doParabar (version 1.0.2)

registerDoParabar: Register Parallel Implementation

Description

The registerDoParabar() function registers the provided backend created by parabar::start_backend() to be used as the parallel processing backend for the foreach::%dopar% operator implementation.

Usage

registerDoParabar(backend)

Value

The registerDoParabar() function returns void.

Arguments

backend

An object of class parabar::Backend representing the backend to be used for the foreach::%dopar% operator implementation.

Completeness

The parallel backend implementation for the foreach::%dopar% operator is provided by the doPar() function. Please check the Details section of its documentation to understand the extent of completeness of the implementation.

Details

Additional information about the registered parallel backend can be extracted using the foreach::getDoParName(), foreach::getDoParRegistered(), foreach::getDoParVersion(), and foreach::getDoParWorkers() functions. See the Examples section.

See Also

doParabar, doPar(), parabar::start_backend() and parabar::stop_backend().

Examples

# Manually load the libraries.
library(doParabar)
library(parabar)
library(foreach)

# Create an asynchronous `parabar` backend.
backend <- start_backend(cores = 2, cluster_type = "psock", backend_type = "async")

# Register the backend with the `foreach` package for the `%dopar%` operator.
registerDoParabar(backend)

# Get the parallel backend name.
getDoParName()

# Check that the parallel backend has been registered.
getDoParRegistered()

# Get the current version of backend registration.
getDoParVersion()

# Get the number of cores used by the backend.
getDoParWorkers()

# Define some variables strangers to the backend.
x <- 10
y <- 100
z <- "Not to be exported."

# Used the registered backend to run a task in parallel via `foreach`.
results <- foreach(i = 1:300, .export = c("x", "y"), .combine = c) %dopar% {
    # Sleep a bit.
    Sys.sleep(0.01)

    # Compute and return.
    i + x + y
}

# Show a few results.
head(results, n = 10)
tail(results, n = 10)

# Verify that the variable `z` was not exported.
try(evaluate(backend, z))

# To make packages available on the backend, see the `.packages` argument.

# Stop the backend.
stop_backend(backend)