Development of Application to Deal with Large Data Using Hadoop for 3D Printer


KIPS Transactions on Software and Data Engineering, Vol. 9, No. 1, pp. 11-16, Jan. 2020
https://doi.org/10.3745/KTSDE.2020.9.1.11, Full Text:
Keywords: Large Data Processing, 3D Printing, G-code, Hadoop, facet
Abstract

3D printing is one of the emerging technologies and getting a lot of attention. To do 3D printing, 3D model is first generated, and then converted to G-code which is 3D printer’s operations. Facet, which is a small triangle, represents a small surface of 3D model. Depending on the height or precision of the 3D model, the number of facets becomes very large and so the conversion time from 3D model to G-code takes longer. Apach Hadoop is a software framework to support distributed processing for large data set and its application range gets widening. In this paper, Hadoop is used to do the conversion works time-efficient way. 2-phase distributed algorithm is developed first. In the algorithm, all facets are sorted according to its lowest Z-value, divided into N parts, and converted on several nodes independently. The algorithm is implemented in four steps; preprocessing – Map – Shuffling - Reduce of Hadoop. Finally, to show the performance evaluation, Hadoop systems are set up and converts testing 3D model while changing the height or precision.


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Cite this article
[IEEE Style]
K. E. Lee and S. Kim, "Development of Application to Deal with Large Data Using Hadoop for 3D Printer," KIPS Transactions on Software and Data Engineering, vol. 9, no. 1, pp. 11-16, 2020. DOI: https://doi.org/10.3745/KTSDE.2020.9.1.11.

[ACM Style]
Kang Eun Lee and Sungsuk Kim. 2020. Development of Application to Deal with Large Data Using Hadoop for 3D Printer. KIPS Transactions on Software and Data Engineering, 9, 1, (2020), 11-16. DOI: https://doi.org/10.3745/KTSDE.2020.9.1.11.