rxSplitXdf: Split a Single Data Set into Multiple Sets
Description
Split an input .xdf file or data frame into multiple .xdf files or a list of data frames.
Usage
rxSplit(inData, outFilesBase = NULL, outFileSuffixes = NULL,
numOut = NULL, splitBy = "rows", splitByFactor = NULL,
varsToKeep = NULL, varsToDrop = NULL, rowSelection = NULL,
transforms = NULL, transformObjects = NULL,
transformFunc = NULL, transformVars = NULL,
transformPackages = NULL, transformEnvir = NULL,
overwrite = FALSE, removeMissings = FALSE, rowsPerRead = -1,
blocksPerRead = 1, updateLowHigh = FALSE, maxRowsByCols = NULL,
reportProgress = rxGetOption("reportProgress"), verbose = 0,
xdfCompressionLevel = rxGetOption("xdfCompressionLevel"), ...)
rxSplitXdf(inFile, outFilesBase = basename(rxXdfFileName(inFile)), outFileSuffixes = NULL,
numOutFiles = NULL, splitBy = "rows", splitByFactor = NULL,
varsToKeep = NULL, varsToDrop = NULL, rowSelection = NULL,
transforms = NULL, transformObjects = NULL,
transformFunc = NULL, transformVars = NULL,
transformPackages = NULL, transformEnvir = NULL,
overwrite = FALSE, removeMissings = FALSE,
rowsPerRead = -1, blocksPerRead = 1, updateLowHigh = FALSE,
reportProgress = rxGetOption("reportProgress"), verbose = 0,
xdfCompressionLevel = rxGetOption("xdfCompressionLevel"), ...)
Arguments
inData
a data frame, a character string defining the path to the input .xdf file, or an RxXdfData object
inFile
a character string defining the path to the input .xdf file, or an RxXdfData object
outFilesBase
a character string or vector defining the file names/paths to use in forming the the output .xdf files. These names/paths will be embellished with any specified outFileSuffixes. For rxSplit, outFilesBase = NULL means that the default value for .xdf and RxXdfDatainData objects will be basename(rxXdfFileName(inData)) while it will be a blank string for inData a data frame.
outFileSuffixes
a vector containing the suffixes to append to the base name(s)/path(s) specified in outFilesBase. Before appending, outFileSuffixes is converted to class character via the as.character function. If NULL, seq(numOutFiles) is used in its place if numOutFiles is not NULL.
numOut
number of outputs to create, e.g., the number of output files or number of data frames returned in the output list.
numOutFiles
number of files to create. This argument is used only when outFilesBase and outFileSuffixes do not provide sufficient information to form unique paths to multiple output files. See the Examples section for its use.
splitBy
a character string denoting the method to use in partitioning the inFile .xdf file. With numFiles defined as the number of output files (formed by the combination of outFilesBase, outFileSuffixes, and numOutFiles arguments), the supported values for splitBy are:
"rows"- To the extent possible, a uniform partition of the number of rows in theinFile.xdf file is performed. The minimum number of rows in each output file is defined byfloor(numRows/numFiles), wherenumRowsis the number of rows ininFile. Additional rows will be distributed uniformly amongst the last set of files."blocks"- To the extent possible, a uniform partition of the number of blocks in theinFile.xdf file is performed. IfblocksPerRead = 1, the minimum number of blocks in each output file is defined byfloor(numBlocks/numFiles), wherenumBlocksis the number of blocks ininFile. Additional blocks will be distributed uniformly amongst the last set of files. ForblocksPerRead > 1, the number of blocks in each output file is reduced accordingly since multiple blocks read at one time are collapsed to a single block upon write. This argument is ignored ifsplitByFactoris a valid factor variable name.
splitByFactor
character string identifying the name of the factor to use in splitting the inFile .xdf data such that each file contains the data corresponding to a single level of the factor. The splitBy argument is ignored if splitByFactor is a valid factor variable name. If splitByFactor = NULL, the splitBy argument is used to define the split method.
varsToKeep
character vector of variable names to include when reading from the input data file. If NULL, argument is ignored. Cannot be used with varsToDrop.
