Abstract
The data volume and the multitude of sources have an exponential number of technical and application challenges. In the past, Big Data solutions have been presented as a replacement for the Parallel Database Management Systems. However, Big Data solutions can be seen as a complement to a RDBMS for analytical applications, because different problems require complex analysis capabilities provided by both technologies. The aim of his work is to integrate a Big Data solution and a classic DBMS, in a goal of queries optimization. We propose a model for OLAP queries process. Then, we valid the proposed optimized model through experiments showing the gain of the execution cost saved up.
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References
Ordonez, C.: Can we analyze big data inside a DBMS?. In: Proceedings of the Sixteenth International Workshop on Data Warehousing and OLAP, ACM, pp. 85–92 (2013)
Fan, W., Bifet, A.: Mining big data: current status, and forecast to the future. In: SIGKDD Explorations, vol. 14, issue 2 (2011)
Doulkeridis, C., Nørvåg, K.: A survey of large-scale analytical query processing in MapReduce. VLDB J. 23(3), 355–380 (2014)
Dean, J., Ghemawats, S.: Mapreduce: Simplified data processing on large clusters. Commun. ACM 51(1), 107–113 (2008)
Brown, P.G.: Object-Relational Database Development: A Plumber’s Guide. Prentice Hall PTR, Upper Saddle River (2000)
Douglas, K., Douglas, S.: PostgreSQL: A Comprehensive Guide to Building, Programming, and Administring PostreSQL Databases, 1st edn. Sams Publishing, (2003)
McClean, A., Conceicao, R., O’halloran, M.: A comparison of MapReduce and parallel database management systems. In: ICONS 2013 The Eighth International Conference on Systems, pp. 64–68 (2013)
Nance, C., Losser, T., Iype, R., Harmon, G.: NOSQL VS RDBMS – why there is room for both. In: Proceedings of the Southern Association for Information Systems Conference Savannah USA, pp. 111–116 (2013)
Stonebraker, M., Abadi, D., Dewitt, D., Madden, S., Paulsone, E., Pavlo, A., Rasin, A.: Mapreduce and parallel dbmss: friends or foes? Commun. ACM 53(1), 64–71 (2010)
Gruska, N., Martin, P.: Integrating MapReduce and RDBMSs. In: Proceedings of the 2010 Conference of the Center for Advanced Studies on Collaborative Research, IBM Corp, pp. 212–223 (2010)
Yui, M., Kojima, I.: A database-hadoop hybrid approach to scalable machine learning. In: Big Data 2013 IEEE International Congress on IEEE, pp. 1–8 (2013)
Abouzeid, A., Pawlikowski, K., Abadi, D., Silberschatz, A., Rasin, A.: Hadoopdb: an architectural hybrid of mapreduce and dbms technologies for analytical workloads. In: Proceedings of the VLDB Endowment, pp. 922–933 (2009)
Pavlo, A., Rasin, A., Madden, S., Stonebraker, M., Dewitt, D., Paulson, E., Shrinivas, L., Abadi, D.: A comparison of approaches to large scale data analysis. In: Proceedings of the 2009 ACM SIGMOD International Conference on Management of data, pp. 165–178 (2009)
Chandrasekar, S., Dakshinamurthy, R., Seshakumar, P.G., Prabavathy, B., Babu, C.: A novel indexing scheme for efficient handling of small files in hadoop distributed file system. In: Computer Communication and Informatics (ICCCI), 2013 International Conference, pp. 1–8 (2013)
Pavlo, A., Paulson, E., Rasin, A., Abadi, D.J., DeWitt, D.J., Madden, S., Stonebraker, M.: A comparison of approaches to large-scale data analysis. In: Proceedings of the 2009 ACM SIGMOD International Conference on Management of data ACM, pp. 165–178 (2009)
Boukorca, A., Faget, Z., Bellatreche, L.: What-if physical design for multiple query plan generation. In: Decker, H., Lhotská, L., Link, S., Spies, M., Wagner, R.R. (eds.) DEXA 2014, Part I. LNCS, vol. 8644, pp. 492–506. Springer, Heidelberg (2014)
Brighen, A.: Conception de bases de données volumineuses sur le cloud. In: Doctoral dissertation, Université Abderrahmane Mira de Béjaia (2012)
Fabrizio, M., Domenico, T., Paolo, T.: P2P-MapReduce: parallel data processing in dynamic cloud environments. J. Comput. Syst. Sci. 78(5), 1382–1402 (2012)
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Jemal, D., Faiz, R., Boukorca, A., Bellatreche, L. (2015). MapReduce-DBMS: An Integration Model for Big Data Management and Optimization. In: Chen, Q., Hameurlain, A., Toumani, F., Wagner, R., Decker, H. (eds) Database and Expert Systems Applications. Globe DEXA 2015 2015. Lecture Notes in Computer Science(), vol 9262. Springer, Cham. https://doi.org/10.1007/978-3-319-22852-5_36
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DOI: https://doi.org/10.1007/978-3-319-22852-5_36
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