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USENIX ATC2020Top-tier venue

PinK: High-speed In-storage Key-value Store with Bounded Tails

Junsu Im, Jinwook Bae, Chanwoo Chung, Arvind, Sungjin Lee

2020Year
85Citations
21Top-tier citations

Abstract

Key-value store based on a log-structured merge-tree (LSMtree) is preferable to hash-based KV store because an LSMtree can support a wider variety of operations and show better performance, especially for writes. However, LSM-tree is difficult to implement in the resource constrained environment of a key-value SSD (KV-SSD) and consequently, KV-SSDs typically use hash-based schemes. We present PinK, a design and implementation of an LSM-tree-based KV-SSD, which compared to a hash-based KV-SSD, reduces 99 th percentile tail latency by 73%, improves average read latency by 42% and shows 37% higher throughput. The key idea in improving the performance of an LSM-tree in a resource constrained environment is to avoid the use of Bloom filters and instead, use a small amount of DRAM to keep/pin the top levels of the LSM-tree.

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