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The toughest thing for e is the Git organization.


Scott

On Thursday, August 11, 2016, Kirk Wolf <[email protected]> wrote:

> Agreed - Rocket's work to port updated tools to z/OS is great.   I believe
> that they have a paid support model, which hopefully will be embraced by
> the community so that they can justify even more good work.
>
> Regarding System R, you can also run this from z/OS batch using the Co:Z
> Launcher utility.  See an example below.
> (The Co:Z Co-Processing Toolkit is available under our free Community
> License and can be downloaded without registering.)
>
> Some features of this approach:
>
> - Run R under the control of a regular z/OS batch job step.
> - processing is offloaded to a Linux server; perhaps an IFL
> - z/OS datasets can be accessed by the distribute process via the job step
> - output goes to z/OS spool files
> - the exit code of the remote process is adopted as the step condition code
>
>
> //R EXEC PROC=COZPROC,
> //        ARGS='[email protected] <javascript:;>'
> //LIFEEXP DD DISP=SHR,DSN=KIRK.LIFEEXP.DATA
> //STDIN DD *
> # Run the R statistical system with an inline program
> # This example is a 2-dimensional multiple regression
> # The dataset is read from a DD using "fromdsn" in a R pipe file.
> # The source of the data is:
> # www.sci.usq.edu.au/staff/dunn/Datasets/applications/health/lifeexp.html
>
> R --no-save  <<EOB
> mypipe = pipe("fromdsn DD:LIFEEXP", open="r")
> life = read.table(mypipe, header=TRUE)
> close(mypipe)
> multilinearFit = lm(LifeExp~PeoplePerTV+PeoplePerDoctor,data=life)
> summary(multilinearFit)
> EOB
> //
>
>
> Kirk Wolf
> Dovetailed Technologies
> http://dovetail.com
>
> PS> Co:Z is agnostic about what you run with it.  You can offload SAS in a
> similar way:
> http://dovetail.com/products/casestudysas.html
>
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