-#' @name de_serialize
-#' @rdname de_serialize
-#' @aliases binarize binarizeTransform getDataInFile
+#' (De)Serialization of a [big]matrix or data stream
#'
-#' @title (De)Serialization of a [big]matrix or data stream
+#' \code{binarize()} serializes a matrix or CSV file with minimal overhead, into a
+#' binary file. \code{getDataInFile()} achieves the inverse task: she retrieves (ASCII)
+#' data rows from indices in the binary file. Finally, \code{binarizeTransform()}
+#' serialize transformations of all data chunks. To use it a data-retrieval function
+#' must be provided -- thus \code{binarize} will most likely be used first
+#' (and then a function defined to seek in generated binary file)
#'
-#' @description \code{binarize()} serializes a matrix or CSV file with minimal overhead,
-#' into a binary file. \code{getDataInFile()} achieves the inverse task: she retrieves
-#' (ASCII) data rows from indices in the binary file. Finally,
-#' \code{binarizeTransform()} serialize transformations of all data chunks; to use it,
-#' a data-retrieval function must be provided, thus \code{binarize} will most likely be
-#' used first (and then a function defined to seek in generated binary file)
-#'
-#' @param data_ascii Either a matrix or CSV file, with items in rows
-#' @param indices Indices of the lines to retrieve
-#' @param data_bin_file Name of binary file on output (\code{binarize})
-#' or input (\code{getDataInFile})
+#' @param data_ascii Either a matrix (by columns) or CSV file or connection (by rows)
+#' @param data_bin_file Name of binary file on output of (\code{binarize})
+#' or input of (\code{getDataInFile})
#' @param nb_per_chunk Number of lines to process in one batch (big.matrix or connection)
-#' @inheritParams claws
#' @param getData Function to retrieve data chunks
#' @param transform Transformation function to apply on data chunks
+#' @param indices Indices of the lines to retrieve
+#' @inheritParams claws
#'
#' @return For \code{getDataInFile()}, the matrix with rows corresponding to the
#' requested indices. \code{binarizeTransform} returns the number of processed lines.
#' \code{binarize} is designed to serialize in several calls, thus returns nothing.
+#'
+#' @name de_serialize
+#' @rdname de_serialize
+#' @aliases binarize binarizeTransform getDataInFile
NULL
#' @rdname de_serialize
#' @export
-binarize = function(data_ascii, data_bin_file, nb_per_chunk,
+binarize <- function(data_ascii, data_bin_file, nb_per_chunk,
sep=",", nbytes=4, endian=.Platform$endian)
{
# data_ascii can be of two types: [big.]matrix, or connection
if (is.character(data_ascii))
- data_ascii = file(data_ascii, open="r")
+ data_ascii <- file(data_ascii, open="r")
else if (methods::is(data_ascii,"connection") && !isOpen(data_ascii))
open(data_ascii)
- is_matrix = !methods::is(data_ascii,"connection")
+ is_matrix <- !methods::is(data_ascii,"connection")
# At first call, the length of a stored row is written. So it's important to determine
# if the serialization process already started.
- first_write = (!file.exists(data_bin_file) || file.info(data_bin_file)$size == 0)
+ first_write <- (!file.exists(data_bin_file) || file.info(data_bin_file)$size == 0)
# Open the binary file for writing (or 'append' if already exists)
- data_bin = file(data_bin_file, open=ifelse(first_write,"wb","ab"))
+ data_bin <- file(data_bin_file, open=ifelse(first_write,"wb","ab"))
if (first_write)
{
# Write data length on first call: number of items always on 8 bytes
writeBin(0L, data_bin, size=8, endian=endian)
if (is_matrix)
- data_length = nrow(data_ascii)
+ data_length <- nrow(data_ascii)
else #connection
{
# Read the first line to know data length, and write it then
- data_line = scan(data_ascii, double(), sep=sep, nlines=1, quiet=TRUE)
+ data_line <- scan(data_ascii, double(), sep=sep, nlines=1, quiet=TRUE)
writeBin(data_line, data_bin, size=nbytes, endian=endian)
- data_length = length(data_line)
+ data_length <- length(data_line)
