Benchmarking can be an important part of the data analysis process. Especially when faced with very large datasets that need to be processed in multiple ways, choosing algorithms that will finish in a reasonable amount of time is important. Benchmarking gives us an empirical basis on which to make these decisions.
For some of the recipes in this chapter, we've used the time macro. For others we've used the Criterium library (https://github.com/hugoduncan/criterium). Why would we want to go to the trouble of using a whole library, just to see how fast our code is?
Generally, when we want to benchmark our code, we'll often start by using something like the time macro. This means:
Get the start time.
Execute the code.
Get the end time.
If you've done this often, you will realize that this has a number of problems, especially for benchmarking small functions that execute quickly. The times are often inconsistent, and they can be dependant on a number of factors external...