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research-article

GRAIL: scalable reachability index for large graphs

Published: 01 September 2010 Publication History

Abstract

Given a large directed graph, rapidly answering reachability queries between source and target nodes is an important problem. Existing methods for reachability trade-off indexing time and space versus query time performance. However, the biggest limitation of existing methods is that they simply do not scale to very large real-world graphs. We present a very simple, but scalable reachability index, called GRAIL, that is based on the idea of randomized interval labeling, and that can effectively handle very large graphs. Based on an extensive set of experiments, we show that while more sophisticated methods work better on small graphs, GRAIL is the only index that can scale to millions of nodes and edges. GRAIL has linear indexing time and space, and the query time ranges from constant time to being linear in the graph order and size.

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  • (2024)ActiveReach: an active learning framework for approximate reachability query answering in large-scale graphsFrontiers in Big Data10.3389/fdata.2024.14271047Online publication date: 19-Nov-2024
  • (2024)Minimum Strongly Connected Subgraph Collection in Dynamic GraphsProceedings of the VLDB Endowment10.14778/3648160.364817317:6(1324-1336)Online publication date: 3-May-2024
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    cover image Proceedings of the VLDB Endowment
    Proceedings of the VLDB Endowment  Volume 3, Issue 1-2
    September 2010
    1658 pages

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    VLDB Endowment

    Publication History

    Published: 01 September 2010
    Published in PVLDB Volume 3, Issue 1-2

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    View all
    • (2025)TDS: fast answering reachability queries with hierarchical traversal treesCluster Computing10.1007/s10586-024-04814-828:3Online publication date: 21-Jan-2025
    • (2024)ActiveReach: an active learning framework for approximate reachability query answering in large-scale graphsFrontiers in Big Data10.3389/fdata.2024.14271047Online publication date: 19-Nov-2024
    • (2024)Minimum Strongly Connected Subgraph Collection in Dynamic GraphsProceedings of the VLDB Endowment10.14778/3648160.364817317:6(1324-1336)Online publication date: 3-May-2024
    • (2024)Fast and Precise Static Null Exception Analysis With Synergistic PreprocessingIEEE Transactions on Software Engineering10.1109/TSE.2024.346655150:11(3022-3036)Online publication date: 1-Nov-2024
    • (2024)Efficient algorithms for reachability and path queries on temporal bipartite graphsThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-024-00854-z33:5(1399-1426)Online publication date: 23-May-2024
    • (2023)Efficient Reachability Ratio Computation for 2-Hop Labeling SchemeElectronics10.3390/electronics1205117812:5(1178)Online publication date: 28-Feb-2023
    • (2023)Reachability Queries on Dynamic Temporal Bipartite GraphsProceedings of the 31st ACM International Conference on Advances in Geographic Information Systems10.1145/3589132.3625647(1-11)Online publication date: 13-Nov-2023
    • (2023)An Overview of Reachability Indexes on GraphsCompanion of the 2023 International Conference on Management of Data10.1145/3555041.3589408(61-68)Online publication date: 4-Jun-2023
    • (2023)Evaluation of Reachability Queries Based on Recursive DAG DecompositionIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.322019135:8(7935-7952)Online publication date: 1-Aug-2023
    • (2023)A Reachability Index for Recursive Label-Concatenated Graph Queries2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00013(67-81)Online publication date: Apr-2023
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