}
}
{
# Data is processed by chunks; although this may not be so useful for (normal) matrix
# input, it could for a file-backed big.matrix. It's easier to follow a unified pattern.
- index = 1
+ index <- 1
}
repeat
{
if (is_matrix)
{
- data_chunk =
+ data_chunk <-
if (index <= ncol(data_ascii))
as.double(data_ascii[,index:min(ncol(data_ascii),index+nb_per_chunk-1)])
else
double(0)
- index = index + nb_per_chunk
+ index <- index + nb_per_chunk
}
else #connection
- data_chunk = scan(data_ascii, double(), sep=sep, nlines=nb_per_chunk, quiet=TRUE)
+ data_chunk <- scan(data_ascii, double(), sep=sep, nlines=nb_per_chunk, quiet=TRUE)
# Data size is unknown in the case of a connection
if (length(data_chunk)==0)
if (first_write)
{
- # Write data_length, = (file_size-1) / (nbytes*nbWritten) at offset 0 in data_bin
- ignored = seek(data_bin, 0)
+ # Write data_length, == (file_size-1) / (nbytes*nbWritten) at offset 0 in data_bin
+ ignored <- seek(data_bin, 0)
writeBin(data_length, data_bin, size=8, endian=endian)
}
close(data_bin)
#' @rdname de_serialize
#' @export
-binarizeTransform = function(getData, transform, data_bin_file, nb_per_chunk,
+binarizeTransform <- function(getData, transform, data_bin_file, nb_per_chunk,
nbytes=4, endian=.Platform$endian)
{
- nb_items = 0 #side-effect: store the number of transformed items
- index = 1
+ nb_items <- 0 #side-effect: store the number of transformed items
+ index <- 1
repeat
{
# Retrieve a chunk of data in a binary file (generally obtained by binarize())
- data_chunk = getData((index-1)+seq_len(nb_per_chunk))
+ data_chunk <- getData((index-1)+seq_len(nb_per_chunk))
if (is.null(data_chunk))
break
# Apply transformation on the current chunk (by columns)
- transformed_chunk = transform(data_chunk)
+ transformed_chunk <- transform(data_chunk)
# Save the result in binary format
binarize(transformed_chunk, data_bin_file, nb_per_chunk, ",", nbytes, endian)
- index = index + nb_per_chunk
- nb_items = nb_items + ncol(data_chunk)
+ index <- index + nb_per_chunk
+ nb_items <- nb_items + ncol(data_chunk)
}
nb_items #number of transformed items
}
#' @rdname de_serialize
#' @export
-getDataInFile = function(indices, data_bin_file, nbytes=4, endian=.Platform$endian)
+getDataInFile <- function(indices, data_bin_file, nbytes=4, endian=.Platform$endian)
{
- data_bin = file(data_bin_file, "rb") #source binary file
+ data_bin <- file(data_bin_file, "rb") #source binary file
- data_size = file.info(data_bin_file)$size #number of bytes in the file
+ data_size <- file.info(data_bin_file)$size #number of bytes in the file
# data_length: length of a vector in the binary file (first element, 8 bytes)
- data_length = readBin(data_bin, "integer", n=1, size=8, endian=endian)
+ data_length <- readBin(data_bin, "integer", n=1, size=8, endian=endian)
# Seek all 'indices' columns in the binary file, using data_length and nbytes
# to compute the offset ( index i at 8 + i*data_length*nbytes )
- data_ascii = do.call( cbind, lapply( indices, function(i) {
- offset = 8+(i-1)*data_length*nbytes
+ data_ascii <- do.call( cbind, lapply( indices, function(i) {
+ offset <- 8+(i-1)*data_length*nbytes
if (offset >= data_size)
return (NULL)
- ignored = seek(data_bin, offset) #position cursor at computed offset
+ ignored <- seek(data_bin, offset) #position cursor at computed offset
readBin(data_bin, "double", n=data_length, size=nbytes, endian=endian)
} ) )
close(data_bin)