IoTDQ: An Industrial IoT Data Analysis Library for Apache IoTDB

There is a growing demand for time series data analysis in industry areas. Apache IoTDB is a time series database designed for the Internet of Things (IoT) with enhanced storage and I/O performance. With User-Defined Functions (UDF) provided, computation for time series can be executed on Apache IoT...

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Veröffentlicht in:Big Data Mining and Analytics 2024-03, Vol.7 (1), p.29-41
Hauptverfasser: Chen, Pengyu, He, Wendi, Ma, Wenxuan, Huang, Xiangdong, Wang, Chen
Format: Artikel
Sprache:eng
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Zusammenfassung:There is a growing demand for time series data analysis in industry areas. Apache IoTDB is a time series database designed for the Internet of Things (IoT) with enhanced storage and I/O performance. With User-Defined Functions (UDF) provided, computation for time series can be executed on Apache IoTDB directly. To satisfy most of the common requirements in industrial time series analysis, we create a UDF library, IoTDQ, on Apache IoTDB. This library integrates stream computation functions on data quality analysis, data profiling, anomaly detection, data repairing, etc. IoTDQ 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 IoT time series with data quality problems. Experiments show that IoTDQ keeps the same level of performance compared to mainstream alternatives, and shortens I/O consumption for Apache IoTDB users.
ISSN:2096-0654
2097-406X
DOI:10.26599/BDMA.2023.9020010