varsToDrop
character vector of variable names to exclude when reading from the input data file. If NULL, argument is ignored. Cannot be used with varsToKeep.
rowSelection
name of a logical variable in the data set (in quotes) or a logical expression using variables in the data set to specify row selection. For example, rowSelection = "old" will use only observations in which the value of the variable old is TRUE. rowSelection = (age > 20) & (age < 65) & (log(income) > 10) will use only observations in which the value of the age variable is between 20 and 65 and the value of the log of the income variable is greater than 10. The row selection is performed after processing any data transformations (see the arguments transforms or transformFunc). As with all expressions, rowSelection can be defined outside of the function call using the expression function.
transforms
an expression of the form list(name = expression, ...) representing the first round of variable transformations. As with all expressions, transforms (or rowSelection) can be defined outside of the function call using the expression function.
transformObjects
a named list containing objects that can be referenced by transforms, transformsFunc, and rowSelection. Ignored for data frames.
transformFunc
variable transformation function. See rxTransform for details.
transformVars
character vector of input data set variables needed for the transformation function. See rxTransform for details.
transformPackages
character vector defining additional R packages (outside of those specified in rxGetOption("transformPackages")) to be made available and preloaded for use in variable transformation functions, e.g., those explicitly defined in RevoScaleR functions via their transforms and transformFunc arguments or those defined implicitly via their formula or rowSelection arguments. The transformPackages argument may also be NULL, indicating that no packages outside rxGetOption("transformPackages") will be preloaded.
transformEnvir
user-defined environment to serve as a parent to all environments developed internally and used for variable data transformation. If transformEnvir = NULL, a new "hash" environment with parent baseenv() is used instead.
overwrite
logical value. If TRUE, an existing outFile will be overwritten, or if appending columns existing columns with the same name will be overwritten. overwrite is ignored if appending rows. Ignored for data frames.
removeMissings
logical value. If TRUE, rows with missing values will not be included in the output data.
rowsPerRead
number of rows to read for each chunk of data read from the input data source. Use this argument for finer control of the number of rows per block in the output data source. If greater than 0, blocksPerRead is ignored. Cannot be used if inFile is the same as outFile.
blocksPerRead
number of blocks to read for each chunk of data read from the data source. Ignored for data frames or if rowsPerRead is positive.
updateLowHigh
logical value. If FALSE, the low and high values for each variable in the inFile .xdf file will be copied to the header of each output file so that all output files reflect the global range of the data. If TRUE, each variable's low and high values are updated to reflect the range of values in the corresponding file, likely resulting in different low and high values for the same variable between output files. Note that when using rxSplit and the output is a list of data frames, the updateLowHigh argument has no effect.
maxRowsByCols
argument sent directly to the rxDataStep function behind the scenes when converting the output .xdf files (back) into a list of data frames. This parameter is provided primarily for the case where rxSplit is being used to split a .xdf file or RxXdfData data source into portions that are then read back into R as a list of data frames. In this case, maxRowsByCols provides a mechanism for the user to control the maximum number of of elements read from the output .xdf file in an effort to limit the amount of memory needed for storing each partition as a data frame object in R.
reportProgress
integer value with options:
0: no progress is reported.1: the number of processed rows is printed and updated.2: rows processed and timings are reported.3: rows processed and all timings are reported.
verbose
integer value. If 0, no additional output is printed. If 1, additional summary information is printed.
xdfCompressionLevel
integer in the range of -1 to 9. The higher the value, the greater the amount of compression - resulting in smaller files but a longer time to create them. If xdfCompressionLevel is set to 0, there will be no compression and files will be compatible with the 6.0 release of Revolution R Enterprise. If set to -1, a default level of compression will be used.
...
additional arguments to be passed directly to the function used to partition the data. For example,
Uniform Partition- afillargument with supported values are"left","center", or"right", can be used to place the remaining rows/blocks in the set of output files. For example, ifsortBy = "blocks",inFilehas15blocks, and the number of output files is6, the distribution of blocks for the set of6output files will be:fill = "left"- 3 3 3 2 2 2fill = "center"- 2 3 3 3 2 2fill = "right"- 2 2 2 3 3 3
Details
rxSplit: Use rxSplit as a general function to partition a data frame or .xdf file.
