runApproach1b.sh

#!/bin/bash

#$ -cwd
#$ -l jabba,mem_free=10G,h_vmem=2G,h_fsize=1G 
#$ -N approach1b
#$ -pe local 20
#$ -m e

echo "**** Job starts ****"
date

## For organization
mkdir -p logs1b
mkdir -p trash

## Run approach test
Rscript testApproach.R -a "approach1b" -m 20 -d FALSE

## Organize log files
mv *.p* trash/
mv approach1b.* logs1b/

### Done
echo "**** Job ends ****"
date

runApproach2.sh

#!/bin/bash

#$ -cwd
#$ -l jabba,mem_free=10G,h_vmem=2G,h_fsize=1G 
#$ -N approach2
#$ -pe local 20
#$ -m e

echo "**** Job starts ****"
date

## For organization
mkdir -p logs2
mkdir -p trash

## Run approach test
Rscript testApproach.R -a "approach2" -m 20 -d FALSE

## Organize log files
mv *.p* trash/
mv approach2.* logs2/

### Done
echo "**** Job ends ****"
date

runApproach3.sh

#!/bin/bash

#$ -cwd
#$ -l jabba,mem_free=10G,h_vmem=2G,h_fsize=1G 
#$ -N approach3
#$ -pe local 20
#$ -m e

echo "**** Job starts ****"
date

## For organization
mkdir -p logs3
mkdir -p trash

## Run approach test
Rscript testApproach.R -a "approach3" -m 20 -d FALSE

## Organize log files
mv *.p* trash/
mv approach3.* logs3/

### Done
echo "**** Job ends ****"
date

runApproach4.sh

#!/bin/bash

#$ -cwd
#$ -l jabba,mem_free=10G,h_vmem=2G,h_fsize=1G 
#$ -N approach3
#$ -pe local 20
#$ -m e

echo "**** Job starts ****"
date

## For organization
mkdir -p logs4
mkdir -p trash

## Run approach test
Rscript testApproach.R -a "approach4" -m 20 -d FALSE

## Organize log files
mv *.p* trash/
mv approach4.* logs4/

### Done
echo "**** Job ends ****"
date

testApproach.R

## Load libraries
library("getopt")
library("parallel")

## Specify parameters
spec <- matrix(c(
	'approach', 'a', 1, "character", "Either 'approach1b', 'approach2' or 'approach3'",
	'mcores', 'm', 1, "integer", "Number of cores",
	'dataAbsent', 'd', 2, "logical", "Is the data absent?",
	'help' , 'h', 0, "logical", "Display help"
), byrow=TRUE, ncol=5)
opt <- getopt(spec)


## if help was asked for print a friendly message
## and exit with a non-zero error code
if (!is.null(opt$help)) {
	cat(getopt(spec, usage=TRUE))
	q(status=1)
}


if(opt$dataAbsent) {
	set.seed(20131113)
	data <- data.frame(matrix(rnorm(1e7), ncol=10))
	dataSplit1b <- split(data, rep(seq_len(opt$mcores), each= nrow(data) / opt$mcores))
	rm(data)
	
	save(dataSplit1b, file="dataSplit1b.Rdata")
}


if(opt$approach == "approach1b") {
	if(!opt$dataAbsent) load("dataSplit1b.Rdata")
		
	## Approach 1b
	res1b <- mclapply(dataSplit1b, rowMeans, mc.cores=opt$mcores)
} else if (opt$approach == "approach2") {
	
	if(!opt$dataAbsent) load("dataSplit1b.Rdata")
	## Save the split data in an environment
	my.env <- new.env()
	for(i in seq_len(opt$mcores)) {
		eval(parse(text=paste0("my.env$data", i, " <- dataSplit1b[[", i, "]]")))
	}
	rm(dataSplit1b)

	## Function that takes indexes, then extracts the data from the environment
	applyMyFun <- function(idx, env) {
		eval(parse(text=paste0("result <- env$", ls(env)[idx])))
		rowMeans(result)
	}
	
	## Approach 2
	index <- seq_len(opt$mcores)
	names(index) <- index
	
	res2 <- mclapply(index, applyMyFun, env=my.env, mc.cores=opt$mcores)
		
} else if(opt$approach == "approach3") {
	if(opt$dataAbsent) {
		## Save the chunks
		for(i in names(dataSplit1b)) {
			chunk <- dataSplit1b[[i]]
			output <- paste0("chunk", i, ".Rdata")
			save(chunk, file=output)
		}
		rm(dataSplit1b)
	}	

	## Function that loads the chunk
	applyMyFun2 <- function(idx) {
		load(paste0("chunk", idx, ".Rdata"))
		rowMeans(chunk)
	}

	## Approach 3
	index <- seq_len(opt$mcores)
	names(index) <- index
	res3 <- mclapply(index, applyMyFun2, mc.cores=opt$mcores)
} else if(opt$approach == "approach4") {
	res4 <- mclapply(splitIndices(nrow(data), opt$mcores),
					 function(i) rowMeans(data[i,]),
					 mc.cores=opt$mcores)
} else {
	stop("Invalid 'approach' option")
}

## Reproducibility
proc.time()
sessionInfo()