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UID:submissions.supercomputing.org_SC23_sess454_ws_eduhpca106@linklings.co
 m
SUMMARY:Program Your Favorite Data Science Pipeline in Spark
DESCRIPTION:H. Martin Bücker, Marieke Plesske, Johannes Schoder, and Wolf 
 Weber (Friedrich Schiller University Jena, Germany)\n\nDesigned for the ma
 ster's degree program in "Computational and Data Science," the Faculty of 
 Mathematics and Computer Science at Friedrich Schiller University Jena, Ge
 rmany, offers a course that introduces students to distributed processing 
 on massive datasets. Within that course, there is a three-week programming
  project where students learn to design, construct, and improve data analy
 sis and machine learning pipelines using Hadoop, MapReduce, and Spark on t
 he university’s central compute cluster. This short note sketches the main
  idea of the programming project, gives an example of a project instance, 
 and reports on classroom experiences.\n\nTag: Education, Heterogeneous Com
 puting, Reproducibility, State of the Practice, Sustainability\n\nRegistra
 tion Category: Workshop Reg Pass\n\nSession Chairs: David P. Bunde (Knox C
 ollege); Sushil K. Prasad (University of Texas at San Antonio); Satish Pur
 i (Missouri University of Science and Technology); Apan Qasem (Texas State
  University); and George K. Thiruvathukal (Loyola University, Chicago; Arg
 onne National Laboratory (ANL))\n\n
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