Abstract
Sorting algorithms help to organize large amounts of data. However, sometimes it is not easy to determine the correct order in large data sets, especially if there are special poses on the input. It often complicates sorting, results in time prolongation or even unable sorting. In such situations, the most common method is to perform sorting process to reshuffled input data or change the algorithm. In this paper, the authors examined quick sort algorithm in two versions for large data sets. The algorithms have been examined in performance tests and the results helped to compare them.
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References
Aho, I.A., Hopcroft, J., Ullman, J.: The design and analysis of computer algorithms. Addison-Wesley Publishing Company, USA (1975)
Bing-Chao, H., Knuth, D.E.: A one-way, stack less Quick sort algorithm. BIT 26, 127–130 (1986)
Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Introduction to Algorithms. The MIT Press, Cambridge (2001)
Francis, R.S., Pannan, L.J.H.: A parallel partition for enhanced parallel quick sort. Parallel Comput. 18(5), 543–550 (1992)
Gedigaa, G., Duntschb, I.: Approximation quality for sorting rules. Comput. Stat. Data Anal. 40, 499–526 (2002)
Knuth, D.E.: The Art of Computer Programming. Addison-Wesley, USA (1998)
LaMarca, A., Ladner, R.E.: The influence of caches on the performance of sorting. In: Proceedings of ACM-SIAM Symposium on Discrete Algorithms, pp. 370–379 (1997)
Larson, P., Graefe, G.: Memory management during run generation in external sorting. In: Proceedings of SIGMOD, pp. 472–483 (1998)
Larson, P.: External sorting: run formation revisited. IEEE Trans. Knowl. Data Eng. 15(4), 961–972 (2003)
MacIlroy, M.: A killer adversary for quick sort. Softw. Pract. Exp. 29, 1–4 (1999)
Marszałek, Z., Połap, D., Woźniak, M.: On preprocessing large data sets by the use of triple merge sort algorithm. In: Proceedings of International Conference on Advances in Information Processing and Communication Technology, The IRED Digital Seek Library (2014) (accepted—in press)
Marszałek, Z., Woźniak, M.: On possible organizing Nosql database systems. Int. J. Inf. Sci. Intell. Syst. 2(2), 51–59 (2013)
Martynez, C., Roura, C.: Optimal sampling strategies in quick sort and quick select. SIAM J. Comput. 31(3), 683–705 (2002)
Pan, Y., Hamdi, M.: Quick sort on a linear array with a reconfigurable pipelined bus system. Working Paper 94–03, The Center for Business and Economics Research, University of Dayton (1994)
Raghaven, P.: Lecture Notes on Randomized Algorithms. Technical Report, IBM Research Division, New York (1990)
Rashid, L., Hassanein, W.M., Hammad, M.A.: Analyzing and Enhancing the Parallel Sort Operation on Multithreaded Architectures. J. Supercomput. Springer, Berlin Heidelberg (2009)
Rauh, A., Arce, G.R.: A fast weighted median algorithm based on quick select. In: Proceedings of IEEE International Conference on Image Processing, pp. 105–108. Hong Kong (2010)
Sedgewick, R.: Implementing quick sort programs. Commun. ACM 21(10), 847–857 (1978)
Trimananda, R., Haryanto, C.Y.: A parallel implementation of hybridized merge-quick sort algorithm on MPICH. In: Proceedings of International Conference on Distributed Framework for Multimedia Applications (2010)
Tsigas, P., Zhang, Y.: A simple, fast parallel implementation of quick sort and its performance evaluation on SUN enterprise 10000. In: Proceedings of Euromicro Workshop on Parallel, Distributed and Network-Based Processing, pp. 372–381 (2003)
Tsigas, P., Zhang, Y.: Parallel quick sort seems to outperform sample sort on cache coherent shared memory multiprocessors: An evaluation on sun enterprise 10000. Technical report, Chalmers University of Technology (2002)
Weiss, M.A.: Data Structure & Algorithm Analysis in C++. Addison Wesley (1999)
Woźniak, M., Marszałek, Z., Gabryel, M., Nowicki R.K.: Modified merge sort algorithm for large scale data sets. Lecture Notes in Artificial Intelligence, Part II, vol. 7895, pp. 612–622. Springer, Berlin (2013)
Woźniak, M., Marszałek, Z., Gabryel, M., Nowicki R.K.: On quick sort algorithm performance for large data sets. In: Skulimowski, A.M.J. (ed.) Looking into the Future of Creativity and Decision Support Systems, pp. 647–656. Progress & Business Publishers, (KICSS’2013), Poland (2013)
Woźniak, M., Marszałek, Z., Gabryel, M., Nowicki R.K.: Triple heap sort algorithm for large data sets. In: Skulimowski, A.M.J. (ed.) Looking into the Future of Creativity and Decision Support Systems, pp. 657–665. Progress & Business Publishers, (KICSS’2013), Poland (2013)
Woźniak, M., Marszałek, Z.: Selected Algorithms for Sorting Large Data Sets. Silesian University of Technology Press, Poland (2013)
Woźniak, M., Marszałek, Z.: Extended Algorithms for Sorting Large Data Sets. Silesian University of Technology Press, Poland (2014)
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Woźniak, M., Marszałek, Z., Gabryel, M., Nowicki, R.K. (2016). Preprocessing Large Data Sets by the Use of Quick Sort Algorithm. In: Skulimowski, A., Kacprzyk, J. (eds) Knowledge, Information and Creativity Support Systems: Recent Trends, Advances and Solutions. Advances in Intelligent Systems and Computing, vol 364. Springer, Cham. https://doi.org/10.1007/978-3-319-19090-7_9
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DOI: https://doi.org/10.1007/978-3-319-19090-7_9
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