Abstract
Graphs are essential modeling and analytical objects for representing information networks. Existing approaches, in on-line analytical processing on graphs, took the first step by supporting multi-level and multi-dimensional queries on graphs, but they do not provide a semantic-driven framework and a language to support n-dimensional computations, which are frequent in OLAP environments. The major challenge here is how to extend decision support on multidimensional networks considering both data objects and the relationships among them. Moreover, one of the critical deficiencies of graph query languages, e.g. SPARQL, is the lack of support for n-dimensional computations. In this paper, we propose a graph data model, GOLAP, for online analytical processing on graphs. This data model enables extending decision support on multidimensional networks considering both data objects and the relationships among them. Moreover, we extend SPARQL to support n-dimensional computations. The approaches presented in this paper have been implemented on top of FPSPARQL, Folder-Path enabled extension of SPARQL, and experimentally validated on synthetic and real-world datasets.
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
Abelló, A., Romero, O.: On-line analytical processing. In: Encyclopedia of Database Systems, pp. 1949–1954. Springer US (2009)
Aggarwal, C.C., Wang, H. (eds.): Managing and Mining Graph Data. Springer (2010)
Balmin, A., Papadimitriou, T., Papakonstantinou, Y.: Hypothetical queries in an olap environment. In: VLDB, pp. 220–231 (2000)
Barbieri, D.F., et al.: C-sparql: Sparql for continuous querying. In: WWW, pp. 1061–1062 (2009)
Beheshti, S.-M.-R., Benatallah, B., Motahari-Nezhad, H.R., Allahbakhsh, M.: Online Analytical Processing on Graphs (GOLAP): Model and Query Language. unsw-cse-tr-201214, University of New South Wales (2012)
Beheshti, S.-M.-R., Benatallah, B., Motahari-Nezhad, H.R., Sakr, S.: A Query Language for Analyzing Business Processes Execution. In: Rinderle-Ma, S., Toumani, F., Wolf, K. (eds.) BPM 2011. LNCS, vol. 6896, pp. 281–297. Springer, Heidelberg (2011)
Chaudhuri, S., Dayal, U.: An overview of data warehousing and OLAP technology. SIGMOD Record 26(1), 65–74 (1997)
Chen, C., Yan, X., Zhu, F., Han, J., Yu, P.S.: Graph OLAP: Towards online analytical processing on graphs. In: ICDM, pp. 103–112 (2008)
Dries, A., Nijssen, S., De Raedt, L.: A query language for analyzing networks. In: CIKM, pp. 485–494 (2009)
Etcheverry, L., Vaisman, A.A.: Enhancing OLAP Analysis with Web Cubes. In: Simperl, E., Cimiano, P., Polleres, A., Corcho, O., Presutti, V. (eds.) ESWC 2012. LNCS, vol. 7295, pp. 469–483. Springer, Heidelberg (2012)
Han, J., Sun, Y., Yan, X., Yu, P.S.: Mining knowledge from data: An information network analysis approach. In: ICDE (2012)
Han, J., Yan, X., Yu, P.S.: Scalable OLAP and mining of information networks. In: EDBT (2009)
Ji, M., Sun, Y., Danilevsky, M., Han, J., Gao, J.: Graph Regularized Transductive Classification on Heterogeneous Information Networks. In: Balcázar, J.L., Bonchi, F., Gionis, A., Sebag, M. (eds.) ECML PKDD 2010, Part I. LNCS, vol. 6321, pp. 570–586. Springer, Heidelberg (2010)
Kämpgen, B., Harth, A.: Transforming statistical linked data for use in OLAP systems. In: I-SEMANTICS, pp. 33–40 (2011)
Leskovec, J., Adamic, L.A., Huberman, B.A.: The dynamics of viral marketing. TWEB 1(1) (2007)
Lima, A.A.B., et al.: Adaptive virtual partitioning for OLAP query processing in a database cluster. JIDM 1(1), 75–88 (2010)
Motahari-Nezhad, H.R., et al.: Event correlation for process discovery from web service interaction logs. The VLDB Journal 20(3), 417–444 (2011)
Prud’hommeaux, E., Seaborne, A.: Sparql query language for rdf (working draft). Technical report, W3C (March 2007)
Qian, T., Yang, Y., Wang, S.: Refining Graph Partitioning for Social Network Clustering. In: Chen, L., Triantafillou, P., Suel, T. (eds.) WISE 2010. LNCS, vol. 6488, pp. 77–90. Springer, Heidelberg (2010)
Qu, Q., Zhu, F., Yan, X., Han, J., Yu, P.S., Li, H.: Efficient Topological OLAP on Information Networks. In: Yu, J.X., Kim, M.H., Unland, R. (eds.) DASFAA 2011, Part I. LNCS, vol. 6587, pp. 389–403. Springer, Heidelberg (2011)
Romero, O., Abelló, A.: A survey of multidimensional modeling methodologies. IJDWM 5(2), 1–23 (2009)
Satish, A., Jain, R., Gupta, A.: Tolkien: an event based storytelling system. Proc. VLDB Endow. 2, 1630–1633 (2009)
Sun, Y., et al.: Rankclus: integrating clustering with ranking for heterogeneous information network analysis. In: EDBT, pp. 565–576 (2009)
Sun, Y., et al.: Relation strength-aware clustering of heterogeneous information networks with incomplete attributes. PVLDB 5(5), 394–405 (2012)
Thomsen, E.: OLAP Solutions: Building Multidimensional Information Systems, 2nd edn. John Wiley & Sons, Inc., New York (2002)
Tian, Y., Hankins, R.A., Patel, J.M.: Efficient aggregation for graph summarization. In: SIGMOD Conference, pp. 567–580 (2008)
Witkowski, A., et al.: Spreadsheets in rdbms for olap. In: SIGMOD Conference, pp. 52–63 (2003)
Xin, D., Shao, Z., Han, J., Liu, H.: C-cubing: Efficient computation of closed cubes by aggregation-based checking. In: ICDE (2006)
Yan, X., Yu, P.S., Han, J.: Graph indexing: A frequent structure-based approach. In: SIGMOD Conference, pp. 335–346 (2004)
Zhao, P., Li, X., Xin, D., Han, J.: Graph cube: on warehousing and olap multidimensional networks. In: SIGMOD 2011, pp. 853–864 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Beheshti, SMR., Benatallah, B., Motahari-Nezhad, H.R., Allahbakhsh, M. (2012). A Framework and a Language for On-Line Analytical Processing on Graphs. In: Wang, X.S., Cruz, I., Delis, A., Huang, G. (eds) Web Information Systems Engineering - WISE 2012. WISE 2012. Lecture Notes in Computer Science, vol 7651. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35063-4_16
Download citation
DOI: https://doi.org/10.1007/978-3-642-35063-4_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35062-7
Online ISBN: 978-3-642-35063-4
eBook Packages: Computer ScienceComputer Science (R0)