R: Create a Parallel Socket Cluster

makeCluster {parallel} | R Documentation

## Create a Parallel Socket Cluster

### Description

Creates a set of copies of R running in parallel and communicating over sockets.

### Usage

    makeCluster(spec, type, ...)
    makePSOCKcluster(names, ...)
    makeForkCluster(nnodes = getOption("mc.cores", 2L), ...)

    stopCluster(cl = NULL)

    setDefaultCluster(cl = NULL)
    getDefaultCluster()

### Arguments

`spec` | A specification appropriate to the type of cluster.
`names` | Either a character vector of host names on which to run the worker copies of R, or a positive integer (in which case that number of copies is run on localhost).
`nnodes` | The number of nodes to be forked.
`type` | One of the supported types: see ‘Details’.
`...` | Options to be passed to the function spawning the workers. See ‘Details’.
`cl` | an object of class `"cluster"`.

### Details

`makeCluster` creates a cluster of one of the supported types. The default type, `"PSOCK"`, calls `makePSOCKcluster`. Type `"FORK"` calls `makeForkCluster`. Other types are passed to package snow.

`makePSOCKcluster` is an enhanced version of `makeSOCKcluster` in package snow. It runs `Rscript` on the specified host(s) to set up a worker process which listens on a socket for expressions to evaluate, and returns the results (as serialized objects).

`makeForkCluster` is merely a stub on Windows. On Unix-alike platforms it creates the worker process by forking.

The workers are most often running on the same host as the master, when no options need be set.

Several options are supported (mainly for `makePSOCKcluster`):

`master`

  The host name of the master, as known to the workers. This may not be the same as it is known to the master, and on private subnets it may be necessary to specify this as a numeric IP address. For example, macOS is likely to detect a machine as somename.local, a name known only to itself.

`port`

  The port number for the socket connection, default taken from the environment variable R_PARALLEL_PORT, then a randomly chosen port in the range `11000:11999`.

`timeout`

  The timeout in seconds for that port. This is the maximum time of zero communication between master and worker before failing. Default is 30 days (and the POSIX standard only requires values up to 31 days to be supported).

`setup_timeout`

  The maximum number of seconds a worker attempts to connect to master before failing. Default is 2 minutes. The waiting time before the next attempt starts at 0.1 seconds and is incremented 50% after each retry.

`outfile`

  Where to direct the `stdout` and `stderr` connection output from the workers. `""` indicates no redirection (which may only be useful for workers on the local machine). Defaults to ‘/dev/null’ (‘nul:’ on Windows). The other possibility is a file path on the worker's host. Files will be opened in append mode, as all workers log to the same file.

`homogeneous`

  Logical, default true. See ‘Note’.

`rscript`

  See ‘Note’.

`rscript_args`

  Character vector of additional arguments for `Rscript` such as --no-environ.

`renice`

  A numerical ‘niceness’ to set for the worker processes, e.g. `15` for a low priority. OS-dependent: see `psnice` for details.

`rshcmd`

  The command to be run on the master to launch a process on another host. Defaults to `ssh`.

`user`

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

`manual`

  Logical. If true the workers will need to be run manually.

`methods`

  Logical. If true (default) the workers will load the methods package: not loading it saves ca 30% of the startup CPU time of the cluster.

`useXDR`

  Logical. If true (default) serialization will use XDR: where large amounts of data are to be transferred and all the nodes are little-endian, communication may be substantially faster if this is set to false.

Function `makeForkCluster` creates a socket cluster by forking (and hence is not available on Windows). It supports options `port`, `timeout` and `outfile`, and always uses `useXDR = FALSE`. It is strongly discouraged to use the `"FORK"` cluster with GUI front-ends or multi-threaded libraries.

It is good practice to shut down the workers by calling `stopCluster`: however the workers will terminate themselves once the socket on which they are listening for commands becomes unavailable, which it should if the master R session is completed (or its process dies).

Function `setDefaultCluster` registers a cluster as the default one for the current session. Using `setDefaultCluster(NULL)` removes the registered cluster, as does stopping that cluster.

### Value

For the cluster creators, an object of class `c("SOCKcluster", "cluster")`.

For the default cluster setter and getter, the registered default cluster or `NULL` if there is no such cluster.

### Note

Option `homogeneous = TRUE` was for years documented as ‘Are all the hosts running identical setups?’, but this was apparently more restrictive than its author intended and not required by the code.

The current interpretation of `homogeneous = TRUE` is that `Rscript` can be launched using the same path on each worker. That path is given by the option `rscript` and defaults to the full path to `Rscript` on the master. (The workers are not required to be running the same version of R as the master, nor even as each other.)

For `homogeneous = FALSE`, `Rscript` on the workers is found on their default shell's path.

For the very common usage of running both master and worker on a single multi-core host, the default settings are the appropriate ones.

### Author(s)

Luke Tierney and R Core.

Derived from the snow package.

[Package parallel version 4.0.5 Index]