The “clusterSplit” Function in R

• Package: parallel

• Purpose: Split data into chunks for parallel processing.

• General class: Parallel computing

• Required argument(s):

• seq: The data to be split.

• cl: The cluster object created with makeCluster.

• Notable optional arguments:

• None

• Example:

• # Load the parallel package
  library(parallel)
  
  # Create a cluster with 4 nodes
  cl <- makeCluster(4)
  
  # Generate sample data
  data <- 1:100
  
  # Split the data into 4 parts (as a list) using clusterSplit
  parts <- clusterSplit(cl, data)
  
  # Use parSapply to take the sqrt of the split sample data
  Result <- parSapply(cl, parts, sqrt)
  
  # Print the resulting matrix as a vector
  print(as.vector(Result))
  
  # Stop the cluster
  stopCluster(cl)

• In this example, we create a cluster cl with 4 nodes using the makeCluster function from the parallel package. Then, we generate sample data and use clusterSplit to split the data into a list with 4 parts. Finally, we use the parSapply function to take the square root of each value.