Apache TsFile中的短时间序列分组压缩及合并方法  

Short Time Series Group Compression and Merging Method in Apache TsFile

作　　者：刘星宇 宋韶旭[1,2,3] 黄向东 王建民[1,2,3] LIU Xing-Yu;SONG Shao-Xu;HUANG Xiang-Dong;WANG Jian-Min(School of Software,Tsinghua University,Beijing 100084,China;National Engineering Research Center for Big Data Software(Tsinghua University),Beijing 100084,China;Beijing National Research Center for Information Science and Technology(Tsinghua University),Beijing 100084,China)

机构地区：[1]清华大学软件学院,北京100084 [2]大数据系统软件国家工程研究中心(清华大学),北京100084 [3]北京信息科学与技术国家研究中心(清华大学),北京100084

出　　处：《软件学报》2025年第3期941-961,共21页Journal of Software

基　　金：国家重点研发计划(2021YFB3300500);国家自然科学基金(62232005,62021002,62072265,92267203);国家电网公司总部科技项目(5700-202435261A-1-1-ZN)。

摘　　要：时间序列数据在工业制造、气象、电力、车辆等领域都有着广泛的应用,促进了时间序列数据库管理系统的发展.越来越多的数据库系统向云端迁移,端边云协同的架构也愈发常见,所需要处理的数据规模愈加庞大.在端边云协同、海量序列等场景中,由于同步周期短、数据刷盘频繁等原因,会产生大量的短时间序列,给数据库系统带来新的挑战.有效的数据管理与压缩方法能显著提高存储性能,使得数据库系统足以胜任存储海量序列的重任.Apache TsFile是一个专为时序场景设计的列式存储文件格式,在Apache IoTDB等数据库管理系统中发挥重要作用.阐述了Apache TsFile中应对大量短时间序列场景所使用的分组压缩及合并方法,特别是面向工业物联网等序列数量庞大的应用场景.该分组压缩方法充分考虑了短时间序列场景中的数据特征,通过对设备分组的方法提高元数据利用率,降低文件索引大小,减少短时间序列并显著提高压缩效果.经过真实世界数据集的验证,分组方法在压缩效果、读取、写入、文件合并等多个方面均有显著提升,能更好地管理短时间序列场景下的Ts File文件.Time-series data are widely used in fields such as industrial manufacturing,meteorology,electric power,and vehicles,which has spurred the development of time-series database management systems.More and more database systems are migrating to the cloud,and the architecture of end-cloud collaboration is becoming more common,leading to increasingly large data scales to be processed.In scenarios such as end-cloud collaboration and massive time series,a large number of short time series are generated due to short synchronization cycles and frequent data flushing,among other reasons,presenting new challenges to database systems.Efficient data management and compression methods can significantly improve storage performance,enabling database systems to handle the storage of massive time series.Apache TsFile is a columnar storage file format specifically designed for time series scenarios,playing an important role in database management systems such as Apache IoTDB.This study elaborates on the group compression and merging methods used in Apache TsFile to address scenarios with a large number of short time series,especially in application scenarios with a vast number of time series such as the Industrial Internet of Things.This group compression method fully considers the data characteristics in the short time series scenario.Through device grouping,it improves metadata utilization,reduces file index size,decreases short time series,and significantly improves compression effectiveness.After validation with real-world datasets,the proposed grouping method shows significant improvements in compression effect,reading,writing,file merging,and other aspects,enabling better management of TsFiles in short time series scenarios.

关 键 词：数据压缩 时间序列数据 数据库 工业物联网 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]