{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T19:39:00Z","timestamp":1772825940934,"version":"3.50.1"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2019,2,21]],"date-time":"2019-02-21T00:00:00Z","timestamp":1550707200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Distrib Parallel Databases"],"published-print":{"date-parts":[[2020,3]]},"DOI":"10.1007\/s10619-019-07260-3","type":"journal-article","created":{"date-parts":[[2019,2,21]],"date-time":"2019-02-21T07:23:07Z","timestamp":1550733787000},"page":"63-100","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Parallel computation of PDFs on big spatial data using Spark"],"prefix":"10.1007","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9421-4100","authenticated-orcid":false,"given":"Ji","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Noel Moreno","family":"Lemus","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Esther","family":"Pacitti","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fabio","family":"Porto","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patrick","family":"Valduriez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,2,21]]},"reference":[{"key":"7260_CR1","doi-asserted-by":"crossref","unstructured":"Campisano, R., Porto, F., Pacitti, E., Masseglia, F., Ogasawara, E.S.: Spatial sequential pattern mining for seismic data. In: Simp\u00f3sio Brasileiro de Banco de Dados (SBBD), pp. 241\u2013246 (2016)","DOI":"10.5753\/sbbd.2016.24335"},{"issue":"4","key":"7260_CR2","doi-asserted-by":"publisher","first-page":"673","DOI":"10.1109\/SURV.2011.060710.00066","volume":"13","author":"F Wang","year":"2011","unstructured":"Wang, F., Liu, J.: Networked wireless sensor data collection: issues, challenges, and approaches. IEEE Commun. Surv. Tutor. 13(4), 673\u2013687 (2011)","journal-title":"IEEE Commun. Surv. Tutor."},{"issue":"2","key":"7260_CR3","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1007\/s11036-013-0489-0","volume":"19","author":"M Chen","year":"2014","unstructured":"Chen, M., Mao, S., Liu, Y.: Big data: a survey. Mob. Netw. Appl. 19(2), 171\u2013209 (2014)","journal-title":"Mob. Netw. Appl."},{"issue":"5","key":"7260_CR4","doi-asserted-by":"publisher","first-page":"2136","DOI":"10.1109\/36.789610","volume":"37","author":"TJ Jackson","year":"1999","unstructured":"Jackson, T.J., Vine, D.M.L., Hsu, A.Y., Oldak, A., Starks, P.J., Swift, C.T., Isham, J.D., Haken, M.: Soil moisture mapping at regional scales using microwave radiometry: the southern great plains hydrology experiment. IEEE Trans. Geosci. Remote Sens. 37(5), 2136\u20132151 (1999)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"7260_CR5","volume-title":"Statistics for Spatial Data","author":"N Cressie","year":"2015","unstructured":"Cressie, N.: Statistics for Spatial Data. Wiley, Hoboken (2015)"},{"key":"7260_CR6","volume-title":"Quantitative Geography: Perspectives on Spatial Data Analysis","author":"S Fotheringham","year":"2000","unstructured":"Fotheringham, S., Brunsdon, C., Charlton, M.: Quantitative Geography: Perspectives on Spatial Data Analysis. SAGE, London (2000)"},{"issue":"1","key":"7260_CR7","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1016\/S0167-8809(00)00169-9","volume":"81","author":"C Michele","year":"2000","unstructured":"Michele, C., Stefano, T., Andrea, S.: Sensitivity and uncertainty analysis in spatial modelling based on GIS. Agric. Ecosyst. Environ. 81(1), 71\u201379 (2000)","journal-title":"Agric. Ecosyst. Environ."},{"key":"7260_CR8","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1007\/978-1-4614-1629-6_3","volume-title":"Computing with Spatial Trajectories","author":"Goce Trajcevski","year":"2011","unstructured":"Trajcevski, G.: Uncertainty in spatial trajectories. In: Computing with Spatial Trajectories, pp. 63\u2013107 (2011)"},{"key":"7260_CR9","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/j.jcp.2015.03.071","volume":"295","author":"F Kathryn","year":"2015","unstructured":"Kathryn, F., Oden, J.T., Faghihi, D.: A bayesian framework for adaptive selection, calibration, and validation of coarse-grained models of atomistic systems. J. Comput. Phys. 295, 189\u2013208 (2015)","journal-title":"J. Comput. Phys."