CC
STC
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CC
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preprocessor stuff - compile time pasting into other files
With extendible macros, you could achieve the following:
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Factor is faster than Zig
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.
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If this isn't the perfect data structure, why?
From your other comments, it seems like your knowledge of hash tables might be limited to closed-addressing/separate-chaining hash tables. The current frontrunners in high-performance, memory-efficient hash table design all use some form of open addressing, largely to avoid pointer chasing and limit cache misses. In this regard, you want to check our SSE-powered hash tables (such as Abseil, Boost, and Folly/F14), Robin Hood hash tables (such as Martinus and Tessil), or Skarupke (I've recently had a lot of success with a similar design that I will publish here soon and is destined to replace my own Robin Hood hash tables). Also check out existing research/benchmarks here and here. But we a little bit wary of any benchmarks you look at or perform because there are a lot of factors that influence the result (e.g. benchmarking hash tables at a maximum load factor of 0.5 will produce wildly different result to benchmarking them at a load factor of 0.95, just as benchmarking them with integer keys-value pairs will produce different results to benchmarking them with 256-byte key-value pairs). And you need to familiarize yourself with open addressing and different probing strategies (e.g. linear, quadratic) first.
- Convenient Containers: A usability-oriented generic container library
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[Noob Question] How do C programmers get around not having hash maps?
CC (Full disclosure: I authored this one)
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New C features in GCC 13
If you're using C23 or have typeof (so GCC or Clang), then yet another approach is to define a type that aliases the specified type if it is unique or otherwise becomes a "dummy" type. Here's what that looks like in CC:
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Convenient Containers v1.0.3: Better compile speed, faster maps and sets
I’d like to share version 1.0.3 of Convenient Containers (CC), my generic container library. The library was previously discussed here and here. As explained elsewhere,
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Popular Data Structure Libraries in C ?
Convenient Containers (CC) - I'm the author of this one.
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So what's the best data structures and algorithms library for C?
"Using macros" is a broad description that covers multiple paradigms. There are libraries that use macros in combination with typed pointers and functions that take void* parameters to provide some degree of API genericity and type safety at the same time (e.g. stb_ds and, as you mentioned, my own CC). There are libraries that use macros (or #include directives) to manually instantiate templates (e.g. STC, M*LIB, and Pottery). And then there are libraries that are implemented entirely or almost entirely as macros (e.g. uthash).
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How do you deal with the extra verbosity of C?
Shameless plug: Take a look a my library Convenient Containers, which solves this exact problem within the (narrow) domain of data structures.
STC
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Macro to automatically unlock a mutex in a block (ansi c)
This technique is often used to implement RAII in C. See example in Standard Template Containers. The library delivers STL-like functionality to C.
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Is using void* considered "evil" in C just as it is in C++?
I'd say it's evil, but quite understandable very commonly used because there are no built-in alternatives in C. I basically never use void* in user-code, simply because there are no need for it when using a templating technique, like in my STC library. Even in the implementation of STC itself, void* is hardly used, if at all.
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Book recommendations for learning C really thoroughly
Study Other Peoples C Code and here's one that is easy to read: https://github.com/stclib/STC/releases
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[Noob Question] How do C programmers get around not having hash maps?
STC
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Should I use templates or stick with rewriting code?
This is more or less how C-ish templates are implemented in STC library.
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What’s the right hash table API?
As the author of a STL-like templated C container library, I had many of the exact same thoughts when implementing the unordered map. In fact, I also changed to many of the suggestions here, rather than consistently following the C++ umap API. E.g.
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What's the fastest high level language?
Sure it is. C misses a proper efficient generic standard/container library, like my https://github.com/stclib/STC, but that is irrelevant.
- STC v4.2 Released (note: new URL)
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Popular Data Structure Libraries in C ?
Smart Template Containers (STC)
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So what's the best data structures and algorithms library for C?
Some data structure and algorithm library in C enable the (optional) separation between the interface of the container (which is expanded in your header) and its implementation (which is expanded in your source), like STC.
What are some alternatives?
rust-bindgen - Automatically generates Rust FFI bindings to C (and some C++) libraries.
ctl - The C Template Library
mlib - Library of generic and type safe containers in pure C language (C99 or C11) for a wide collection of container (comparable to the C++ STL).
stent - Completely avoid dangling pointers in C.
Klib - A standalone and lightweight C library
SDS - Simple Dynamic Strings library for C
ctl - My variant of the C Template Library
Generic-Data-Structures - A set of Data Structures for the C programming language
CommonC - Common utilities for C
stb - stb single-file public domain libraries for C/C++
ccan - The C Code Archive Network