RProtoBuf: Efficient Cross-Language Data Serialization in R
This work addresses data serialization bottlenecks for R users in statistical computing, though it is incremental as it adapts an existing method (Protocol Buffers) to a new environment.
The paper tackles the problem of inefficient and language-dependent data serialization in statistical computing by introducing RProtoBuf, a package that provides a complete interface to Protocol Buffers in R, enabling efficient cross-language data exchange for applications like large-scale data pipelines and web services.
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.