Create a resources argument for tar_target()
or tar_option_set().
Usage
tar_resources(
aws = tar_option_get("resources")$aws,
clustermq = tar_option_get("resources")$clustermq,
crew = tar_option_get("resources")$crew,
custom_format = tar_option_get("resources")$custom_format,
feather = tar_option_get("resources")$feather,
fst = tar_option_get("resources")$fst,
future = tar_option_get("resources")$future,
gcp = tar_option_get("resources")$gcp,
network = tar_option_get("resources")$network,
parquet = tar_option_get("resources")$parquet,
qs = tar_option_get("resources")$qs,
repository_cas = tar_option_get("resources")$repository_cas,
url = tar_option_get("resources")$url
)Arguments
- aws
Output of function
tar_resources_aws(). Amazon Web Services (AWS) S3 storage settings fortar_target(..., repository = "aws"). See the cloud storage section of https://books.ropensci.org/targets/data.html for details for instructions.- clustermq
Output of function
tar_resources_clustermq(). Optionalclustermqsettings fortar_make_clustermq(), including thelog_workerandtemplatearguments ofclustermq::workers().clustermqworkers are persistent, so there is not a one-to-one correspondence between workers and targets. Theclustermqresources apply to the workers, not the targets. So the correct way to assignclustermqresources is throughtar_option_set(), nottar_target().clustermqresources in individualtar_target()calls will be ignored.- crew
Output of function
tar_resources_crew()with target-specific settings for integration with thecrewR package. These settings are arguments to thepush()method of the controller or controller group object which control things like auto-scaling behavior and the controller to use in the case of a controller group.- custom_format
Output of function
tar_resources_custom_format()with configuration details fortar_format()storage formats.- feather
Output of function
tar_resources_feather(). Non-default arguments toarrow::read_feather()andarrow::write_feather()forarrow/feather-based storage formats. Applies to all formats ending with the"_feather"suffix. For details on formats, see theformatargument oftar_target().- fst
Output of function
tar_resources_fst(). Non-default arguments tofst::read_fst()andfst::write_fst()forfst-based storage formats. Applies to all formats ending with"fst"in the name. For details on formats, see theformatargument oftar_target().- future
Output of function
tar_resources_future(). Optionalfuturesettings fortar_make_future(), including theresourcesargument offuture::future(), which can include values to insert in template placeholders infuture.batchtoolstemplate files. This is how to supply theresourcesargument offuture::future()fortargets. Resources supplied throughfuture::plan()andfuture::tweak()are completely ignored.- gcp
Output of function
tar_resources_gcp(). Google Cloud Storage bucket settings fortar_target(..., repository = "gcp"). See the cloud storage section of https://books.ropensci.org/targets/data.html for details for instructions.- network
Output of function
tar_resources_network(). Settings to configure how to handle unreliable network connections in the case of uploading, downloading, and checking data in situations that rely on network file systems or HTTP/HTTPS requests. Examples include retries and timeouts for internal storage management operations forstorage = "worker"orformat = "file"(on network file systems),format = "url",repository = "aws", andrepository = "gcp". These settings do not apply to actions you take in the custom R command of the target.- parquet
Output of function
tar_resources_parquet(). Non-default arguments toarrow::read_parquet()andarrow::write_parquet()forarrow/parquet-based storage formats. Applies to all formats ending with the"_parquet"suffix. For details on formats, see theformatargument oftar_target().- qs
Output of function
tar_resources_qs(). Non-default arguments toqs2::qs_read()andqs2::qs_save()for targets withformat = "qs". For details on formats, see theformatargument oftar_target().- repository_cas
Output of function
tar_resources_repository_cas()with configuration details fortar_repository_cas()storage repositories.- url
Output of function
tar_resources_url(). Non-default settings for storage formats ending with the"_url"suffix. These settings include thecurlhandle for extra control over HTTP requests. For details on formats, see theformatargument oftar_target().
Value
A list of objects of class "tar_resources" with
non-default settings of various optional backends for data storage
and high-performance computing.
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().)
See also
Other resources:
tar_resources_aws(),
tar_resources_clustermq(),
tar_resources_crew(),
tar_resources_custom_format(),
tar_resources_feather(),
tar_resources_fst(),
tar_resources_future(),
tar_resources_gcp(),
tar_resources_network(),
tar_resources_parquet(),
tar_resources_qs(),
tar_resources_repository_cas(),
tar_resources_url()
Examples
# Somewhere in you target script file (usually _targets.R):
tar_target(
name,
command(),
format = "qs",
resources = tar_resources(
qs = tar_resources_qs(preset = "fast"),
future = tar_resources_future(resources = list(n_cores = 1))
)
)
#> <tar_stem>
#> name: name
#> description:
#> command:
#> command()
#> format: qs
#> repository: local
#> iteration method: vector
#> error mode: stop
#> memory mode: auto
#> storage mode: worker
#> retrieval mode: auto
#> deployment mode: worker
#> priority: 0
#> resources:
#> future: <environment>
#> qs: <environment>
#> cue:
#> seed: TRUE
#> file: TRUE
#> iteration: TRUE
#> repository: TRUE
#> format: TRUE
#> depend: TRUE
#> command: TRUE
#> mode: thorough
#> packages:
#> targets
#> stats
#> graphics
#> grDevices
#> utils
#> datasets
#> methods
#> base
#> library:
#> NULL