Create a PSOCK cluster of R workers for parallel processing

The makeClusterPSOCK() function creates a cluster of R workers for parallel processing. These R workers may be background R sessions on the current machine, R sessions on external machines (local or remote), or a mix of such. For external workers, the default is to use SSH to connect to those external machines. This function works similarly to makePSOCKcluster() of the parallel package, but provides additional and more flexibility options for controlling the setup of the system calls that launch the background R workers, and how to connect to external machines.

  makeNode = makeNodePSOCK,
  port = c("auto", "random"),
  autoStop = FALSE,
  verbose = getOption("future.debug", FALSE)

makeNodePSOCK( worker = "localhost", master = NULL, port, connectTimeout = getOption("future.makeNodePSOCK.connectTimeout", as.numeric(Sys.getenv("R_FUTURE_MAKENODEPSOCK_CONNECTTIMEOUT", 2 * 60))), timeout = getOption("future.makeNodePSOCK.timeout", as.numeric(Sys.getenv("R_FUTURE_MAKENODEPSOCK_TIMEOUT", 30 * 24 * 60 * 60))), rscript = NULL, homogeneous = NULL, rscript_args = NULL, rscript_startup = NULL, rscript_libs = NULL, methods = TRUE, useXDR = TRUE, outfile = "/dev/null", renice = NA_integer_, rshcmd = getOption("future.makeNodePSOCK.rshcmd", Sys.getenv("R_FUTURE_MAKENODEPSOCK_RSHCMD")), user = NULL, revtunnel = TRUE, rshlogfile = NULL, rshopts = getOption("future.makeNodePSOCK.rshopts", Sys.getenv("R_FUTURE_MAKENODEPSOCK_RSHOPTS")), rank = 1L, manual = FALSE, dryrun = FALSE, verbose = FALSE )


The hostnames of workers (as a character vector) or the number of localhost workers (as a positive integer).


A function that creates a "SOCKnode" or "SOCK0node" object, which represents a connection to a worker.


The port number of the master used for communicating with all the workers (via socket connections). If an integer vector of ports, then a random one among those is chosen. If "random", then a random port in is chosen from 11000:11999, or from the range specified by environment variable R_FUTURE_RANDOM_PORTS. If "auto" (default), then the default (single) port is taken from environment variable R_PARALLEL_PORT, otherwise "random" is used. Note, do not use this argument to specify the port number used by rshcmd, which typically is an SSH client. Instead, if the SSH daemon runs on a different port than the default 22, specify the SSH port by appending it to the hostname, e.g. "" or via SSH options -p, e.g. rshopts = c("-p", "2200").

Optional arguments passed to makeNode(workers[i], ..., rank = i) where i = seq_along(workers).


If TRUE, the cluster will be automatically stopped


If TRUE, informative messages are outputted.


The hostname or IP number of the machine where the worker should run.


The hostname or IP number of the master / calling machine, as known to the workers. If NULL (default), then the default is[["nodename"]] unless worker is localhost or revtunnel = TRUE in case it is "localhost".


The maximum time (in seconds) allowed for each socket connection between the master and a worker to be established (defaults to 2 minutes). See note below on current lack of support on Linux and macOS systems.


The maximum time (in seconds) allowed to pass without the master and a worker communicate with each other (defaults to 30 days).

rscript, homogeneous

The system command for launching Rscript on the worker and whether it is installed in the same path as the calling machine or not. For more details, see below.


Additional arguments to Rscript (as a character vector). This argument can be used to customize the R environment of the workers before they launches. For instance, use rscript_args = c("-e", shQuote('setwd("/path/to")')) to set the working directory to /path/to on all workers.


An R expression or a character vector of R code, or a list with a mix of these, that will be evaluated on the R worker prior to launching the worker's event loop. For instance, use rscript_startup = 'setwd("/path/to")' to set the working directory to /path/to on all workers.


A character vector of R library paths that will be used for the library search path of the R workers. An asterisk ("*") will be resolved as the current .libPaths() on the worker. That is, to prepend a folder, instead of replacing the existing ones, use rscript_libs = c("new_folder", "*").


If TRUE, then the methods package is also loaded.


If TRUE, the communication between master and workers, which is binary, will use big-endian (XDR).


Where to direct the stdout and stderr connection output from the workers. If NULL, then no redirection of output is done, which means that the output is relayed in the terminal on the local computer. On Windows, the output is only relayed when running R from a terminal but not from a GUI.


A numerical 'niceness' (priority) to set for the worker processes.

rshcmd, rshopts

The command (character vector) to be run on the master to launch a process on another host and any additional arguments (character vector). These arguments are only applied if machine is not localhost. For more details, see below.


