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...dback. -- this is an observation that I wasn't considering when I wrote this mainly because I am, in fact, working with rather small data sets. BTW: There is code there, it's under the bitbucket link -- here's the direct link if you'd still like to look at it: https://bitbucket.org/CoherentLogic/jdataframe Re "for practical purposes is doesn't seem like the most efficient solution" and "So the JSON route is very roughly ~13x slower than using Java directly." I've not benchmarked this and will take a closer look at what you have today -- in fact I may include...

Hi Folks, If you need to send data from Java to R you may consider using the JDataFrame API -- which is used to convert data into JSON which then can be converted into a data frame in R. Here's the project page: https://coherentlogic.com/middleware-development/jdataframe/ and here's a partial example which demonstrates what the API looks like: String result = new JDataFrameBuilder() .addColumn("Code", new Object[] {"WV", "VA", }) .addColumn("Description", new Object[] {&qu...

> On Jan 15, 2016, at 12:35 PM, Thomas Fuller <thomas.fuller at coherentlogic.com> wrote: > > Hi Simon, > > Thanks for your feedback. -- this is an observation that I wasn't > considering when I wrote this mainly because I am, in fact, working > with rather small data sets. BTW: There is code there, it's under the > bitbucket link -- here&...

...s you may see more overhead. If you need process separation, it may be a different story - in principle it is faster to use more native serialization than JSON since parsing is the slowest part for big datasets. Cheers, Simon > On Jan 14, 2016, at 4:52 PM, Thomas Fuller <thomas.fuller at coherentlogic.com> wrote: > > Hi Folks, > > If you need to send data from Java to R you may consider using the > JDataFrame API -- which is used to convert data into JSON which then > can be converted into a data frame in R. > > Here's the project page: > > https://cohe...