Skip to main content

CUDA-Powered CTBE Algorithm for Zero-Latency Data Warehouse

  • Conference paper
  • First Online:
Book cover New Trends in Databases and Information Systems (ADBIS 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 539))

Included in the following conference series:

  • East European Conference on Advances in Databases and Information Systems
  • 1233 Accesses

Abstract

The systems dedicated for Zero-Latency Data Warehouses must meet the growing requirements for the most up-to-date data. The currently used sequential algorithms are not suited to deal with the pressure on receiving the freshest data. The one-module architecture implemented in current solutions, limits the development opportunities and increases the risk of critical system failure. In this paper we propose a new, innovative, multi-modular system that is based on parallel Choose Transaction by Election (CTBE) algorithm. Additionally we utilize the CUDA architecture to boost system efficiency, using computing power of multi-core graphic processors. The aim of this paper is to highlight pros and cons of such a solution. Performed tests and results show the potential and capabilities of the multi-modular system, using CUDA architecture.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bruckner, R.M., Tjoa, A.M.: Capturing Delays and Valid Times in Data Warehouses - Towards Timely Consistent Analyses. J. Intell. Inf. Syst. 19(2), 169–190 (2002)

    Article  Google Scholar 

  2. Gorawski, M., Gorawska, A.: Research on the stream ETL process. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B. (eds.) BDAS 2014. CCIS, vol. 424, pp. 61–71. Springer, Heidelberg (2014)

    Chapter  Google Scholar 

  3. Gorawski, M., Gorawski, M., Dyduch, S.: Use of grammars and machine learning in ETL systems that control load balancing process. In: HPCC 2013 Fourth International Workshop on Frontiers of Heterogeneous Computing, FHC 2013, vol. 370, pp. 1709–1714, Institute of Electrical and Electronics Engineers, Piscataway (2013)

    Google Scholar 

  4. Gorawski, M., Lis, D., Gorawski, M.: The use of a cloud computing and the CUDA architecture in zero-latency data warehouses. In: Kwiecień, A., Gaj, P., Stera, P. (eds.) CN 2013. CCIS, vol. 370, pp. 312–322. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  5. Gorawski, M., Lorek, M., Gorawska, A.: CUDA powered user-defined types and aggregates. In: 27th International Conference on Advanced Information Networking and Applications Workshops, WAINA 2013, pp. 1423–1428. IEEE Computer Society (2013)

    Google Scholar 

  6. Gorawski, M., Wardas, R.: The Workload Balancing ETL System Basing on a Learning Machine. Studia Informatica 31((2A (89))), 517–530 (2010)

    Google Scholar 

  7. Gorawski, M., Lis, D., Gorawska, A.: Zero–latency data warehouse system based on parallel processing and cache module. In: Corchado, E., Lozano, J.A., Quintián, H., Yin, H. (eds.) IDEAL 2014. LNCS, vol. 8669, pp. 465–474. Springer, Heidelberg (2014)

    Google Scholar 

  8. Karagiannis, A., Vassiliadis, P., Simitsis, A.: Scheduling Strategies for Efficient ETL Execution. Inf. Syst. 38(6), 927–945 (2013)

    Article  Google Scholar 

  9. Nguyen, T.M., Brezany, P., Tjoa, A.M., Weippl, E.: Toward a Grid-Based Zero-Latency Data Warehousing Implementation for Continuous Data Streams Processing. IJDWM 1(4), 22–55 (2005)

    Google Scholar 

  10. Nguyen, T.M., Tjoa, A.M.: Zero-latency data warehousing (ZLDWH): the state-of-the-art and experimental implementation approaches. In: 4th International Conference on Computer Sciences: Research, Innovation and Vision for the Future RIFV, pp. 167–176. IEEE (2006)

    Google Scholar 

  11. Thiele, M., Fischer, U., Lehner, W.: Partition-based Workload Scheduling in Living Data Warehouse Environments. Inf. Syst. 34(4–5), 382–399 (2009)

    Article  Google Scholar 

  12. Waas, F., Wrembel, R., Freudenreich, T., Thiele, M., Koncilia, C., Furtado, P.: On-Demand ELT Architecture for Right-Time BI: Extending the Vision. IJDWM 9(2), 21–38 (2013)

    Google Scholar 

  13. Gorawski, M., Marks, P., Gorawski, M.: Collecting data streams from a distributed radio-based measurement system. In: Haritsa, J.R., Kotagiri, R., Pudi, V. (eds.) DASFAA 2008. LNCS, vol. 4947, pp. 702–705. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Marcin Gorawski .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Gorawski, M., Lis, D., Gorawska, A. (2015). CUDA-Powered CTBE Algorithm for Zero-Latency Data Warehouse. In: Morzy, T., Valduriez, P., Bellatreche, L. (eds) New Trends in Databases and Information Systems. ADBIS 2015. Communications in Computer and Information Science, vol 539. Springer, Cham. https://doi.org/10.1007/978-3-319-23201-0_37

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-23201-0_37

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23200-3

  • Online ISBN: 978-3-319-23201-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics