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Top 7 C++ hash-map Projects
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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fph-table
Flash Perfect Hash Table: an implementation of a dynamic perfect hash table, extremely fast for lookup
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HashTableBenchmark
A simple cross-platform speed & memory-efficiency benchmark for the most common hash-table implementations in the C++ world
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In my example the table stores the hash codes themselves instead of the keys (because the hash function is invertible)
Oh, I see, right. If determining the home bucket is trivial, then the back-shifting method is great. The issue is just that it’s not as much of a general-purpose solution as it may initially seem.
“With a different algorithm (Robin Hood or bidirectional linear probing), the load factor can be kept well over 90% with good performance, as the benchmarks in the same repo demonstrate.”
I’ve seen the 90% claim made several times in literature on Robin Hood hash tables. In my experience, the claim is a bit exaggerated, although I suppose it depends on what our idea of “good performance” is. See these benchmarks, which again go up to a maximum load factor of 0.95 (Although boost and Absl forcibly grow/rehash at 0.85-0.9):
https://strong-starlight-4ea0ed.netlify.app/
Tsl, Martinus, and CC are all Robin Hood tables (https://github.com/Tessil/robin-map, https://github.com/martinus/robin-hood-hashing, and https://github.com/JacksonAllan/CC, respectively). Absl and Boost are the well-known SIMD-based hash tables. Khash (https://github.com/attractivechaos/klib/blob/master/khash.h) is, I think, an ordinary open-addressing table using quadratic probing. Fastmap is a new, yet-to-be-published design that is fundamentally similar to bytell (https://www.youtube.com/watch?v=M2fKMP47slQ) but also incorporates some aspects of the aforementioned SIMD maps (it caches a 4-bit fragment of the hash code to avoid most key comparisons).
As you can see, all the Robin Hood maps spike upwards dramatically as the load factor gets high, becoming as much as 5-6 times slower at 0.95 vs 0.5 in one of the benchmarks (uint64_t key, 256-bit struct value: Total time to erase 1000 existing elements with N elements in map). Only the SIMD maps (with Boost being the better performer) and Fastmap appear mostly immune to load factor in all benchmarks, although the SIMD maps do - I believe - use tombstones for deletion.
I’ve only read briefly about bi-directional linear probing – never experimented with it.
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
C++ hash-map related posts
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Fibonacci Hashing: An Optimization the World Forgot (Better Than Integer Modulo)
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How to create std::map that preserves the order of insertion just using standard C++?
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boost::unordered map is a new king of data structures
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Updating map_benchmarks: Send your hashmaps!
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Yes, this is embarrassingly slow .so I solved your problem
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Unum blog: Apple to Apple Comparison: M1 Max vs Intel. How a DDR5-powered MacBook beat a DDR4-powered MacBook and approached a $50K Server in Hash-Table Benchmarks
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Hacker News top posts: Dec 24, 2021
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Index
What are some of the best open-source hash-map projects in C++? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | sparsepp | 1,230 |
| 2 | robin-map | 1,184 |
| 3 | Hopscotch map | 704 |
| 4 | ordered-map | 504 |
| 5 | fph-table | 38 |
| 6 | HashTableBenchmark | 10 |
| 7 | qc-hash | 10 |
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