| Title: | Big data architecture, design and evolution using ARES and DrMUST |
| Authors: | Stanley James Kaethler, Author |
| Material Type: | ISU internship report |
| Publisher: | Illkirch-Graffenstaden (France) : International Space University, 2016 |
| Size: | 1 electronic resource (57 p.) / col. ill. |
| Bibliography note: | Includes bibliographical references |
| Languages: | English |
| Description: | This study focusses on how to leverage ESOC’s existing big data cluster, ARES, which is currently primarily used as a long term data storage archive, as a high‐performance data analysis engine using the latest big data technologies. The study shows how big data technologies can enable high speed telemetry data analysis, faster anomaly investigations, scalable long‐term data archiving, better use of computing resources, reduced‐cost hardware, and increased speed of development through rapid prototyping and deployment. |
| ISU program : | Master of Space Studies |
| Permalink: | https://isulibrary.isunet.edu/index.php?lvl=notice_display&id=9925 |
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 Kaethler, Stanley James_INT report (1.44MB) Adobe Acrobat PDF |
