3 releases (1 stable)
2.2.3 | Oct 16, 2022 |
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0.1.1 | Oct 10, 2022 |
0.1.0 | Oct 9, 2022 |
#897 in Encoding
74KB
1.5K
SLoC
Concurrent hash maps.
This is a clone of https://gitlab.redox-os.org/redox-os/chashmap, which at time of writing seems largely unmaintained. I take no credit for the original author's hard work. My contributions are to add serde support and any other features that I may personally need.
This crate implements concurrent hash maps, based on bucket-level multi-reader locks. It has excellent performance characteristics¹ and supports resizing, in-place mutation and more.
The API derives directly from std::collections::HashMap
, giving it a familiar feel.
¹Note that it heavily depends on the behavior of your program, but in most cases, it's really good. In some (rare) cases you might want atomic hash maps instead.
How it works
chashmap
is not lockless, but it distributes locks across the map such that lock contentions
(which is what could make accesses expensive) are very rare.
Hash maps consists of so called "buckets", which each defines a potential entry in the table. The bucket of some key-value pair is determined by the hash of the key. By holding a read-write lock for each bucket, we ensure that you will generally be able to insert, read, modify, etc. with only one or two locking subroutines.
There is a special-case: reallocation. When the table is filled up such that very few buckets are free (note that this is "very few" and not "no", since the load factor shouldn't get too high as it hurts performance), a global lock is obtained while rehashing the table. This is pretty inefficient, but it rarely happens, and due to the adaptive nature of the capacity, it will only happen a few times when the map has just been initialized.
Collision resolution
When two hashes collide, they cannot share the same bucket, so there must be an algorithm which can resolve collisions. In our case, we use linear probing, which means that we take the bucket following it, and repeat until we find a free bucket.
This method is far from ideal, but superior methods like Robin-Hood hashing works poorly (if at all) in a concurrent structure.
The API
The API should feel very familiar, if you are used to the libstd hash map implementation. They share many of the methods, and I've carefully made sure that all the items, which have similarly named items in libstd, matches in semantics and behavior.
Serde
Support for Serde has been added and should™ work with the Serde Serializer/Deserializer of your choosing.
fn main() {
//================================================================================
// serialize
//================================================================================
let cmap1 = CHashMap::<String, String>::new();
cmap1.insert("key1".to_string(), "val1".to_string());
cmap1.insert("key2".to_string(), "val2".to_string());
let j1 = serde_json::to_string(&cmap1);
assert!(j1.is_ok());
//================================================================================
// deserialize
//================================================================================
let j1 = j1.unwrap();
let cmap1x: CHashMap<String, String> = serde_json::from_str(j1.as_str()).unwrap();
assert_eq!(*cmap1.get("key1").unwrap(), *cmap1x.get("key1").unwrap());
assert_eq!(*cmap1.get("key2").unwrap(), *cmap1x.get("key2").unwrap());
}
Dependencies
~0.8–6MB
~34K SLoC