R- Speed up calculation related with subset of data.table - r

Question

Need help on speed up for case below:
I am having roughly 8.5 Millions rows of orders history for 1.3M orders. I need to calculate the time it take between two steps of each order. I use calculation as below:
History[, time_to_next_status:=
get_time_to_next_step(id_sales_order_item_status_history,
id_sales_order_item, History_subset),
by='id_sales_order_item_status_history']
In the code above:
id_sales_order_item - id of a sales order item - there are multiple history record have the same id_sales_order_item
id_sales_order_item_status_history - id of a row
History_subset is a subset of History which contains only 3 columns [id_sales_order_item_status_history, id_sales_order_item, created_at] needed in the calculations.
created_at is the time the history was created
The function get_time_to_next_step is defined as below
get_time_to_next_step <- function(id_sales_order_item_status_history, filter_by,
dataSet){
dataSet <- dataSet %.% filter(id_sales_order_item == filter_by)
index <- match(currentId, dataSet$id_sales_order_item_status_history)
time_to_next_status <- dataSet[index + 1, created_at] - dataSet[index, created_at]
time_to_next_status
}
The issues is that it take 15mins to run arround 10k records of the History. So it would take up to ~9 days to complete the calculation. Is there anyway I can fasten this up without break the data in to multiple subset?

Answer 1

I will take a shot. Can't you try something like this..
History[ , Index := 1:.N, by= id_sales_order_item]
History[ , time_to_next_status := created_at[Index+1]-created_at[Index], by= id_sales_order_item]
I would think this would be pretty fast.