Converting Loops to Parallel Loops in R

[omario]

I have this dataset over here (e.g. students wrote an exam many times over a period of years and either pass or failed - I am interested in studying the effect of the previous test on the next test):

id = sample.int(10000, 100000, replace = TRUE)
res = c(1,0)
results = sample(res, 100000, replace = TRUE)
date_exam_taken = sample(seq(as.Date('1999/01/01'), as.Date('2020/01/01'), by="day"), 100000, replace = TRUE)

my_data <- my_data[order(my_data$id, my_data$date_exam_taken),]

my_data$general_id = 1:nrow(my_data)
my_data$exam_number = ave(my_data$general_id, my_data$id, FUN = seq_along)
my_data$general_id = NULL

     id results date_exam_taken exam_number
7992   1       1      2004-04-23           1
24837  1       0      2004-12-10           2
12331  1       1      2007-01-19           3
34396  1       0      2007-02-21           4
85250  1       0      2007-09-26           5
11254  1       1      2009-12-20           6

I wrote this standard FOR LOOP and everything seems to work fine:

my_list = list()

for (i in 1:length(unique(my_data$id)))
    
{ 
    {tryCatch({
        
        start_i = my_data[my_data$id == i,]
        
        pairs_i =  data.frame(first = head(start_i$results, -1), second = tail(start_i$results, -1))
        frame_i =  as.data.frame(table(pairs_i))
        frame_i$id = i
        print(frame_i)
        my_list[[i]] = frame_i
    }, error = function(e){})
    }}


 final_a = do.call(rbind.data.frame, my_list)

Now, I am trying to "optimize" this loop by using "doParallel" libraries in R.

I tried to convert my loop as follows:

# does this mean I can set makeCluster() to makeCluster(8)???
 > detectCores()
[1] 8
my_list = list()
max = length(unique(my_data$id))

library(doParallel)
registerDoParallel(cl <- makeCluster(3))

test = foreach(i = 1:max) %dopar% {

    {tryCatch({
        
        start_i = my_data[my_data$id == i,]
        
        pairs_i =  data.frame(first = head(start_i$results, -1), second = tail(start_i$results, -1))
        frame_i =  as.data.frame(table(pairs_i))
        frame_i$id = i
        print(frame_i)
        my_list[[i]] = frame_i
    }, error = function(e){})
    }}


 final_b = do.call(rbind.data.frame, test)

Based on this - I have the following questions:

• Have I correctly used the "doParallel" functionalities as they are intended to be used?
• Is there yet a better way to do this?

Thanks!