[R-sig-Geo] Revolution R Enterprise - solution to handling large (spatial) data?
Roger Bivand
Roger.Bivand at nhh.no
Fri Sep 10 15:03:21 CEST 2010
On Fri, 10 Sep 2010, Tomislav Hengl wrote:
>
> (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.
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
>
> [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
>
> _______________________________________________
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> R-sig-Geo at stat.math.ethz.ch
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>
--
Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Helleveien 30, N-5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: Roger.Bivand at nhh.no
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