I never looked into this, so I have some questions.
Isn't the overhead of a new function every time going to slow it down? Like I know that LLVM has special instructions for Haskell-functions to reduce overhead, but there is still more overhead than with a branch, right? And if you don't use Haskell, the overhead is pretty extensive, pushing all registers on the stack, calling new function, push buffer-overflow protection and eventual return and pop everything again. Plus all the other stuff (kinda language dependent).
I don't understand what advantage is here, except for stuff where recursive makes sense due to being more dynamic.
They aren't talking about using recursion instead of loops. They are talking about the map method for iterators. For each element yielded by the iterator, map applies a specified function/closure and collects the results in a new iterator (usually a list). This is a functional programming pattern that's common in many languages including Python and Rust.
This pattern has no risk of stack overflow since each invocation of the function is completed before the next invocation. The construct does expand to some sort of loop during execution. The only possible overhead is a single function call within the loop (whereas you could have written it as the loop body). However, that won't be a problem if the compiler can inline the function.
The fact that this is functional programming creates additional avenues to optimize the program. For example, a chain of maps (or other iterator adaptors) can be intelligently combined into a single loop. In practice, this pattern is as fast as hand written loops.
A great point in favour of maps is that each iteration is independent, so could theoretically be executed in parallel. This heavily depends on the language implementation, though.
Compiler optimizations like function inlining are your friend.
Especially in functional languages, there are a lot of tricks a compiler can use to output more efficient code due to not needing to worry about possible side effects.
Also, in a lot of cases the performance difference does not matter.
I'm not familiar with any special LLVM instructions for Haskell. Regardless, LLVM is not actually a commonly used backend for Haskell (even though you can) since it's not great for optimizing the kind of code that Haskell produces. Generally, Haskell is compiled down to native code directly.
Haskell has a completely different execution model to imperative languages. In Haskell, almost everything is heap allocated, though there may be some limited use of stack allocation as an optimization where it's safe. GHC has a number of aggressive optimizations it can do (that is, optimizations that are safe in Haskell thanks to purity that are unsafe in other languages) to make this quite efficient in practice. In particular, GHC can aggressively inline a lot more code than compilers for imperative languages can, which very often can eliminate the indirection associated with function calls entirely. https://gitlab.haskell.org/ghc/ghc/-/wikis/commentary/compiler/generated-code goes into a lot more depth about the execution model if you're interested.
As for languages other than Haskell without such an execution model (especially imperative languages), it's true that there can be the overhead you describe, which is why the vast majority of them use iterators to achieve the effect, which avoids the overhead. Rust (which has mapping/filtering, etc. as a pervasive part of its ecosystem) does this, for example, even though it's a systems programming language with a great deal of focus on performance.
As for the advantage, it's really about expressiveness and clarity of code, in addition to eliminating the bugs so often resulting from mutation.
So it basically enables some more compiler magic. As an embedded guy I'll stay away from it, since I like my code being translated a bit more directly, but maybe I'll look into the generated code and see if I can apply some of the ideas for optimizations in the future.
I looked at the post again and they do talk about recursion for looping (my other reply talks about map over an iterator). Languages that use recursion for looping (like scheme) use an optimization trick called 'Tail Call Optimization' (TCO). The idea is that if the last operation in a function is a recursive call (call to itself), you can skip all the complexities of a regular function call - like pushing variables to the stack and creating a new stack frame. This way, recursion becomes as performant as iteration and avoids problems like stack overflow.
Not just calls to self - any time a function’s last operation is to call another function and return its result (a tail call), tail call elimination can convert it to a goto/jump.
Some languages have to optimize it with various tricks. There's a good reason why I call heavily functional "programmer wankery". It took me a while to run into an issue that was caused by a variable modified in a wrong way, which I fixed by saving the value of the variable before a call that seems to alter it. Probably I should have instead properly fix it so I could understand the actual root cause, but I have limited time to spend on things.
I learned some Haskell. Did some problems on Advent of Code and such. But since then I've heard about OCaml, which seems super interesting. Hopefully the tooling is simpler, but I've not had time to try anything yet.
what's the appeal of haskell? (this is a genuine question.) i've been a bit curious about it for a while but haven't really found the motivation to take a closer look at it.
purely functional paradigm (immutable data structures and no shared state, which is great for e.g. concurrency) and advanced type system (for example you could have linear types that can be only used once). Lisps build on the premise that everything is data, leaving little room for bloated data structures or tight coupling with call chains that are hard to maintain or test. In Haskell on the other hand, everything is a computation, hence why writing it feels more like writing mathematical equations than computer programs somehow. It might, along Scala be good for data-driven applications.
Also the purely functional syntax means that on average, functional programming languages will arrive at the same solution in approx. 4 times less LOC than procedural/OO according to some research. Just look at solutions to competetive programming problems.
And even though I'm not a big fan of opinionated frameworks, compare some Phoenix codebase to a Symfony or even a Rails one to see how much cleaner the code is.
But if you're new to FP you should rather pick Scheme, Elixir or Clojure since the paradigm itself can be a little bit hard enough to wrap your head around at first (though Elixir and is a bit imperative, depends on how deep are you ready to dive in), not to mention having to learn about ADTs and category theory.
It's been noted that functional code accumulates less bugs, because there's no way to accidentally change something important somewhere else, and Haskell is the standard for functional languages. Also, it might just be me, but the type system also feels perfect when I use it. Like, my math intuition says there's no better way to describe a function; it's showing the logic to me directly.
Where Haskell is weak is when interactivity - either with the real world or with other components - comes up. You can do it, but it really feels like you're writing normal imperative code, and then just squirreling it away in a monad. It's also slower than the mid-level languages. That being said, if I need to quickly generate some data, Haskell is my no-questions go to. Usually I can do it in one or two lines.