Abdelrahman Said
52 lines
3.1 KiB
Markdown
52 lines
3.1 KiB
Markdown
# Hash Tables References
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## SwissTable
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- [Designing a Fast, Efficient, Cache-friendly Hash Table, Step by Step](https://www.youtube.com/watch?v=ncHmEUmJZf4)
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- [Abseil blog announcement](https://abseil.io/blog/20180927-swisstables)
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- [Abseil design notes](https://abseil.io/about/design/swisstables)
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- [Faultlore hashbrown-TLDR](https://faultlore.com/blah/hashbrown-tldr)
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- [hashbrown source](https://github.com/rust-lang/hashbrown/tree/master/src/raw)
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- [Faster Go maps with Swiss Tables](https://go.dev/blog/swisstable)
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### 64-bit hash from 128-bit hash
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MurmurHash3 and SipHash return 128 bits. SwissTable expects 64 bits. XOR folding is the approach to use:
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```c
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uint64_t fold_128_to_64(uint128_t hash) {
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return (uint64_t)(hash >> 64) ^ (uint64_t)(hash & 0xFFFFFFFFFFFFFFFF);
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}
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```
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## Robin Hood
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- [Celis (1986) — original paper proving O(1) variance, Θ(log n) max probe](https://cs.uwaterloo.ca/research/tr/1986/CS-86-14.pdf)
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- [Gankra/Faultlore — clearest walkthrough from first principles](https://faultlore.com/blah/robinhood-part-1)
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- [On Worst Case Robin Hood Hashing](https://cglab.ca/~morin/publications/hashing/robinhood-siamjc.pdf)
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- [Sebastian Sylvan — popularized Robin Hood in systems programming](https://www.sebastiansylvan.com/post/robin-hood-hashing-should-be-your-default-hash-table-implementation/)
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- [Emmanuel Goossaert — detailed C++ implementation + backward-shift deletion](http://codecapsule.com/2013/11/11/robin-hood-hashing/)
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- [Martinus (Ankerl) — most widely used C++ implementation](https://github.com/martinus/unordered_dense)
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- [Tessil — clean header-only C++ implementation](https://github.com/Tessil/robin-map)
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- [Malte Skarupke — Robin Hood with probe count limit](https://github.com/skarupke/flat_hash_map)
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- [Robin Hood Hashing – Fairness in Collision Resolution](https://blog.hieunt.me/blog/robinhood-hashing)
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## Robin Hood vs SwissTable
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- [Rust migration PR](https://github.com/rust-lang/rust/pull/56241)
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- [hashbrown deletion discussion](https://github.com/rust-lang/hashbrown/issues/503)
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- [Jackson Allan benchmark](https://jacksonallan.github.io/c_cpp_hash_tables_benchmark/)
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- [Richter et al. (VLDB 2015)](https://bigdata.uni-saarland.de/publications/p249-richter.pdf)
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- [Poblete & Viola (2018)](https://www.cambridge.org/core/journals/combinatorics-probability-and-computing/article/abs/analysis-of-robin-hood-and-other-hashing-algorithms-under-the-random-probing-model/933D4F203E3C70EF15053287412242E0)
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## Hybrid Open-Addressing/Separate-Chaining
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- [Verstable](https://github.com/JacksonAllan/Verstable)
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## Double Hashing
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- Knuth, TAOCP Vol. 3 §6.4 — definitive analysis of double hashing probe counts
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- Guibas & Szemerédi (1978) — proved double hashing is asymptotically equivalent to uniform probing
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- [Heileman & Luo (2005) — "How Caching Affects Hashing" — cache-aware experimental comparison](http://siam.org/meetings/alenex05/papers/13gheileman.pdf)
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- [VT Hashing Tutorial — excellent pedagogical walkthrough](https://research.cs.vt.edu/AVresearch/hashing/double.php)
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- [Paul Khuong — "The Other Robin Hood Hashing" (original Celis double-hashing variant)](https://www.pvk.ca/Blog/2013/11/26/the-other-robin-hood-hashing/)
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