{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,29]],"date-time":"2025-06-29T04:04:24Z","timestamp":1751169864026,"version":"3.41.0"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031969997","type":"print"},{"value":"9783031970009","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-97000-9_13","type":"book-chapter","created":{"date-parts":[[2025,6,28]],"date-time":"2025-06-28T06:52:01Z","timestamp":1751093521000},"page":"211-224","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Non-dominated Sorting Genetic Algorithm for\u00a0Multiple Objectives Query Optimization in\u00a0Spark SQL"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9560-1180","authenticated-orcid":false,"given":"Trung-Dung","family":"Le","sequence":"first","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,6,29]]},"reference":[{"key":"13_CR1","doi-asserted-by":"publisher","unstructured":"Armbrust, M., et al.: Spark SQL: relational data processing in spark. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data (SIGMOD), pp. 1383\u20131394. ACM (2015). https:\/\/doi.org\/10.1145\/2723372.2742797","DOI":"10.1145\/2723372.2742797"},{"key":"13_CR2","doi-asserted-by":"publisher","unstructured":"Cheng, G., Ying, S., Wang, B.: Tuning configuration of Apache Spark on public clouds by combining multi-objective optimization and performance prediction model. J. Syst. Softw. 180 (2021). https:\/\/doi.org\/10.1016\/j.jss.2021.111028","DOI":"10.1016\/j.jss.2021.111028"},{"key":"13_CR3","doi-asserted-by":"publisher","unstructured":"Coello, C.A.C., Cort\u00e9s, N.C.: Solving multiobjective optimization problems using an artificial immune system. Genetic Programm. Evol. Mach. 6, 163\u2013190 (2005). https:\/\/doi.org\/10.1007\/s10710-005-6164-x","DOI":"10.1007\/s10710-005-6164-x"},{"key":"13_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1007\/978-3-319-51469-7_9","volume-title":"Machine Learning, Optimization, and Big Data","author":"JA Cordero","year":"2016","unstructured":"Cordero, J.A., et al.: Dynamic multi-objective optimization with jMetal and spark: a case study. In: Pardalos, P.M., Conca, P., Giuffrida, G., Nicosia, G. (eds.) MOD 2016. LNCS, vol. 10122, pp. 106\u2013117. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-51469-7_9"},{"key":"13_CR5","unstructured":"Databricks: Cost-based optimizer in Apache Spark SQL. Databricks Documentation (2024). https:\/\/docs.databricks.com\/spark\/latest\/spark-sql\/cbo.html"},{"key":"13_CR6","doi-asserted-by":"crossref","unstructured":"Deb, K., Jain, H.: An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach. IEEE Trans. Evol. Comput. 18(4), 577\u2013601 (2014). https:\/\/doi.org\/10.1109\/TEVC.2013.2281535","DOI":"10.1109\/TEVC.2013.2281535"},{"key":"13_CR7","doi-asserted-by":"crossref","unstructured":"Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182\u2013197 (2002). https:\/\/doi.org\/10.1109\/4235.996017","DOI":"10.1109\/4235.996017"},{"key":"13_CR8","doi-asserted-by":"crossref","unstructured":"Deb, K., Thiele, L., Laumanns, M., Zitzler, E.: Scalable multi-objective optimization test problems. In: Proceedings of the 2002 Congress on Evolutionary Computation (CEC 2002), vol. 1, pp. 825\u2013830. IEEE (2002). https:\/\/doi.org\/10.1109\/CEC.2002.1007032","DOI":"10.1109\/CEC.2002.1007032"},{"key":"13_CR9","doi-asserted-by":"crossref","unstructured":"Doka, K., Papailiou, N., Tsoumakos, D., Mantas, C., Koziris, N.: IReS: intelligent, Multi-Engine Resource Scheduler for Big Data Analytics Workflows. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data (SIGMOD 2015), pp. 1451\u20131456. ACM (2015). https:\/\/doi.org\/10.1145\/2723372.2735377","DOI":"10.1145\/2723372.2735377"},{"key":"13_CR10","doi-asserted-by":"crossref","unstructured":"Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA data mining software: an update. SIGKDD Explor. Newslett. 11(1), 10\u201318 (2009). https:\/\/doi.org\/10.1145\/1656274.1656278","DOI":"10.1145\/1656274.1656278"},{"key":"13_CR11","doi-asserted-by":"crossref","unstructured":"Hulgeri, A., Sudarshan, S.: Parametric query optimization for linear and piecewise linear cost functions. In: Proceedings of the 28th International Conference on Very Large Data Bases (VLDB 2002), pp. 167\u2013178. VLDB Endowment (2002). https:\/\/dl.acm.org\/doi\/10.5555\/1287369.1287385","DOI":"10.1016\/B978-155860869-6\/50023-8"},{"key":"13_CR12","doi-asserted-by":"crossref","unstructured":"Ishibuchi, H., Imada, R., Setoguchi, Y., Nojima, Y.: Performance comparison of NSGA-II and NSGA-III on various many-objective test problems. In: 2016 IEEE Congress on Evolutionary Computation (CEC), pp. 3045\u20133052. IEEE (2016). https:\/\/doi.org\/10.1109\/CEC.2016.7744174","DOI":"10.1109\/CEC.2016.7744174"},{"key":"13_CR13","doi-asserted-by":"crossref","unstructured":"Kolev, B., Bondiombouy, C., Vakluriez, P., Jimenez-Peris, R., Pau, R., Pereira, J.: The CloudMdsQL Multistore System. In: Proceedings of the 2016 International Conference on Management of Data (SIGMOD 2016), pp. 2113\u20132116. ACM (2016). https:\/\/doi.org\/10.1145\/2882903.2899400","DOI":"10.1145\/2882903.2899400"},{"key":"13_CR14","doi-asserted-by":"crossref","unstructured":"Le, T.