makeJobCollection
takes multiple job ids and creates an object of class “JobCollection” which holds all
necessary information for the calculation with doJobCollection
. It is implemented as an environment
with the following variables:
file.dir
of the Registry.
work.dir
of the Registry.
Unique identifier of the job. Used to create names on the file system.
data.table
holding individual job information. See examples.
Location of the designated log file for this job.
Named list of of specified computational resources.
Location of the job description file (saved with link[base]{saveRDS}
on the file system.
integer(1)
Seed of the Registry.
character
with required packages to load via require
.
codecharacter with required packages to load via requireNamespace
.
character
with list of files to source before execution.
character
with list of files to load before execution.
character(1)
of the array environment variable specified by the cluster functions.
logical(1)
signaling if jobs were submitted using chunks.as.arrayjobs
.
If your ClusterFunctions uses a template, brew
will be executed in the environment of such
a collection. Thus all variables available inside the job can be used in the template.
makeJobCollection(ids = NULL, resources = list(), reg = getDefaultRegistry())
ids | [ |
---|---|
resources | [ |
reg | [ |
[JobCollection
].
Other JobCollection:
doJobCollection()
batchtools:::example_push_temp(1) tmp = makeRegistry(file.dir = NA, make.default = FALSE, packages = "methods")#>#>#># resources are usually set in submitJobs() jc = makeJobCollection(1:3, resources = list(foo = "bar"), reg = tmp) ls(jc)#> [1] "array.jobs" "array.var" "compress" "file.dir" "job.hash" #> [6] "job.name" "jobs" "load" "log.file" "namespaces" #> [11] "packages" "resources" "seed" "source" "uri" #> [16] "work.dir"jc$resources#> $foo #> [1] "bar" #>