View source: R/tar_resources_future.R
tar_resources_future | R Documentation |
future
high-performance computingCreate the future
argument of tar_resources()
to specify optional high-performance computing settings
for tar_make_future()
.
This is how to supply the resources
argument of future::future()
for targets
.
Resources supplied through
future::plan()
and future::tweak()
are completely ignored.
For details, see the documentation of the future
R package
and the corresponding argument names in this help file.
tar_resources_future(
plan = NULL,
resources = targets::tar_option_get("resources")$future$resources
)
plan |
A |
resources |
Named list, |
Object of class "tar_resources_future"
, to be supplied
to the future
argument of tar_resources()
.
Functions tar_target()
and tar_option_set()
each takes an optional resources
argument to supply
non-default settings of various optional backends for data storage
and high-performance computing. The tar_resources()
function
is a helper to supply those settings in the correct manner.
In targets
version 0.12.2 and above, resources are inherited one-by-one
in nested fashion from tar_option_get("resources")
.
For example, suppose you set
tar_option_set(resources = tar_resources(aws = my_aws))
,
where my_aws
equals tar_resources_aws(bucket = "x", prefix = "y")
.
Then, tar_target(data, get_data()
will have bucket "x"
and
prefix "y"
. In addition, if new_resources
equals
tar_resources(aws = tar_resources_aws(bucket = "z")))
, then
tar_target(data, get_data(), resources = new_resources)
will use the new bucket "z"
, but it will still use the prefix "y"
supplied through tar_option_set()
. (In targets
0.12.1 and below,
options like prefix
do not carry over from tar_option_set()
if you
supply non-default resources to tar_target()
.)
Other resources:
tar_resources()
,
tar_resources_aws()
,
tar_resources_clustermq()
,
tar_resources_crew()
,
tar_resources_custom_format()
,
tar_resources_feather()
,
tar_resources_fst()
,
tar_resources_gcp()
,
tar_resources_network()
,
tar_resources_parquet()
,
tar_resources_qs()
,
tar_resources_repository_cas()
,
tar_resources_url()
# Somewhere in you target script file (usually _targets.R):
tar_target(
name,
command(),
resources = tar_resources(
future = tar_resources_future(resources = list(n_cores = 2))
)
)
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