LinKV: An RDMA-Enabled KVS for High Performance and Strict Consistency Under Skew

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Abstract

We present LinKV, a novel distributed key-value store that can leverage RDMA network to simultaneously provide high performance and strict consistency (i.e., per-key linearizability) for skewed workloads. To avoid the potential performance loss caused by load imbalance under skew, existing solutions will replicate popular items into different nodes’ caches to support quick and even accesses. But for those writes hitting cache, there will be multiple consistency actions to guarantee linearizability, which degrade the overall performance. In this paper, we present a batch method to make multiple writes amortize those overheads caused by a round of consistency actions. While for reads, we introduce a lease-based scheme to make them quickly return the most recently completed batches of writes. Comparing to the state-of-the-art solutions, LinKV with above strategies can improve the throughput by 1.5 - 3 × and reduce the latency to about 10 % with different write ratios under skew.

Original languageEnglish
Title of host publicationWeb and Big Data - 5th International Joint Conference, APWeb-WAIM 2021, Proceedings
EditorsLeong Hou U, Marc Spaniol, Yasushi Sakurai, Junying Chen
PublisherSpringer Science and Business Media Deutschland GmbH
Pages190-198
Number of pages9
ISBN (Print)9783030858957
DOIs
StatePublished - 2021
Event5th International Joint Conference on Asia-Pacific Web and Web-Age Information Management, APWeb-WAIM 2021 - Guangzhou, China
Duration: 23 Aug 202125 Aug 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12858 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Joint Conference on Asia-Pacific Web and Web-Age Information Management, APWeb-WAIM 2021
Country/TerritoryChina
CityGuangzhou
Period23/08/2125/08/21

Keywords

  • Caching
  • Key-value store
  • Linearizability
  • RDMA

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