| Title |
Deduplication Adapted CaseDB for Edge Computing |
| Authors |
(Khikmatullo Tulkinbekov) ; (Joo-Hwan Kim) ; (Deok-Hwan Kim) |
| DOI |
https://doi.org/10.5573/IEIESPC.2020.9.4.317 |
| Keywords |
Key-value store; CaseDB; Deduplication; Space amplification; Write amplification |
| Abstract |
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 multi-level 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. |