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Real-Time Data Warehousing: A Rewrite/Merge Approach

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8646))

Abstract

This paper focuses on Real-Time Data Warehousing systems, a relevant class of Data Warehouses where the main requirement consists in executing classical data warehousing operations (e.g., loading, aggregation, indexing, OLAP query answering, and so forth) under real-time constraints. This makes classical DW architectures not suitable to this goal, and puts the basis for a novel research area which has tight relationship with emerging Cloud architectures. Inspired by this motivation, in this paper we proposed a novel framework for supporting Real-Time Data Warehousing which makes use of a rewrite/merge approach. We also provide an extensive experimental campaign that confirms the benefits deriving from our framework.

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References

  1. Vassiliadis, P., Simitsis, A.: Near Real Time ETL. In: New Trends in Data Warehousing and Data Analysis. Annals of Information Systems, vol. 3, pp. 1–31 (2009)

    Google Scholar 

  2. Jain, T., Rajasree, S., Saluja, S.: Refreshing Datawarehouse in Near Real-Time. International Journal of Computer Applications 46(18), 24–29 (2012)

    Article  Google Scholar 

  3. Zuters, J.: Near Real-Time Data Warehousing with Multi-stage Trickle and Flip. In: Grabis, J., Kirikova, M. (eds.) BIR 2011. LNBIP, vol. 90, pp. 73–82. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  4. Santos, R.J., Bernardino, J.: Real-Time Data Warehouse Loading Methodology. In: Proceedings of ACM IDEAS, pp. 49–58 (2008)

    Google Scholar 

  5. Nguyen, M., Tjoav, A.M.: Zero-Latency Data Warehousing for Heterogeneous Data Sources and Continuous Data Streams. In: Proceedings of iiWAS (2003)

    Google Scholar 

  6. Zhu, Y., An, L., Liu, S.: Data Updating and Query in Real-time Data Warehouse System. In: Proceedings of IEEE CSSE, pp. 1295–1297 (2008)

    Google Scholar 

  7. Ferreira, N.: Realtime Warehouses: Architecture and Evaluation. MSc Thesis, U. Coimbra (June 2013)

    Google Scholar 

  8. Vertica, http://www.vertica.com/the-analytics-platform/real-time-loading-querying/

  9. Oracle, Best Practices for Real-time Data Warehousing. White Paper (2012)

    Google Scholar 

  10. Zhu, Y., An, L., Liu, S.: Data Updating and Query in Real-time Data Warehouse System. In: Proceedings of IEEE CSSE (2008)

    Google Scholar 

  11. Chaudhuri, S., Dayal, U.: An Overview of Data Warehousing and OLAP Technology. SIGMOD Record 26(1), 65–74 (1997)

    Article  Google Scholar 

  12. Shi, J., Bao, Y., Leng, F., Yu, G.: Study on Log-based Change Data Capture and Handling Mechanism in Real-time Data Warehouse. In: Proceedings of IEEE CSSE, pp. 478–481 (2008)

    Google Scholar 

  13. Ram, P., Do, L.: Extracting Delta for Incremental Data Warehouse Maintenance. In: Proceedings of IEEE ICDE, pp. 220–229 (2000)

    Google Scholar 

  14. Furtado, P.: Efficiently Processing Query-Intensive Databases over a Non-Dedicated Local Network. In: Proceedings of IEEE IPDPS, p. 72 (2005)

    Google Scholar 

  15. O’Neil, P., O’Neil, E., Chen, X., Revilak, S.: The Star Schema Benchmark and Augmented Fact Table Indexing. In: Nambiar, R., Poess, M. (eds.) TPCTC 2009. LNCS, vol. 5895, pp. 237–252. Springer, Heidelberg (2009)

    Google Scholar 

  16. Cuzzocrea, A.: A Framework for Modeling and Supporting Data Transformation Services over Data and Knowledge Grids with Real-Time Bound Constraints. Concurrency and Computation: Practice and Experience 23(5), 436–457 (2011)

    Google Scholar 

  17. Cuzzocrea, A.: Providing probabilistically-bounded approximate answers to non-holistic aggregate range queries in OLAP. In: Proceedings of ACM DOLAP, pp. 97–106 (2005)

    Google Scholar 

  18. Cuzzocrea, A., Serafino, P.: LCS-Hist: taming massive high-dimensional data cube compression. In: Proceedings of ACM EDBT, pp. 768–779 (2009)

    Google Scholar 

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Cuzzocrea, A., Ferreira, N., Furtado, P. (2014). Real-Time Data Warehousing: A Rewrite/Merge Approach. In: Bellatreche, L., Mohania, M.K. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2014. Lecture Notes in Computer Science, vol 8646. Springer, Cham. https://doi.org/10.1007/978-3-319-10160-6_8

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  • DOI: https://doi.org/10.1007/978-3-319-10160-6_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10159-0

  • Online ISBN: 978-3-319-10160-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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