ClusterFunctionsMulticore.addExperiments() in combination with
combination method "bind" and repls > 1 where
experiments have been duplicated.addExperiments() now also accepts a vector of
replications (instead of a single scalar value) for argument
repls.ClusterFunctionsSlurm.waitForJobs()batchMap() now supports unnamed
more.args.delayedAssign().data.table from Depends to
Imports. User scripts might need to explicitly attach
data.table via library() now.ClusterFunctionsMulticore.system2() for R-devel (to be
released as R-4.0.0).compress to select the
compression algorithm (passed down to saveRDS()).chunkIds().fs.timeout in the cluster
function constructor is 0 (was NA
before).findConfFile() and
findTemplateFile().TMPDIR instead of the R session’s
temporary directory.fs is now used internally for all file system
operations.getStatus() now includes a time
stamp.chunk() now optionally shuffles the ids before
chunking.submitJobs().blas.threads and omp.threads.assertRegistry().unwrap() as alias to
flatten(). The latter causes a name clash with package
purrr and will be deprecated in a future version.waitForJobs().foreach is now supported for nested
parallelization as an alternative to parallelMap.flatten() to manually unnest/unwrap
lists in data frames.getProblemIds() and
getAlgorithmIds(). Instead, you can just access
reg$problems or reg$algorithms,
respectively.loadRegistry().ExperimentRegistry.waitForJobs() and
submitJobs() can now be set via the configuration
file.waitForJobs() has been reworked to allow control over
the heuristic to detect expired jobs. Jobs are treated as expired if
they have been submitted but are not detected on the system for
expire.after iterations (default 3 iterations, before 1
iteration).writeable for loadRegistry()
to allow loading registries explicitly as read-only.update.paths from
loadRegistry(). Paths are always updated, but the registry
on the file system remains unchanged unless loaded in read-write
mode.ClusterFunctionsSlurm now come with an experimental
nodename argument. If set, all communication with the master is handled
via SSH which effectively allows you to submit jobs from your local
machine instead of the head node. Note that mounting the file system
(e.g., via SSHFS) is mandatory.file.dir with special chars like
whitespace.findExperiments() (argument
ids is now first).addExperiments() now warns if a design is passed as
data.frame with factor columns and
stringsAsFactors is TRUE.setJobNames() and
getJobNames() to control the name of jobs on batch systems.
Templates should be adapted to use job.name instead of
job.hash for naming.flatten of getJobResources(),
getJobPars() and getJobTable() is deprecated
and will be removed. Future versions of the functions will behave like
flatten is set to FALSE explicitly. Single
resources/parameters must be extracted manually (or with
tidyr::unnest()).findStarted(),
findNotStarted() and getStatus().findExperiments() now performs an exact string match
(instead of matching substrings) for patterns specified via
prob.name and algo.name. For substring
matching, use prob.pattern or algo.pattern,
respectively.reduceResultsDataTable()
fill, now is always TRUEflatten to control if the result should be
represented as a column of lists or flattened as separate columns.
Defaults to a backward-compatible heuristic, similar to
getJobPars.n.array.jobs has been
removed from JobCollection in favor of the new variable
array.jobs (logical).findExperiments() now has two additional arguments to
match using regular expressions. The possibility to prefix a string with
“~” to enable regular expression matching has been removed.batchReduce().estimateRuntimes().removeRegistry().missing.val has been added to
reduceResultsList() and
reduceResultsDataTable() and removed from
loadResult() and batchMapResults().makeClusterFunctionsTorque which now must be called via
makeClusterFunctionsTORQUE()chunkIds() has been deprecated. Use
chunk(), lpt() or binpack()
instead.ClusterFunctionsLSF and
ClusterFunctionsOpenLava (thanks to @phaverty).NULL results in
reduceResultsList()getJobTable() returned
difftimes with the wrong unit (e.g., in minutes instead of
seconds).ClusterFunctionsDocker.Initial CRAN release. See the vignette for a brief comparison with BatchJobs/BatchExperiments.