C. Albrecht, N. Bobroff, B. Elmegreen, Marcus Freitag, H. Hamann, Ildar Khabibrakhmanov, Klein Levente, Siyuan Lu, F. Marianno, J. Schmude, X. Shao, Carlo Siebenschuh, Rui Zhang
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Pairs (Re)Loaded: System Design & Benchmarking For Scalable Geospatial Applications
In this paper we benchmark a previously introduced big data platform that enables the analysis of big data from remote sensing and other geospatial-temporal data. The platform, called IBM PAIRS Geoscope, has been developed by leveraging open source big data technologies (Hadoop/HBase) that are in principle scalable in storage and compute to hundreds of PetaBytes. Currently, PAIRS hosts multiple PetaBytes of curated and geospatial-temporally indexed data. It organizes all data with key-value combinations, performing analytics close to the data to minimize data movement.
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