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 |
[ |
... |
[ANY] |
args |
[ |
more.args |
[ |
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)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.