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#' @title Target resources: `clustermq` high-performance computing
#' @export
#' @family resources
#' @description Create the `clustermq` argument of `tar_resources()`
#' to specify optional high-performance computing settings
#' for `tar_make_clustermq()`.
#' For details, see the documentation of the `clustermq` R package
#' and the corresponding argument names in this help file.
#' @details `clustermq` workers are *persistent*,
#' so there is not a one-to-one correspondence between workers and targets.
#' The `clustermq` resources apply to the workers, not the targets.
#' So the correct way to assign `clustermq` resources is through
#' [tar_option_set()], not [tar_target()]. `clustermq` resources
#' in individual [tar_target()] calls will be ignored.
#' @inheritSection tar_resources Resources
#' @return Object of class `"tar_resources_clustermq"`, to be supplied
#' to the `clustermq` argument of `tar_resources()`.
#' @param template Named list, `template` argument to
#' `clustermq::workers()`. Defaults to an empty list.
#' @examples
#' # Somewhere in you target script file (usually _targets.R):
#' tar_target(
#' name,
#' command(),
#' resources = tar_resources(
#' clustermq = tar_resources_clustermq(template = list(n_cores = 2))
#' )
#' )
tar_resources_clustermq <- function(
template = targets::tar_option_get("resources")$clustermq$template
) {
template <- template %|||% list()
out <- resources_clustermq_init(
template = template
)
resources_validate(out)
out
}
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