AMS: Adaptive Multiget Scheduling Algorithm for Distributed Key-Value Stores

Abstract

Distributed key-value stores provide the Multiget API, where many key-value operations are batched together, to meet the parallel requirement of applications. Correspondingly, reducing the latency of Multigets is crucial for the responsiveness of the distributed key-value stores. The latency of a Multiget depends on both which replica server its key-value operations are scheduled to, i.e., the replica selection for each key-value operation, and when these key-value operations are served, i.e., the scheduling of the service sequence at different replica servers. Existing solutions solely focus on either one of them and accordingly lead to suboptimal latency for Multigets. To address these issues, this paper proposes an Adaptive Multiget Scheduling (AMS) algorithm in this paper, and specifically, our AMS re-architectures the framework to remove the conflict between replica selection and service sequence scheduling in the existing solution Rein. Based on the new framework, a sophisticated replica selection method is designed. Furthermore, AMS guides both replica selection and service sequence scheduling by the piggybacked information of replica servers, being adaptive to the heterogeneous time-varying server performance. Consequently, AMS can respectively reduce the median, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$95^{th}$</tex-math></inline-formula> , and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$99^{th}$</tex-math></inline-formula> percentile latencies of Multigets by a factor of 4, 3.1, and 1.86 compared to the default FIFO algorithm and significantly outperforms Rein.