-D., Kantere, V., d\u2019Orazio, L.: An efficient multi-objective genetic algorithm for cloud computing: NSGA-G. In: 2018 IEEE International Conference on Big Data (Big Data), Seattle, WA, USA, 2018, pp. 3883\u20133888 (2018). https:\/\/doi.org\/10.1109\/BigData.2018.8622148","DOI":"10.1109\/BigData.2018.8622148"},{"key":"13_CR15","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1007\/978-3-662-62386-2_2","volume-title":"Transactions on Large-Scale Data- and Knowledge-Centered Systems XLVI","author":"T-D Le","year":"2020","unstructured":"Le, T.-D., Kantere, V., d\u2019Orazio, L.: Dynamic estimation and grid partitioning approach for multi-objective optimization problems in medical cloud federations. In: Hameurlain, A., Tjoa, A.M. (eds.) Transactions on Large-Scale Data- and Knowledge-Centered Systems XLVI. LNCS, vol. 12410, pp. 32\u201366. Springer, Heidelberg (2020). https:\/\/doi.org\/10.1007\/978-3-662-62386-2_2"},{"key":"13_CR16","unstructured":"Le, T.-D., Kantere, V., d\u2019Orazio, L.: Optimizing DICOM data management with NSGA-G. In: Proceedings of the 2019 International Workshop on Data Warehouse Design and OLAP (DOLAP) (2019)"},{"key":"13_CR17","doi-asserted-by":"crossref","unstructured":"Misegiannis, M.G., Kantere, V., d\u2019Orazio, L.: Multi-objective query optimization in Spark SQL. In: Proceedings of the 26th International Database Engineering & Applications Symposium (IDEAS), pp. 70\u201374 (2022). https:\/\/doi.org\/10.1145\/3548785.3548800","DOI":"10.1145\/3548785.3548800"},{"key":"13_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1007\/978-3-319-57741-8_4","volume-title":"Data Management and Analytics for Medicine and Healthcare","author":"D Nguyen-Cong","year":"2017","unstructured":"Nguyen-Cong, D., d\u2019Orazio, L., Tran, N., Hacid, M.-S.: Storing and querying DICOM data with HYTORMO. In: Wang, F., Yao, L., Luo, G. (eds.) DMAH 2016. LNCS, vol. 10186, pp. 43\u201361. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-57741-8_4"},{"key":"13_CR19","unstructured":"Papakonstantinou, Y.: Polystore query rewriting: the challenges of variety. In: EDBT\/ICDT Workshops (2016)"},{"key":"13_CR20","doi-asserted-by":"crossref","unstructured":"Selinger, P.G., Astrahan, M.M., Chamberlin, D.D., Lorie, R.A., Price, T.G.: Access path selection in a relational database management system. In: Proceedings of the 1979 ACM SIGMOD International Conference on Management of Data (SIGMOD 1979), pp. 23\u201334. ACM (1979). https:\/\/doi.org\/10.1145\/582095.582099","DOI":"10.1145\/582095.582099"},{"key":"13_CR21","doi-asserted-by":"crossref","unstructured":"Song, F., et al.: Spark-based cloud data analytics using multi-objective optimization. In: IEEE 37th International Conference on Data Engineering (ICDE), Chania, Greece, 2021, pp. 396\u2013407 (2021). https:\/\/doi.org\/10.1109\/ICDE51399.2021.00041","DOI":"10.1109\/ICDE51399.2021.00041"},{"key":"13_CR22","unstructured":"Soong, T.T.: Fundamentals of Probability and Statistics for Engineers. Wiley (2004)"},{"key":"13_CR23","unstructured":"Veldhuizen, D.A.V., Lamont, G.B.: Evolutionary computation and convergence to a pareto front. In: Late Breaking Papers at the Genetic Programming 1998 Conference, pp. 221\u2013228 (1998)"},{"key":"13_CR24","unstructured":"Veldhuizen, D.A.V.: Multiobjective evolutionary algorithms: classifications, analyses, and new innovations. Ph.D. thesis, Air Force Institute of Technology (1999)"},{"key":"13_CR25","doi-asserted-by":"crossref","unstructured":"Zhang, Q., Li, H.: MOEA\/D: a multiobjective evolutionary algorithm based on decomposition. IEEE Trans. Evol. Comput. 11(6), 712\u2013731 (2007). https:\/\/doi.org\/10.1109\/TEVC.2007.892759","DOI":"10.1109\/TEVC.2007.892759"},{"key":"13_CR26","doi-asserted-by":"crossref","unstructured":"Zitzler, E., Thiele, L., Laumanns, M., Fonseca, C.M., da Fonseca, V.G.: Performance assessment of multiobjective optimizers: an analysis and review. IEEE Trans. Evol. Comput. 7(2), 117\u2013132 (2003). https:\/\/doi.org\/10.1109\/TEVC.2003.810758","DOI":"10.1109\/TEVC.2003.810758"}],"container-title":["Lecture Notes in Computer Science","Computational Science and Its Applications \u2013 ICCSA 2025"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-97000-9_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,28]],"date-time":"2025-06-28T06:52:08Z","timestamp":1751093528000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-97000-9_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031969997","9783031970009"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-97000-9_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"29 June 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICCSA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Science and Its Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Istanbul","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"T\u00fcrkiye","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 June 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iccsa2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iccsa.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}