EKRM: Efficient Key-Value Retrieval Method to Reduce Data Lookup Overhead for Redis
Document Type
Conference Proceeding
Publication Date
1-1-2024
Abstract
As an open-source key-value system, Redis has been widely used in internet service stations. A key-value lookup in Redis usually involves several chained memory accesses, and the address translation overhead can significantly increase the lookup latency. This paper introduces a new software-based approach that can reduce chained memory accesses and total address translation overhead of lookup requests by placing key-value entries in a specially managed memory space organized as huge pages with a fast hash table and enabling a fast lookup approach with simple hash functions, while keeping the integrity of Redis data structure. The new approach brings up to 1.38× average speedup for the key-value retrieval process, and significantly reduces misses in TLB and last-level cache. It outperforms SLB, an address caching software approach and has match the performance to STLT, a software-hardware co-designed address-centric design.
Publication Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN
[9783031695766]
Recommended Citation
Yao, Y.,
Wang, X.,
Zhou, D.,
Li, L.,
Wu, J.,
Zhu, L.,
Wang, Z.,
&
Luo, Y.
(2024).
EKRM: Efficient Key-Value Retrieval Method to Reduce Data Lookup Overhead for Redis.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
14801 LNCS, 166-179.
http://doi.org/10.1007/978-3-031-69577-3_12
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p2/1009