makeJobCollection {batchtools} | R Documentation |
JobCollection Constructor
Description
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
file.dir
of the Registry.- work.dir:
work.dir
of the Registry.- job.hash
Unique identifier of the job. Used to create names on the file system.
- jobs
data.table
holding individual job information. See examples.- log.file
Location of the designated log file for this job.
- resources:
Named list of of specified computational resources.
- uri
Location of the job description file (saved with
link[base]{saveRDS}
on the file system.- seed
integer(1)
Seed of the Registry.- packages
character
with required packages to load viarequire
.- namespaces
codecharacter with required packages to load via
requireNamespace
.- source
character
with list of files to source before execution.- load
character
with list of files to load before execution.- array.var
character(1)
of the array environment variable specified by the cluster functions.- array.jobs
logical(1)
signaling if jobs were submitted usingchunks.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.
Usage
makeJobCollection(ids = NULL, resources = list(), reg = getDefaultRegistry())
Arguments
ids |
[ |
resources |
[ |
reg |
[ |
Value
[JobCollection
].
See Also
Other JobCollection:
doJobCollection()
Examples
tmp = makeRegistry(file.dir = NA, make.default = FALSE, packages = "methods")
batchMap(identity, 1:5, reg = tmp)
# resources are usually set in submitJobs()
jc = makeJobCollection(1:3, resources = list(foo = "bar"), reg = tmp)
ls(jc)
jc$resources