R for the JVM: 60% complete, help wanted!

http://code.google.com/p/renjin/wiki/PlanOfAttack

by bedatadriven • 15 years ago

109 15 15 years ago

code.google.com

epistasis• 15 years ago

The primary reason to use R is the large number of stats packages, which are written in a mixture of C, Fortran, and R. I don't see mention of JNI anywhere, but hooking into Fortran and C seem like the most difficult but most essential piece of making this useful.

Wilduck• 15 years ago

I agree. The reason I'll drop into R instead of python is often that I need to do some complicated analysis like adaptive multivariate integration over hypercubes (http://cran.r-project.org/web/packages/cubature/index.html) or general maximum pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples (http://cran.r-project.org/web/packages/survey/index.html).

There are currently > 3500 packages in CRAN, many of which can be found nowhere else. Being able to access java libraries is great, but I an access java libraries from all sorts of different languages. Until it is seamless to install and use these CRAN packages, I'm sticking with the standard interpreter.

bedatadriven4• 15 years ago

Yeah, there are some killer packages that won't be able to run on Renjin without porting their C sources to java/R. That's a bummer.

But others -- like the survey package -- are pure R and run well on renjin. (Just do library(survey, lib.loc='/path/to/R/library') )

The central goal at this point is to support embedding packages like 'survey' in web apps or larger java apps. If you're looking for a seamless user experience for ad-hoc analysis, we're still quite a ways off!

codekiller• 15 years ago

it is mentioned that the project relies on netlib, I assume this takes care of the JNI part

Nrsolis• 15 years ago

What about Incanter? It seems like a perfect opportunity to gather two languages trying to do the same thing into a single JVM-focused project.

S4M• 15 years ago

Incanter is quite nice and I really like Clojure (disclaimer: I am still a beginner), but it has far less libraries than R. I also think the creators of R did a really good job in making seamless the installation of a package (install.packages(...)) and having lots of functions pretty well documented, so a statistician who is not a programmer can easily do his work and quickly come up with results. AFAIK this is still unmatched anywhere else.

_delirium• 15 years ago

Perhaps as importantly, R has significant buy-in in the statistics community, so a paper on a new technique will often be accompanied by an R package implementing it; in fact several journals explicitly prefer R packages for accompanying code, because the reviewers are likely to be familiar with how to use it. That's partly due to its semi-continuity with Bell Labs S (http://en.wikipedia.org/wiki/S_(programming_language)), I believe, which was a language designed by-statisticians-for-statisticians. It's fairly hard to replicate that; would require considerable effort to migrate the whole community to a new consensus environment.

zeratul• 15 years ago

bedatadriven: R native code is usually slow and always memory hungry. Nonetheless, running R on Google AppEngine is very tempting. Could you give us some idea how the memory usage looks like using Renjin when compared to any other R distribution? Here is example how to measure memory:

http://heuristically.wordpress.com/2010/01/04/r-memory-usage...

bedatadriven4• 15 years ago

Re: performance of R language code, Renjin is a bit faster there than R2.X, and should get faster the more we get into byte code. (Though renjin is currently slower in other areas like giant matrix manipulation)

As for memory usage, I believe object.size() will double-count your input data when it is referenced by the resulting model objects. Better to check memory.profile()

At present, Renjin benefits from the JVM's state-of-the art garbage collection, so you may see some improvements even at present, but I expect the big difference will be once we roll out non-memory-backed stores for R Vectors. Then your input data could be stored in a database and only partially loaded into memory as needed.

jacobquick• 15 years ago

I'm not looking to move things to the jvm anymore, I can't trust oracle with the future of stuff I may need to update and maintain.

bigbird• 15 years ago

Looks like a very interesting project.

Does the JVM environment have any tools that would facilitate building a better R debugger? That's one area of the R ecosystem that could use a serious upgrade IMO.

bedatadriven4• 15 years ago

Eclipse is a pretty good framework for building IDEs; there's already a set of plugins for R (StatET) that support debugging with the original interpreter.

One of the projects for 2012 is to integrate Renjin into StatET, including a line-by-line debugger. Any takers?

R for the JVM: 60% complete, help wanted!

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