The “parSapply” Function in R

• Package: parallel

• Purpose: Applies a function to each element of a list or vector in parallel and simplifies the results into a vector or matrix.

• General class: Parallel computing

• Required argument(s):

• cl: A cluster object specifying the cluster to use for parallel processing.

• X: A list or vector to be processed.

• fun: The function to apply to each element of X.

• Notable optional arguments:

• ...: Additional arguments passed to the function fun.

• Example:

• # Load the parallel library
  library(parallel)
  
  # Create a cluster object with 2 cores
  cl <- makeCluster(2)
  
  # Define a function to square a number
  square <- function(x) { return(x^2) }
  
  # Create a list of numbers
  numbers <- list(1, 2, 3, 4, 5)
  
  # Apply the square function to each element of the list in parallel and simplify the result to a vector
  result <- parSapply(cl, numbers, square)
  
  # Close the cluster
  stopCluster(cl)
  
  # Print the result
  print(result)

• This example demonstrates how to use the parSapply function from the parallel package to apply a function (square) to each element of a list (numbers) in parallel using a cluster object (cl). The ... argument allows passing additional arguments to the function square. The output is a vector containing the squared values of the elements in the list.