IoTDQ: An Industrial IoT Data Analysis Library for Apache IoTDB
作者机构:School of SoftwareTsinghua UniversityBeijing 100084China National Engineering Research Center for Big Data Software(NERCBDS)Tsinghua UniversityBeijing 100084China
出 版 物:《Big Data Mining and Analytics》 (大数据挖掘与分析(英文))
年 卷 期:2024年第7卷第1期
页 面:29-41页
核心收录:
学科分类:12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0812[工学-计算机科学与技术(可授工学、理学学位)]
主 题:industrial big data data quality data mining and analytics
摘 要:There is a growing demand for time series data analysis in industry *** loTDB is a time series database designed for the Internet of Things(loT)with enhanced storage and I/O *** User-Defined Functions(UDF)provided,computation for time series can be executed on Apache loTDB *** satisfy most of the common requirements in industrial time series analysis,we create a UDF library,loTDQ,on Apache *** library integrates stream computation functions on data quality analysis,data profiling,anomaly detection,data repairing,*** enables users to conduct a wide range of analyses,such as monitoring,error diagnosis,equipment reliability *** provides a framework for users to examine loT time series with data quality *** show that loTDQ keeps the same level of performance compared to mainstream alternatives,and shortens I/O consumption for Apache loTDB users.