```
if (FALSE) {
restoreResults <- TRUE
sfInit(parallel=FALSE)
## Execute in cluster or sequential.
sfLapply(1:10, exp)
## Execute with intermediate result saving and restore on wish.
sfClusterApplySR(1:100, exp, name="CALC_EXP", restore=restoreResults)
sfClusterApplySR(1:100, sum, name="CALC_SUM", restore=restoreResults)
sfStop()
##
## Small bootstrap example.
##
sfInit(parallel=TRUE, cpus=2)
require(mvna)
data(sir.adm)
sfExport("sir.adm", local=FALSE)
sfLibrary(cmprsk)
wrapper <- function(a) {
index <- sample(1:nrow(sir.adm), replace=TRUE)
temp <- sir.adm[index, ]
fit <- crr(temp$time, temp$status, temp$pneu, failcode=1, cencode=0)
return(fit$coef)
}
result <- sfLapply(1:100, wrapper)
mean( unlist( rbind( result ) ) )
sfStop()
}
```

Run the code above in your browser using DataLab