The Design of an Efficient Lossy Compressor for Time Series Databases
文献类型：期刊论文
| 作者 | Zou, Xiangyu2; Wang, Shihao2; Shi, Yang2; Chen, Xinyu3; Jin, Sian4; Tao, Dingwen1; Xia, Wen2,5 |
| 刊名 | ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION
 |
| 出版日期 | 2025-12-01 |
| 卷号 | 22期号:4页码:27 |
| 关键词 | IoT database time-series data lossy compression |
| ISSN号 | 1544-3566 |
| DOI | 10.1145/3767158 |
| 英文摘要 | Time-series databases (denoted as TSDB), which are designed for handling rapidly growing time-series data, usually apply compression techniques to reduce storage overhead. However, existing compressors are limited in key metrics for TSDB compression, such as compression ratio or decompression speed, primarily due to a mismatch between their design and the features specific to TSDB. To this end, we propose a lossy compressor Machete. It achieves a much higher compression ratio and fast decompression speed, while promising a user-specific and point-wise error bound to preserve the analytical value of the data. First, Machete proposes a pattern-based predictor and an efficient hybrid encoder to monitor data trends, which successfully achieve higher compression rates through better understanding of the data. Second, Machete proposes a SIMD-based decompression acceleration technique, which exploits the repeatedly intermediate calculations in decompression and shares them in decompression iterations through parallelism.Our evaluation on four real-world datasets shows that Machete outperforms state-of-the-art compressors by 69%-114% on compression ratio and achieves the fastest decompression speed on two datasets. When applied to a well-known time series database InfluxDB, Machete saves disk usage 40%-72% and improves the query performance of the InfluxDB database by saving I/O. |
| 资助项目 | Major Key Project of PCL[PCL2024A05] ; National Natural Science Foundation of China[62502119] ; National Natural Science Foundation of China[62472127] ; National Natural Science Foundation of China[62032023] ; National Natural Science Foundation of China[T2125013] ; Innovation Funding of ICT, CAS[E461050] ; National Key Research and Development Program of China[2020YFA0907000] ; National Key Research and Development Program of China[2025YFB30037002] ; Shenzhen Science and Technology Program[GXWD20231128111309001] ; Shenzhen Science and Technology Program[KJZD202310230-94701003] ; GuangDong Basic and Applied Basic Research Foundation[2023A1515110072] ; Ant Group |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:001667658800009 |
| 出版者 | ASSOC COMPUTING MACHINERY |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/42839]  |
| 专题 | 中国科学院计算技术研究所 |
| 通讯作者 | Xia, Wen |
| 作者单位 | 1.Chinese Acad Sci, Inst Comp Technol, State Key Lab Processors, Beijing 100190, Peoples R China 2.Harbin Inst Technol Shenzhen, Inst Cyberspace Secur, Shenzhen, Peoples R China 3.Washington State Univ, Pullman, WA 99164 USA 4.Temple Univ, Philadelphia, PA USA 5.Pengcheng Lab, Shenzhen, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zou, Xiangyu,Wang, Shihao,Shi, Yang,et al. The Design of an Efficient Lossy Compressor for Time Series Databases[J]. ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION,2025,22(4):27. |
| APA | Zou, Xiangyu.,Wang, Shihao.,Shi, Yang.,Chen, Xinyu.,Jin, Sian.,...&Xia, Wen.(2025).The Design of an Efficient Lossy Compressor for Time Series Databases.ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION,22(4),27. |
| MLA | Zou, Xiangyu,et al."The Design of an Efficient Lossy Compressor for Time Series Databases".ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION 22.4(2025):27. |
入库方式： OAI收割
来源：计算技术研究所
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