304.3661897(1-12)Online publication date: 14-Jun-2024
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Zhang ZLu YZheng WLin X(2024)A Comprehensive Survey and Experimental Study of Subgraph Matching: Trends, Unbiasedness, and InteractionProceedings of the ACM on Management of Data10.1145/36393152:1(1-29)Online publication date: 26-Mar-2024
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