[R] Putting R Based open source analytics for collobrative spreadsheet working on the Cloud

Ajay ohri ohri2007 at gmail.com
Mon Jun 22 05:15:22 CEST 2009


>
>
> Dear All,

I just posted an interview with Karim Chine of http://www.biocep.net/ who
has successfully built a latform for on demand data mining enabled by the
cloud through R.

Here is an except

BIOCEP is built on top of R and Scilab and anything that you can do within
those environments is accessible through BIOCEP. Here is what you have
uniquely with this new R/Scilab-based e-platform:

- *High productivity* via the most advanced cross-platform workbench
available *for the R environment*.

- *Advanced Graphics: with BIOCEP, a graphic transducer allows the rendering
on client side of graphics produced on server s*ide and enables advanced
capabilities like zooming/unzooming/scrolling for R graphics. a client side
mouse tracker allows to display dynamically information related to the
graphics and depending on coordinates. Several virtual R Devices showing
different data can be coupled in zooming/scrolling and this helps comparing
visually complex graphics.

- *Extensibility with plug-ins:* new views (IDE-like views, analytical
interfaces...) can be created very easily either programmatically or via
drag-and-drop GUI designers.

- *Extensibility with server-side extensions: any java code can be packaged
and used on server side.* The code can interact seamlessly with R and Scilab
or provide generic bridges to other software. For example, I provide an
extension that allows you to use openoffice as a universal converter between
various files formats on server side.

- *Seamless High Performance Computing:* working with an R or Scilab on
clusters/grids/clouds becomes as simple as working with them locally.
Distributed computing becomes seamless, creating a large number R and Scilab
remote engines and using them to solve large scale problems becomes easier
than ever. From the R console the user can create logical links to existing
R engines or to newly created ones and use those logical links to pilot the
remote workers from within his R session. R functions enable using the
logical links to import/export variables from the R session to the different
workers and vice versa. R commands/scripts can be executed by the R workers
synchronously or asynchronously. Many logical R links can be aggregated into
one logical cluster variable that can be used to pilot the R workers in a
coordinated way. A cluster.apply function allows the usage of the logical
cluster to apply a function to a big data structure by slicing it and
sending elementary execution commands to the workers. The workers apply the
user's function to the slices in parallel. The elementary results are
aggregated to compose the final result that becomes available within the R
session.

- *Collaboration:* your R/scilab server running in the cloud can be accessed
simultaneously by you and your collaborators. Everything gets broadcasted
including Graphics. A spreadsheet enables to view and edit data
collaboratively. Anyone can write plug-ins to take advantage of the
collaborative capabilities of the frameworks. If your IP address is public,
you can provide a URL to anyone and get him connect to your locally running
R.

*- Powerful frameworks for Java developers:* BIOCEP provides Frameworks and
tools to use R as if it was an Object Oriented Java Toolkit or a Web Toolkit
for R-based dynamic application.

- *Webservices for C#, Perl, Python users/developers:* Most of the
capabilities of BIOCEP including piloting of R/Scilab engines on the cloud
for distributed computing or for building scalable analytical web
application are accessible from most of the programming languages thanks to
the SOAP front-end.

- *RESTful API:* simple URLs can perform computing using R/Scilab engines
and return the result as an XML or as graphics in any format. This works
like google charts and has all the power of R since the graphic is described
with an R script provided as a parameter of the URL. The same API can be
exposed on demand by the workbench. This allow for example to integrate a
Cloud-R with Excel or OpenOffice. The workbench works as a bridge between
the cloud and those applications.

While a screenshot is attached- you can read the rest of the interview at

 http://tr.im/Rcloud

or http://www.decisionstats.com/



Thanks,

Ajay Ohri


More information about the R-help mailing list