fastr

That's right, we will be able to cut it down in the future. Let me explain why: 1. Enso compiler bases on GraalVM which is 400Mb (packed)[1]. 2. The package contains GraalVM implementations of Python[2], R[3], and JavaScript[4] compilers, which weight 150Mb, 70Mb, and 50Mb respectivelly. 3. The package contains OpenCV library, as Enso has built-in bindings for it, which is 200Mb. 4. The rest (approx 200Mb) are core Enso libraries and tooling. We will be able to cut it down in the future as soon as we release Enso Marketplace which would allow you to install these things on-demand. [1] https://github.com/graalvm/graalvm-ce-builds/releases/tag/vm... [2] https://github.com/oracle/graalpython [3] https://github.com/oracle/fastr/releases/tag/vm-21.1.0 [4] https://github.com/oracle/graaljs

He were are, mostly one developper in only a few years has managed to create ~the fastest R runtime thanks to the graalVM infrastructure https://github.com/oracle/fastr + it get polyglotism for free. See also graalphp: https://github.com/abertschi/graalphp/blob/master/results.md Oracle has managed to create a language framework that enable unprecedented performance and polyglotism but there are no human resources allocated to actually tuning the implementations. Without such framework imagining one developer to implement a language and expect it to outperform the reference vm made by an army of people through decades wouldn't be a realistic expectation but now anythings possible. Though it would be nice if others companies than Oracle understood the extent of this technological leap. Actually there is only one: shopify which invest in tru

I tested it out with some fairly dependency-heavy node JS projects and it worked great (albeit with a human-noticeable perf difference vs node). R projects suffer the usual R-on-JVM issues, see eg https://github.com/oracle/fastr#status-and-limitations . I could, however, use ggplot2 and dplyr, which I don't recall working the last time I tried R-on-JVM. So that's awesome. Being able to reasonably use R stuff from clojure (and other languages better for general purpose programming) is my data science dream. Though I can't say I'm sad with my current unix-y solutions.

Graal dev here. If you want to checkout all the sources/licenses of GraalVM CE. They are here: Graal: https://github.com/oracle/graal (GPLv2 with CPE) JavaScript with Node Integration: https://github.com/graalvm/graaljs (UPL - BSD license) Ruby: https://github.com/oracle/truffleruby (EPL, GPLv2, LGPL) R: https://github.com/oracle/fastr (GPLv2) Python: https://github.com/graalvm/graalpython (UPL - BSD license) LLVM/Sulong: https://github.com/graalvm/sulong

Thought this was about https://github.com/oracle/fastr

Well supposedly you'd use native data.frame's if you're using a faster R implementation. However, I would agree with you that at this point in time it's fair to assume that R is no longer a language in and of itself - it's more akin to a collection of APIs around years of optimized C++ code, somewhat separated into a few universes (bioinformatics, time series analysis with xtz, data.table aficionados and tidyverse acolytes). And thus making a faster R alternative should focus on 100% package compatibility along with speeding up native R code. Renjin, pqR [1], et. al. all seem to be compromises that work for some workflows but not all of them. The project that I'm excited for is fastR [2] - bringing R, C, C++ and FORTRAN code together into one Truffle/Graal environment would be absolutely huge for this ecosystem. However, I've tested fastR

FastR [1], an R implementation for the JVM using Truffle aims to be both fast and compatible, including C and fortran calls from R using Truffle's polyglot framework. The thing that makes this even more awesome is inter language optimization - inline your C code into your R code at runtime, which can result in zero overhead inter language calls. [1] https://github.com/graalvm/fastr

It's not easy, but it's possible. Check out FastR: https://github.com/graalvm/fastr Here's a good video about the language and this implementation: http://download.oracle.com/technetwork/java/javase/community...