Should I prefer hadoop vs condor when working with R?

I am looking for ways to send works for multiple computers on 开发者_如何学编程my University computer grid.

Currently it is running Condor and also offers Hadoop.

My question is thus, should I try and interface with R to Hadoop or to the Conder for my projects?

For the discussion, let's assume we are talking about Embarrassingly parallel tasks.

p.s: I've seen the resources described in the CRAN task views.

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You can do both.

You can use HDFS for your data sets and Condor for your job scheduling. Using Condor to place executors on machines and HDFS + Hadoops Map-Reduce features to process your data (assuming your problem is map-reduce mappable). Then you're using the most appropriate tool for the job: Condor is a job scheduler, and as such does that work better than Hadoop. And Hadoop's HDFS and M-R framework are things Condor doesn't have (but are really helpful for jobs running on Condor to use).

I would personally look at has HDFS to share data among jobs that run discretely as Condor jobs. Especially in a university environment, where shared compute resources are not 100% reliable and can come and go at will, Condor's resilience in this type of set up is going to make getting work done a whole lot easier.