Behind the scenes, the rxSplitXdf function is called by rxSplit after converting the inData data source into
a (temporary) .xdf file. If both outFilesBase and outFileSuffixes are NULL (the default),
then the type of output is determined by the type of inData: if the inData is an .xdf file name
or an RxXdfData object, and list of RxXdfData data sources representing the new
split .xdf files is returned. If the inData is a data frame, then the output is returned
as a list of data frames.
If outFilesBase is an empty character string and outFileSuffixes is NULL, a list of
data frames is always returned.
In the case that a list of data frames is returned, the names of the list are in shortFileName.splitType.NumberOrFactor
format, e.g., iris.Species.versicolor or myXdfFile.rows.3.
rxSplitXdf: Use rxSplitXdf to partition an .xdf file.
The inFile .xdf file is uniformly partitioned (to the extent possible) and each partition is
written to a distinct user-specified file. As an example, if inFile contains a million rows, splitBy = "rows",
and the number of output files we specify to create is five, then each output file will contain two hundred
thousand observations, assuming none were dropped via a rowSelection argument specification.
The number of output files is controlled either directly or indirectly through a combination of
arguments: inFile, outFilesBase, outFileSuffixes, and numOutFiles.
In general, the values of these arguments are pasted together to form a character vector of output file paths,
with scalar values auto-expanded to vectors (of an appropriate size) prior to pasting.
This scheme allows the user to either specify directly the full paths to the output files they wish
to form or do so implicitly (and perhaps more conveniently) using various combinations of these arguments.
We illustrate the use of these combinations in the examples below, which are assumed to be run under Windows.
``
| Col 1 | Col 2 | Col 3 |
|---|---|---|
| INPUT ARGUMENTS | OUTPUT FILE VECTOR | |
inFile = "foo.xdf", numOutFiles = 3 |
"foo1.xdf", "foo2.xdf", "foo3.xdf" |
|
outFilesBase = "out", numOutFiles = 4 |
"out1.xdf", "out2.xdf", "out3.xdf", "out4.xdf" |
|
outFilesBase = "golf", outFileSuffixes = c("club", "tee", "score") |
"golfclub.xdf", "golftee.xdf", "golfscore.xdf" |
|
outFilesBase = "C:\\myDir\\", outFileSuffixes = c("a\\same", "b\\same", "c\\same") |
"C:\\myDir\\a\\same.xdf", "C:\\myDir\\b\\same.xdf", "C:\\myDir\\c\\same.xdf" |
|
outFilesBase = c("C:\\here\\file1.xdf", "D:\\there\\file2.xdf", "E:\\everywhere\\file3.xdf") |
"C:\\here\\file1.xdf", "D:\\there\\file2.xdf", "E:\\everywhere\\file3.xdf" |
Value
a list of data frames or an invisible list of RxXdfData data source objects corresponding to the created output files.
Author(s)
Microsoft Corporation Microsoft Technical Support
See Also
rxDataStep, rxImport, rxTransform
Examples
#####
# rxSplit Examples
# DF -> DF : Data frame input to list of data frames
IrisDFList <- rxSplit(iris, numOut = 3, reportProgress = 0, verbose = 0)
names(IrisDFList)
head(IrisDFList[[3]])
IrisDFList <- rxSplit(iris, splitByFactor = "Species", reportProgress = 0, verbose = 0)
names(IrisDFList)
head(IrisDFList[[1]])
# DF -> XDF : Data frame input to .xdf outputs (list of RxXdfData data sources)
irisXDFs <- rxSplit(iris, splitByFactor = "Species", outFilesBase = file.path(tempdir(),"iris"),
reportProgress = 0, verbose = 0, overwrite = TRUE)
print(irisXDFs)
invisible(sapply(irisXDFs, function(x) if (file.exists(x@file)) unlink(x@file)))
# XDF -> DF : .xdf file to a list of data frames
# Return a list of data frames instead of creating .xdf files by specifying
# outFilesBase = ""
XDF <- file.path(tempdir(), "iris.xdf")