},{"key":"7260_CR10","unstructured":"Hpc geophysical simulation test suite. https:\/\/hpc4e.eu\/downloads\/hpc-geophysical-simulation-test-suite"},{"key":"7260_CR11","doi-asserted-by":"crossref","unstructured":"Marelli, S., Sudret, B.: UQLab: A Framework for Uncertainty Quantification in MATLAB. ETH-Z\u00fcrich (2014)","DOI":"10.1061\/9780784413609.257"},{"key":"7260_CR12","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1007\/978-3-642-29737-3_44","volume-title":"Euro-Par 2011: Parallel Processing Workshops","author":"Ernesto E. Prudencio","year":"2012","unstructured":"Prudencio, E.E., Schulz, K.W.: The parallel C++ statistical library \u2019QUESO\u2019: Quantification of uncertainty for estimation, simulation and optimization. In: Euro-Par: Parallel Processing Workshops, pp. 398\u2013407 (2011)"},{"issue":"3","key":"7260_CR13","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1016\/j.bdr.2015.04.001","volume":"2","author":"OY Al-Jarrah","year":"2015","unstructured":"Al-Jarrah, O.Y., Yoo, P.D., Muhaidat, S., Karagiannidis, G.K., Taha, K.: Efficient machine learning for big data: a review. Big Data Res. 2(3), 87\u201393 (2015)","journal-title":"Big Data Res."},{"key":"7260_CR14","doi-asserted-by":"crossref","unstructured":"Condie, T., Mineiro, P., Polyzotis, N., Weimer, M.: Machine learning on big data. In: 29th IEEE International Conference on Data Engineering, ICDE, pp. 1242\u20131244 (2013)","DOI":"10.1109\/ICDE.2013.6544913"},{"issue":"4","key":"7260_CR15","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1145\/2627534.2627557","volume":"41","author":"S Suthaharan","year":"2014","unstructured":"Suthaharan, S.: Big data classification: problems and challenges in network intrusion prediction with machine learning. ACM SIGMETRICS Perform. Eval. Rev. 41(4), 70\u201373 (2014)","journal-title":"ACM SIGMETRICS Perform. Eval. Rev."},{"issue":"5786","key":"7260_CR16","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1126\/science.1127647","volume":"313","author":"GE Hinton","year":"2006","unstructured":"Hinton, G.E., Salakhutdinov, R.R.: Reducing the dimensionality of data with neural networks. Science 313(5786), 504\u2013507 (2006)","journal-title":"Science"},{"key":"7260_CR17","doi-asserted-by":"publisher","first-page":"621","DOI":"10.1016\/j.procs.2013.05.226","volume":"18","author":"Bastian Bohn","year":"2013","unstructured":"Bohn, B., Garcke, J., Iza-Teran, R., Paprotny, A., Peherstorfer, B., Schepsmeier, U., Thole, C.: Analysis of car crash simulation data with nonlinear machine learning methods. In: International of the Conference on Computational Science ICCS, pp. 621\u2013630 (2013)","journal-title":"Procedia Computer Science"},{"key":"7260_CR18","doi-asserted-by":"crossref","unstructured":"Gheisari, M., Wang, G., Bhuiyan,M.Z.A.: A survey on deep learning in big data. In: IEEE International of the Conference on Computational Science and Engineering, CSE, and IEEE International of the Conference on Embedded and Ubiquitous Computing, EUC, pp. 173\u2013180 (2017)","DOI":"10.1109\/CSE-EUC.2017.215"},{"key":"7260_CR19","unstructured":"Zaharia, M., Chowdhury, M., Franklin, M.\u00a0J., Shenker, S., Stoica, I.: Spark: cluster computing with working sets. In: USENIX Workshop on Hot Topics in Cloud Computing (HotCloud). (2010)"},{"issue":"2","key":"7260_CR20","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1504\/IJCC.2018.093765","volume":"7","author":"Ji Liu","year":"2018","unstructured":"Liu, J., Pacitti, E., Valduriez, P.: A survey of scheduling frameworks in big data systems. In: International Journal of Cloud Computing, pp. 27 (2018)","journal-title":"International Journal of Cloud Computing"},{"key":"7260_CR21","unstructured":"Chalabi, Y., W\u00fcrtz, D.: Flexible distribution modeling with the generalized lambda distribution. (2012)"},{"key":"7260_CR22","doi-asserted-by":"publisher","DOI":"10.1201\/9781420038040","volume-title":"Fitting Statistical Distributions: The Generalized Lambda Distribution and Generalized Bootstrap Methods","author":"EDZ Karian","year":"2000","unstructured":"Karian, E.D.Z.: Fitting Statistical Distributions: The Generalized Lambda Distribution and Generalized Bootstrap Methods. Chapman and Hall\/CRC, London (2000)"},{"key":"7260_CR23","unstructured":"Coile, R.V., Balomenos, G., Pandey, M., Caspeele, R., Criel, P., Wang, L., Alfred, S.: Computationally efficient estimation of the probability density function for the load bearing capacity of concrete columns exposed to fire. In: International Symposium of the International Association for Life-Cycle Civil Engineering (IALCCE), pp. 8 (2016)"},{"issue":"1","key":"7260_CR24","first-page":"1","volume":"78","author":"JR Val del","year":"2017","unstructured":"del Val, J.R., Simmross-Wattenberg, F., Alberola-L\u00f3pez, C.: libstable: fast, parallel, and high-precision computation of $$\\alpha $$ \u03b1 -stable distributions in R, C\/C++, and matlab. J. Stat. Softw. 