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Verlagsausgabe
DOI: 10.5445/IR/1000081164
Originalveröffentlichung
DOI: 10.1186/s40537-018-0119-6

Concept and benchmark results for Big Data energy forecasting based on Apache Spark

González Ordiano, Jorge Ángel; Bartschat, Andreas; Ludwig, Nicole; Braun, Eric; Waczowicz, Simon; Renkamp, Nicolas; Peter, Nico; Düpmeier, Clemens; Mikut, Ralf; Hagenmeyer, Veit

Abstract:
The present article describes a concept for the creation and application of energy forecasting models in a distributed environment. Additionally, a benchmark comparing the time required for the training and application of data-driven forecasting models on a single computer and a computing cluster is presented. This comparison is based on a simulated dataset and both R and Apache Spark are used. Furthermore, the obtained results show certain points in which the utilization of distributed computing based on Spark may be advantageous.


Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Publikationstyp Zeitschriftenaufsatz
Jahr 2018
Sprache Englisch
Identifikator ISSN: 2196-1115
URN: urn:nbn:de:swb:90-811640
KITopen ID: 1000081164
HGF-Programm 37.98.11; LK 01
Erschienen in Journal of Big Data
Band 5
Heft 1
Seiten Art.Nr. 11
Vorab online veröffentlicht am 06.03.2018
Schlagworte Big Data, Forecasting, Energy, Data-driven, EnergyLab 2.0
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