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Reachability queries on large dynamic graphs: a total order approach

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Published:18 June 2014Publication History

ABSTRACT

Reachability queries are a fundamental type of queries on graphs that find important applications in numerous domains. Although a plethora of techniques have been proposed for reachability queries, most of them require that the input graph is static, i.e., they are inapplicable to the {\em dynamic} graphs (e.g., social networks and the Semantic Web) commonly encountered in practice. There exist a few techniques that can handle dynamic graphs, but none of them can scale to sizable graphs without significant loss of efficiency. To address this deficiency, this paper presents a novel study on reachability indices for large dynamic graphs. We first introduce a general indexing framework that summarizes a family of reachability indices with the best performance among the existing techniques for static graphs. Then, we propose general and efficient algorithms for handling vertex insertions and deletions under the proposed framework. In addition, we show that our update algorithms can be used to improve the existing reachability techniques on static graphs, and we also propose a new approach for constructing a reachability index from scratch under our framework. We experimentally evaluate our solution on a large set of benchmark datasets, and we demonstrate that our solution not only supports efficient updates on dynamic graphs, but also provides even better query performance than the state-of-the-art techniques for static graphs.

References

  1. https://sites.google.com/site/totalorderlabelling.Google ScholarGoogle Scholar
  2. I. Abraham, D. Delling, A. V. Goldberg, and R. F. F. Werneck. Hierarchical hub labelings for shortest paths. InESA, pages 24--35, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. R. Agrawal, A. Borgida, and H. V. Jagadish. Efficient management of transitive relationships in large data and knowledge bases. In SIGMOD, pages 253--262, 1989. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. R. Bramandia, B. Choi, and W. K. Ng. Incremental maintenance of 2-hop labeling of large graphs. IEEE Trans. Knowl. Data Eng., 22(5):682--698, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. J. Cai and C. K. Poon. Path-hop: efficiently indexing large graphs for reachability queries. In CIKM, pages 119--128, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. L. Chen, A. Gupta, and M. E. Kurul. Stack-based algorithms for pattern matching on dags. In VLDB, pages 493--504, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Y. Chen and Y. Chen. An efficient algorithm for answering graph reachability queries. In ICDE, pages 893--902, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. J. Cheng, S. Huang, H. Wu, and A. W.-C. Fu. Tf-label: a topological-folding labeling scheme for reachability querying in a large graph. In SIGMOD, pages 193--204, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. J. Cheng, Z. Shang, H. Cheng, H. Wang, and J. X. Yu. K-reach: Who is in your small world. PVLDB, 5(11):1292--1303, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. J. Cheng, J. X. Yu, X. Lin, H. Wang, and P. S. Yu. Fast computing reachability labelings for large graphs with high compression rate. In EDBT, pages 193--204, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. E. Cohen, E. Halperin, H. Kaplan, and U. Zwick. Reachability and distance queries via 2-hop labels. In SODA, pages 937--946, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. C. Demetrescu and G. F. Italiano. Fully dynamic all pairs shortest paths with real edge weights. J. Comput. Syst. Sci., 72(5):813--837, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. M. R. Henzinger and V. King. Fully dynamic biconnectivity and transitive closure. In FOCS, pages 664--672, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. H. V. Jagadish. A compression technique to materialize transitive closure. ACM Trans. Database Syst., 15(4):558--598, 1990. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. R. Jin, N. Ruan, S. Dey, and J. X. Yu. Scarab: scaling reachability computation on large graphs. In SIGMOD, pages 169--180, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. R. Jin, N. Ruan, Y. Xiang, and H. Wang. Path-tree: An efficient reachability indexing scheme for large directed graphs. ACM Trans. Database Syst., 36(1):7, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. R. Jin and G. Wang. Simple, fast, and scalable reachability oracle. PVLDB, 6(14):1978--1989, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. R. Jin, Y. Xiang, N. Ruan, and D. Fuhry. 3-hop: a high-compression indexing scheme for reachability query. In SIGMOD, pages 813--826, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. R. Jin, Y. Xiang, N. Ruan, and H. Wang. Efficiently answering reachability queries on very large directed graphs. In SIGMOD, pages 595--608, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. I. Krommidas and C. D. Zaroliagis. An experimental study of algorithms for fully dynamic transitive closure. ACM Journal of Experimental Algorithmics, 12, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. L. Roditty. Decremental maintenance of strongly connected components. In SODA, pages 1143--1150, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. L. Roditty and U. Zwick. A fully dynamic reachability algorithm for directed graphs with an almost linear update time. In STOC, pages 184--191, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. R. Schenkel, A. Theobald, and G. Weikum. Hopi: An efficient connection index for complex xml document collections. In EDBT, pages 237--255, 2004.Google ScholarGoogle ScholarCross RefCross Ref
  24. R. Schenkel, A. Theobald, and G. Weikum. Efficient creation and incremental maintenance of the hopi index for complex xml document collections. In ICDE, pages 360--371, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. S. Seufert, A. Anand, S. J. Bedathur, and G. Weikum. Ferrari: Flexible and efficient reachability range assignment for graph indexing. In ICDE, pages 1009--1020, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. R. E. Tarjan. Depth-first search and linear graph algorithms. SIAM J. Comput., 1(2):146--160, 1972.Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. S. Trißl and U. Leser. Fast and practical indexing and querying of very large graphs. In SIGMOD, pages 845--856, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. S. J. van Schaik and O. de Moor. A memory efficient reachability data structure through bit vector compression. In SIGMOD, pages 913--924, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. H. Wang, H. He, J. Yang, P. S. Yu, and J. X. Yu. Dual labeling: Answering graph reachability queries in constant time. In ICDE, page 75, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Y. Yano, T. Akiba, Y. Iwata, and Y. Yoshida. Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In CIKM, pages 1601--1606, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. H. Yildirim, V. Chaoji, and M. J. Zaki. Grail: Scalable reachability index for large graphs. PVLDB, 3(1):276--284, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. H. Yildirim, V. Chaoji, and M. J. Zaki. Dagger: A scalable index for reachability queries in large dynamic graphs. CoRR, abs/1301.0977, 2013.Google ScholarGoogle Scholar

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    • Published in

      cover image ACM Conferences
      SIGMOD '14: Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data
      June 2014
      1645 pages
      ISBN:9781450323765
      DOI:10.1145/2588555

      Copyright © 2014 ACM

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      Publication History

      • Published: 18 June 2014

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      SIGMOD '14 Paper Acceptance Rate107of421submissions,25%Overall Acceptance Rate785of4,003submissions,20%

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