Articles | Volume XLII-3/W12-2020
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-255-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-255-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
PAIRS (RE)LOADED: SYSTEM DESIGN & BENCHMARKING FOR SCALABLE GEOSPATIAL APPLICATIONS
C. M. Albrecht
IBM T.J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, 10598, NY, USA
N. Bobroff
IBM T.J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, 10598, NY, USA
B. Elmegreen
IBM T.J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, 10598, NY, USA
M. Freitag
IBM T.J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, 10598, NY, USA
H. F. Hamann
IBM T.J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, 10598, NY, USA
I. Khabibrakhmanov
IBM T.J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, 10598, NY, USA
L. Klein
IBM T.J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, 10598, NY, USA
S. Lu
IBM T.J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, 10598, NY, USA
F. Marianno
IBM T.J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, 10598, NY, USA
J. Schmude
IBM T.J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, 10598, NY, USA
X. Shao
IBM T.J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, 10598, NY, USA
C. Siebenschuh
IBM T.J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, 10598, NY, USA
R. Zhang
IBM T.J. Watson Research Center, 1101 Kitchawan Road, Yorktown Heights, 10598, NY, USA
Keywords: big data analytics, ML, AI, distributed geo-spatial data structures, Hadoop, HBase, Spark, GeoMesa, PAIRS Geoscope
Abstract. 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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How to cite. Albrecht, C. M., Bobroff, N., Elmegreen, B., Freitag, M., Hamann, H. F., Khabibrakhmanov, I., Klein, L., Lu, S., Marianno, F., Schmude, J., Shao, X., Siebenschuh, C., and Zhang, R.: PAIRS (RE)LOADED: SYSTEM DESIGN & BENCHMARKING FOR SCALABLE GEOSPATIAL APPLICATIONS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W12-2020, 255–260, https://doi.org/10.5194/isprs-archives-XLII-3-W12-2020-255-2020, 2020.