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Revolution R Enterprise - solution to handling large (spatial) data?

5 messages · Tomislav Hengl, Roman Luštrik, Matthew Landis +2 more

Original
Tomislav Hengl
# 
(Maybe this is not really suited for the R-sig-geo, but since we often 
experience problems with loading and visualizing large data)

Has anyone yet used the Revolution R Entrerprise Version of R? 
Apparently it fixes/reduces the problem of large data and has an 
excellent GUI.

[http://www.revolutionanalytics.com/downloads/free-academic.php]

Read more:

"Startup wants to be R alternative to IBM, SAS"
[http://www.networkworld.com/news/2010/050410-startup-wants-to-be-r.html?hpg1=bn]

"A Community Site for R ? Sponsored by Revolution Analytics"
[http://www.inside-r.org]


T. Hengl
http://spatial-analyst.net
Matthew Landis
# 
Tomislav,
For what it's worth, the raster package has solved the problem of 
loading large data sets for me, at least as far as gridded spatial data 
is concerned.

Matt
On 9/10/2010 8:11 AM, Tomislav Hengl wrote:

  
    

      
      
    

  


  


      

    

    

      
      

        


  

        

      Roger Bivand
    

    

      
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On Fri, 10 Sep 2010, Tomislav Hengl wrote:

        

            

      
      
      
    

        
No, it provides 64-bit support, which R for all platforms already does - 
the user has to provide the RAM as before. It does ship with a more 
integrated support for using multiple cores, but those facilities are also 
available for R anyway, provided the relevant packages are installed and 
loaded.

If you are thinking of "NEW! Big Data Analysis for Terabyte-Class File 
Structures ? A comprehensive solution that provides fast, scalable 
statistical analysis of large data sets without the RAM barrier of 
standard R" - this does not apply to the 2G limit on single R objects, 
which for most geodata problems are addressed quite adequately by tiling, 
as in the raster package.

What it provides apparently is a visual IDE and debugging, in addition to 
support. It does not provide contributed packages beyond those Revolution 
Analytics themselves write and maintain (they do, they are pro-active 
people, and are doing a good job in relation to business).

If your university will not let you install regular R, this is a good 
solution, because it gives IT departments a "supplier". Certainly worth 
trying for comparison, but on the same hardware it is unlikely to perform 
differently from R itself (since they cannot fork R and leave GPL, so any 
dramatic breakthroughs in performance would be merged back into trunk, if 
they work cross-platform). The RevoScaleR package is not on CRAN, and 
simply provides facilities similar to those such as biglm, ff and sqldf 
for doing analyses of chunks of large data frames using a different XDF 
file structure. Present status is summarised in the Large memory and 
out-of-memory data section of the HPC task view.

Hope this helps,

Roger

            

      
      
      
    

        

      
      
    

        

  
    

      
      
    

  


  


      

    

    

      
      

        


  

        

      Barry Rowlingson
    

    

      
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On Fri, Sep 10, 2010 at 1:11 PM, Tomislav Hengl

        
<hengl at spatial-analyst.net> wrote:

            

      
      
      
    

        
I'm not sure their definition of 'Wide Platform Support' corresponds to mine:

Wide Platform Support: Available for 32-bit and 64-bit Windows and Red
Hat Enterprise Linux

So no use to my Mac, and problematic on Ubuntu Linux? What about my
HPC cluster of Solaris boxes? I don't know, haven't tried. Of course,
if I had the source I could compile it myself on any platform - or at
least try to - and contribute my solutions back to the community.

Barry