Making sense of the foreach - r

Question

I'm new to paralleling the for loop using foreach and struggle to understand how it works. As an example for the exercise, I created a simple list (input2) based on a dataframe (input). I try to calculate b by looping through h and j.
library(doParallel)
library(foreach)
library(dplyr)
input <- data.frame(matrix(rnorm(200*200, 0, .5), ncol=200))
input[input <=0] =0
input['X201'] <- seq(from = 0, to = 20, length.out = 10)
input <- input %>% select(c(X201, 1:200))
input2 <- split(input, f= input$X201)
a = 0
b= 0
cl <- parallel::makeCluster(20)
doParallel::registerDoParallel(cl)
tm1 <- system.time(
y <-
foreach (h = length(input2),.combine = 'cbind') %:%
foreach (j = nrow(input2[[h]]),.combine = 'c',packages = 'foreach') %dopar%{
a = input2[[h]][j,3]
b = b + a
}
)
parallel::stopCluster(cl)
registerDoSEQ()
print("Cluster stopped.")
y is about 0.55 (the exact value depends on the random number one generated), which is the value of input2[[10]][20,3], not the accumulative value I desired. I checked the manual of the foreach package but still not sure I fully understand the mechanism of the foreach function.

Answer 1

R foreach returns back results instead allows the outside variable to be changed. So don't expect a, b to be updated correctly.
Try the following
cl <- parallel::makeCluster(20)
doParallel::registerDoParallel(cl)
tm2 <- system.time(
results <- foreach(h = (1:length(input2)), .combine = "c") %dopar%{
sum( input2[[h]][1:nrow(input2[[h]]),3])
},
b <- sum(results[1:length(results)])
)
parallel::stopCluster(cl)
registerDoSEQ()
b
tm2