(optional) The user name to be used when communicating with another host.


If TRUE, a reverse SSH tunnel is set up for each worker such#' that the worker R process sets up a socket connection to its local port (port - rank + 1) which then reaches the master on port port. If FALSE, then the worker will try to connect directly to port port on master. For more details, see below.


(optional) If a filename, the output produced by the rshcmd call is logged to this file, of if TRUE, then it is logged to a temporary file. The log file name is available as an attribute as part of the return node object. Warning: This only works with SSH clients that support option -E out.log.


A unique one-based index for each worker (automatically set).


If TRUE the workers will need to be run manually. The command to run will be displayed.


If TRUE, nothing is set up, but a message suggesting how to launch the worker from the terminal is outputted. This is useful for troubleshooting.


An object of class c("SOCKcluster", "cluster") consisting of a list of "SOCKnode" or "SOCK0node" workers.

makeNodePSOCK() returns a "SOCKnode" or "SOCK0node" object representing an established connection to a worker.

Definition of localhost

A hostname is considered to be localhost if it equals:

  • "localhost",

  • "", or


It is also considered localhost if it appears on the same line as the value of[["nodename"]] in file /etc/hosts.

Default SSH client and options (arguments rshcmd and rshopts)

Arguments rshcmd and rshopts are only used when connecting to an external host.

The default method for connecting to an external host is via SSH and the system executable for this is given by argument rshcmd. The default is given by option future.makeNodePSOCK.rshcmd. If that is not set, then the default is to use ssh. Most Unix-like systems, including macOS, have ssh preinstalled on the PATH. This is also true for recent Windows 10 (since version 1803; April 2018) (*).

For Windows systems prior to Windows 10, it is less common to find ssh on the PATH. Instead it is more likely that such systems have the PuTTY software and its SSH client plink installed. PuTTY puts itself on the system PATH when installed, meaning this function will find PuTTY automatically if installed. If not, to manually set specify PuTTY as the SSH client, specify the absolute pathname of plink.exe in the first element and option -ssh in the second as in rshcmd = c("C:/Path/PuTTY/plink.exe", "-ssh"). This is because all elements of rshcmd are individually "shell" quoted and element rshcmd[1] must be on the system PATH.

Furthermore, when running R from RStudio on Windows, the ssh client that is distributed with RStudio will also be considered. This client, which is from MinGW MSYS, is searched for in the folder given by the RSTUDIO_MSYS_SSH environment variable - a variable that is (only) set when running RStudio.

You can override the default set of SSH clients that are searched for by specifying them in rshcmd using the format <...>, e.g. rshcmd = c("<rstudio-ssh>", "<putty-plink>", "<ssh>"). See below for examples.

If no SSH-client is found, an informative error message is produced.

(*) Known issue with the Windows 10 SSH client: There is a bug in the SSH client of Windows 10 that prevents it to work with reverse SSH tunneling (; Oct 2018). Because of this, it is recommended to use the PuTTY SSH client or the RStudio SSH client until this bug has been resolved in Windows 10.

Additional SSH options may be specified via argument rshopts, which defaults to option future.makeNodePSOCK.rshopts. For instance, a private SSH key can be provided as rshopts = c("-i", "~/.ssh/my_private_key"). PuTTY users should specify a PuTTY PPK file, e.g. rshopts = c("-i", "C:/Users/joe/.ssh/my_keys.ppk"). Contrary to rshcmd, elements of rshopts are not quoted.

Accessing external machines that prompts for a password

IMPORTANT: With one exception, it is not possible to for these functions to log in and launch R workers on external machines that requires a password to be entered manually for authentication. The only known exception is the PuTTY client on Windows for which one can pass the password via command-line option -pw, e.g. rshopts = c("-pw", "MySecretPassword").

Note, depending on whether you run R in a terminal or via a GUI, you might not even see the password prompt. It is also likely that you cannot enter a password, because the connection is set up via a background system call.

The poor man's workaround for setup that requires a password is to manually log into the each of the external machines and launch the R workers by hand. For this approach, use manual = TRUE and follow the instructions which include cut'n'pasteable commands on how to launch the worker from the external machine.

However, a much more convenient and less tedious method is to set up key-based SSH authentication between your local machine and the external machine(s), as explain below.

Accessing external machines via key-based SSH authentication

The best approach to automatically launch R workers on external machines over SSH is to set up key-based SSH authentication. This will allow you to log into the external machine without have to enter a password.

