1,310
Views
46
CrossRef citations to date
0
Altmetric
Original Articles

A spatiotemporal indexing approach for efficient processing of big array-based climate data with MapReduce

, , , , , & show all
Pages 17-35 | Received 05 Jul 2015, Accepted 10 Nov 2015, Published online: 12 Jan 2016

References

  • Berrick, S.W., Shen, S.S. and Ostrenga, D., 2008. Modern era retrospective-analysis for research and applications (MERRA) data and services at the GES DISC. In: AGU fall meeting abstracts, 15–19 December, San Francisco, CA. Vol. 1, 0225.
  • Bloom, S., et al., 2005. Documentation and validation of the Goddard Earth Observing System (GEOS) data assimilation system - version 4. Technical Report Series on Global Modeling and Data Assimilation 104606, v26.
  • Buck, J.B., et al., 2011. Scihadoop: array-based query processing in hadoop. In: Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis. ACM, 66.
  • Chandola, V., Banerjee, A. and Kumar, V., 2009. Anomaly detection: a survey. ACM Computing Surveys (CSUR), 41 (3), 15.
  • Das, M. and Parthasarathy, S., 2009. Anomaly detection and spatio-temporal analysis of global climate system. In: Proceedings of the third international workshop on knowledge discovery from sensor data, 28 June–1 July, Paris. New York: ACM, 142–150.
  • Dean, J. and Ghemawat, S., 2008. MapReduce: simplified data processing on large clusters. Communications of the ACM, 51 (1), 107–113. doi:10.1145/1327452
  • Duffy, D.Q., et al., 2012. Preliminary evaluation of MapReduce for high-performance climate data analysis [online]. NASA new technology report white paper. Available from: http://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20120009187.pdf [Accessed 5 January 2016].
  • Edwards, P.N., 2010. A vast machine: Computer models, climate data, and the politics of global warming. Cambridge, MA: MIT Press, 518.
  • Eldawy, A., et al., 2015. SHAHED: a MapReduce-based system for querying and visualizing spatio-temporal satellite data. In: IEEE 31st international conference on data engineering, 13–17 April, Seoul. doi:10.1109/icde.2015.7113427
  • Eldawy, A. and Mokbel, M.F., 2013. A demonstration of spatialhadoop: an efficient mapreduce framework for spatial data. Proceedings of the VLDB Endowment, 6 (12), 1230–1233. doi:10.14778/2536274
  • Finkel, R.A. and Bentley, J.L., 1974. Quad trees a data structure for retrieval on composite keys. Acta Informatica, 4 (1), 1–9. doi:10.1007/BF00288933
  • Geng, Y., et al., 2013. SciHive: array-based query processing with HiveQL. In: 12th IEEE international conference on Trust, security and privacy in computing and communications (TrustCom), 16–18 July, Melbourne. IEEE.
  • Geng, Y., Huang, X., and Yang, G., 2014. Adaptive indexing for distributed array processing. Adaptive indexing for distributed array processing. In: IEEE international congress on big data (BigData Congress), 27 June–2 July, Anchorage. IEEE.
  • Guttman, A., 1984. R-trees: a dynamic index structure for spatial searching. In: Proceedings of the 1984 ACM SIGMOD international conference on management of data. New York: ACM, 47–57.
  • Li, Z., et al., 2013. A high performance web-based system for analyzing and visualizing spatiotemporal data for climate studies. In: S. Liang, X. Wang, and C. Claramunt, eds. W2GIS. lecture notes in computer science, Vol. 7820. Berlin: Springer, 190–198.
  • Li, Z., et al., 2015. Enabling big geoscience data analytics with a cloud-based, MapReduce-enabled and service-oriented workflow framework. Plos One, 10 (3), e0116781. doi:10.1371/journal.pone.0116781
  • Malik, T., 2013. GeoBase: indexing NetCDF files for large-scale data analysis. In: W.C. Hu, ed. Big data management, technologies, and applications. Hershey, PA: IGI Global, 295–313.
  • Mayer-Schönberger, V. and Cukier, K., 2013. Big data: a revolution that will transform how we live, work, and think. Boston, MA: Houghton Mifflin Harcourt.
  • Overpeck, J.T., et al., 2011. Climate data challenges in the 21 st century. Science(Washington), 331 (6018), 700–702. doi:10.1126/science.1197869
  • Rienecker, M.M., et al., 2011. MERRA: NASA’s modern-era retrospective analysis for research and applications. Journal of Climate, 24 (14), 3624–3648. doi:10.1175/JCLI-D-11-00015.1
  • Schnase, J.L., et al., 2014. MERRA analytic services: meeting the big data challenges of climate science through cloud-enabled climate analytics-as-a-service. Computers, Environment and Urban Systems. doi:10.1016/j.compenvurbsys.2013.12.003
  • Skytland, N., 2012. Big data: what is NASA doing with big data today? Open.Gov open access article. Available from: http://open.nasa.gov/blog/2012/10/04/what-is-nasa-doing-with-big-data-today/ [Accessed 15 March 2015].
  • Sun, M., et al., 2012. A web-based geovisual analytical system for climate studies. Future Internet, 4 (4), 1069–1085. doi:10.3390/fi4041069
  • White, T., 2009. Hadoop: the definitive guide: the definitive guide. Sebastopol, CA: O’Reilly Media, Inc.
  • Wu, K., et al., 2009. FastBit: interactively searching massive data. Journal of Physics: Conference Series, 180 (1), 012053.
  • Yang, C., et al., 2011. Using spatial principles to optimize distributed computing for enabling the physical science discoveries. Proceedings of the National Academy of Sciences, 108 (14), 5498–5503. doi:10.1073/pnas.0909315108
  • Zhao, H., et al., 2010. Parallel accessing massive NetCDF data based on mapreduce. In: F. Wang, ed. Web information systems and mining. Berlin: Springer, 425–431.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.