Limitations of CAP theorem imply that if availability is desired in the presence of network partitions, one must sacrifice sequential consistency, a consistency model that is more natural for system design. We focus on the problem of what a designer should do if she has an algorithm that works correctly with sequential consistency but is faced with an underlying key-value store that provides a weaker (e.g., eventual or causal) consistency. We propose a detect-rollback based approach: The designer identifies a correctness predicate, say P , and continue to run the protocol, as our system monitors P . If P is violated (because the underlying key-value store provides a weaker consistency), the system rolls back and resumes the computation at a state where P holds. We evaluate this approach in the Voldemort key-value store. Our experiments with deployment of Voldemort on Amazon AWS shows that using eventual consistency with monitoring can provide 20 - 40% increase in throughput when compared with sequential consistency. We also show that the overhead of the monitor itself is small (typically less than 8%) and the latency of detecting violations is very low. For example, more than 99.9% violations are detected in less than 1 second.
@article{arxiv.1801.07319,
title = {Optimistic Execution in Key-Value Store},
author = {Duong Nguyen and Aleksey Charapko and Sandeep Kulkarni and Murat Demirbas},
journal= {arXiv preprint arXiv:1801.07319},
year = {2018}
}