Abstract
A key aspect of any hash map design is the problem of dynamically resizing it in order to deal with hash collisions. Compression in tree-based hash maps is the ability of reducing the depth of the internal hash levels that support the hash map. In this context, elasticity refers to the ability of automatically resizing the internal data structures that support the hash map operations in order to meet varying workloads, thus optimizing the overall memory consumption of the hash map. This work extends a previous lock-free hash trie map design to support elastic hashing, i.e., expand saturated hash levels and compress unused hash levels, such that, at each point in time, the number of levels in a path is adjusted, as closely as possible, to the set of keys that is stored in the data structure. To materialize our design, we introduce a new compress operation for hash levels, which requires redesigning the existing search, insert, remove and expand operations in order to maintain the lock-freedom property of the data structure. Experimental results show that elasticity effectively improves the search operation and, in doing so, our design becomes very competitive when compared to other state-of-the-art designs implemented in Java.

Abstract

Abstract
Hash tries are a trie-based data structure with nearly ideal characteristics for the implementation of hash maps. In this paper, we present a novel, simple and scalable hash trie map design that fully supports the concurrent search, insert and remove operations on hash maps. To the best of our knowledge, our proposal is the first that puts together the following characteristics: (i) be lock-free; (ii) use fixed size data structures; and (iii) maintain the access to all internal data structures as persistent memory references. Our design is modular enough to allow different types of configurations aimed for different performances in memory usage and execution time and can be easily implemented in any type of language, library or within other complex data structures. We discuss in detail the key algorithms required to easily reproduce our implementation by others and we present a proof of correctness showing that our proposal is linearizable and lock-free for the search, insert and remove operations. Experimental results show that our proposal is quite competitive when compared against other state-of-the-art proposals implemented in Java. © 2021 Elsevier Inc.

Abstract

Abstract