UPDATE: The brand new RCall.jl package by Douglas Bates is very helpful https://github.com/JuliaStats/RCall.jl
On Saturday, December 20, 2014 at 1:57:03 AM UTC-8, Pavel wrote: > > Thank you Stefan, helpful info, the ZeroMQ-discussion in particular. > Although I am still not sure about the custom type exchange and possibly > coroutine-like setup for R, this is a starting point. > > On Thursday, December 18, 2014 7:08:46 AM UTC-8, Stefan Karpinski wrote: >> >> Redis, perhaps? There are some Julia bindings: >> >> https://github.com/msainz/Redis.jl >> https://github.com/markmo/HiRedis.jl >> >> >> I'm not sure which is better to use – the Redis.jl package is a pure >> Julia implementation of a Redis client while HiRedis.jl uses the hiredis >> library to interact with Redis. It would be nice to eventually have one >> true way to interact with Redis, but for now there's a choice. >> >> You could also try using Rif.jl <https://github.com/lgautier/Rif.jl> to >> call R directly from Julia. >> >> Yet another option would be to push chunks of data from Julia to R using >> ZeroMQ messaging. Here's a thread about that approach: >> >> https://groups.google.com/forum/#!topic/julia-users/umHiBwVLQ4g >> >> On Thu, Dec 18, 2014 at 4:26 AM, Pavel <[email protected]> wrote: >> >>> This is a fairly general question about structuring an application that >>> relies on both Julia and R code. The Julia part takes time series input and >>> performs extensive parallel computations (thank you core developers for the >>> efficient pmap), producing the output that is not that demanding in terms >>> of data storage. The R part collects some data from the web every minute >>> via REST APIs forming the time series for Julia input, and also uses Julia >>> output for further computations (not as demanding as the Julia functions so >>> that the R-side performance is not limiting the overall process). >>> >>> Now as I am trying to integrate everything for a production environment, >>> the question is about data sharing between Julia and R. Saving chunks of >>> time series as HDFS files works in development but is inefficient. Is there >>> a suitable non-relational database with both Julia and R bindings >>> available? Should I look into setting up Julia web-server and have R talk >>> to it via REST API? Any thoughts/advice on structuring my application >>> (planning to use Google cloud) would be helpful. Thanks for reading. >>> >> >>