Key-based SSH authentication is taken care of by the SSH client and not R. To configure this, see the manuals of your SSH client or search the web for "ssh key authentication".

Reverse SSH tunneling

The default is to use reverse SSH tunneling (revtunnel = TRUE) for workers running on other machines. This avoids the complication of otherwise having to configure port forwarding in firewalls, which often requires static IP address as well as privileges to edit the firewall, something most users don't have. It also has the advantage of not having to know the internal and / or the public IP address / hostname of the master. Yet another advantage is that there will be no need for a DNS lookup by the worker machines to the master, which may not be configured or is disabled on some systems, e.g. compute clusters.

Default value of argument rscript

If homogeneous is FALSE, the rscript defaults to "Rscript", i.e. it is assumed that the Rscript executable is available on the PATH of the worker. If homogeneous is TRUE, the rscript defaults to file.path(R.home("bin"), "Rscript"), i.e. it is basically assumed that the worker and the caller share the same file system and R installation.

Default value of argument homogeneous

The default value of homogeneous is TRUE if and only if either of the following is fulfilled:

  • worker is localhost

  • revtunnel is FALSE and master is localhost

  • worker is neither an IP number nor a fully qualified domain name (FQDN). A hostname is considered to be a FQDN if it contains one or more periods

In all other cases, homogeneous defaults to FALSE.

Connection time out

Argument connectTimeout does not work properly on Unix and macOS due to limitation in R itself. For more details on this, please see R-devel thread 'BUG?: On Linux setTimeLimit() fails to propagate timeout error when it occurs (works on Windows)' on 2016-10-26 ( When used, the timeout will eventually trigger an error, but it won't happen until the socket connection timeout timeout itself happens.

Communication time out

If there is no communication between the master and a worker within the timeout limit, then the corresponding socket connection will be closed automatically. This will eventually result in an error in code trying to access the connection.


Failing to set up local workers: When setting up a cluster of localhost workers, that is, workers running on the same machine as the master R process, occasionally a connection to a worker ("cluster node") may fail to be set up. When this occurs, an informative error message with troubleshooting suggestions will be produced. The most common reason for such localhost failures is due to port clashes. Retrying will often resolve the problem.

Failing to set up remote workers: A cluster of remote workers runs R processes on external machines. These external R processes are launched over, typically, SSH to the remote machine. For this to work, each of the remote machines needs to have R installed, which preferably is of the same version as what is on the main machine. For this to work, it is required that one can SSH to the remote machines. Ideally, the SSH connections use authentication based on public-private SSH keys such that the set up of the remote workers can be fully automated (see above). If makeClusterPSOCK() fails to set up one or more remote R workers, then an informative error message is produced. There are a few reasons for failing to set up remote workers. If this happens, start by asserting that you can SSH to the remote machine and launch Rscript by calling something like:

{local}$ ssh -l alice
{remote}$ Rscript --version
R scripting front-end version 3.6.1 (2019-07-05)
{remote}$ logout

When you have confirmed the above to work, then confirm that you can achieve the same in a single command-line call;

{local}$ ssh -l alice Rscript --version
R scripting front-end version 3.6.1 (2019-07-05)

The latter will assert that you have proper startup configuration also for non-interactive shell sessions on the remote machine.

  • makeClusterPSOCK
  • makeNodePSOCK
## NOTE: Drop 'dryrun = TRUE' below in order to actually connect.  Add
## 'verbose = TRUE' if you run into problems and need to troubleshoot.

## EXAMPLE: Two workers on the local machine
workers <- c("localhost", "localhost")
cl <- makeClusterPSOCK(workers, dryrun = TRUE)

## EXAMPLE: Three remote workers
## Setup of three R workers on two remote machines are set up
workers <- c("", "", "")
cl <- makeClusterPSOCK(workers, dryrun = TRUE)

## EXAMPLE: Local and remote workers
## Same setup when the two machines are on the local network and
## have identical software setups
cl <- makeClusterPSOCK(
  revtunnel = FALSE, homogeneous = TRUE,
  dryrun = TRUE

## EXAMPLE: Remote workers with specific setup
## Setup of remote worker with more detailed control on
## authentication and reverse SSH tunnelling
cl <- makeClusterPSOCK(
  "", user = "johnny",
  ## Manual configuration of reverse SSH tunnelling
  revtunnel = FALSE,
  rshopts = c("-v", "-R 11000:gateway:11942"),
  master = "gateway", port = 11942,
  ## Run Rscript nicely and skip any startup scripts
  rscript = c("nice", "/path/to/Rscript"),
  rscript_args = c("--vanilla"),
  dryrun = TRUE

