SCMKV: A Lightweight Log-Structured Key-Value Store on SCM - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2017

SCMKV: A Lightweight Log-Structured Key-Value Store on SCM

Zhenjie Wang
  • Fonction : Auteur
  • PersonId : 1027970
Linpeng Huang
  • Fonction : Auteur
  • PersonId : 1027971
Yanmin Zhu
  • Fonction : Auteur
  • PersonId : 1027972

Résumé

Storage Class Memories (SCMs) are promising technologies that would change the future of storage, with many attractive capabilities such as byte addressability, low latency and persistence. Existing key-value stores proposed for block devices use SCMs as block devices, which conceal the performance that SCMs provide. A few existing key-value stores for SCMs fail to provide consistency when hardware supports such as cache flush on power failure are unavailable. In this paper, we present a key-value store called SCMKV that provides consistency, performance and scalability. It takes advantage of characteristics of key-value workloads and leverages the log-structured technique for high throughput. In particular, we propose a static concurrent cache-friendly hash table to accelerate accesses to key-value objects, and maintain separate data logs and memory allocators for each worker thread for achieving high concurrency. To reduce write latency, it tries to reduce writes to SCMs and cache flushing instructions. Our experiments show that SCMKV achieves much higher throughput and has better scalability than state-of-the-art key-value stores.
Fichier principal
Vignette du fichier
457609_1_En_1_Chapter.pdf (727.95 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01705441 , version 1 (09-02-2018)

Licence

Paternité

Identifiants

Citer

Zhenjie Wang, Linpeng Huang, Yanmin Zhu. SCMKV: A Lightweight Log-Structured Key-Value Store on SCM. 14th IFIP International Conference on Network and Parallel Computing (NPC), Oct 2017, Hefei, China. pp.1-12, ⟨10.1007/978-3-319-68210-5_1⟩. ⟨hal-01705441⟩
103 Consultations
106 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More