distributeFiles(files, to = tempdir(),
protocol = c("R", "RCP", "SCP"), hierarchicallyDist = FALSE,
master=TRUE, delExistTo=FALSE,
full.names=TRUE,
cluster, verbose = getOption("verbose"))
character
vector containing the names of the files.character
that defines the path where the files should be stored at the slaves. Default: tempdir()character
that defines the Copy-Protocol: "R", "RCP", "SCP"TRUE
data will be hierarchically distributed to all slaves.
If FALSE
at every slave only a part of data is available.TRUE
all data will be copied to the 'to' directory at the master node. Default = TRUETRUE
directory 'to' will be deleted at master and all nodes first. Default = FALSETRUE
, the directory path is prepended to the file names (in slot CELfiles).
If FALSE
, only the file names are returned ..affyParaInternalEnv$cl
will be used.TRUE
it writes out some messages. default: getOption("verbose")character
that defines the path where the files are located at the slaves.characters
, how the files are distributed to the slaves. Depending on full.names
only the filenames or path/filenames.to
directory at the slaves. If hierarchicallyDist
is TRUE
, all slaves change the files among each other and in the end at every slave all files are located. (But this is not necessary for distributed computing with the affyPara
package.
For using this function a computer cluster using the SNOW package has to be started.
Starting the cluster with the command makeCluster
generates an cluster object in the affyPara environment (.affyParaInternalEnv) and
no cluster object in the global environment. The cluster object in the affyPara environment will be used as default cluster object,
therefore no more cluster object handling is required.
The makeXXXcluster
functions from the package SNOW can be used to create an cluster object in the global environment and
to use it for the preprocessing functions.library(affyPara)
makeCluster(10)
path <- "tmp/CELfiles"
CELfiles <- list.files(path,full.names=TRUE)
distList <- distributeFiles(CELfiles, protocol="RCP", verbose=TRUE)
stopCluster()
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