## EXAMPLE: Two workers running in Docker on the local machine
## Setup of 2 Docker workers running rocker/r-parallel
cl <- makeClusterPSOCK(
  rep("localhost", times = 2L),
  ## Launch Rscript inside Docker container
  rscript = c(
    "docker", "run", "--net=host", "rocker/r-parallel",
  ## IMPORTANT: Because Docker runs inside a virtual machine (VM) on macOS
  ## and Windows (not Linux), when the R worker tries to connect back to
  ## the default 'localhost' it will fail, because the main R session is
  ## not running in the VM, but outside on the host.  To reach the host on
  ## macOS and Windows, make sure to use master = "host.docker.internal"
  # master = "host.docker.internal",  # <= macOS & Windows
  dryrun = TRUE

## EXAMPLE: Two workers running in Singularity on the local machine
## Setup of 2 Singularity workers running rocker/r-parallel
cl <- makeClusterPSOCK(
  rep("localhost", times = 2L),
  ## Launch Rscript inside Docker container
  rscript = c(
    "singularity", "exec", "docker://rocker/r-parallel",
  dryrun = TRUE

## EXAMPLE: One worker running in udocker on the local machine
## Setup of a single worker running rocker/r-parallel
cl <- makeClusterPSOCK(
  ## Launch Rscript inside Docker container (using udocker)
  rscript = c(
    "", "run", "rocker/r-parallel",
  ## Manually launch parallel workers
  ## (need double shQuote():s because drops one level)
  rscript_args = c(
    "-e", shQuote(shQuote("parallel:::.slaveRSOCK()"))
  dryrun = TRUE

## EXAMPLE: Remote worker running on AWS
## Launching worker on Amazon AWS EC2 running one of the
## Amazon Machine Images (AMI) provided by RStudio
## (
public_ip <- ""
ssh_private_key_file <- "~/.ssh/my-private-aws-key.pem"
cl <- makeClusterPSOCK(
  ## Public IP number of EC2 instance
  ## User name (always 'ubuntu')
  user = "ubuntu",
  ## Use private SSH key registered with AWS
  rshopts = c(
    "-o", "StrictHostKeyChecking=no",
    "-o", "IdentitiesOnly=yes",
    "-i", ssh_private_key_file
  ## Set up .libPaths() for the 'ubuntu' user
  ## and then install the future package
  rscript_startup = quote(local({
    p <- Sys.getenv("R_LIBS_USER")
    dir.create(p, recursive = TRUE, showWarnings = FALSE)
  dryrun = TRUE

## EXAMPLE: Remote worker running on GCE
## Launching worker on Google Cloud Engine (GCE) running a
## container based VM (with a #cloud-config specification)
public_ip <- ""
user <- "johnny"
ssh_private_key_file <- "~/.ssh/google_compute_engine"
cl <- makeClusterPSOCK(
  ## Public IP number of GCE instance
  ## User name (== SSH key label (sic!))
  user = user,
  ## Use private SSH key registered with GCE
  rshopts = c(
    "-o", "StrictHostKeyChecking=no",
    "-o", "IdentitiesOnly=yes",
    "-i", ssh_private_key_file
  ## Launch Rscript inside Docker container
  rscript = c(
    "docker", "run", "--net=host", "rocker/r-parallel",
  dryrun = TRUE

## EXAMPLE: Remote worker running on Linux from Windows machine
## Connect to remote Unix machine '' on port 2200
## as user 'bob' from a Windows machine with PuTTY installed.
## Using the explicit special rshcmd = "<putty-plink>", will force
## makeClusterPSOCK() to search for and use the PuTTY plink software,
## preventing it from using other SSH clients on the system search PATH.
cl <- makeClusterPSOCK(
  "", user = "bob",
  rshcmd = "<putty-plink>",
  rshopts = c("-P", 2200, "-i", "C:/Users/bobby/.ssh/putty.ppk"),
  dryrun = TRUE

## EXAMPLE: Remote worker running on Linux from RStudio on Windows
## Connect to remote Unix machine '' on port 2200
## as user 'bob' from a Windows machine via RStudio's SSH client.
## Using the explicit special rshcmd = "<rstudio-ssh>", will force
## makeClusterPSOCK() to use the SSH client that comes with RStudio,
## preventing it from using other SSH clients on the system search PATH.
cl <- makeClusterPSOCK(
  "", user = "bob", rshcmd = "<rstudio-ssh>",
  dryrun = TRUE
# }
Documentation reproduced from package future, version 1.16.0, License: LGPL (>= 2.1)

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