Some kinds of data should not be kept in memory any longer than they are needed. Helpers for clearing sensitive data on the stack and heap. This method is far from ideal, but superior methods like Robin-Hood hashing works poorly (if at all) in a concurrent structure. In our case, we use linear probing, which means that we take the bucket following it, and repeat until we find a free bucket. When two hashes collide, they cannot share the same bucket, so there must be an algorithm which can resolve collisions. 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. 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. with only one or two locking subroutines. By holding a read-write lock for each bucket, we ensure that you will generally be able to insert, read, modify, etc. The bucket of some key-value pair is determined by the hash of the key. Hash maps consists of so called "buckets", which each defines a potential entry in the table. chashmap (v2.2.2)įast, concurrent hash maps with extensive API.Ĭhashmap is not lockless, but it distributes locks across the map such that lock contentions (which is what could make accesses expensive) are very rare. This is a pure Rust implementation of the ChaCha20-Poly1305 AEAD from RFC 7539. Extern crate backoff extern crate reqwest use backoff :: chacha20-poly1305-aead (v0.1.2)
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