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SCP: Skyline Computation Planner for Distributed, Update Intensive Environment

  • R. D. KulkarniEmail author
  • B. F. Momin
Conference paper
  • 1k Downloads
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 83)

Abstract

The most promising objects of a multi dimensional dataset are identified by a skyline query. In case of a higher dimensional, distributed, large dataset undergoing the frequent updates, the response time of skyline queries becomes intolerable. It can be significantly improvised, if a proper execution plan is used for the subsequent queries. In this paper, we have proposed a skyline computation model, SCP. The model presents certain strategies which make use of results of the pre-executed queries. Using these strategies, the execution of the subsequent queries is planned in order to achieve a positive gain in response time of the overall skyline computation. The model is suitable for a distributed dataset which is update intensive.

Keywords

Skyline queries Query profiler Skyline computing strategies 

References

  1. 1.
    Kulkarni, R.D., Momin, B.F.: Skyline computation for frequent queries in update intensive environment. J. Elsevier, King Saud Univ. Comput. Inf. Sci. 28(4), 447–456 (2016)Google Scholar
  2. 2.
    Borzsonyi, S., Kossmann, D., Stocker, K.: The Skyline Operator. In: Proceedings of IEEE International Conference on Data Engineering, pp. 421–430 (2001)Google Scholar
  3. 3.
    Chomicki, J., Godfrey, P., Gryz, J., Liang, D.: Skyline with presorting. In: IEEE International Conference on Data Engineering, pp. 717–719 (2003)Google Scholar
  4. 4.
    Godfrey, P., Shipley, P., Gryz, J.: Maximal vector computation in large data sets. In: IEEE International Conference on Very Large Databases, pp. 229–240 (2005)Google Scholar
  5. 5.
    Bartolini, I., Ciaccia, P., Patella, M.: SaLSa: computing the skyline without scanning the whole sky. In: ACM International Conference on Information and Knowledge Management, pp. 405–411 (2006)Google Scholar
  6. 6.
    Papadias, D., Tao, Y., Fu, G., Seeger, B.: Progressive skyline computation in database systems. ACM Trans. Database Syst. 30(1), 41–82 (2005)CrossRefGoogle Scholar
  7. 7.
    Zheng, W., Zou, L., Lian, X., Hong, L., Zhao, D.: Efficient subgraph skyline search over large graphs. In: ACM International Conference on Information and Knowledge Management, pp. 1529–1538 (2014)Google Scholar
  8. 8.
    Xia, T., Zhang, D.: Refreshing the sky: the compressed skycube with efficient support for frequent updates. In: ACM SIGMOD International Conference on Management of Data, pp. 493–501 (2005)Google Scholar
  9. 9.
    Wu, P., Zhang, C., Feng, Y., Zhao, B., Agrawal, D., Abbadi, A.: Parallelizing skyline queries for scalable distribution. In: IEEE International Conference on Extending Database Technology, pp. 112–130 (2006)Google Scholar
  10. 10.
    Zhang, N., Li, C., Hassan, N., Rajasekaran, S., Das, G.: On skyline groups. IEEE Trans. Knowl. Data Eng. 26(4), 942–956 (2014)CrossRefGoogle Scholar
  11. 11.
    Wang, S., Vu, Q., Ooi, B., Tung, A., Xu, L.: Skyframe: a framework for skyline query processing in peer-to-peer systems. VLDB J. 18(1), 345–362 (2009)CrossRefGoogle Scholar
  12. 12.
    Chen, L., Cui, B., Lu, H., Xu, L., Xu, Q.: iSky: efficient and progressive skyline computing in a structured P2P network. In: IEEE International Conference on Distributed Computing Systems, pp. 160–167 (2008)Google Scholar
  13. 13.
    Hose, K., Lemke, C., Sattler, K.: Processing relaxed skylines in PDMS using distributed data summaries. In: ACM International Conference on Information and Knowledge Management, pp. 425–434 (2006)Google Scholar
  14. 14.
    Hose, K., Lemke, C., Sattler, K., Zinn, D.: A relaxed but not necessarily constrained way from the top to the sky. In: ACM International Conference on On the Move to Meaningful Internet Systems, pp. 339–407 (2007)Google Scholar
  15. 15.
    Junior, R., Vlachou, J. A., Doulkeridis, C., Nørvág, K. :AGiDS: a grid-based strategy for distributed skyline query processing. In: ACM International Conference on Data Management in Grid and Peer-to-Peer Systems, pp. 12–23 (2009)Google Scholar
  16. 16.
    Vlachou, A., Doulkeridis, C., Nørvåg, K.: Distributed top-k query processing by exploiting skyline summaries. J Distrib. Parallel Databases 30(3–4), 239–271 (2012)Google Scholar
  17. 17.
    Chen, L., Cui, B., Lu, H.: Constrained skyline query processing against distributed data sites. IEEE Trans. Knowl. Data Eng. 23(2), 204–217 (2011)CrossRefGoogle Scholar
  18. 18.
    Woods, L., Alonso, G., Teubner, J.: Parallel computation of skyline queries. In: IEEE 21st Annual International Symposium on Field-Programmable Custom Computing Machines, pp. 1–8 (2008)Google Scholar
  19. 19.
    Papapetrou, O., Garofalakis, M.: Continuous fragmented skylines over distributed streams. In: IEEE International Conference on Data Engineering, pp. 124–135 (2014)Google Scholar
  20. 20.
    Bhattacharya, A., Teja, P., Dutta, S.: Caching stars in the sky: a semantic caching approach to accelerate skyline queries. In: International Conference on Database and Expert systems Applications, pp. 493–501 (2011)Google Scholar
  21. 21.
    Li, Y., Qu, W., Li, Z., Xu, Y., Ji, C., Wu, J.: Parallel dynamic skyline query using MapReduce. In: IEEE International Conference on Cloud Computing and Big data, pp. 95–100 (2014)Google Scholar
  22. 22.
    Park, Y., Min, J., Shim, K.: Parallel computation of skyline and reverse skyline queries using MapReduce. J. VLDB Endowment 6(14), 2002–2013 (2013)CrossRefGoogle Scholar
  23. 23.
    Zhang, J., Jiang, J., Ku, W., Qin, X.: Efficient parallel skyline evaluation using mapreduce. IEEE Trans. Parallel Distrib. Syst. 27(7), 1996–2009 (2016)CrossRefGoogle Scholar
  24. 24.
    Bai, M., Xin, J., Wang, G., Zimmermann, R., Wang, X.: Skyline-join query processing in distributed databases. J. Front. Comput. Sci. 10(2), 330–352 (2016)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringWalchand College of EngineeringSangliIndia

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