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.
makeClusterPSOCK(
workers,
makeNode = makeNodePSOCK,
port = c("auto", "random"),
...,
autoStop = FALSE,
tries = getOptionOrEnvVar("parallelly.makeNodePSOCK.tries", 3L),
delay = getOptionOrEnvVar("parallelly.makeNodePSOCK.tries.delay", 15),
validate = getOptionOrEnvVar("parallelly.makeNodePSOCK.validate", TRUE),
verbose = getOptionOrEnvVar("parallelly.debug", FALSE)
)
makeNodePSOCK(
worker = "localhost",
master = NULL,
port,
connectTimeout = getOptionOrEnvVar("parallelly.makeNodePSOCK.connectTimeout", 2 * 60),
timeout = getOptionOrEnvVar("parallelly.makeNodePSOCK.timeout", 30 * 24 * 60 * 60),
rscript = NULL,
homogeneous = NULL,
rscript_args = NULL,
rscript_envs = NULL,
rscript_libs = NULL,
rscript_startup = NULL,
methods = TRUE,
useXDR = getOptionOrEnvVar("parallelly.makeNodePSOCK.useXDR", FALSE),
outfile = "/dev/null",
renice = NA_integer_,
rshcmd = getOptionOrEnvVar("parallelly.makeNodePSOCK.rshcmd", NULL),
user = NULL,
revtunnel = TRUE,
rshlogfile = NULL,
rshopts = getOptionOrEnvVar("parallelly.makeNodePSOCK.rshopts", NULL),
rank = 1L,
manual = FALSE,
dryrun = FALSE,
quiet = FALSE,
verbose = FALSE
)workers |
The hostnames of workers (as a character vector) or the number of localhost workers (as a positive integer). |
makeNode |
A function that creates a |
port |
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 |
... |
Optional arguments passed to
|
autoStop |
If TRUE, the cluster will be automatically stopped
using |
tries, delay |
Maximum number of attempts done to launch each node
with |
validate |
If TRUE, after the nodes have been created, they are all
validated that they work by inquiring about their session information,
which is saved in attribute |
verbose |
If TRUE, informative messages are outputted. |
worker |
The hostname or IP number of the machine where the worker should run. |
master |
The hostname or IP number of the master / calling machine, as
known to the workers. If NULL (default), then the default is
|
connectTimeout |
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. |
timeout |
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_args |
Additional arguments to |
rscript_envs |
A named character vector environment variables to
set on worker at startup, e.g.
|
rscript_libs |
A character vector of R library paths that will be
used for the library search path of the R workers. An asterisk
( |
rscript_startup |
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 |
methods |
If TRUE, then the methods package is also loaded. |
useXDR |
If TRUE, the communication between master and workers, which is binary, will use big-endian (XDR). |
outfile |
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. |
renice |
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 |
user |
(optional) The user name to be used when communicating with another host. |
revtunnel |
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
|
rshlogfile |
(optional) If a filename, the output produced by the
|
rank |
A unique one-based index for each worker (automatically set). |
manual |
If TRUE the workers will need to be run manually. The command to run will be displayed. |
dryrun |
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. |
quiet |
If TRUE, then no output will be produced other than that from
using |
An object of class c("RichSOCKcluster", "SOCKcluster", "cluster")
consisting of a list of "SOCKnode" or "SOCK0node" workers (that also
inherit from RichSOCKnode).
makeNodePSOCK() returns a "SOCKnode" or
"SOCK0node" object representing an established connection to a worker.
A hostname is considered to be localhost if it equals:
"localhost",
"127.0.0.1", or
Sys.info()[["nodename"]].
It is also considered localhost if it appears on the same line
as the value of Sys.info()[["nodename"]] in file ‘/etc/hosts’.
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 parallelly.makeNodePSOCK.rshcmd. If that is not
set, then the default is to use ssh on Unix-like systems,
including macOS as well as Windows 10. On older MS Windows versions, which
does not have a built-in ssh client, the default is to use
(i) plink from the PuTTY
project, and then (ii) the ssh client that is distributed with
RStudio.
PuTTY puts itself on Windows' 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.
To use this SSH client outside of RStudio, set RSTUDIO_MSYS_SSH
accordingly.
You can override the default set of SSH clients that are searched for
by specifying them in argument rshcmd or via option
parallelly.makeNodePSOCK.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.
Additional SSH options may be specified via argument rshopts, which
defaults to option parallelly.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.
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.
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".
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
on your outgoing router, 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.
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.
If specified, argument rscript should be a character vector with one more
more elements.
all elements are automatically shell quoted using base::shQuote(), except
those that are of format <ENVVAR>=<VALUE>, that is, the ones matching the
regular expression '^[[:alpha:]_][[:alnum:]_]*=.*'.
Another exception is when rscript inherits from 'AsIs'.
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.
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
(https://stat.ethz.ch/pipermail/r-devel/2016-October/073309.html).
When used, the timeout will eventually trigger an error, but it won't happen
until the socket connection timeout timeout itself happens.
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.
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.
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.server.org
{remote}$ Rscript --version
R scripting front-end version 3.6.1 (2019-07-05)
{remote}$ logout
{local}$When you have confirmed the above to work, then confirm that you can achieve the same in a single command-line call;
{local}$ ssh -l alice remote.server.org Rscript --version
R scripting front-end version 3.6.1 (2019-07-05)
{local}$The latter will assert that you have proper startup configuration also for non-interactive shell sessions on the remote machine.
Another reason for failing to setup remote workers could be that they are
running an R version that is not compatible with the version that your main
R session is running. For instance, if we run R (>= 3.6.0) locally and the
workers run R (< 3.5.0), we will get:
Error in unserialize(node$con) : error reading from connection.
This is because R (>= 3.6.0) uses serialization format version 3 whereas
R (< 3.5.0) only supports version 2. We can see the version of the R
workers by adding rscript_args = c("-e", shQuote("getRversion()")) when
calling makeClusterPSOCK().
options(parallelly.debug = TRUE)
## 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("n1.remote.org", "n2.remote.org", "n1.remote.org")
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(
workers,
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(
"remote.server.org", 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",
"Rscript"
),
## 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 Linux container
rscript = c(
"singularity", "exec", "docker://rocker/r-parallel",
"Rscript"
),
dryrun = TRUE
)
## EXAMPLE: One worker running in udocker on the local machine
## Setup of a single udocker.py worker running rocker/r-parallel
cl <- makeClusterPSOCK(
"localhost",
## Launch Rscript inside Docker container (using udocker)
rscript = c(
"udocker.py", "run", "rocker/r-parallel",
"Rscript"
),
## Manually launch parallel workers
## (need double shQuote():s because udocker.py 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
## (http://www.louisaslett.com/RStudio_AMI/)
public_ip <- "1.2.3.4"
ssh_private_key_file <- "~/.ssh/my-private-aws-key.pem"
cl <- makeClusterPSOCK(
## Public IP number of EC2 instance
public_ip,
## 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)
.libPaths(p)
install.packages("future")
})),
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 <- "1.2.3.4"
user <- "johnny"
ssh_private_key_file <- "~/.ssh/google_compute_engine"
cl <- makeClusterPSOCK(
## Public IP number of GCE instance
public_ip,
## 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",
"Rscript"
),
dryrun = TRUE
)
## EXAMPLE: Remote worker running on Linux from Windows machine
## Connect to remote Unix machine 'remote.server.org' 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(
"remote.server.org", 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 'remote.server.org' 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(
"remote.server.org", user = "bob", rshcmd = "<rstudio-ssh>",
dryrun = TRUE
)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.