I think reducing this to "using mmap is basic" is pretty unfair.
The trick she did overriding malloc & friends to validate that the optimization would be worth doing is, in my mind, one of the high-points of the paper. It's a very clever way of making a meaningful measurement, which was the keystone of the entire change.
I've never heard of, thought of, or used that trick, and the fact she had it in her arsenal to apply to this very specific situation is pretty impressive, to me at least.
Systems Programmer is itself a niche field, when compares to other fields of interest in Software Developement. So let's not trivialize anything, cause it can be amazing to someone, but not to another. It depends from person to person.
it's as much engineering as is gluing mmap, recv and send... there are people who can do that and can't piece together a dataframe pipeline, no need to be passive agressive here
> "it's as much engineering as is gluing mmap, recv and send"
As you can see from comments up this thread (ref. various GitHub issues) - the people "gluing mmap" don't actually have a single clue. They can't properly measure memory consumption (they don't understand what the numbers they're seeing actually mean). They don't understand how paging, swapping or virtual memory work. They don't actually understand the concept of memory-mapped files, why they're there and how they work. They can't explain why their code behaves differently when using memory-mapped files.
Moments like this are here to remind you that there's actual knowledge and skill to building scalable and efficient software, and that hustling and copy-pasting StackOverflow examples will only get you so-far, as will "piecing together dataframe pipelines" in Python.
