Map Operation for Batch Systems
A parallel and asynchronous Map/mapply for batch systems.
Note that this function only defines the computational jobs.
The actual computation is started with submitJobs.
Results and partial results can be collected with reduceResultsList, reduceResults or
loadResult.
batchMap( fun, ..., args = list(), more.args = list(), reg = getDefaultRegistry() )
fun |
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... |
[ANY] |
args |
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more.args |
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reg |
[ |
[data.table] with ids of added jobs stored in column “job.id”.
# example using "..." and more.args tmp = makeRegistry(file.dir = NA, make.default = FALSE) f = function(x, y) x^2 + y ids = batchMap(f, x = 1:10, more.args = list(y = 100), reg = tmp) getJobPars(reg = tmp) testJob(6, reg = tmp) # 100 + 6^2 = 136 # vector recycling tmp = makeRegistry(file.dir = NA, make.default = FALSE) f = function(...) list(...) ids = batchMap(f, x = 1:3, y = 1:6, reg = tmp) getJobPars(reg = tmp) # example for an expand.grid()-like operation on parameters tmp = makeRegistry(file.dir = NA, make.default = FALSE) ids = batchMap(paste, args = data.table::CJ(x = letters[1:3], y = 1:3), reg = tmp) getJobPars(reg = tmp) testJob(6, reg = tmp)
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