78(1), 1\u201325 (2017)","journal-title":"J. Stat. Softw."},{"issue":"1","key":"7260_CR25","doi-asserted-by":"publisher","first-page":"330","DOI":"10.1016\/j.physa.2016.07.016","volume":"463","author":"LV Ballestra","year":"2016","unstructured":"Ballestra, L.V., Pacellib, G., Radi, D.: A very efficient approach to compute the first-passage probability density function in a time-changed brownian model: applications in finance. Phys. A 463(1), 330\u2013344 (2016)","journal-title":"Phys. A"},{"key":"7260_CR26","doi-asserted-by":"publisher","first-page":"308","DOI":"10.1093\/comjnl\/7.4.308","volume":"7","author":"JA Nelder","year":"1965","unstructured":"Nelder, J.A., Mead, R.: A simplex method for function minimization. Comput. J. 7, 308\u2013313 (1965)","journal-title":"Comput. J."},{"key":"7260_CR27","unstructured":"Singer, S., Singer, S.: Complexity analysis of Nelder\u2013Mead search iterations. In: Conference on Applied Mathematics and Computation, pp. 185\u2013196 (1999)"},{"key":"7260_CR28","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1007\/978-3-319-98539-8_19","volume-title":"Big Data Analytics and Knowledge Discovery","author":"Riccardo Campisano","year":"2018","unstructured":"Campisano, R., Borges, H., Porto, F., Perosi, F., Pacitti, E., Masseglia, F., Ogasawara, E.S.: Discovering tight space-time sequences. In: International of the Conference on Big Data Analytics and Knowledge Discovery, pp. 247\u2013257 (2018)"},{"issue":"2","key":"7260_CR29","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1145\/360827.360840","volume":"17","author":"J Ramberg","year":"1974","unstructured":"Ramberg, J., Schmeiser, B.W.: An approximate method for generating asymmetric random variables. Commun. ACM 17(2), 78\u201382 (1974)","journal-title":"Commun. ACM"},{"issue":"3","key":"7260_CR30","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1214\/ss\/1030037906","volume":"12","author":"J Aldrich","year":"1997","unstructured":"Aldrich, J.: RA fisher and the making of maximum likelihood 1912\u20131922. Stat. Sci. 12(3), 162\u2013176 (1997)","journal-title":"Stat. Sci."},{"key":"7260_CR31","volume-title":"Understanding Machine Learning-From Theory to Algorithms","author":"S Shalev-Shwatrz","year":"2017","unstructured":"Shalev-Shwatrz, S., Ben-David, S.: Understanding Machine Learning-From Theory to Algorithms. Cambridge University Press, Cambridge (2017)"},{"key":"7260_CR32","doi-asserted-by":"crossref","unstructured":"Kraska, T., Beutel, A., Chi, E.H., Dean, J., Polyzotis, N.: The case for learned index structures. In: International of the Conference on Management of Data (SIGMOD), pp. 489\u2013504 (2018)","DOI":"10.1145\/3183713.3196909"},{"issue":"34","key":"7260_CR33","first-page":"1","volume":"17","author":"X Meng","year":"2016","unstructured":"Meng, X., Bradley, J., Yavuz, B., Sparks, E., Venkataraman, S., Liu, D., Freeman, J., Tsai, D., Amde, M., Owen, S., Xin, D., Xin, R., Franklin, M.J., Zadeh, R., Zaharia, M., Talwalkar, A.: MLlib: machine learning in Apache Spark. J. Mach. Learn. Res. 17(34), 1\u20137 (2016)","journal-title":"J. Mach. Learn. Res."},{"issue":"3","key":"7260_CR34","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1016\/S0034-4257(97)00049-7","volume":"61","author":"M Friedl","year":"1997","unstructured":"Friedl, M., Brodley, C.: Decision tree classification of land cover from remotely sensed data. Remote Sens. Environ. 61(3), 399\u2013409 (1997)","journal-title":"Remote Sens. Environ."