Tag: foreach

Revolution R Enterprise 6.0 launched!

Just got the email-more software is good news!

Revolution R Enterprise 6.0 for 32-bit and 64-bit Windows and 64-bit Red Hat Enterprise Linux (RHEL 5.x and RHEL 6.x) features an updated release of the RevoScaleR package that provides fast, scalable data management and data analysis: the same code scales from data frames to local, high-performance .xdf files to data distributed across a Windows HPC Server cluster or IBM Platform Computing LSF cluster.  RevoScaleR also allows distribution of the execution of essentially any R function across cores and nodes, delivering the results back to the user.

Detailed information on what’s new in 6.0 and known issues:
http://www.revolutionanalytics.com/doc/README_RevoEnt_Windows_6.0.0.pdf

and from the manual-lots of function goodies for Big Data

 

  • IBM Platform LSF Cluster support [Linux only]. The new RevoScaleR function, RxLsfCluster, allows you to create a distributed compute context for the Platform LSF workload manager.
  •  Azure Burst support added for Microsoft HPC Server [Windows only]. The new RevoScaleR function, RxAzureBurst, allows you to create a distributed compute context to have computations performed in the cloud using Azure Burst
  • The rxExec function allows distributed execution of essentially any R function across cores and nodes, delivering the results back to the user.
  • functions RxLocalParallel and RxLocalSeq allow you to create compute context objects for local parallel and local sequential computation, respectively.
  • RxForeachDoPar allows you to create a compute context using the currently registered foreach parallel backend (doParallel, doSNOW, doMC, etc.). To execute rxExec calls, simply register the parallel backend as usual, then set your compute context as follows: rxSetComputeContext(RxForeachDoPar())
  • rxSetComputeContext and rxGetComputeContext simplify management of compute contexts.
  • rxGlm, provides a fast, scalable, distributable implementation of generalized linear models. This expands the list of full-featured high performance analytics functions already available: summary statistics (rxSummary), cubes and cross tabs (rxCube,rxCrossTabs), linear models (rxLinMod), covariance and correlation matrices (rxCovCor),
    binomial logistic regression (rxLogit), and k-means clustering (rxKmeans)example: a Tweedie family with 1 million observations and 78 estimated coefficients (categorical data)
    took 17 seconds with rxGlm compared with 377 seconds for glm on a quadcore laptop

     

    and easier working with R’s big brother SAS language

     

    RevoScaleR high-performance analysis functions will now conveniently work directly with a variety of external data sources (delimited and fixed format text files, SAS files, SPSS files, and ODBC data connections). New functions are provided to create data source objects to represent these data sources (RxTextData, RxOdbcData, RxSasData, and RxSpssData), which in turn can be specified for the ‘data’ argument for these RevoScaleR analysis functions: rxHistogram, rxSummary, rxCube, rxCrossTabs, rxLinMod, rxCovCor, rxLogit, and rxGlm.


    example, 

    you can analyze a SAS file directly as follows:


    # Create a SAS data source with information about variables and # rows to read in each chunk
    sasDataFile <- file.path(rxGetOption(“sampleDataDir”),”claims.sas7bdat”)
    sasDS <- RxSasData(sasDataFile, stringsAsFactors = TRUE,colClasses = c(RowNum = “integer”),rowsPerRead = 50)

    # Compute and draw a histogram directly from the SAS file
    rxHistogram( ~cost|type, data = sasDS)
    # Compute summary statistics
    rxSummary(~., data = sasDS)
    # Estimate a linear model
    linModObj <- rxLinMod(cost~age + car_age + type, data = sasDS)
    summary(linModObj)
    # Import a subset into a data frame for further inspection
    subData <- rxImport(inData = sasDS, rowSelection = cost > 400,
    varsToKeep = c(“cost”, “age”, “type”))
    subData

 

The installation instructions and instructions for getting started with Revolution R Enterprise & RevoDeployR for Windows: http://www.revolutionanalytics.com/downloads/instructions/windows.php

Parallel Programming using R in Windows

Ashamed at my lack of parallel programming, I decided to learn some R Parallel Programming (after all parallel blogging is not really respect worthy in tech-geek-ninja circles).

So I did the usual Google- CRAN- search like a dog thing only to find some obstacles.

Obstacles-

Some Parallel Programming Packages like doMC are not available in Windows

http://cran.r-project.org/web/packages/doMC/index.html

Some Parallel Programming Packages like doSMP depend on Revolution’s Enterprise R (like –

http://blog.revolutionanalytics.com/2009/07/simple-scalable-parallel-computing-in-r.html

and http://www.r-statistics.com/2010/04/parallel-multicore-processing-with-r-on-windows/ (No the latest hack didnt work)

or are in testing like multicore (for Windows) so not available on CRAN

http://cran.r-project.org/web/packages/multicore/index.html

fortunately available on RForge

http://www.rforge.net/multicore/files/

Revolution did make DoSnow AND foreach available on CRAN

see http://blog.revolutionanalytics.com/2009/08/parallel-programming-with-foreach-and-snow.html

but the documentation in SNOW is overwhelming (hint- I use Windows , what does that tell you about my tech acumen)

http://sekhon.berkeley.edu/snow/html/makeCluster.html and

http://www.stat.uiowa.edu/~luke/R/cluster/cluster.html

what is a PVM or MPI? and SOCKS are for wearing or getting lost in washers till I encountered them in SNOW


