[R] Accelerating binRead

[Philippe de Rochambeau]

Hello,
the following function, which stores numeric values extracted from a binary file, into an R matrix, is very slow, especially when the said file is several MB in size.
Should I rewrite the function in inline C or in C/C++ using Rcpp? If the latter case is true, how do you « readBin »  in Rcpp (I’m a total Rcpp newbie)?
Many thanks.
Best regards,
phiroc


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# inputPath is something like http://myintranet/getData?pathToFile=/usr/lib/xxx/yyy/data.bin <http://myintranet/getData?pathToFile=/usr/lib/xxx/yyy/data.bin>

PLTreader <- function(inputPath){
	URL <- file(inputPath, "rb")
	PLT <- matrix(nrow=0, ncol=6)
	compteurDePrints = 0
	compteurDeLignes <- 0
	maxiPrints = 5
	displayData <- FALSE
	while (TRUE) {
		periodIndex <- readBin(URL, integer(), size=4, n=1, endian="little") # int (4 bytes)
		eventId <- readBin(URL, integer(), size=4, n=1, endian="little") # int (4 bytes)
		dword1 <- readBin(URL, integer(), size=4, signed=FALSE, n=1, endian="little") # int
		dword2 <- readBin(URL, integer(), size=4, signed=FALSE, n=1, endian="little") # int
		if (dword1 < 0) {
			dword1 = dword1 + 2^32-1;
		}
		eventDate = (dword2*2^32 + dword1)/1000
		repNum <- readBin(URL, integer(), size=2, n=1, endian="little") # short (2 bytes)
		exp <- readBin(URL, numeric(), size=4, n=1, endian="little") # float (4 bytes, strangely enough, would expect 8)
		loss <- readBin(URL, numeric(), size=4, n=1, endian="little") # float (4 bytes)
		PLT <- rbind(PLT, c(periodIndex, eventId, eventDate, repNum, exp, loss))
	} # end while
	return(PLT)
	close(URL)
}

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