Abstract
Near-real-time data warehousing defines how updates from data sources are combined and transformed for storage in a data warehouse as soon as the updates occur. Since these updates are not in warehouse format, they need to be transformed and a join operator is usually required to implement this transformation. A stream-based algorithm called X-HYBRIDJOIN (Extended Hybrid Join), with a favorable asymptotic runtime behavior, was previously proposed. However, X-HYBRIDJOIN does not tune its components under limited available memory resources and without assigning an optimal division of memory to each join component the performance of the algorithm can be suboptimal. This paper presents a variant of X-HYBRIDJOIN called Tuned X-HYBRIDJOIN. The paper shows that after proper tuning the algorithm performs significantly better than that of the previous X-HYBRIDJOIN, and also better as other join operators proposed for this application found in the literature. The tuning approach has been presented, based on measurement techniques and a revised cost model. The experimental results demonstrate the superior performance of Tuned X-HYBRIDJOIN.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Naeem, M.A., Dobbie, G., Weber, G.: X-HYBRIDJOIN for Near-Real-Time Data Warehousing. In: Fernandes, A.A.A., Gray, A.J.G., Belhajjame, K. (eds.) BNCOD 2011. LNCS, vol. 7051, pp. 33–47. Springer, Heidelberg (2011)
Anderson, C.: The Long Tail: Why the Future of Business is Selling Less of More. Hyperion (2006)
Milton, A., Irene, A.S.: Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. Ninth Dover printing, Tenth GPO printing, New York (1964)
Labio, W.J., Wiener, J.L., Garcia-Molina, H., Gorelik, V.: Efficient resumption of interrupted warehouse loads. SIGMOD Rec. 29(2), 46–57 (2000)
Golab, L., Tamer Özsu, M.: Processing Sliding Window Multi-Joins in Continuous Queries over Data Streams. In: VLDB 2003, Berlin, Germany, pp. 500–511 (2003)
Wilschut, A.N., Apers, P.M.G.: Dataflow query execution in a parallel main-memory environment. Distrib. Parallel Databases 1(1), 103–128 (1993)
Gupta, A., Mumick, I.S.: Maintenance of Materialized Views: Problems, Techniques, and Applications. IEEE Data Engineering Bulletin 18, 3–18 (2000)
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)
Naeem, M.A., Dobbie, G., Weber, G.: R-MESHJOIN for Near-real-time Data Warehousing. In: DOLAP 2010: Proceedings of the ACM 13th International Workshop on Data Warehousing and OLAP. ACM, Toronto (2010)
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)
Naeem, M.A., Dobbie, G., Weber, G.: HYBRIDJOIN for Near-real-time Data Warehousing. International Journal of Data Warehousing and Mining (IJDWM)Â 7(4) (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Naeem, M.A. (2013). Tuned X-HYBRIDJOIN for Near-Real-Time Data Warehousing. In: Ishikawa, Y., Li, J., Wang, W., Zhang, R., Zhang, W. (eds) Web Technologies and Applications. APWeb 2013. Lecture Notes in Computer Science, vol 7808. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37401-2_49
Download citation
DOI: https://doi.org/10.1007/978-3-642-37401-2_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37400-5
Online ISBN: 978-3-642-37401-2
eBook Packages: Computer ScienceComputer Science (R0)