Yes, mutating something at one place in memory is more efficient, because you don't need to allocate new memories.
I don't know all to much about other functional languages, as I learned perl -> ruby -> javascript -> little bit C & Java & Go -> now doing Clojure. But I find Clojures collection data structures interesting. The vector (collection like lists or array) type look immutable, but under the hood are trees. When you append to a vector, you seem get a new vector returned.
In reality, you added the new element as a node in a tree. Then just modified pointers to that the new and old version share almost all of the pointers & allocations. With simple arrays or lists, you would allocate every element anew.
Personally, most things in business I find easily parallelisable. You mostly decouple the I/O parts of something with the logic parts of it. But yeah I still have much to learn. Thanks for the link! Interesting :)
That's cool, In Ruby Hash merges are really expensive. I played around with a non-mutating data structure that uses references two two hashes and behaves as if it had been merged instead of allocating. It was a fun thought experiment but wasn't 100% API backwards compatible, as mutations got ugly. Thanks for the link.
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Yes, mutating something at one place in memory is more efficient, because you don't need to allocate new memories.
I don't know all to much about other functional languages, as I learned perl -> ruby -> javascript -> little bit C & Java & Go -> now doing Clojure. But I find Clojures collection data structures interesting. The vector (collection like lists or array) type look immutable, but under the hood are trees. When you append to a vector, you seem get a new vector returned.
In reality, you added the new element as a node in a tree. Then just modified pointers to that the new and old version share almost all of the pointers & allocations. With simple arrays or lists, you would allocate every element anew.
Idk if I can properly explain. Found this blog post very interesting and easier to follow: http://hypirion.com/musings/understanding-persistent-vector-...
Personally, most things in business I find easily parallelisable. You mostly decouple the I/O parts of something with the logic parts of it. But yeah I still have much to learn. Thanks for the link! Interesting :)
That's cool, In Ruby Hash merges are really expensive. I played around with a non-mutating data structure that uses references two two hashes and behaves as if it had been merged instead of allocating. It was a fun thought experiment but wasn't 100% API backwards compatible, as mutations got ugly. Thanks for the link.