},{"key":"7260_CR35","unstructured":"Dean, J., Ghemawat, S.: Mapreduce: Simplified data processing on large clusters. In: Symposium on Operating System Design and Implementation (OSDI), pp. 137\u2013150 (2004)"},{"key":"7260_CR36","doi-asserted-by":"crossref","unstructured":"Shvachko, K., Kuang, H., Radia, S., Chansler, R.: The hadoop distributed file system. In: IEEE Symposium on Mass Storage Systems and Technologies (MSST), pp. 1\u201310 (2010)","DOI":"10.1109\/MSST.2010.5496972"},{"key":"7260_CR37","doi-asserted-by":"crossref","unstructured":"Ghemawat, S., Gobioff, H., Leung, S.: The google file system. In: ACM Symposium on Operating Systems Principles (SOSP), pp. 29\u201343 (2003)","DOI":"10.1145\/1165389.945450"},{"key":"7260_CR38","unstructured":"Spark MLib. https:\/\/spark.apache.org\/mllib\/"},{"issue":"1","key":"7260_CR39","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1186\/s40537-015-0032-1","volume":"2","author":"S Landset","year":"2015","unstructured":"Landset, S., Khoshgoftaar, T.M., Richter, A.N., Hasanin, T.: A survey of open source tools for machine learning with big data in the hadoop ecosystem. J. Big Data 2(1), 24 (2015)","journal-title":"J. Big Data"},{"key":"7260_CR40","unstructured":"Dixon, W.\u00a0J., Massey, F.\u00a0J.: Introduction to statistical analysis. (1968)"},{"key":"7260_CR41","doi-asserted-by":"publisher","first-page":"718","DOI":"10.1007\/978-3-642-04898-2_326","volume-title":"International Encyclopedia of Statistical Science","author":"Raul H. C. Lopes","year":"2011","unstructured":"Lopes, R.H.C.: Kolmogorov-smirnov test. In: International of the Encyclopedia of Statistical Science, pp. 718\u2013720 (2011)"},{"key":"7260_CR42","unstructured":"Sandberg, R., Goldberg, D., Kleiman, S., Walsh, D., Lyon, B.: Design and implementation of the sun network file system. In: the Summer USENIX conference, pp. 119\u2013130 (1985)"},{"key":"7260_CR43","unstructured":"Harold, E.R.: Java I\/O: Tips and Techniques for Putting I\/O to Work, pp. 131\u2013132 (2006)"},{"key":"7260_CR44","unstructured":"Snyder, P.: tmpfs: a virtual memory file system. In: European UNIX Users Group Conference, pp. 241\u2013248 (1990)"},{"issue":"3","key":"7260_CR45","doi-asserted-by":"publisher","first-page":"660","DOI":"10.1109\/21.97458","volume":"21","author":"SR Safavian","year":"1991","unstructured":"Safavian, S.R., Landgrebe, D.: A survey of decision tree classifier methodology. IEEE Trans. Syst Man Cybern. 21(3), 660\u2013674 (1991)","journal-title":"IEEE Trans. Syst Man Cybern."},{"issue":"4","key":"7260_CR46","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1080\/03081070902857563","volume":"38","author":"R Belohl\u00e1vek","year":"2009","unstructured":"Belohl\u00e1vek, R., Baets, B.D., Outrata, J., Vychodil, V.: Inducing decision trees via concept lattices. Int. J. Gen. Syst. 38(4), 455\u2013467 (2009)","journal-title":"Int. J. Gen. Syst."},{"key":"7260_CR47","unstructured":"Zadrozny, B., Elkan, C.: Obtaining calibrated probability estimates from decision trees and naive bayesian classifiers. In: International of the Conference on Machine Learning (ICML), pp. 609\u2013616 (2001)"},{"key":"7260_CR48","doi-asserted-by":"crossref","unstructured":"Marelli, S., Sudret, B.: Uqlab: A framework for uncertainty quantification in MATLAB. In: International of the Conference on Vulnerability, Risk Analysis and Management (ICVRAM), pp. 2554\u20132563 (2014)","DOI":"10.1061\/9780784413609.257"}],"container-title":["Distributed and Parallel Databases"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10619-019-07260-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10619-019-07260-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10619-019-07260-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,13]],"date-time":"2023-09-13T21:06:12Z","timestamp":1694639172000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10619-019-07260-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,2,21]]},"references-count":48,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2020,3]]}},"alternative-id":["7260"],"URL":"https:\/\/doi.org\/10.1007\/s10619-019-07260-3","relation":{},"ISSN":["0926-8782","1573-7578"],"issn-type":[{"value":"0926-8782","type":"print"},{"value":"1573-7578","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,2,21]]},"assertion":[{"value":"21 February 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}