Abstract
Operational reporting differs from informational reporting in that its scope is on day-to-day operations and thus requires data on the detail of individual transactions. It is often not desirable to maintain data on such detailed level in the data warehouse, due to both exploding size of the warehouse and the update frequency required for operational reports. Using an ODS as the source for operational reporting exhibits a similar information latency.
In this paper, we propose an OLTP database architecture that serves the conventional OLTP load out of a row-store database and serves operational reporting queries out of a column-store database which holds the subset of the data in the row store required for operational reports. The column store is updated within the transaction of the row database, hence OLTP changes are directly reflected in operational reports. We also propose the virtual cube as a method for consuming operational reports from a conventional warehousing environment.
The paper presents the results of a project we did with SAP AG. The described solution for operational reporting has been implemented in SAP Business ByDesign and SAP Business Warehouse.
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References
Abadi, D.J.: Query Execution in Column-Oriented Database Systems. PhD thesis, Massachusetts Institute of Technology, Cambridge, MA, USA (Feburary 2008)
Abadi, D.J., Madden, S.R., Ferreira, M.: Integrating Compression and Execution in Column-Oriented Database Systems. In: SIGMOD 2006: Proceedings of the 2006 ACM SIGMOD international conference on Management of data, pp. 671–682. ACM Press, New York (2006)
Adzic, J., Fiore, V., Spelta, S.: Data Warehouse Population Platform. In: Jonker, W. (ed.) VLDB-WS 2001 and DBTel 2001. LNCS, vol. 2209, p. 9. Springer, Heidelberg (2001)
Boncz, P.: Monet: A Next-Generation DBMS Kernel for Query-Intensive Applications. PhD thesis, Universiteit van Amsterdam, Amsterdam, Netherlands (May 2002)
Brobst, S.: Enterprise Application Integration and Active Data Warehousing. In: Proceedings of Data Warehousing 2002, Heidelberg, Germany, pp. 15–23. Physica-Verlag GmbH (2000)
Chang, F., Dean, J., Ghemawat, S., Hsieh, W.C., Wallach, D.A., Burrows, M., Chandra, T., Fikes, A., Gruber, R.E.: Bigtable: A Distributed Storage System for Structured Data. In: USENIX 2006: Proceedings of the 7th conference on USENIX Symposium on Operating Systems Design and Implementation, Berkeley, CA, USA, p. 15. USENIX Association (2006)
Codd, E.F.: A Relational Model of Data for Large Shared Data Banks. Communications of the ACM 13, 377–387 (1970)
Copeland, G.P., Khoshafian, S.: A Decomposition Storage Model. In: Navathe, S.B. (ed.) Proceedings of the 1985 ACM SIGMOD International Conference on Management of Data, Austin, Texas, May 28-31, pp. 268–279. ACM Press, New York (1985)
Inmon, W.H.: Information Management: World-Class Business Intelligence. DM Review Magazine (March 2000)
Inmon, W.H.: Operational and Informational Reporting: Information Management: Charting the Course. DM Review Magazine (July 2000)
Inmon, W.H.: Building the Data Warehouse, 3rd edn. John Wiley & Sons, Inc., New York (2002)
Kimball, R., Caserta, J.: The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning. John Wiley & Sons, Inc., New York (2004)
Legler, T., Lehner, W., Ross, A.: Data Mining with the SAP NetWeaver BI Accelerator. In: VLDB 2006: Proceedings of the 32nd International Conference on Very Large Data Bases, pp. 1059–1068. VLDB Endowment (2006)
Mahapatra, N.R., Venkatrao, B.: The Processor-Memory Bottleneck: Problems and Solutions. Crossroads 5(3), 2 (1999)
Moss, L., Adelman, A.: Data Warehousing Methodology. Journal of Data Warehousing 5, 23–31 (2000)
Noaman, A.Y., Barker, K.: A Horizontal Fragmentation Algorithm for the Fact Relation in a Distributed Data Warehouse. In: CIKM 1999: Proceedings of the Eighth International Conference on Information and Knowledge Management, pp. 154–161. ACM Press, New York (1999)
Ramamurthy, R., DeWitt, D.J., Su, Q.: A case for fractured mirrors. VLDB J. 12(2), 89–101 (2003)
Shukla, A., Deshpande, P., Naughton, J.F.: Materialized view selection for multi-cube data models. In: Zaniolo, C., Grust, T., Scholl, M.H., Lockemann, P.C. (eds.) EDBT 2000. LNCS, vol. 1777, pp. 269–284. Springer, Heidelberg (2000)
Simitsis, A., Vassiliadis, P., Sellis, T.: State-Space Optimization of ETL Workflows. IEEE Transactions on Knowledge and Data Engineering 17(10), 1404–1419 (2005)
Stonebraker, M., Abadi, D.J., Batkin, A., Chen, X., Cherniack, M., Ferreira, M., Lau, E., Lin, A., Madden, S.R., O’Neil, E., O’Neil, P., Rasin, A., Tran, N., Zdonik, S.: C-Store: A Column-oriented DBMS. In: VLDB 2005: Proceedings of the 31st International Conference on Very Large Data Bases, pp. 553–564. VLDB Endowment (2005)
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Schaffner, J., Bog, A., Krüger, J., Zeier, A. (2009). A Hybrid Row-Column OLTP Database Architecture for Operational Reporting. In: Castellanos, M., Dayal, U., Sellis, T. (eds) Business Intelligence for the Real-Time Enterprise. BIRTE 2008. Lecture Notes in Business Information Processing, vol 27. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03422-0_5
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DOI: https://doi.org/10.1007/978-3-642-03422-0_5
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