This function is like tar_make() except that targets run in parallel with persistent clustermq workers. It requires that you set global options like clustermq.scheduler and clustermq.template inside the _targets.R script. clustermq is not a strict dependency of targets, so you must install clustermq yourself.

  names = NULL,
  reporter = "verbose",
  workers = 1L,
  log_worker = FALSE,
  callr_function = callr::r,
  callr_arguments = list()



Names of the targets to build or check. Set to NULL to check/build all the targets (default). Otherwise, you can supply symbols, a character vector, or tidyselect helpers like starts_with().


Character of length 1, name of the reporter to user. Controls how messages are printed as targets run in the pipeline. Choices:

  • "verbose": print one message for each target that runs (default).

  • "silent": print nothing.

  • "timestamp": print a time-stamped message for each target that runs.

  • "summary": print a running total of the number of each targets in each status category (queued, running, skipped, build, canceled, or errored).


Positive integer, number of persistent clustermq workers to create.


Logical, whether to write a log file for each worker. Same as the log_worker argument of clustermq::Q() and clustermq::workers().


A function from callr to start a fresh clean R process to do the work. Set to NULL to run in the current session instead of an external process (but restart your R session just before you do in order to clear debris out of the global environment). callr_function needs to be NULL for interactive debugging, e.g. tar_option_set(debug = "your_target"). However, callr_function should not be NULL for serious reproducible work.


A list of arguments to callr_function.


NULL except if callr_function = callr::r_bg(), in which case a handle to the callr background process is returned. Either way, the value is invisibly returned.


To use with a cluster, you will need to set the global options clustermq.scheduler and clustermq.template inside _targets.R. To read more about configuring clustermq for your scheduler, visit # nolint and navigate to the appropriate link under "Setting up the scheduler". Wildcards in the template file are filled in with elements from tar_option_get("resources").


if (!identical(tolower([["sysname"]]), "windows")) { if (identical(Sys.getenv("TAR_LONG_EXAMPLES"), "true")) { tar_dir({ # tar_dir() runs code from a temporary directory. tar_script({ options(clustermq.scheduler = "multicore") # Does not work on Windows. tar_option_set() list(tar_target(x, 1 + 1)) }, ask = FALSE) tar_make_clustermq() }) } }