Online Querying of Concept Hierarchies in P2P Systems

  • Katerina Doka
  • Athanasia Asiki
  • Dimitrios Tsoumakos
  • Nectarios Koziris
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5331)


In this paper we describe HIS, a system that enables efficient storage and querying of data organized into concept hierarchies and dispersed over a network. Our scheme utilizes an adaptive algorithm that automatically adjusts the level of indexing according to the granularity of the incoming queries, without assuming any prior knowledge of the query workload. Efficient roll-up and drill-down operations increase the exact-match query ratio by shifting to the most favorable hierarchy level. Combined with soft-state indices created after query misses, our system achieves maximization of performance by minimizing query flooding. Extensive experimental evaluations show that, on top of the advantages that a distributed storage offers, our method answers the large majority of incoming queries without flooding the network and at the same time it manages to preserve the hierarchical nature of data. It shows remarkable performance especially for skewed workloads, which are frequently documented in the majority of Internet-scale applications. These characteristics are maintained even after sudden shifts in the workload.


Control Message Data Cube Concept Hierarchy Query Workload Dimension Hierarchy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Gray, J., Chaudhuri, S., Bosworth, A., Layman, A., Reichart, D., Venkatrao, M., Pellow, F., Pirahesh, H.: Data cube: A relational aggregation operator generalizing group-by, cross-tab, and sub-totals. Data Min. Knowl. Discov. 1(1), 29–53 (1997)CrossRefGoogle Scholar
  2. 2.
    Ooi, B., Shu, Y., Tan, K., Zhou, A.: PeerDB: A P2P-based System for Distributed Data Sharing. In: ICDE 2003 (2003)Google Scholar
  3. 3.
    Huebsch, R., Hellerstein, J., Boon, N.L., Loo, T., Shenker, S., Stoica, I.: Querying the Internet with PIER. In: VLDB 2003 (2003)Google Scholar
  4. 4.
    Halevy, A., Ives, Z., Madhavan, J., Mork, P., Suciu, D., Tatarinov, I.: The Piazza Peer Data Management System. IEEE Transactions on Knowledge and Data Engineering (2003)Google Scholar
  5. 5.
    Cha, M., Kwak, H., Rodriguez, P., Ahn, Y., Moon, S.: I tube, you tube, everybody tubes: analyzing the world’s largest user generated content video system. In: IMC 2007: Proceedings of the 7th ACM SIGCOMM conference on Internet measurement (2007)Google Scholar
  6. 6.
    Ripeanu, M., Foster, I., Iamnitchi, A.: Mapping the gnutella network: Properties of large-scale peer-to-peer systems and implications for system design. IEEE Internet Computing Journal 6(1) (2002)Google Scholar
  7. 7.
    Sen, S., Wong, J.: Analyzing peer-to-peer traffic across large networks. In: SIGCOMM Internet Measurments Workshop (2002)Google Scholar
  8. 8.
    Chu, J., Labonte, K., Levine, B.: Availability and locality measurements of peer-to-peer file systems. In: SPIE 2002 (2002)Google Scholar
  9. 9.
  10. 10.
    APB-1: OLAP Council APB-1 Benchmark,
  11. 11.
    Loo, T., Hellerstein, J., Huebsch, R., Shenker, S., Stoica, I.: Enchancing p2p file-sharing with an internet-scale query processor. In: VLDB (2004)Google Scholar
  12. 12.
    Aberer, K., Cudre-Mauroux, P., Hauswirth, M.: The Chatty Web: Emergent Semantics Through Gossiping. In: WWW Conference (2003)Google Scholar
  13. 13.
    Aberer, K., Cudre-Mauroux, P., Hauswirth, M., Pelt, T.V.: Gridvine:Building internet-scale semantic overlay networks. In: International Semantic Web Conference (2004)Google Scholar
  14. 14.
    Tang, C., Xu, Z., Dwarkadas, S.: Peer-to-peer information retrieval using self-organizing semantic overlay networks. In: SIGCOMM (2003)Google Scholar
  15. 15.
    Koloniari, G., Pitoura, E.: Content-based routing of path quieries in peer-to-peer systems. In: EDBT (2004)Google Scholar
  16. 16.
    Sismanis, Y., Deligiannakis, A., Kotidis, Y., Roussopoulos, N.: Hierarchical dwarfs for the rollup cube. In: DOLAP (2003)Google Scholar
  17. 17.
    Ester, M., Kohlhammer, J., Kriegel, P.: The dc-tree: A fully dynamic index structure for data warehouses. In: ICDE (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Katerina Doka
    • 1
  • Athanasia Asiki
    • 1
  • Dimitrios Tsoumakos
    • 1
  • Nectarios Koziris
    • 1
  1. 1.Computing Systems Laboratory School of Electrical and Computer EngineeringNational Technical University of AthensGreece

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