[OskarS]

> HashMap implements Extend, so just h0.extend(h1) and you're done, the people who made your HashMap type are much better equipped to optimize this common operation.

Are you sure? I'm not very used to reading Rust stdlib, but this seems to be the implementation of the default HashMap extend [1]. It just calls self.base.extend. self.base seems to be hashbrown::hash_map, and this is the source for it's extend [2]. In other words, does exactly the same thing, just iterates through hash map and inserts it.

Maybe I'm misreading something going through the online docs, or Rust does the "random seed" thing that abseil does, but just blinding assuming something doesn't happen "because Rust" is a bit silly.

[1]: https://doc.rust-lang.org/src/std/collections/hash/map.rs.ht...

[2]: https://docs.rs/hashbrown/latest/src/hashbrown/map.rs.html#4...

[tialaramex]

Yes, HashMap will by default be randomly seeded in Rust, but also the code you linked intelligently reserves capacity. If h0 is empty, it reserves enough space for all of h1, and if it isn't then it reserves enough extra space for half of h1, which turns out to be a good compromise.

Note that the worst case is we ate a single unneeded growth, while the best case is that we avoided N - 1 grows where N may be quite large.

[attractivechaos]

First of all, as khuey pointed out, the current implementation accumulates values. extend() replaces values instead. It wouldn't achieve the same functionality.

I tried extend() anyway. It didn't work well. Based on your description, extend() implements a variation of preallocation (i.e. Solution II). However, because it doesn't always reserve enough space to hold the merged hash table, clustering still happens depending on N. I have updated the rust implementation (with the help of LLM as I am not a good rust programmer). You can try it yourself with "ht-merge-rust 1 -e -n14m" or point out if I made mistakes.

> HashMap will by default be randomly seeded in Rust

Yes, so it is with Abseil. The default rust hash functions, siphash in the standard library and foldhash in hashbrown, are ~3X as slow in comparison to simple hash functions on pure insertion load. When performance matters, we will use faster hash functions at least for small keys and will need a solution from my post.

> In a new enough C++ in theory you might find the same functionality supported, but Quality of Implementation tends to be pretty frightful.

This is not necessary. The rust libraries are a port of Abseil, a C++ library. Boost is as fast as Rust. Languages/libraries should learn from each other, not fight each other.

[tialaramex]

> First of all, as khuey pointed out, the current implementation accumulates values. extend() replaces values instead. It wouldn't achieve the same functionality.

Ah! Yes, I apologise. I missed the + in += and I'm not used to a hash table which defaults initialization for unseen entries (as the C++ hash tables all tend to because its native container types behave that way) so I wasn't looking for it.

The SipHash will be noticeably slower, no question about it, and so if you need to and know what you're paying you can replace the hash, including with integer_hasher which gives you what you'd likely know from many C++ stdlib implementations - an identity function presented as a hash.

> This is not necessary. The rust libraries are a port of Abseil, a C++ library.

More specifically HashBrown is a port [edited: actually a re-implementation I think, design->Rust not C++->Rust] of Abseil's Swiss Tables, and these days Rust's HashMap (and HashSet of course) use HashBrown but that's not what I was getting at here

I was thinking about analogues of Extend (because as I wrote above, I didn't notice that you're accumulating not overwriting) and modern C++ has this kind of feature in Ranges::to however it doesn't quite have Extend and as I said QoI is poor, there are often trivial optimisations that Rust does but the C++ means the same but isn't optimised.

I am interested in a quite different benchmark for hash tables, rather than merging I'm interested in very small hash tables. Clearly for two items it will be faster to try them both, and clearly for a million items trying them all is awful, so I measure a VecMap type (same API as a hash table but actually just the growable array of unordered key->value pairs, searched linearly) against HashMap and other implementations of this API.

For N=25 VecMap is still competitive, but even at N=5 if we use a very fast hash (such as that identity function) instead of SipHash we can beat VecMap for most operations. I suspect this sort of benchmark would fare very differently on older hardware (faster memory relative to ALU operations) and the direction of travel is likely to stay the same for the foreseeable future. In 1975 if you have six key->value pairs you don't want a hash table because it's too slow but in 2025 you probably do.