Finally I did the following-and made the parallel programming work in Windows using R

require(doSNOW)
cl<-makeCluster(2) # I have two cores
registerDoSNOW(cl)
# create a function to run in each itteration of the loop

check <-function(n) {

+ for(i in 1:1000)

+ {

+ sme <- matrix(rnorm(100), 10,10)

+ solve(sme)

+ }

+ }
times <- 100     # times to run the loop
system.time(x <- foreach(j=1:times ) %dopar% check(j))
user  system elapsed
0.16    0.02   19.17
system.time(for(j in 1:times ) x <- check(j))
user  system elapsed</pre>
39.66    0.00   40.46

stopCluster(cl)

And it works!

Making NeW R

Tal G in his excellent blog piece talks of “Why R Developers  should not be paid” http://www.r-statistics.com/2010/09/open-source-and-money-why-r-developers-shouldnt-be-paid/

His argument of love is not very original though it was first made by these four guys

I am going to argue that “some” R developers should be paid, while the main focus should be volunteers code. These R developers should be paid as per usage of their packages.

Let me expand.

Imagine the following conversation between Ross Ihaka, Norman Nie and Peter Dalgaard.

Norman- Hey Guys, Can you give me some code- I got this new startup.

Ross Ihaka and Peter Dalgaard- Sure dude. Here is 100,000 lines of code, 2000 packages and 2 decades of effort.

Norman- Thanks guys.

Ross Ihaka- Hey, What you gonna do with this code.

Norman- I will better it. Sell it. Finally beat Jim Goodnight and his **** Proc GLM and **** Proc Reg.

Ross- Okay, but what will you give us? Will you give us some code back of what you improve?

Norman – Uh, let me explain this open core …

Peter D- Well how about some royalty?

Norman- Sure, we will throw parties at all conferences, snacks you know at user groups.

Ross – Hmm. That does not sound fair. (walks away in a huff muttering)-He takes our code, sells it and wont share the code

Peter D- Doesnt sound fair. I am back to reading Hamlet, the great Dane, and writing the next edition of my book. I am glad I wrote a book- Ross didnt even write that.

Norman-Uh Oh. (picks his phone)- Hey David Smith, We need to write some blog articles pronto – these open source guys ,man…

———–I think that sums what has been going on in the dynamics of R recently. If Ross Ihaka and R Gentleman had adopted an open core strategy- meaning you can create packages to R but not share the original where would we all be?

At this point if he is reading this, David Smith , long suffering veteran of open source  flameouts is rolling his eyes while Tal G is wondering if he will publish this on R Bloggers and if so when or something.

Lets bring in another R veteran-  Hadley Wickham who wrote a book on R and also created ggplot. Thats the best quality, most often used graphics package.

In terms of economic utilty to end user- the ggplot package may be as useful if not more as the foreach package developed by Revolution Computing/Analytics.

Now http://cran.r-project.org/web/packages/foreach/index.html says that foreach is licensed under http://www.apache.org/licenses/LICENSE-2.0

However lets come to open core licensing ( read it here http://alampitt.typepad.com/lampitt_or_leave_it/2008/08/open-core-licen.html ) which is where the debate is- Revolution takes code- enhances it (in my opinion) substantially with new formats XDF for better efficieny, web services API, and soon coming next year a GUI (thanks in advance , Dr Nie and guys)

and sells this advanced R code to businesses happy to pay ( they are currently paying much more to DR Goodnight and HIS guys)

Why would any sane customer buy it from Revolution- if he could download exactly the same thing from http://r-project.org

Hence the business need for Revolution Analytics to have an enhanced R- as they are using a product based software model not software as a service model.

If Revolution gives away source code of these new enhanced codes to R core team- how will R core team protect the above mentioned intelectual property- given they have 2 decades experience of giving away free code , and back and forth on just code.

Now Revolution also has a marketing budget- and thats how they sponsor some R Core events, conferences, after conference snacks.

How would people decide if they are being too generous or too stingy in their contribution (compared to the formidable generosity of SAS Institute to its employees, stakeholders and even third party analysts).

Would it not be better- IF Revolution can shift that aspect of relationship to its Research and Development budget than it’s marketing budget- come with some sort of incentive for “SOME” developers – even researchers need grants and assistantships, scholarships, make a transparent royalty formula say 17.5 % of the NEW R sales goes to R PACKAGE Developers pool, which in turn examines usage rate of packages and need/merit before allocation- that would require Revolution to evolve from a startup to a more sophisticated corporate and R Core can use this the same way as John M Chambers software award/scholarship

Dont pay all developers- it would be an insult to many of them – say Prof Harrell creator of HMisc to accept – but can Revolution expand its dev base (and prospect for future employees) by even sponsoring some R Scholarships.

