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RProtoBuf: Efficient Cross-Language Data Serialization in R

Author

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  • Eddelbuettel, Dirk
  • Stokely, Murray
  • Ooms, Jeroen

Abstract

Modern data collection and analysis pipelines often involve a sophisticated mix of applications written in general purpose and specialized programming languages. Many formats commonly used to import and export data between different programs or systems, such as CSV or JSON, are verbose, inefficient, not type-safe, or tied to a specific programming language. Protocol Buffers are a popular method of serializing structured data between applications - while remaining independent of programming languages or operating systems. They offer a unique combination of features, performance, and maturity that seems particularly well suited for data-driven applications and numerical computing. The RProtoBuf package provides a complete interface to Protocol Buffers from the R environment for statistical computing. This paper outlines the general class of data serialization requirements for statistical computing, describes the implementation of the RProtoBuf package, and illustrates its use with example applications in large-scale data collection pipelines and web services.

Suggested Citation

  • Eddelbuettel, Dirk & Stokely, Murray & Ooms, Jeroen, 2016. "RProtoBuf: Efficient Cross-Language Data Serialization in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 71(i02).
    • Handle: RePEc:jss:jstsof:v:071:i02
    DOI: http://hdl.handle.net/10.18637/jss.v071.i02
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    Cited by:

    1. Narasimhan, Balasubramanian & Rubin, Daniel L. & Gross, Samuel M. & Bendersky, Marina & Lavori, Philip W., 2017. "Software for Distributed Computation on Medical Databases: A Demonstration Project," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 77(i13).
    2. Amogh Shukla & Tapan Kumar Das & Sanjiban Sekhar Roy, 2023. "TRX Cryptocurrency Profit and Transaction Success Rate Prediction Using Whale Optimization-Based Ensemble Learning Framework," Mathematics, MDPI, vol. 11(11), pages 1-27, May.

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