SSCJ: A Semi-Stream Cache Join Using a Front-Stage Cache Module

  • M. Asif Naeem
  • Gerald Weber
  • Gillian Dobbie
  • Christof Lutteroth
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8057)


Semi-stream processing has become an emerging area of research in the field of data stream management. One common operation in semi-stream processing is joining a stream with disk-based master data using a join operator. This join operator typically works under limited main memory and this memory is generally not large enough to hold the whole disk-based master data. Recently, a number of semi-stream join algorithms have been proposed in the literature to achieve an optimal performance but still there is room to improve the performance. In this paper we propose a novel Semi-Stream Cache Join (SSCJ) using a front-stage cache module. The algorithm takes advantage of skewed distributions, and we present results for Zipfian distributions of the type that appear in many applications. We analyze the performance of SSCJ with a well known related join algorithm, HYBRIDJOIN (Hybrid Join). We also provide the cost model for our approach and validate it with experiments.


Semi-stream processing Stream-based join Data warehousing Performance measurement 


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  1. 1.
    Anderson, C.: The Long Tail: Why the Future of Business Is Selling Less of More. Hyperion (2006)Google Scholar
  2. 2.
    Bornea, M.A., Deligiannakis, A., Kotidis, Y., Vassalos, V.: Semi-streamed index join for near-real time execution of ETL transformations. In: IEEE 27th International Conference on Data Engineering (ICDE 2011), pp. 159–170 (April 2011)Google Scholar
  3. 3.
    Chakraborty, A., Singh, A.: A partition-based approach to support streaming updates over persistent data in an active datawarehouse. In: IPDPS 2009: Proceedings of the 2009 IEEE International Symposium on Parallel & Distributed Processing, pp. 1–11. IEEE Computer Society, Washington, DC (2009)CrossRefGoogle Scholar
  4. 4.
    Karakasidis, A., Vassiliadis, P., Pitoura, E.: ETL queues for active data warehousing. In: IQIS 2005: Proceedings of the 2nd International Workshop on Information Quality in Information Systems, pp. 28–39. ACM, New York (2005)CrossRefGoogle Scholar
  5. 5.
    Knuth, D.E.: The art of computer programming, 2nd edn. Sorting and searching, vol. 3. Addison Wesley Longman Publishing Co., Inc., Redwood City (1998)MATHGoogle Scholar
  6. 6.
    Asif Naeem, M., Dobbie, G., Weber, G.: An event-based near real-time data integration architecture. In: EDOCW 2008: Proceedings of the 2008 12th Enterprise Distributed Object Computing Conference Workshops, pp. 401–404. IEEE Computer Society, Washington, DC (2008)CrossRefGoogle Scholar
  7. 7.
    Asif Naeem, M., Dobbie, G., Weber, G.: HYBRIDJOIN for near-real-time data warehousing. International Journal of Data Warehousing and Mining (IJDWM) 7(4), 21–42 (2011)CrossRefGoogle Scholar
  8. 8.
    Asif Naeem, M., Dobbie, G., Weber, G., Alam, S.: R-MESHJOIN for near-real-time data warehousing. In: DOLAP 2010: Proceedings of the ACM 13th International Workshop on Data Warehousing and OLAP, Toronto, Canada. ACM (2010)Google Scholar
  9. 9.
    Polyzotis, N., Skiadopoulos, S., Vassiliadis, P., Simitsis, A., Frantzell, N.E.: Supporting streaming updates in an active data warehouse. In: ICDE 2007: Proceedings of the 23rd International Conference on Data Engineering, Istanbul, Turkey, pp. 476–485 (2007)Google Scholar
  10. 10.
    Polyzotis, N., Skiadopoulos, S., Vassiliadis, P., Simitsis, A., Frantzell, N.: Meshing streaming updates with persistent data in an active data warehouse. IEEE Trans. on Knowl. and Data Eng. 20(7), 976–991 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2013

Authors and Affiliations

  • M. Asif Naeem
    • 1
  • Gerald Weber
    • 2
  • Gillian Dobbie
    • 2
  • Christof Lutteroth
    • 2
  1. 1.School of Computing and Mathematical SciencesAuckland University of TechnologyNew Zealand
  2. 2.Department of Computer ScienceThe University of AucklandAucklandNew Zealand

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