And I am sure that if Revolution opens up some more code to the community- they would the rest of the world and it’s help useful. If it cant trust people like R Gentleman with some source code – well he is a board member.

——————————————————————————————–

Now to sum up some technical discussions on NeW R

1)  An accepted way of benchmarking efficiencies.

2) Code review and incorporation of efficiencies.

3) Multi threading- Multi core usage are trends to be incorporated.

4) GUIs like R Commander E Plugins for other packages, and Rattle for Data Mining to have focussed (or Deducer). This may involve hiring User Interface Designers (like from Apple 😉  who will work for love AND money ( Even the Beatles charge royalty for that song)

5) More support to cloud computing initiatives like Biocep and Elastic R – or Amazon AMI for using cloud computers- note efficiency arguements dont matter if you just use a Chrome Browser and pay 2 cents a hour for an Amazon Instance. Probably R core needs more direct involvement of Google (Cloud OS makers) and Amazon as well as even Salesforce.com (for creating Force.com Apps). Note even more corporates here need to be involved as cloud computing doesnot have any free and open source infrastructure (YET)

_______________________________________________________

Debates will come and go. This is an interesting intellectual debate and someday the liitle guys will win the Revolution-

From Hugh M of Gaping Void-

http://www.gapingvoid.com/Moveable_Type/archives/cat_microsoft_blue_monster_series.html

HOW DOES A SOFTWARE COMPANY MAKE MONEY, IF ALL

SOFTWARE IS FREE?

“If something goes wrong with Microsoft, I can phone Microsoft up and have it fixed. With Open Source, I have to rely on the community.”

And the community, as much as we may love it, is unpredictable. It might care about your problem and want to fix it, then again, it may not. Anyone who has ever witnessed something online go “viral”, good or bad, will know what I’m talking about.

and especially-

http://gapingvoid.com/2007/04/16/how-well-does-open-source-currently-meet-the-needs-of-shareholders-and-ceos/

Source-http://gapingvoidgallery.com/

Kind of sums up why the open core licensing is all about.

Kill R? Wait a sec

1) Is R efficient? (scripting wise, and performance wise) _ Depends on how you code it- some Packages like foreach can help but basic efficiency come from programmer. XDF formats from Revoscalar -the non open R package further improve programming efficiency

2) Should R be written from scratch?

You got to be kidding- It depends on how you define scratch after 2 million users

This has been done with S, then S Plus and now R.

3) What should be the license of R (if it was made a new)?

GPL license is fine. You need to do a better job of executing the license. Currently interfaces to R exist from SPSS, SAS, KXEN , other companies as well. To my knowledge royalty payments as well as formal code sharing does not agree.

R core needs to do a better job of protecting the work of 2500 package-creators rather than settling for a few snacks at events, sponsorships, Corporate Board Membership for Prof Gentleman, and 4-5 packages donated to it. The only way R developers can currently support their research is write a book (ny Springer mostly)

Eg GGplot and Hmisc are likely to be used more by average corporate user. Do their creators deserve royalty if creators of RevoScalar are getting it?

If some of 2 million users gave 1 $ to R core (compared to 9 million in last round of funding in Revolution Analytics)- you would have enough money to create a 64 bit optimized R for Linux (missing in Enterprise R), Amazon R APIs (like Karim Chine’s efforts), R GUIs (like Rattle’s commercial version) etc etc

The developments are not surprising given that Microsoft and Intel are funding Revolution Analytics http://www.dudeofdata.com/?p=1967

R controversies come and go (this has happened before including the NYT article and shakeup at Revo)

An interesting debate on whether R should be killed to make an upgrade to a more efficient language.

From Tal (creator R Bloggers) and on R help list-

There is currently a (very !) lively discussions happening around the web, surrounding the following topics:
1) Is R efficient? (scripting wise, and performance wise)
2) Should R be written from scratch?
3) What should be the license of R (if it was made a new)?

Very serious people have taken part in the debates so far.  I hope to let you know of the places I came by, so you might be able to follow/participate
in these (IMHO) important discussions.

The discussions started in the response for the following blog post on
Xi’An’s blog:
http://xianblog.wordpress.com/2010/09/06/insane/


Followed by the (short) response post by Ross Ihaka:
http://xianblog.wordpress.com/2010/09/13/simply-start-over-and-build-something-better/


Other discussions started to appear on Andrew Gelman’s blog:
http://www.stat.columbia.edu/~cook/movabletype/archives/2010/09/ross_ihaka_to_r.html

And (many) more responses started to appear in the hackers news website:
http://news.ycombinator.com/item?id=1687054

I hope these discussions will have fruitful results for our community,
Tal

—————-Contact
Details:——————————————————-
Contact me: Tal.Galili@gmail.com |  972-52-7275845
Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) |
www.r-statistics.com (English)

My 0 cents ( see it would 2 cents but it;s free)

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