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https://github.com/oracle/fastr

A high-performance implementation of the R programming language, built on GraalVM.
https://github.com/oracle/fastr

graalvm r r-language

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A high-performance implementation of the R programming language, built on GraalVM.

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# FastR



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



FastR aims to be:

* [efficient](https://medium.com/graalvm/faster-r-with-fastr-4b8db0e0dceb#4ab6): executing R language scripts faster than any other R runtime and as fast as `Rcpp`

* [polyglot](https://medium.com/graalvm/faster-r-with-fastr-4b8db0e0dceb#0f5c): allowing fast [polyglot interoperability](https://www.graalvm.org/22.3/reference-manual/embed-languages/) with other languages in the GraalVM ecosystem.

* [compatible](https://medium.com/graalvm/faster-r-with-fastr-4b8db0e0dceb#fff5): with the reference R implementation including the [R extensions C API](https://cran.r-project.org/doc/manuals/r-release/R-exts.html)

* [embeddable](https://github.com/graalvm/examples/tree/master/r_java_embedding): 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 by `ggplot2` running on FastR and it shows peak performance of the [raytracing example](http://www.tylermw.com/throwing-shade/).

The measurements were [reproduced independently](https://web.archive.org/web/20181017111641/https://nextjournal.com/sdanisch/fastr-benchmark).



![Java embedding](documentation/assets/javaui.png)

![Speedup](documentation/assets/speedup.png)



 ## Getting Started



See the documentation on the GraalVM website on how to [get GraalVM](https://www.graalvm.org/22.3/docs/getting-started/) and [install and use FastR](https://www.graalvm.org/22.3/reference-manual/r/).



```

$JAVA_HOME/bin/R

Type 'q()' to quit R.

> print("Hello R!")

[1] "Hello R!"

>

```



## Current Status



The goal of FastR is to be a drop-in replacement for GNU-R, the reference implementation of the R language,

including the [R extensions C API](https://cran.r-project.org/doc/manuals/r-release/R-exts.html).

FastR faithfully implements the R language, and any difference in behavior is considered to be a bug.



### CRAN Packages



FastR can currently install and run basic examples of many of the popular R packages, such as `ggplot2`, `jsonlite`, `testthat`, `assertthat`, `dplyr`, `knitr`, `Shiny`, `Rcpp`, `quantmod`, and more. 

However, one should take into account **the 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 a [fixed snapshot](https://github.com/oracle/fastr/blob/master/com.oracle.truffle.r.native/Makefile#L37) of CRAN (via [MRAN](https://mran.microsoft.com/)). 

Function `install.packages` therefore does not install the latest versions. 

This can be overridden by passing `repos` argument to `install.packages` pointing to CRAN.



FastR provides its own replacements for `rJava` and `data.table` packages, which can be installed with `install.fastr.packages(c("rJava", "data.table"))`.



### Native Extensions Performance



Packages that use the [R extensions C API](https://cran.r-project.org/doc/manuals/r-release/R-exts.html) in hot paths, especially via `Rcpp`, **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 the [GraalVm LLVM runtime](https://www.graalvm.org/22.3/reference-manual/llvm/). 

Preview of the support is available via the `--R.BackEnd=llvm` option.

Note that most of the times FastR running R code equivalent to given `Rcpp` code is as

fast as GNU-R/Rcpp and sometimes even faster because of the advanced optimizations of the Graal dynamic compiler.



## Documentation



FastR reference documentation which explains its advantages, its current limitations, compatibility, and additional functionality is available on the [GraalVM website](https://www.graalvm.org/22.3/reference-manual/r/).



Further documentation, including contributor and developer-oriented information, is in the [documentation folder](documentation/Index.md) of this repository.



## Stay Connected with the Community



See [graalvm.org/community](https://www.graalvm.org/community/) on how to stay connected with the development community.

The discussion on [Slack](https://www.graalvm.org/slack-invitation/) 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 the [Oracle Contributor Agreement (OCA)](https://oca.opensource.oracle.com/).

The access point for contributions, issues and questions about FastR is the [GitHub repository](https://github.com/oracle/fastr).



## Authors



FastR is developed by Oracle Labs and is based on [the GNU-R runtime](http://www.r-project.org/).

It contains contributions by researchers at Purdue University ([purdue-fastr](https://github.com/allr/purdue-fastr)), Northeastern University, JKU Linz, TU Dortmund and TU Berlin.  



## License



FastR is available under a GPLv3 license.