Calculating row sums
The second bottleneck identified was calculating the row sums.
total <- apply(d, 1, sum)
In the previous exercise you switched the underlying object to a matrix. This makes the above apply operation three times faster.
But there's one further optimization you can use - switch apply() with rowSums().
This exercise is part of the course
Writing Efficient R Code
Exercise instructions
- Complete the
r_sum()function usingrowSums(). - Use the
microbenchmark()function to compare the timings ofapp()andr_sum().
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Example data
rolls
# Define the previous solution
app <- function(x) {
apply(x, 1, sum)
}
# Define the new solution
r_sum <- function(x) {
___(x)
}
# Compare the methods
microbenchmark(
app_sol = app(rolls),
r_sum_sol = ___
)