Deduplication adapted CaseDB for edge computing

被引：0
作者：
Tulkinbekov K. [1 ]
Kim J.-H. [1 ]
Kim D.-H. [1 ]
机构：
[1] Department of Electronic Engineering, Inha University, Incheon
来源：
IEIE Transactions on Smart Processing and Computing | 2020年 / 9卷 / 04期
基金：
新加坡国家研究基金会;
关键词：
CaseDB; Deduplication; Key-value store; Space amplification; Write amplification;
D O I：
10.5573/IEIESPC.2020.9.4.317
中图分类号：
学科分类号：
摘要：
Log-structured merge-tree (LSM-tree) family key-value stores are becoming the databases most in demand for big data systems. They provide an easy-to-implement interface, and they automatically perform garbage collection by applying a compaction procedure over the multilevel structure. CaseDB offers various advantages by reducing write amplification considerably, using a metadata compaction technique. However, it suffers from a space amplification problem in update-intensive workloads. As an implementation of the LSM-tree structure, CaseDB refuses to instantly perform deletes, but delays them for the compaction process, resulting in an increasing amount of deprecated data. This paper proposes a deduplication extended compaction method for CaseDB. It scans for duplicated keys within the compaction method and removes the old values. Experiment results show that the proposed technique offers various threshold values of deduplication for different balances between space amplification and write amplification. Copyrights © 2020 The Institute of Electronics and Information Engineers
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页码：317 / 324
页数：7
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