rxDataStep(iris, XDF, overwrite = TRUE)
IrisDFList <- rxSplit(XDF, splitByFactor = "Species", outFilesBase = "",
reportProgress = 0, verbose = 0, overwrite = TRUE)
names(IrisDFList)
head(IrisDFList[[1]])
if (file.exists(XDF)) file.remove(XDF)
# Split the fourth graders data by gender and use row selection
# to collect information only on blue eyed children
fourthGradersXDF <- file.path(rxGetOption("sampleDataDir"), "fourthgraders.xdf")
rxSplit(fourthGradersXDF, splitByFactor = "male", outFilesBase = "",
rowSelection = (eyecolor == "Blue"))
# XDF -> XDF : .xdf file into multiple .xdf files
XDF <- tempfile(pattern = "iris", fileext = ".xdf")
outXDF1 <- tempfile(pattern = "irisOut", fileext = ".xdf")
outXDF2 <- tempfile(pattern = "irisOut", fileext = ".xdf")
rxDataStep(iris, XDF)
outFiles <- rxSplit(XDF, outFilesBase = tempdir(), outFileSuffixes = basename(c(outXDF1, outXDF2)),
reportProgress = 0, verbose = 0, overwrite = TRUE)
print(outFiles)
# Remove created files
invisible(sapply(outFiles, function(x) if (file.exists(x@file)) unlink(x@file)))
if (file.exists(XDF)) file.remove(XDF)
if (file.exists(outXDF1)) file.remove(outXDF1)
if (file.exists(outXDF2)) file.remove(outXDF2)
#####
# rxSplitXdf Examples
# Split CensusWorkers.xdf data into five files
# with a (nearly) uniform distribution of rows across the files.
# Put the files in a temporary directory and use "Census" as the
# basename for the files. Append each file with "-byRows" and
# an index indicating the file number in the set.
inFile <- file.path(rxGetOption("sampleDataDir"), "CensusWorkers")
outFilesBase <- file.path(tempdir(), "byRowsDir", "Census-byRows")
rxSplitXdf(inFile, outFilesBase = outFilesBase,
numOutFiles = 5, splitBy = "rows", verbose = 1)
# Obtain information from each of the resulting output files
# and remove the files along with the parent directory.
byRowFiles <- list.files(dirname(outFilesBase), full = TRUE)
infoByRows <- sapply(byRowFiles, rxGetInfo, simplify = FALSE)
unlink(dirname(outFilesBase), recursive = TRUE)
# Perform a similar split by blocks
outFilesBase <- file.path(tempdir(), "byBlocksDir", "Census-byBlocks")
rxSplitXdf(inFile, outFilesBase = outFilesBase,
numOutFiles = 5, splitBy = "blocks", verbose = 1)
# Obtain information from each of the resulting output files
# and remove the files along with the parent directory.
byBlockFiles <- list.files(dirname(outFilesBase), full = TRUE)
infoByBlocks <- sapply(byBlockFiles, rxGetInfo, simplify = FALSE)
unlink(dirname(outFilesBase), recursive = TRUE)
# Create a barplot comparing the two methods on the resulting
# number of rows in each output file. The barplot of the
# "rows" split case is uniform while the "blocks" split is
# highly non-uniform.
rows <- sapply(infoByRows, "[[", "numRows")
blocks <- sapply(infoByBlocks, "[[", "numRows")
numRowsData <- cbind(rows, blocks)
barplot(numRowsData, beside = TRUE,
main = "CensusWorkers Partition: Row Distribution",
xlab = "sortBy Method",
ylab = "Number of Rows",
legend.text = basename(rownames(numRowsData)),
args.legend = list(x = "topright"),
ylim = c(0, 1.5 * max(numRowsData)))
# Create a similar plot comparing the number of resulting blocks
# in the output .xdf files.
rows <- sapply(infoByRows, "[[", "numBlocks")
blocks <- sapply(infoByBlocks, "[[", "numBlocks")
numBlocksData <- cbind(rows, blocks)
barplot(numBlocksData, beside = TRUE,
main = "CensusWorkers Partition: Block Distribution",
xlab = "sortBy Method",
ylab = "Number of Blocks",
legend.text = basename(rownames(numBlocksData)),
args.legend = list(x = "topright"),
ylim = c(0, 1.5 * max(numBlocksData)))