Abstract
Graph data is ubiquitous in various data applications, such as chemical compounds, proteins, and social network. Graph containment query processing in large-scale graph databases is one of the key challenges to the database community. The graph feature based index structures are widely used to narrow the isomorphism validating space. However, most of the existing index structures have expensive constructing overheads for the mining of frequent graph features. This paper proposes a novel way to query containment digraphs based on the partial order constraints. Firstly, the partial orders in digraphs, which are easier to obtain, are proved to be capable of filtering graph containment queries. Secondly, the partial orders are converted into layered vertex sequences, which can filter the digraphs in an efficient way. Thirdly, two optimized layered vertex sequences are further introduced to improve the filter ability. Finally, experimental results are presented to show the effectiveness and efficiency of the proposed algorithms.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Shasha, D., Wang, J.T.L., Giugno, R.: Algorithmics and Applications of Tree and Graph Searching. In: Proceedings of the 21st ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems (PODS), pp. 39–52 (June 2002)
Yan, X., Yu, P.S., Han, J.: Graph Indexing: A Frequent Structure Based Approach. In: Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), pp. 335–346 (June 2004)
Yan, X., Yu, P.S., Han, J.: Graph Indexing Based on Discriminative Frequent Structure Analysis. ACM Transactions on Database Systems (TODS) 30(4), 960–993 (2005)
Cheng, J., Ke, Y., Ng, W., et al.: FG-Index: Towards Verification Free Query Processing on Graph Databases. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, pp. 857–872 (June 2007)
Zhang, S., Hu, M., Yang, J.: Treepi: A Novel Graph Indexing Method. In: Proceedings of the 23rd International Conference on Data Engineering (ICDE), pp. 966–975 (April 2007)
Zhao, P., Yu, J.X., Yu, P.S.: Graph Indexing: Tree + Delta > = Graph. In: Proceedings of the 33rd International Conference on Very Large Data Bases (VLDB), pp. 938–949 (September 2007)
Jiang, H., Wang, H., Yu, P.S., et al.: Gstring: A Novel Approach for Efficient Search in Graph Databases. In: Proceedings of the 23nd International Conference on Data Engineering (ICDE), pp. 566–575 (April 2007)
He, H., Singh, A.K.: Closure-tree: An Index Structure for Graph Queries. In: Proceedings of the 22nd International Conference on Data Engineering (ICDE), pp. 38–47 (April 2006)
Zou, L., Chen, L., Yu, J.X., Lu, Y.: A novel spectral coding in a large graph database. In: Proceedings of the 11th International Conference on Extending Database Technology (EDBT), pp. 181–192 (March 2008)
Han, W.S., Lee, J., Pham, M.D., et al.: iGraph: A Framework for Comparisons of Disk-Based Graph Indexing Techniques. In: Proceedings of the 36rd International Conference on Very Large Data Bases (VLDB), pp. 449–559 (September 2010)
Huan, J., Wang, W., Prins, J.: Efficient Mining of Frequent Subgraphs in the Presence of Isomorphism. In: Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM), pp. 549–552 (2003)
Haeupler, B., Kavitha, T., Mathew, R., Sen, S., Tarjan, R.E.: Incremental Cycle Detection, Topological Ordering, and Strong Component Maintenance. ACM Transactions on Algorithms 8(1), 3 (2012)
Corman, T.H., Leiserson, C.E., Rivest, R.L., et al.: Introduction to Algorithms. The MIT Press (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Lu, J., Lu, N., Xi, Y., Zhang, B. (2014). Digraph Containment Query Is Like Peeling Onions. In: Decker, H., Lhotská, L., Link, S., Spies, M., Wagner, R.R. (eds) Database and Expert Systems Applications. DEXA 2014. Lecture Notes in Computer Science, vol 8644. Springer, Cham. https://doi.org/10.1007/978-3-319-10073-9_40
Download citation
DOI: https://doi.org/10.1007/978-3-319-10073-9_40
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10072-2
Online ISBN: 978-3-319-10073-9
eBook Packages: Computer ScienceComputer Science (R0)