Repository files navigation

FastR is a high-performance implementation of the R programming language, built on GraalVM.

FastR aims to be:

• efficient: executing R language scripts faster than any other R runtime and as fast asRcpp
• polyglot: allowing fastpolyglot interoperability with other languages in the GraalVM ecosystem.
• compatible: with the reference R implementation including theR extensions C API
• embeddable: allowing integration using the R embedding API or the GraalVM polyglot embedding SDK for Java

The screenshot below shows Java application with embedded FastR engine.The plot below was generated byggplot2 running on FastR and it shows peak performance of theraytracing example.The measurements werereproduced independently.

See the documentation on the GraalVM website on how toget GraalVM andinstall and use FastR.

$JAVA_HOME/bin/RType 'q()' to quit R.> print("Hello R!")[1] "Hello R!">

The goal of FastR is to be a drop-in replacement for GNU-R, the reference implementation of the R language,including theR extensions C API.FastR faithfully implements the R language, and any difference in behavior is considered to be a bug.

FastR can currently install and run basic examples of many of the popular R packages, such asggplot2,jsonlite,testthat,assertthat,dplyr,knitr,Shiny,Rcpp,quantmod, and more.However, one should take into accountthe experimental state of FastR, there can be packages that are not compatible yet, and if you try FastR on a complex R application, it can stumble on those.If this happens, please submit an issue on GitHub.

To provide better stability, FastR uses by default afixed snapshot of CRAN (viaMRAN).Functioninstall.packages therefore does not install the latest versions.This can be overridden by passingrepos argument toinstall.packages pointing to CRAN.

FastR provides its own replacements forrJava anddata.table packages, which can be installed withinstall.fastr.packages(c("rJava", "data.table")).

Packages that use theR extensions C API in hot paths, especially viaRcpp,may exhibit slower performance on FastR due to the high cost of transitions between the native and managed code.This can be mitigated by using theGraalVm LLVM runtime.Preview of the support is available via the--R.BackEnd=llvm option.Note that most of the times FastR running R code equivalent to givenRcpp code is asfast as GNU-R/Rcpp and sometimes even faster because of the advanced optimizations of the Graal dynamic compiler.

FastR reference documentation which explains its advantages, its current limitations, compatibility, and additional functionality is available on theGraalVM website.

Further documentation, including contributor and developer-oriented information, is in thedocumentation folder of this repository.

Seegraalvm.org/community on how to stay connected with the development community.The discussion onSlack is a good way to get in touch with us.

We would like to grow the FastR open-source community to provide a free R implementation atop the Truffle/Graal stack.We encourage contributions, and invite interested developers to join in.Prospective contributors need to sign theOracle Contributor Agreement (OCA).The access point for contributions, issues and questions about FastR is theGitHub repository.

FastR is developed by Oracle Labs and is based onthe GNU-R runtime.It contains contributions by researchers at Purdue University (purdue-fastr), Northeastern University, JKU Linz, TU Dortmund and TU Berlin.

This project welcomes contributions from the community. Before submitting a pull request, pleasereview our contribution guide

Please consult thesecurity guide for our responsible security vulnerability disclosure process

FastR is available under a GPLv3 license.