IoTDQ: An Industrial IoT Data Analysis Library for Apache IoTDB

查看全文 作　　者：Pengyu [1]Chen;Wendi [1]He;Wenxuan [1]Ma;Xiangdong [1]Huang;Chen [2]Wang

机构地区：[1]School of Software,Tsinghua University,Beijing 100084,China;[2]National Engineering Research Center for Big Data Software(NERCBDS),Tsinghua University,Beijing 100084,China

出　　处：《Big Data Mining and Analytics》索引2024年第7卷第1期,共13页

摘　　要：There is a growing demand for time series data analysis in industry areas.Apache loTDB is a time series database designed for the Internet of Things(loT)with enhanced storage and I/O performance.With User-Defined Functions(UDF)provided,computation for time series can be executed on Apache loTDB directly.To satisfy most of the common requirements in industrial time series analysis,we create a UDF library,loTDQ,on Apache loTDB.This library integrates stream computation functions on data quality analysis,data profiling,anomaly detection,data repairing,etc.loTDQ enables users to conduct a wide range of analyses,such as monitoring,error diagnosis,equipment reliability analysis.It provides a framework for users to examine loT time series with data quality problems.Experiments show that loTDQ keeps the same level of performance compared to mainstream alternatives,and shortens I/O consumption for Apache loTDB users. 关键词：industrial big data data quality data mining and analytics

相关文献

参考文献（35）
引证文献（2）
耦合文献（0）

参考文献(35)

引证文献(2)

互联网出版许可证新出网证(渝)字10号全国400电话 - 免长途话费

IoTDQ: An Industrial IoT Data Analysis Library for Apache IoTDB

参考文献(35)

引证文献(2)

用户提示