The size of a data structure (i.e., the number of elements in it) is a widely used property of a data set. However, for concurrent programs, obtaining a correct size efficiently is non-trivial. In fact, the literature does not offer a mechanism to obtain a correct (linearizable) size of a concurrent data set without resorting to inefficient solutions, such as taking a full snapshot of the data structure to count the elements, or acquiring one global lock in all update and size operations. This paper presents a methodology for adding a concurrent linearizable size operation to sets and dictionaries with a relatively low performance overhead. Theoretically, the proposed size operation is wait-free with asymptotic complexity linear in the number of threads (independently of data-structure size). Practically, we evaluated the performance overhead by adding size to various concurrent data structures in Java−a skip list, a hash table and a tree. The proposed linearizable size operation executes faster by orders of magnitude compared to the existing option of taking a snapshot, while incurring a throughput loss of 1%−20% on the original data structure's operations.
@article{arxiv.2209.07100,
title = {Concurrent Size},
author = {Gal Sela and Erez Petrank},
journal= {arXiv preprint arXiv:2209.07100},
year = {2022}
}