R algorithm integration with Statistical Manager

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Revision as of 09:00, 19 June 2014 by Emmanuel.blondel (Talk | contribs) (Activity Workflow)

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Hypothesis and Thesis

The SDMX Data converter is part of serie of experiments to test and assess how data managers / developers can plug easily algorithms (especially R algorithms) in the infrastructure, through the Statistical Manager tool, and respond quickly to data analysis needs while benefiting of iMarine computing resources.

The product of this experiment is a service that allows to convert a SDMX dataset, provided through a SDMX service URL, to the CSV format.

The broader scope of this experiment is:

  • to assess how a data manager / developer can plug an algorithm by their own,
  • to identify potential improvements to make the R script integration quick and easy

Outcome

TBD

Activity Workflow

  • The activity was done by familiarizing with the Statistical Manager, relying both on the documentation and a tutorial made available to facilitate the integration of algorithms.
  • A basic R script was created to test the Statistical Manager. This script allows to convert a SDMX-ML dataset to CSV.
  • In order to integrate the R script, a separate Java Maven project was created (with the aim to add further algorithm later).
  • Few exchange with the Statistical Managers developers was required for the project settings, an highlighted some few scatter in the documentation
  • The R script was integrated in the project, tested and sent to Statistical Manager team for its deployment
  • Additional exchange with the team took place, to have some clarifications on:
    • algorithms inputs (difference between a File input and remote resource - URL - input)
    • the need for data managers to indicate the eventual R package dependencies to install prior to the algorithm deployment
    • how to add the algorithm within a given category of algorithms (for display purpose)
  • The algorithm was successfully deployed and is currently operational in the development portal

Conclusion

TBD

Recommendations & future developments

TBD

Experimentation

TBD

Related links