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='k...@linux1.dovetail.com'
//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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