JIPS (한국정보처리학회)
Current Result Document :
| 한글제목(Korean Title) |
Improvement of RocksDB Performance via Large-Scale Parameter Analysis and Optimization |
| 영문제목(English Title) |
Improvement of RocksDB Performance via Large-Scale Parameter Analysis and Optimization |
| 저자(Author) |
Huijun Jin
Won Gi Choi
Jonghwan Choi
Hanseung Sung
Sanghyun Park
|
| 원문수록처(Citation) |
VOL 18 NO. 03 PP. 0374 ~ 0388 (2022. 06) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
Database systems usually have many parameters that must be configured by database administrators and users. RocksDB achieves fast data writing performance using a log-structured merged tree. This database has many parameters associated with write and space amplifications. Write amplification degrades the database performance, and space amplification leads to an increased storage space owing to the storage of unwanted data. Previously, it was proven that significant performance improvements can be achieved by tuning the database parameters. However, tuning the multiple parameters of a database is a laborious task owing to the large number of potential configuration combinations. To address this problem, we selected the important parameters that affect the performance of RocksDB using random forest. We then analyzed the effects of the selected parameters on write and space amplifications using analysis of variance. We used a genetic algorithm to obtain optimized values of the major parameters. The experimental results indicate an insignificant reduction (-5.64%) in the execution time when using these optimized values; however, write amplification, space amplification, and data processing rates improved considerably by 20.65%, 54.50%, and 89.68%, respectively, as compared to the performance when using the default settings. |
| 키워드(Keyword) |
Database
Genetic Algorithm
Log-Structured Merge-Tree
Optimization
Random Forest
Space Amplification
Write Amplification
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| 파일첨부 |
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